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Indian J Community Med
v.41(3); Jul-Sep 2016

Twin Studies: A Unique Epidemiological Tool

Monalisha sahu.

Department of Community Medicine, Lady Hardinge Medical College, New Delhi, India

Josyula G Prasuna

Twin studies are a special type of epidemiological studies designed to measure the contribution of genetics as opposed to the environment, to a given trait. Despite the facts that the classical twin studies are still being guided by assumptions made back in the 1920s and that the inherent limitation lies in the study design itself, the results suggested by earlier twin studies have often been confirmed by molecular genetic studies later. Use of twin registries and various innovative yet complex software packages such as the (SAS) and their extensions (e.g., SAS PROC GENMOD and SAS PROC PHREG) has increased the potential of this epidemiological tool toward contributing significantly to the field of genetics and other life sciences.

Introduction

The debate of nature versus nurture is known since antiquity. The close resemblance of twins has been the subject of many works of fiction as well. Means of distinguishing between the effects of tendencies received due to genes at birth and those imposed by the different environments they were exposed to during their lives after birth have always been the subject of interest to researchers. The objection to statistical evidence in proof of the inheritance of peculiar traits has always been blamed upon similar environmental conditions playing as a confounder.( 1 ) Twin studies provide a strong basis for exploring the importance of any potential risk factors on a trait or condition by controlling the genetic variations. It has been one of the favorite research tools of behavioral geneticists and psychologists since long, mainly utilized to estimate the heritability of traits and to quantify the effect of a person's shared environment (family) and unique environment (the individual events that shape a life) on a trait.( 2 )

Evolution of Twin Studies

The similarity between twins has been a source of curiosity since time immemorial. The idea of using twins to study the heritability of traits can be traced back to the British researcher Sir Francis Galton. His pioneering work The History of Twins in 1875 inspired much debate by suggesting that England's “chief men of genius” were the product more of good breeding (nature) than of good rearing (nurture). Based on the similarities he found between twins from 80 questionnaires, Galton proudly announced his conclusion to the world that nature soundly beats nurture, though his sample was too small and consisted of all upper-class individals, without any control group. After nearly five decades, in the 1920s researchers “perfected' Galton's methods by comparing identical and fraternal twins and inferring heritability from the differences between the two.( 3 )

The first reported classical twin study was a study performed by Walter Jablonski in 1922, investigating the contribution of heredity to refraction in human eyes. Jablonski examined the eyes of 52 twin pairs and by comparing the size of within-pair differences between identical and nonidentical twins was able to infer the heritability of a trait.( 4 )

Even later, in 1990, Thomas J. Bouchard, Jr. and his colleagues (including esteemed twin researcher Nancy L. Segal) at the University of Minnesota conducted one of the most famous research studies on genetic influence in humans. They studied identical twins separated since birth and raised by different families (adoption studies), and so assumed that similarities, if found any, must be those that are heavily influenced by a person's genetic heritage. The study was invoked by the sensational news reports of two identical twins reunited after a lifetime apart. James Lewis and James Springer were separated 4 weeks after birth and each infant was taken in by a different adoptive family. When they were reunited at the age of 39, an extraordinary collection of coincidences emerged. Both of the “Jim twins” had married and divorced women named Linda. Both had second marriages with women named Betty. Both had police training and worked part-time with law enforcement agencies. Both had childhood pets named Toy. They had identical drinking and smoking patterns, and both chewed their fingernails to the nub. Their firstborn sons were named James Alan Lewis and James Allan Springer.( 5 ) Bouchard and Segal reported that about 70% of the variance in intelligence quotient (IQ) found in their particular sample of identical twins was found to be associated with genetic variation. Furthermore, identical twins reared apart were eerily similar to identical twins reared together in various measures of personality, personal mannerisms, expressive social behavior, and occupational and leisure-time interests. However, they did not find outstanding similarities between identical twins on measures such as standardized personality tests. Still, Bouchard's findings can be interpreted as strong support for genetic influences on personality. Bouchard's data set was unique and probably a one-time event in history because modern adoption agencies no longer break up sets of identical twins.( 6 , 7 )

The modern-day classical twin study design relies on studying twins raised in the same family environments, which provides control not only for genetic background but also for shared environment in early life. As monozygotic (identical) twins develop from a single egg fertilized by a single sperm, which splits after the egg starts to develop, they are expected to share all of their genes, whereas dizygotic (fraternal) twins share only about 50% of them, which is the same as nontwin siblings.( 8 ) Thus, if any excess similarity is seen between the identical twins when a researcher compares the similarity between sets of identical twins to the similarity between sets of fraternal twins for a trait or condition, then most probably the reason behind this similarity is due to genes rather than environment.

Some assumptions are also made in twin studies; one of them is the assumption of random mating, which assumes that people are as likely to choose partners who are different from themselves as they are to choose partners who are similar for a particular trait. If, instead, people tend to choose mates like themselves, then fraternal twins could share a greater percentage of their genes than expected. In the case of nonrandom mating, fraternal twins would have more genetically influenced traits in common than expected because the genes they receive from their mothers and fathers would be similar to each other. Similarly, the assumption of equal environments is also made, which assumes that fraternal and identical twins raised in the same homes experience similar environments. It is assumed that genes and the environment typically make only separate and distinct contributions to a trait. In general, it is also assumed that only one type of genetic mechanism—usually additive—operates for a particular trait. However, traits can be inherited through different genetic mechanisms. Additive genetic mechanisms mix together the effects of each allele. For example, if genes for curly hair were additive, a curly-haired father and a straight-haired mother might have a child who has wavy hair.( 8 )

There can be variations in the classical model, which may sometimes provide an added advantage, for example if twins are followed up over longer duration of time in longitudinal manner to assess the development of adult-onset traits and conditions. This slight deviation will allow for a more complete and accurate assessment of environmental factors over time. Similarly, on combining with molecular genetics, information about the presence or absence of specific genetic variants to determine the impact on the trait of interest can be explored. The advances in molecular genetics have substantiated hypotheses generated by the traditional twin research design by pinpointing the effects of a particular gene. Depending on the objectives of the study, one may need only monozygotic or dizygotic twins, or a combination of the two.( 8 )

Twin Registries: Unique Database

A twin registry is a database of information about both identical twins and fraternal twins, which is often maintained on a country-wide level or by an academic institution, such as a university or other research institution. There are various twin registries all around the world, including in Sweden, Denmark, Norway, Finland, Australia, Sri Lanka, and the United Kingdom.( 9 , 10 )

Registration of some twin registries are mandatory by law, for example Norway, where all births of twins since 1967 have been registered by the Norwegian government.( 9 , 10 ) However, enlisting with the Australian( 11 ) and Sri Lankan( 12 ) registries is voluntary. The twin registry in some countries have also made extensive outreach efforts, for example examining hospital birth records and then making multiple follow-up efforts such as in-person visits to find the twins and have them agree to be registered.

The Danish Twin Registry is the oldest national twin register in the world, initiated in 1954, and contains information about more than 88,000 twin pairs born in Denmark since 1870, in addition to triplets and quadruplets.( 13 )

The Danish Twin Registry is used as a source for studies on genetic influence on normal variation in clinical parameters associated with clinical studies of specific diseases, the metabolic syndrome and cardiovascular diseases, and aging and age-related health problems. In all cohorts the ascertainment has been population-based and independent of the traits studied, although different procedures of ascertainment have been employed.( 13 , 14 )

The Swedish Twin Registry (STR), managed by the Karolinska Institute, is the largest population-based twin registry in the world (containing approximately 1,70,176 twins in 85,088 pairs born 1886-2000). There are 1, 37 414 twins still alive and living in Sweden.( 15 , 16 )

It is a unique resource for clinical, epidemiological, and genetic studies. Information has been mainly collected for demographic, medical, and lifestyle characteristics, with special attention to general health, cardiovascular and respiratory disease, legal drug use, and dietary and psychosocial conditions. It is currently in the final phase of a complete telephone interview screening of all twins born in 1958 or earlier regardless of gender composition or vital status of the pair. This effort is known as the Screening Across the Lifespan Twin study (SALT).( 15 , 16 )

The famous Minnesota Twin Registry is a registry of all twins born in Minnesota from 1936 to 1955 and from 1961 to 1964; it was started in 1983. The Minnesota Center for Twin and Family Research (MCTFR) presently oversees two longitudinal studies: The Minnesota Twin Family Study (MTFS) and the Sibling Interaction and Behavior Study (SIBS). Both studies include over 9800 individuals comprising twins, siblings, and parents. The MTFS began in 1989, when it enrolled 1,400 pairs of identical and same-sex fraternal twins and their families from the upper Midwest. Twins were identified through public birth records and invited to participate with their parents in a full-day intake assessment. SIBS is a study of adoptive as well as biological sibling and their parents.( 17 ) The primary purpose of SIBS are to understand how siblings interact and influence one another, how family environment has an impact on the psychological health of adolescents, and how adoptive families are similar to and different from nonadoptive families. It is one of the largest studies of adolescents and their families ever conducted.( 17 )

The Sri Lankan Twin registry (SLTR), established in 1996, is the first ever and only existing population-based Twin Registry in a low- and middle-income country (LMIC).( 15 ) It is presently confined to Colombo district, the most populous among the 25 administrative districts of Sri Lanka. It is comprised of a volunteer cohort of 14,120 twins (7,060 pairs) and 119 sets of triplets, and a population-based cohort of 19,040 (9,520 pairs) twins and 89 sets of triplets. Several studies have been conducted using this registry, including the Colombo Twin and Singleton Study (CoTaSS 1; 4,387 twins, 2,311 singletons), which have explored the prevalence and heritability of a range of psychiatric disorders as well as genetic/environmental interplay. SLTR is a classic showcase of successful North-South partnership in building a progressive research infrastructure in a LMIC.( 12 , 18 )

Indian Scenario

Though there are many small-scale twin studies published in various journals related to metabolic syndromes,( 19 , 20 , 21 ) cardiovascular diseases,( 22 ) respiratory diseases,( 23 ) cerebrovascular diseases,( 24 ) epilepsy,( 25 , 26 ) dermatology,( 27 , 28 ) ophthalmology,( 29 , 30 ) psychology( 31 ) chromosomal disorders,( 32 ) and dentistry,( 33 , 34 , 35 , 36 ) among others, there exists no twin registry in India to documenting the details of twins borne. In addition, there is no provision of any law for mandatory twin registration. There are many practical problems associated with registering twins borne, one of the important concerns being the large number of home deliveries. In a country where recording the birth weight of every newborn is not yet possible, mandatory twin registration may prove a distant dream for the already overburdened health-work force. Still, outreach activities can be planned to register the twins. Apex medical institutes and tertiary care centers can take the initiative to maintain and analyze data regarding twins in their areas to find out various genetic as well as environmental confounders in various diseases.

Methods Used in Twin Research

The large pool of data related to twins gathered can be analyzed in various ways with the help of new, innovative as well as complex statistical softwares. Twin studies intend to measure the heritability of a trait, which can be determined by concordance rates.

Concordance rate (CR) for a disease or trait among identical and fraternal twin pairs is actually a statistical measure of probability: If one twin has a specific trait or condition, what is the probability that the other twin has (or will develop) that same trait or disease? Historically, CRs are computed separately for monozygotic (MZ) and dizygotic (DZ) pairs. When MZ concordances are greater than DZ concordances, genetic influences are indicated.( 37 )

Quantitative genetic analyses and heritability estimation, including comparisons of concordances or intraclass correlations and structural equation modelling, can also be used to investigate the relative importance of genetic and environmental influences on a particular trait or condition. Linear structural equations and fit models over all types of twins can be used to describe the causes of variation in a phenotype. Structural equation modelling of data can provide further refinement in the results. The total variance in the trait can be partitioned into genetic variance, common environmental variance including shared (familial) environmental variance, and unique environmental variance. In order to estimate the parameters of interest, the equation for the twins is written and the parameters studied. Heritability, the relative importance of genetic influences for variation in a trait, is defined as genetic variance divided by the total phenotypic variance.

Tetrachoric correlations

It is calculated for two normally distributed phenotypic variables that are both expressed as a dichotomy (disease or no disease) and reflect the similarity of twin pairs. Thus, differences in correlations between various groups provide information about the presence of genetic effects.

Multivariate analyses of twin data can additionally offer estimates of the extent to which allelic variants and environment may influence different traits and conditions.( 37 )

The co-twin control analyses method is applied in situ ations where one wants to investigate the importance of an expected risk factor after controlling for genetic and shared environmental effects. It should be noted that the co-twin control method may entail control of factors in the biological pathway between exposure and disease, which may cause an underestimation of the exposure studied.

Co-twin control analyses: Disease-discordant twins

In studies of disease-discordant twins, two control groups usually are used: External controls and internal or co-twin controls. The analysis classically is conducted in three steps.

Step 1 : Association between exposure and outcome (comparison with external controls). The first step, which is essentially a classic case-control study, is to compare twins diagnosed as cases with external controls (other twins not related to the index probands), and to evaluate the risk for disease given an exposure. This approach facilitates comparisons with results from ordinary case-control studies on singletons.

Step 2 : Controlling for confounding from unmeasured early environment (healthy co-twin as control). In the second step, the healthy co-twin (in both MZ and DZ twin pairs) can be used as a control for the diseased twin. Because twins share the same intrauterine environment and typically are reared together, the co-twin control method provides a very effective tool to minimize confounding by differences in an (unmeasured) childhood or adolescent environment.

If analyses with external controls show associations between exposure and disease and the relative risk remains similarly high in the within-pair (co-twin) analyses, it speaks in favor of a causal effect of the exposure on the disease. On the other hand, if the relative risk is not increased in the within-pair comparisons (but only in the first-step analyses with external comparisons), this indicates that environmental factors early in life (for example, fetal environment, maternal smoking, or childhood socioeconomic status (SES)) are responsible for the initially observed findings. If the relative risks from steps 1 and 2 differ, a direct test of significance of difference in risks can be performed by applying regression: The exposure on control status (external versus internal control).

Step 3 : Controlling for unmeasured genetic background (healthy monozygotic co-twin as control). In the third step, analyses are applied only to disease-discordant MZ pairs. This design is ideal in controlling for potential confounding from genetic factors, as the cases and controls are genetically identical. Thus, one is confident that an observed effect is not confounded by genetic predisposition. If the twin with the exposure in MZ pairs more often has a specific chronic disease, this will provide strong support for the likelihood that the exposure contributes to the causation of the disease. On the other hand, if an association exists in analyses of external controls among disease-discordant DZ pairs but not among MZ pairs, genetic effects have probably confounded the results.

Co-twin control analyses: Exposure-discordant twins

As mentioned above, one can also focus on exposure-discordant pairs that are followed longitudinally for a disease outcome. In this case, t -tests or proportional hazard regressions can be utilized for estimating the relative risk between exposed and unexposed individuals, whereas matched analyses should be used in within-pair analyses, similar to the disease-discordant pairs.

Finally, as the twin registries contain longitudinal data on large samples, they can therefore be used for conventional epidemiological analyses disregarding twinship status. Several studies have been performed on the association between exposure and outcomes using the registries as a population-based cohort or as the basis for nested case-control studies. When using twin data for these types of studies, the dependency between the twins in a pair should be taken into account by using generalized linear models or other techniques.( 15 , 37 , 38 )

Statistical methods and analysis

Various complex software packages such as Statistical Analysis System (SAS), Mx (Mx is a software developed by (Michale Neale, Department of Psychiatry and School of Medicine, Virginia Common Wealth University, Richmond, VA-23298-0126, USA. Mx is a matrix algebra interpreter and numerical optimizer for structural equation modeling and other types of statistical modeling of data.)) are used for statistical analysis for the twin studies: For applying logistic regression, SAS PROC GENMOD using generalized estimating equation (GEE) model can be used, while for conditional logistic regression, SAS PROC PHREG can be used.( 38 , 39 )

Advantages of twin studies

Twin studies allow disentanglement of the shared genetic and environmental factors for the trait of interest.
Researchers can estimate the proportion of variance in a trait attributable to genetic variation versus the proportion that is due to shared environment or unshared environment.
The use of twins can improve the statistical power of a genetic study by reducing the amount of genetic and/or environmental variability; the extent to which different assumptions matter may depend on which trait is being studied.

Limitations of twin studies

Results from twin studies cannot be directly generalized to the general population, due to lack of randomization; in addition, they are different with regard to their developmental environment, as two fetuses growing simultaneously.
Some researchers also suggest that genetic factors may lead to a higher incidence of twin births in some women.
Though lot of changes happened in the field of genetics over time, twin studies today are also based on the same assumptions that were made back in 1920s. Many of these are deeply flawed.
Findings from twin studies are often misunderstood, misinterpreted, and blown out of proportion, not just by the media, but even by serious scientists who get their work published.
Many twin registries depend on the voluntary participation of twins. This leads to volunteer bias or recruitment bias, a special type of selection bias, which may lead to overinclusion of identical and female twins, resulting in overestimation of the heritability of the trait or condition under study.
The use of twins does not allow the researcher to consider the effects of both shared-environment and gene/environment interaction simultaneously. This can be addressed by including additional siblings in the design.

Scholars have long studied twins to address the “nature and nurture” question; however, opposing “nature” to “nurture” is misleading. Genes combine with the environment to produce complex human traits. The importance of genes suggested by earlier twin studies has often been confirmed by later molecular genetic studies. Therefore, twin studies will continue to inform mankind about the relative importance of genes and the environment on traits in ways that no other type of research ever can. Though they have received much criticism, the advancement of statistical techniques (such as structural equation modelling) and the implementation of additional controls have allayed some of the concerns, if not all. The original twin study design has expanded to include studies of twins' extended families, longitudinal studies, and other variations. Some of these variations may allow researchers to address previous limitations also. Many molecular genetic studies have shown the usefulness of twin studies as an exploratory tool, whether or not the assumptions of equal environments and assortative mating are exactly met.

Therefore, twin studies will continue to be an important tool along with emerging genome and molecular research methods in shedding light on various aspects of human genetics and on how environmental factors and genetics combine to create human traits and behaviors.

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Twin Studies by Nancy L. Segal LAST REVIEWED: 19 March 2013 LAST MODIFIED: 19 March 2013 DOI: 10.1093/obo/9780199828340-0101

Twin research is an informative approach for understanding the genetic and environmental influences affecting behavioral, physical, and medical traits. The simple yet elegant logic of the twin method derives from the differences in genetic relatedness between the two types of twins. Identical (monozygotic or MZ) twins share 100 percent of their genes, while fraternal (dizygotic or DZ) share 50 percent of their genes, on average. MZ twins result when a fertilized egg (ovum) divides during the first two weeks following conception, while DZ twins result when a woman simultaneously releases two eggs that are fertilized by two separate sperm. MZ twins are always same sex, whereas DZ twins may be same-sex or opposite-sex. However, rare events occasionally produce unusual MZ and DZ twin variations. Twin researchers compare the resemblance between MZ and DZ twins with reference to a particular trait, such as height or weight. Greater resemblance between MZ twins than DZ twins demonstrates that the trait under study is under partial genetic control. There are also various ways that twins and their families can be used in research to increase the potential yield of a study. Sophisticated biometrical techniques can estimate the extent of difference among people associated with their genes, shared environments and nonshared environments. Twin research has proliferated in recent years. This is largely because the power of the twin method for understanding the origin and development of human traits has become increasingly appreciated by investigators representing diverse fields. Twinning rates have also increased dramatically since 1980, especially the rate of fraternal twinning as a consequence of fertility treatments. There have been stunning advances in quantitative mathematical methodology that continue to increase the value of twin studies. Lastly, there have been enormous developments in the molecular genetics and genomics fields with respect to associating genes posing increased risks for specific behaviors and disease. Twins will continue to play a prominent role in these endeavors. The sources presented in this article represent a wide range of areas and topics within twin research. General overviews of the field, both historical and current, are provided, as well as a listing of special collections in twin research, that is, books and journals focusing on a particular topic or theme and web addresses. The largest section includes topics reflecting the widening range of psychological, biological, and medical traits that have been examined via twin research methods. The section on twin-based perspectives provides sources treating unusual twin-related topics.

Twin research has had a successful yet controversial past, a trend that has continued through the present. Despite the wealth of information that has been derived from twin studies, various methodological and interpretive aspects continue to be questioned. The historical roots of twin studies, its acceptance into the mainstream of psychological and medical research, and its challenges are documented in a number of books, articles, and essays. The resources in this section span a wide range of twin-related topics. The five books are appropriate for experienced investigators and new scientists, as well as general audiences searching for information about the many ways twins are used in scientific studies. Johnson, et al. 2009 and Boomsma, et al. 2002 go more deeply into current trends in twin research but will interest anyone concerned with what twin studies have (and can potentially) reveal about the origins of variation in human behavioral and physical traits. The selections here include general overviews of the biological and psychological aspects of twinship ( Scheinfeld 1967 ), the nature-nurture debates ( Wright 1997 ), overviews of unusual topics in the study of twins ( Segal 2000 ), and cultural issues ( Stewart 2003 , Piontelli 2008 ). An older, but still informative account of the biology and psychology of twinning is also provided ( Bryan 1983 ).

Boomsma, Dorret, Andreas Busjahn, and Leona Peltonen. 2002. Classical twin studies and beyond. Nature Reviews (Genetics) 3:872–882.

DOI: 10.1038/nrg932

Describes and documents the potential of large twin registries to study complex human traits. Discusses various twin research designs (e.g., classic twin study, co-twin control, genotyping of marker loci) and their application in scientific research. Includes lists of twin registers in and outside European countries.

Bryan, Elizabeth. 1983. The nature and nurture of twins . London: Ballière Tindall.

A comprehensive examination of biological and psychological aspects of twinning by a British physician. Includes helpful information on twin types, twinning rates, and related topics. Also includes some specific topics not covered elsewhere, such as twin loss and twins with special needs.

Johnson, Wendy, Eric Turkheimer, Irving I. Gottesman, and Thomas J. Bouchard Jr. 2009. Beyond heritability: Twin studies in behavioral research. Current Directions in Psychological Science 18:217–220.

DOI: 10.1111/j.1467-8721.2009.01639.x

Makes the argument that the heritability of most behavioral traits is now known, yet twin studies retain a vital place in psychological research. Twin research should direct greater attention to environmental influences on behavior in a quest to identify its underlying mechanisms.

Piontelli, Alessandra. 2008. Twins in the world: The legends they inspire and the lives they lead . New York: Palgrave Macmillan.

Examines beliefs and practices regarding twinship from a cross-cultural perspective. The author’s background in neurology, psychiatry, psychoanalysis, and obstetrics substantially enriches the firsthand experiences she describes.

Scheinfeld, Amram. 1967. Twins and supertwins . Philadelphia: J. B. Lippincott.

An older, but complete survey of the history, biology, and psychology of twins before this became mainstream science. Often includes information that is difficult to find elsewhere.

Segal, Nancy L. 2000. Entwined lives: Twins and what they tell us about human behavior . New York: Plume.

A comprehensive overview of the background, methods, findings, and implications of twin research. Nine of the sixteen chapters address special topics such as athletic performance, legal circumstances, conjoined twinning, and noteworthy twin pairs. Written by a professor of psychology.

Stewart, Ellen. 2003. Exploring twins: Towards a social analysis of twinship . London: Palgrave Macmillan.

Addresses the social, societal, and cultural aspects of twinship. Also considers various views of twins from the perspectives of the twins, their family members, and society at large. Draws on sources from multiple disciplines.

Wright, Lawrence. 1997. Twins and what they tell us about who we are . New York: John Wiley.

An account of research concerning genetic and environmental events making MZ twins both alike and different in behavior. The focus is largely, but not exclusively, on separately raised twins. A very good starting point for work in this area, although more recent publications from the Minnesota Study of Twins Reared Apart should be consulted. Written by a well-known journalist.

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The Oxford Handbook of Quantitative Methods in Psychology: Vol. 2: Statistical Analysis

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10 Twin Studies and Behavior Genetics

Gabriëlla A.M. Blokland, Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, School of Psychology and Centre for Advanced Imaging, University of Queensland, Brisbane, Australia

Miriam A. Mosing, Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, School of Psychology, University of Queensland, Brisbane, Australia

Karin J.H. Verweij, Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, School of Psychology, University of Queensland, Brisbane, Australia

Sarah E. Medland, Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, School of Psychology, University of Queensland, Brisbane, Australia

Published: 01 October 2013
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Twin studies and behavior genetics address the questions raised by the nature versus nurture debate. Their aim is to estimate the extent to which individual differences in complex traits or phenotypes result from genetic and environmental influences. The vast majority of human behaviors and characteristics are complex traits and are influenced by both genetic and environmental influences, as well as the interplay between these two. Based on the differing genetic relatedness of monozygotic co-twins and dizygotic co-twins, the classical twin model allows for an estimation of the relative importance of these etiological factors. The classical twin model can be extended in multiple ways, depending on the phenotype, research question, and research design. In addition to the classical twin methodology, several such extensions are described in this chapter.

Introduction

In this chapter we will discuss some of the methodologies used in the genetic analysis of quantitative traits. The aim of this chapter is to provide an introduction to basic genetics and to the twin design as a method to study the etiology of individual differences in complex traits.

The phenotypic variation among species is extensive. In humans, this variation is observed across physical (e.g., height or weight), physiological (e.g., blood pressure or brain volume), cognitive (e.g., intelligence), and psychological (e.g., personality or depression) domains. The question of whether these individual differences in complex behavioral traits are caused by genetic (heritable) or environmental influences, or a combination of the two, is referred to as the nature versus nurture debate (Fig. 10.1 ), and dates back to ancient Greece ( Loehlin, 2009 ).

Comparing individual variation at the population level to the variation within a family shows that there is less variation within families than between families, with the least variation observed between individuals sharing their entire genome (i.e., identical twins). In the late 1800s, Francis Galton developed a number of statistical techniques including the correlation coefficient and regression, in order to study the way in which family resemblance for many traits increased with family relatedness ( Galton, 1889 ). These statistics underlie much of the behavioral and quantitative genetic techniques used today ( Plomin, DeFries, McClearn, & McGuffin, 2001 ).

The broad aim of quantitative genetic analyses is to estimate the extent to which differences observed among individuals result from genetic and environmental influences, and can thus directly address the questions raised by the nature-nurture debate. As shown in Figure 10.1 , within the scientific community it is generally accepted that the vast majority of human behaviors and characteristics are complex traits and are influenced by both genetic and environmental influences, as well as the interplay between these two.

Nature versus Nurture.

Notes: Individual differences on traits result from genetic and/or environmental influences, or a combination of both. Mendelian traits, such as Huntington’s disease, are (almost) entirely inherited, while traumatic brain injury can be caused by environmental exposures, such as a car accident. Quantitative traits are generally influenced by a combination of genetic and environmental influences.

Although the degree of sharing of environmental factors among related (as well as unrelated) individuals is hard to measure, the sharing of genetic factors between individuals is easy to quantify, because inheritance of most genetic material follows very simple rules. These rules were first postulated by Gregor Mendel in 1866 and have come to be referred to as the basic laws of heredity ( Plomin, DeFries, McClearn, & McGuffin, 2001 ). In his experimentation with pea plants, Mendel found that when crossing plants with different colored flowers (white and purple) the flowers of the resulting plant would still be purple (rather than lavender). These results led him to develop the idea of genetic loci (which he termed “heredity units"), which could either be additive or dominant. He concluded that each individual has two alleles , or versions of the genetic locus, one from each parent (note that didactic examples such as this one, are usually illustrated using the example of a bi-allelic locus with two variants, A and a; however, some types of loci have many more than two possible variants).

Within somatic cells, the DNA is arranged in two paired strands. Mendel established that, following the binomial distribution, within each individual the alleles at each locus can be paired as aa, Aa , or AA , with each pairing being referred to as a genotype . Cases where the genotype is composed of two copies of the same allele (i.e., AA or aa ), are denoted homozygotes , while those with differing alleles (i.e., Aa ), are referred to as heterozygotes . The frequency of each genotype reflects the frequency of each allele in the population. For example, if a has an allele frequency of p, and A has a frequency of q in the population, the frequencies of the three genotypes, aa, Aa , or AA , are p 2 , 2pq and q 2 . In didactic examples, q = 1 − p , however, this is not always true. Note also, that the frequency of the heterozygote is twice pq as this genotype can arise in two ways, Aa and aA , where the A allele can be inherited from either the mother or the father.

Mendel’s findings are summarized in two laws: (1) the law of segregation; and (2) the law of independent assortment ( Plomin, DeFries, McClearn, & McGuffin, 2001 ). The process of segregation occurs during gametogenesis , when the gametes or sex cells (egg and sperm) are formed. During this process the genotype separates; for example, a male with a heterozygous Aa genotype will usually develop approximately equal numbers of sperm carrying the A allele and the a allele. Thus, each of the parental alleles has an equal chance of being transmitted, regardless of the frequency of each allele within the population. Assortment refers to the process of segregation among many loci. This principle states that the inheritance of these loci is independent such that the process of segregation is random at each locus. An important caveat is that this principle does not hold if the loci are closely located on the same chromosome. This is because at the physical level stretches of DNA are co-inherited. This fact forms the basis of linkage analysis, which will be discussed in Chapter 11 .

A genetic effect is described as dominant if the heterozygous individuals show the same behavior or phenotype as one of the homozygotes. By convention, a capital letter (e.g., A ), is used to represent the dominant allele, while a lower case letter (e.g., a ), is used to describe the recessive allele. However, if the gene effects are additive (i.e., the trait value increases with each additional increasing allele, denoted A ), the observed trait or phenotype in the heterozygote will lie midway between the two homozygotes. While Mendelian laws were initially thought to apply only to traits influenced by single genes, it was subsequently shown by R.A. Fisher (1918 ) that they also apply to many complex and quantitative traits, where the phenotype results in part from the combined influence of multiple genes (Fig. 10.2 ).

At a genome-wide level the average amount of genetic sharing between two relatives can be calculated based on biometric genetic theory. A child shares 50% of their autosomal (i.e., non-sex chromosome) DNA with each of his parents. Similarly, siblings share on average 50% of their genetic material, and grandparents share on average 25% of their genetic material with their grandchildren (the same applies for half siblings and avuncular relationships). Analysis of data from related individuals, making use of the differences in genetic sharing between relatives, provides one way of estimating the relative magnitude of genetic (or heritable) and environmental influences on trait variation.

Heritability can be defined as the proportion of the phenotypic variance in a trait that is attributable to the effects of genetic variation ( Neale & Maes, 2004 ). Generally, the more diverse the relatedness of the participants included (i.e., parents, siblings, and cousins), the greater the power to disentangle genetic and environmental influences on trait variation ( Medland & Hatemi, 2009 ). A particularly attractive design to investigate genetic and environmental influences on trait variation is the adoption study. By comparing the resemblance between the adoptee and the adoptive family (environmental influence) versus the resemblance between the adoptee and the biological family (genetic influence) for a given trait, the relative contribution of genes and environment to variance in this trait can be estimated. However, this design is complicated by the difficulties associated with collecting data from the biological family, the nonrandom placement of adoptees and the effects of pre-adoptive experiences.

Genotypes to phenotypes: From single gene action to complex polygenic traits.

Notes: Given that each gene has 3 possible combinations of alleles ( aa, Aa , and AA ), under the assumption of additive genetic effects the homozygotes would be on the lower ( aa ) and the upper ( AA ) end of the phenotypic distribution, while the heterozygote is in the middle. If we extend this to include multiple genes, as would be the case for complex polygenic traits, with the inclusion of each new gene the distribution of phenotypic values in the sample increasingly resembles a normal distribution.

Arguably, the classical twin study represents the most practical and powerful family design available to researchers. This method compares the within-pair similarity of identical (monozygotic ; MZ) and non-identical (dizygotic; DZ) twins. Monozygotic twins develop when the developing zygote (fertilized egg) divides, usually within 2 weeks of fertilization, and the two parts continue to develop independently (Fig. 10.3 ). In this case, both twins originate from the same sperm and egg, which makes them genetically identical and, therefore, they are always of the same sex. The later the twinning event occurs, the more likely the twins are to share chorion (which is comprised of the placenta and related membranes) and amniotic sacs ( Derom et al., 2001 ; Baergen, 2011 ). In contrast, DZ twinning occurs when more than one egg is released by the ovaries at the same time and, subsequently, each of the eggs is fertilized by a separate sperm cell. As a result, DZ twins do not differ from normal siblings genetically, sharing on average 50% of their genetic loci. However, they do have shared prenatal environments, as they were conceived at the same time and shared the womb. Dizygotic twins, like normal siblings, can either be of the same or of the opposite sex (i.e., a male and a female).

In order to facilitate the use of twin designs many countries have set up twin registries, collecting information on twins and their families. The oldest national twin register is the Danish Twin Registry, initiated in 1954, currently listing more than 75,000 twin pairs ( Skytthe et al., 2006 ). Subsequently, many more countries have followed the Danish example by setting up large nationwide twin registries (e.g., Sweden, Australia, and the Netherlands). One of the biggest challenges for twin registries is the correct ascertainment of the zygosity of twins (MZ versus DZ). Until recently, zygosity was mainly determined by means of a questionnaire assessing twin similarity between same-sex twins. This method has proven to be efficient in 95% of cases ( Kasriel & Eaves, 1976 ). Over the past thirty years, however, gene-finding methods became available, enabling the precise determination of zygosity status; these have largely been used to confirm and replace zygosity determination based on questionnaires ( Plomin, DeFries, McClearn, & McGuffin, 2001 ). To date numerous twin studies on a very large variety of traits have been conducted. Although originally the focus was on “simple” (physical) traits such as height, soon twin studies were used to explore the variation in increasingly complex traits, such as intelligence, personality, psychiatric disorders, etc.

The development of monozygotic versus dizygotic twins.

As mentioned above, the phenotypes and genotypes of related individuals are not independent, nor are they identically distributed; therefore, many standard statistical tests cannot and/or should not be applied in the analyses of relatives. Most analyses based on related individuals use statistical approaches based on likelihood, as this very general statistical framework has high modeling flexibility (e.g., Maes et al., 2009 ; Neale & Maes, 2004 ). These statistical approaches will be explained in this chapter.

The Classical Twin Model

As mentioned above, the classical twin design draws its explanatory power from the differences in genetic sharing of MZ and DZ twins. Using simultaneous equations, this knowledge can be used to partition the variance in a phenotype into that which results from additive genetic (A), dominant genetic (D), common or shared environmental (C) and unique or unshared environmental (E) influences. Additive and dominant genetic influences refer to the cumulative effect of genes acting in an additive or dominant manner. Common environmental influences refer to experiences shared by co-twins, including the intrauterine environment, and the social and cultural rearing environment (i.e., same socio-economic status, parents, diet, etc.) Unique environmental factors comprise all aspects of the physical and social environment experienced differentially by individuals in a family, such as illness, physical and psychological trauma, peers, teachers, etc. This component also includes measurement error and gene–environment interactions when not accounted for in the modeling ( Eaves, Last, Martin, & Jinks, 1977 ; Jinks & Fulker, 1970 ).

The classical twin model assumes that phenotypic variation results from the sum of these sources, such that the total variance can be written as: A + C + D + E. Monozygotic twins share approximately 100% of their genetic information (A and D), as well as 100% of their common or shared environment (C).Thus, the MZ covariance (i.e., the covariance between twin 1 and 2 of an MZ pair) can be written as: A + C + D. Conversely, DZ twins are assumed to share, on average, 50% of their segregating genes, and 25% of the time they share the same paternal and maternal alleles (which are required to share dominant effects). In addition, they are assumed to share 100% of the common environment. Thus, the DZ covariance can be written as: 0.5A + C + 0.25D.

As will be obvious from these three equations, there is insufficient information within the classical twin model to simultaneously estimate the magnitude of all four sources of variance. As such, twin studies tend to estimate either C or D. This is because these measures are negatively confounded; that is, dominance effects tend to reduce the DZ correlation relative to the MZ correlation (i.e., make MZ twins more similar), whereas the common environment tends to increase the DZ correlation relative to the MZ correlation (i.e., makes DZ twins more similar). One or the other source can be assumed absent depending on whether the DZ twin correlation is greater or less than half the MZ correlation. In general an ACE model would be estimated if the DZ correlation is greater than half of the MZ correlation, and an ADE model if the DZ correlation is less than half of the MZ correlation.

In either case, the extent to which MZ twin pairs resemble each other more for a trait (i.e., show higher twin correlations) than DZ twin pairs gives information on the relative influence of genetic versus environmental factors on a trait. Under the ACE model, the proportion of variance resulting from additive effects (A) or the heritability ( a 2 ), can be calculated as twice the difference between the MZ and DZ correlations ( Holzinger, 1929 ): a 2 = 2 ( r MZ ∼ r DZ ). An estimate of shared environment (C or c 2 ) can be calculated via twice the DZ correlation minus the MZ correlation: c 2 = 2 r DZ ∼ r MZ . Because MZ twins do not share the non-shared environmental variance (E or e 2 ), 1 minus the MZ correlation gives the contribution of the non-shared environment: e 2 = 1 − r MZ . Because correlations are standardized (with unit variance), the total phenotypic variance (A + C + E) is also standardized. Therefore, each variance component represents the relative contribution to a trait.

Twin correlations.

Notes: Scatter plots showing MZ and DZ twin pair correlations for (a) height in cm (males only) and (b) adolescent misconduct based on questionnaire data. Twin correlations for height indicate a high heritability for this trait, whereas twin correlations for adolescent misconduct point to moderate heritability. Data were provided by the Genetic Epidemiology Laboratory, Queensland Institute of Medical Research.

If we apply these formulas to the example data for height in Figure 10.4a , where the MZ twin correlation is 0.88 and the DZ correlation is 0.44, the heritability would be a 2 = 2 * (0.88 − 0.44) = 0.88, and the common environmental influence would be c 2 = (2 * 0.44) − 0.88 = 0. A heritability of 0.88 should be interpreted to mean that 88% of the population variance in a trait can be attributed to variation at the genetic level. Importantly, this cannot be interpreted as height being genetically controlled for 88% of individuals. The estimate of the proportion of variance accounted for by E for this trait is 12%; notably, variance resulting from measurement error is also included in this estimate. For adolescent misconduct (Fig. 10.4b ), where the MZ twin correlation is 0.70 and the DZ correlation is 0.47, the heritability would be a 2 = 2 * (0.70 − 0.47) = 0.46 and the common environmental influence would be c 2 = (2*0.47)− 0.70 = 0.24.

Figure 10.4b also illustrates how the range of values for the trait under investigation can affect the data distribution. In twin modeling it is important that the trait of interest shows a normal distribution in the entire sample, as well as in the MZ and DZ subsamples. If this is not the case, transformation of the data may be necessary. Otherwise, alternative models are available for data that violate this assumption ( see section on the liability threshold model).

Structural Equation Modeling

The formulas developed by Holzinger (1929 ) are limited in their application to continuous phenotypes and univariate contexts. As much of the focus of modern quantitative genetics is on estimating the contribution of genetic effects to the covariation between phenotypes, the Holzinger method is seldom used in contemporary studies. The majority of current studies now use more sophisticated structural equation models to estimate these influences ( Eaves, 1969 ; Eaves, Last, Martin, & Jinks, 1977 ; Martin & Eaves, 1977 ). These new methodologies allowed the development of models that more accurately reflect the complexities of human behavior and development ( Mehta & Neale, 2005 ). Structural equation modeling (SEM) is used to test complex relationships between observed (measured) and unobserved (latent) variables and also relationships between two or more latent variables ( Wright, 1921 ). For a more detailed explanation of structural equation modeling methodology, please refer to Chapter 15 . The parameters of the structural equation model for the pattern of MZ and DZ variances and covariances can be estimated by several approaches, including maximum likelihood and weighted least squares . In this chapter we will assume that maximum likelihood methods are used.

Path diagrams (Fig. 10.5 ) provide a graphical representation of models. Path diagrams can be mapped directly to mathematical equations and are sometimes easier to understand. Structural equation modeling allows us to obtain maximum likelihood estimates of phenotypic means and genetic and environmental variance components, while also allowing for the explicit modeling of effects of covariates (e.g., sex, age, IQ) and interaction effects. The aim of maximum likelihood estimation is to find the parameter values that explain the observed data best. Likelihood ratio tests, which are asymptotically distributed as chi-square (χ 2 ), are used to compare the goodness of fit of reduced submodels (i.e., AE, CE, and E models) with that of the full ACE model. Model fit is evaluated according to the principle of parsimony , in which models with fewer parameters are considered preferable if they show no significant worsening of fit ( p > 0.05) when compared to a full ACE model. A larger χ 2 (corresponding to a low probability) indicates a poor fit of the submodel; a smaller x 2 (accompanied by a non-significant p value) indicates that the data are consistent with the fitted model.

For example, if dropping the A parameter from the ACE model (i.e., by equating the additive genetic path coefficient to zero) results in a significant worsening of model fit ( p < 0.05), this signifies that the simpler CE model is not an accurate description of the observed data, and thereby indicates the significance of the genetic influences. Components of variance (A, C, or E) are calculated by dividing the squared value of the corresponding path coefficient by the total variance (i.e., the summed squared values of all path coefficients).

From Figure 10.5 , the following algebraic statements can be derived for the variance/covariance matrices of MZ and DZ twins (Matrix 10.1 ), where the variance for each twin is located on the diagonal (shaded dark gray) with the covariance between twins on the off-diagonal (shaded light grey).

As mentioned previously, when estimating an ACE model it is assumed that there is no variance resulting from non-additive genetic influences (D).

Path diagram depicting the classical twin model. Notes: P = phenotype; T1 = twin 1 of a pair; T2 = twin 2 of a pair; MZ = monozygotic; DZ = dizygotic; A = additive genetic influences; C = common environmental influences; E = unique environmental influences; a = additive genetic path coefficient; c = common environmental path coefficient; e = unique environmental path coefficient. Circles represent latent, unobserved variables; squares represent observed phenotypes; single-headed arrows represent influences of latent variables on observed variables; double-headed arrows represent (co) variances. Correlations between additive genetic factors (A) are fixed at 1 for MZ pairs and 0.5 for DZ pairs, because MZ twins share 100% of their segregating genes and DZ twins on average 50%. Correlations between common environmental factors (C) are fixed at 1 for both MZ and DZ twins, because both types of twins share 100% of their familial environment. By definition, E factors are left uncorrelated in both MZ and DZ twins because they are unique for each individual.

Variance resulting from non-additive genetic influences (D) may also be estimated, where correlations between MZ twins are fixed at 1 and correlations between DZ twins are fixed at 0.25. The covariance structure of an ADE model is summarized in Figure 10.6 and in the matrix below (Matrix 10.2 ), where the variance for each twin is located on the diagonal (shaded dark gray) with the covariance between twins on the off-diagonal (shaded light grey).

The most commonly used software package for twin modeling is the flexible matrix algebra program, Mx ( Neale, Boker, Xie, & Maes, 2002 ); Mx can be downloaded from: http://www.vcu.edu/mx/ . The Mx website also contains (links to) example code for various models. Recently, Mx has been implemented within the R programming environment under the new name OpenMx ( Boker et al., 2011 ); OpenMx and R can be downloaded from the following pages: http://openmx.psyc.virginia.edu/installingopenmx and http://www.r-project.org/ , respectively. The OpenMx website also contains example code as well as a forum where OpenMx-related topics can be discussed. Another program suitable for twin modeling is Mplus ( Muthen & Muthen, 1998-2010 ); the Mplus homepage can be found at: http://www.statmodel.com/ . For family studies, when not utilizing twin data, SOLAR (Sequential Oligogenic Linkage Analysis Routines) can be used; the software can be downloaded from: http://solar.sfbrgenetics.org/download.html .

Path diagram depicting the ADE model.

Notes: P = phenotype; T1 = twin 1 of a pair; T2 = twin 2 of a pair; MZ = monozygotic; DZ = dizygotic; A = additive genetic influences; D = dominance genetic influences; E = unique environmental influences; a = additive genetic path coefficient; d = dominance genetic path coefficient; e = unique environmental path coefficient. Circles represent latent, unobserved variables; squares represent observed phenotypes; single-headed arrows represent influences of latent variables on observed variables; double-headed arrows represent (co)variances.

Assumptions of the Classical Twin Model

Several assumptions underlie the classical twin design, including generalizability, random mating, equal environments, and absence of genotype-environment interaction or genotype-environment correlation. These assumptions will be explained below.

Generalizability

A frequently asked question regarding twin studies is whether their results can be generalized to the general population (i.e., singletons). The experience of being a twin, including the sharing of limited space and resources during gestation, and the differences in the birth process, may cause twins to be different from singletons. Generalizability can be assessed by comparing means and variances for a trait between twins and members of the general population, which are matched for age and sex. However, the best method of assessing generalizability is by extending the twin design to include the twins’ own siblings within the analysis. Comparing the DZ co-twin correlation with twin-sibling correlations allows an examination of the role of pre-or perinatal factors on the trait of interest (correcting for age). One of the advantages of comparing twins with their own non-twin siblings is that by using siblings as the control group we can, at least partly, control for variance in maternal size (i.e., intrauterine size and body shape, which may influence the length of gestation and ease of delivery) and the effects of genetic transmission (as both DZ twins and their full siblings share, on average, 50% of their genetic material). Although twins do differ from singletons for some traits, especially those related to prenatal growth, most studies generally do not find differences in personality and social traits ( Evans, Gillespie, & Martin, 2002 ). If this assumption is violated, additional twin-specific effects will need to be incorporated in the model.

Random Mating

The assumption that DZ twins share on average 50% of their genes no longer holds true in the case of assortative mating . Visscher et al. (2006 ) used molecular data to get exact measures of average genetic sharing of sibling pairs, which in a sample of 4,401 sibling pairs ranged from 37% to 61%. Assortative mating may be based on phenotypic similarity (positive assortment) or dissimilarity (negative assortment). Positive assortative mating refers to the situation where prospective mating partners are more likely to select each other when they possess similar traits. As these traits will probably be at least partly caused by similar gene variants, their children are likely to share more than 50% of their genetic information, for genetic loci influencing the trait of interest. To illustrate, Maes et al. (1998 ) investigated assortative mating in the context of major depression, generalized anxiety disorder, panic disorder, and phobias, and found considerable associations between partners for most psychiatric diagnoses. Assortment was observed both within and between classes of psychiatric disorders. Variables correlated with the psychiatric diagnoses, such as age, religious attendance, and education, did explain part, but not all, of the assortment between partners.

Because assortative mating increases the correlations between mates, estimates of the relative genetic and environmental influences based on a twin design will be biased if assortative mating is present and is not appropriately accounted for. When parents are more genetically alike than expected by chance, the DZ twins’ genetic resemblance will on average be more than 50% because of the transmission of the correlated parental genes. As a result, the resemblance of DZ twin pairs will increase relative to MZ twin pairs. Unmodeled assortative mating will therefore result in artificially inflated estimates of the shared environmental component and an underestimation of heritability. The presence of assortative mating can be studied by calculation of the phenotypic correlation between the parents of twins, or the phenotypic correlation between twins and their spouses, assuming that the extent of assortative mating does not change across generations.

The Degree of Genetic Similarity Between MZ Twins

Although MZ twins are assumed to be genetically identical, a study of19 MZ twin pairs detected subtle differences in copy number variations of the DNA ( Bruder et al., 2008 ). These differences occur when a set of coding nucleotide bases in DNA are missing or when extra copies appear. It is currently theorized that at the time of conception MZ twins are genetically identical; however, during subsequent DNA replications and cell division, a small number of mutations may occur. The same phenomenon would also decrease the “known” degree of relatedness between DZ twins (50%), parents and children (50%), half siblings (25%), etc. This would also mean that age differences would influence the degree of relatedness in family studies (i.e., newborns would have fewer mutations than their older family members simply because they are younger).

Equal Environments

The twin method partitions the environment into that which is shared between co-twins and that which is unshared. Generally the shared environment is assumed to include prenatal effects and the effects of growing up in the same household. This interpretation relies on the assumption that MZ and DZ twins experience shared environments to the same extent (i.e., that trait-relevant environmental influences contribute equally to the resemblance of MZ and DZ twin pairs). This assumption has received much attention. It has been found that MZ twins are treated more similarly than DZ twins in certain aspects; as young children they share a bedroom and are dressed alike more often, and they are more likely to share the same friends and stay in closer contact once they leave home ( Cohen, Dibble, Grawe, & Pollin, 1973 ; Kendler, Heath, Martin, & Eaves, 1987 ; Loehlin & Nichols, 1976 ). However, it is not clear whether greater environmental similarity results in greater phenotypic similarity.

Furthermore, as highlighted by Heath et al. (1989 ), environmental inequality would only result in bias if the trait of interest happened to be affected by those environmental factors that differ between twins. Salient environmental influences that are more similar for MZ compared to DZ twins would increase twin correlations in MZ twins, inappropriately inflating estimates of trait heritability. Several methods have been used to test the equal environments assumption, including correlating perceived zygosity with the trait while controlling for actual zygosity ( Kendler et al., 1993 ; Matheny, Wilson, & Dolan, 1976 ; Plomin, Willerman, & Loehlin, 1976 ; Scarr, 1982 ; Scarr & Carter-Saltzman, 1979 ), direct observation of family members and others to examine their self-initiated and twin-initiated behaviors toward the different twin types ( Lytton, Martin, & Eaves, 1977 ), and correlating the similarity of the twin environments with the trait while controlling for actual zygosity ( Borkenau, Riemann, Angleitner, & Spinath, 2002 ; Heath, Jardine, & Martin, 1989 ; Kendler et al., 1987 ; Martin et al., 1986 ).

A modeling-based approach is the extension of the classical ACE model by partitioning the common environment into the usual common environment, C residual , which is completely correlated for all twin pairs, and that which is influenced by the perceived zygosity, C specigc , which is parameterized to be completely correlated if both twins perceive themselves to be MZ, completely uncorrelated if both twins perceive themselves to be DZ, and correlated at 0.5 if the twins disagree about their perceived zygosity ( Hettema, Neale, & Kendler, 1995 ; Kendler et al., 1993 ; Scarr & Carter-Saltzman, 1979 ; Xian et al., 2000 ).

Furthermore, when data have been collected from non-twin siblings, checking for differences between the DZ covariance and the twin–sibling and sibling–sibling covariances can provide an additional test of the equal environments assumption. Arguably, if the more similar treatment of MZ twins were affecting their trait values, one might also expect more similar treatment of DZ twins as compared to regular siblings. When using ordinal data, equality of the thresholds of MZ and DZ twins indicates there are no differences in variances between MZ and DZ twin pairs, excluding the possibility of an extra environmental influence specific to MZ twins. The most recent method to remove equal environment biases allows heritability to be estimated from non-twin siblings ( Visscher et al., 2006 ).

Although MZ and DZ mean differences have been found for traits such as birth weight ( Koziel, 1998 ) and similar dress ( Matheny, Wilson, & Dolan, 1976 ), rigorous and frequent testing of characteristics such as physical twin similarity( Hettema, Neale, & Kendler, 1995 ), self-perceived zygosity ( Xian et al., 2000 ), perceived zygosity and associated parental approach to rearing their twins ( Cronk et al., 2002 ; Kendler & Gardner, 1998 ; Kendler et al., 1993 ; Kendler et al., 1994 ), self-reported similarity of childhood experiences ( Borkenau, Riemann, Angleitner, & Spinath, 2002 ), and physical and emotional closeness between the twins ( Cronk et al., 2002 ; Kendler & Gardner, 1998 ; LaBuda, Svikis, & Pickens, 1997 ), has shown that these traits are uncorrelated with zygosity differences in intelligence, personality, and psychiatric disorders such as alcohol and illicit drug dependence, major depression, anxiety, and externalizing disorders, thereby supporting the validity of the equal environmental assumption in twin studies assessing these phenotypes.

Genotype-Environment Interaction

The classical twin model does not take the possible presence of genotype–environment (GxE) interaction into account. Gene–environment interaction occurs when environments have differential effects on different genotypes. For example, Boomsma and colleagues (1999) found that a religious upbringing reduces the influence of genetic factors on disinhibition. A recent study of borderline personality disorder by Distel et al. (2011 ) also found evidence for GxE interaction. For individuals who had experienced a divorce/break-up, violent assault, sexual assault, or job loss, environmental variance for borderline personality disorder features was higher, leading to a lower heritability in exposed individuals. Jinks and Fulker (1970 ) suggested a screening test for GxE interaction using data from MZ twin pairs, whereby the intrapair differences are plotted against the sum of the co-twins’ phenotypic values. A significant correlation between these two indicates the presence of GxE interaction. However, to avoid spurious results, this test requires data from MZ twins reared apart, and it is unsuitable for binary data. Purcell (2002 ) proposed another approach to the detection of GxE interaction, which allows the explicit modeling of the interaction through extension of the classical twin design. In order to model the interaction, the environmental covariate(s) must be entered into the analysis as an observed variable, thus limiting the application of this approach to the study of already known or suspected environmental covariates.

Genotype-Environment Correlation

Gene–environment correlation ( r GE ) occurs when individuals actively or passively expose themselves to different environments depending on their genotype, or when individuals’ genotypes affect their social interactions or influence the responses they elicit from other individuals ( Falconer & Mackay, 1996 ; Plomin, DeFries, & Loehlin, 1977 ). If r GE is positive it could result in an increase in the total phenotypic variance of the trait. Alternatively, in the case of a negative r GE , the total phenotypic variance would be decreased. Distel et al. (2011 ) also found evidence for gene–environment correlation. The genetic effects that influence borderline personality disorder features also increased the likelihood of being exposed to certain life events. Three types of r GE have been described by Plomin et al. (1977 ), namely cultural transmission, autocorrelation, and sibling effects .

Cultural transmission refers to the environmental effect of the parental phenotype on the offspring’s phenotype ( Neale & Maes, 2004 ; i.e., resemblance between parents and offspring that results from a home environment created by the parents). To use a simplistic example, imagine two children taking part in a study of reading ability. Both children come from the same socio-economic strata and have very similar backgrounds. The parents of child A enjoy reading and have many books in their home, thus child A is read to as young child, observes his/her parents reading, and grows up in an environment where books are accessible. The parents of child B do not enjoy reading; they do not own many books and do not use the local library. Child B thus grows up in an environment where books are less accessible, and despite being read to as young child because the parents feel this is important, child B does not often observe his/her parents reading. As it is likely that the environmental differences between the two children are related to the genetic variants influencing reading ability, the environmental and genetic effects become correlated. Failure to model this correlation can inflate the heritability of reading ability in the children. The effects of cultural transmission may be examined by extending the twin design to include parental data. Such a design also allows for a test of the assumption of random or non-assortative mating ( Neale & Maes, 2004 ).

Gene–environment autocorrelation occurs when environments are not randomly assigned to each individual but are, in part, individually selected on the basis of genetically influenced preferences. For example, when gifted individuals create or evoke situations that further enhance their intellectual ability, or when genetically introverted individuals choose to avoid situations where they may be the focus of attention.

Sibling interactions may be either cooperative, increasing the trait value of the co-twin (imitation effect), or competitive, decreasing the trait value in the co-twin (contrast effect; Carey, 1986 ). Cooperation effects increase the variance and decrease the covariance of MZ twins relative to DZ twins, while competition produces the opposite effects.

Correlated effects of genotypes and environments are difficult to detect. If not explicitly modeled, r GE between the latent A and E variables behave like additive effects, whereas r GE between the latent A and C variables acts like C.

Extensions to the Classical Twin Model

The classical twin model is the most basic twin model one can employ. There are many extensions available, the most basic of which is the incorporation of covariates to improve the estimation of phenotypic means. This allows for correction for effects such as age and gender, but also for effects of other variables that may confound the estimation of heritability. For example, if our trait of interest is cerebro-vascular disease in addition to age and gender, we may want to include smoking behavior as a covariate; if our trait of interest is education, we may want to include socio-economic status as a covariate.

Sex Limitation

Sex differences may obscure the data in different ways. Opposite-sex DZ twins can reduce the overall DZ twin covariance significantly if males and females differ greatly in their phenotypic values. Sex limitation refers to sex differences in the magnitude and/or proportion of the variance accounted for by genetic and environmental effects ( Neale & Maes, 2004 ). If twin pair correlations differ between the sexes within zygosity, it is better to estimate A, C, and E separately for males and females. Three types of sex limitation have been described: quantitative, qualitative, and scalar.

In the quantitative sex limitation model the genetic and environmental sources of variance and covariance in males and females are assumed to be the same (i.e., sex-specific pathways are fixed to zero) but the magnitudes of these effects are allowed to differ and the correlations for additive genetic and common environmental influences in the opposite-sex DZ pairs are assumed to be 0.5 and 1, respectively. If data from opposite-sex DZ twins have been collected, the difference in fit (χ 2 ) between this model and the qualitative sex limitation model can be used to examine whether the same genetic or environmental factors are influencing males and females ( Neale & Maes, 2004 ). Silventoinen et al. (2001 ) did this for height in two cohorts of twins (born in 1938-1949 and in 1975-1979) and found that the heritability estimates were higher among men ( h 2 = 0.87 in the older cohort and h 2 = 0.82 in the younger cohort) than women ( h 2 = 0.78 and h 2 = 0.67, respectively). Sex-specific genetic factors were not statistically significant in either cohort, suggesting that the same genes contribute to variation in body height for both men and women.

The hypothesis underlying qualitative sex limitation models is that different genetic or environmental factors influence trait variation in males and females. This model includes an extra genetic or environmental component ( m 2 ) that contributes to either males or females. Differences in both genetic and environmental effects cannot be tested simultaneously when working with twin and sibling data. Therefore, one would usually run this model twice; once specifying m 2 as an additive genetic parameter ( r = 0.5 for DZ twins) and once specifying m 2 as a common environment parameter ( r = 1 for DZ twins). Derks and colleagues (2007 ) found this to be the case for attention deficit-hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD). The heritabilities for both ADHD and ODD were high and of a similar magnitude for boys and girls. However, the source of this genetic variation differed between boys and girls, indicating that some genetic loci may be having sex-specific influences on these traits.

The scalar sex limitation is the simplest and most restrictive of the three models. Here the absolute magnitude of the total variance, and thus the unstandardized variance components, differ between males and females while the proportion of variance accounted for by genetic and environmental effects, that is, the standardized variance components, are equal across sexes. In the scalar model not only are the sex-specific effects removed, but the variance components for females are all constrained to be equal to a scalar multiple ( k ) of the male variance components, such that a f 2 = k a m 2 , , and e f 2 = k e m 2 ( Neale & Maes, 2004 ). This model is a submodel of both the quantitative and qualitative sex limitation models, and can only be tested using continuous data, as variances are fixed to unity when working with ordinal data.

Normally you would test for the presence of sex limitation as part of testing a series of assumptions prior to fitting the ACE or ADE model. These assumptions include the equality of means and variances across zygosity and birth order, the equality of means and variances between twins and siblings, and the equality of means, variances, and covariances across the two sexes.

Liability Threshold Model

The classical twin design assumes that the trait of interest is a continuous variable, with a normal distribution. However, many traits that may be of interest are ordinal or dichotomous variables, such as medical or psychiatric diagnoses. For such variables, a liability threshold model can be used to estimate twin correlations and heritability. Threshold models assume that there is an underlying continuum of liability (e.g., to depression or ADHD) that is normally distributed in the population, and that our measurement categories (e.g., depressed/not depressed) result from one or more artificial divisions (thresholds) overlaying this normal distribution. Analyses are effectively performed on the underlying liability to the trait, resulting in estimates of the heritability of the liability. Figure 10.7 illustrates the threshold model. Panel A shows a model with a single threshold, separating persons into two classes, unaffected or affected, such as children with ADHD and controls. Panel B shows a liability threshold model with four thresholds (i.e., five categories), which could apply to a study of self-rated health, where the response categories were “very good,” “good,” “fair,” “poor", and “very poor” (e.g., Mosing etal., 2009 ). Liability to psychiatric disorders such as ADHD, depression, anxiety, and schizophrenia has been found to be influenced by genetic factors ( Hettema, Neale, & Kendler, 2001 ; Jepsen & Michel, 2006 ; Kendler, Gatz, Gardner, & Pedersen, 2006a , 2006b ; Sullivan, Kendler, & Neale, 2003 ; Sullivan, Neale, & Kendler, 2000 ), with heritability estimates of >70%.

The threshold model.

Notes: (a) Univariate normal distribution for dichotomous phenotype. One threshold is shown (at z-value +0.5) corresponding to 2 categories with the frequencies 69% and 31%. (b) Univariate normal distribution with thresholds distinguishing ordered response categories. Four thresholds are shown (at z-values −2.30, −1.70, −0.5, and +1) corresponding to 5 categories with the frequencies, 1%, 3%, 27%, 53%, and 16%.

Including Data from Additional Family Members

As briefly mentioned above, the classical twin design can be extended by including singleton (non-twin) siblings, parents, children, and spouses. Including additional family members substantially enhances the statistical power to detect non-additive genetic and common environmental influences resulting from a greater number of observed covariance statistics ( Posthuma et al., 2003 ). The power to detect common environmental influences is maximized when there are four times as many DZ pairs as MZ pairs ( Nance & Neale, 1989 ). As siblings have the same amount of genetic material in common as DZ twins (on average 50%), including data from extra siblings in the model effectively increases the DZ to MZ ratio. As discussed above, adding data from non-twin siblings makes it possible to test for twin-specific environmental influences. The variance and covariance of additional siblings are modeled in the same way as for a DZ twin (Fig. 10.8 ). If we were to include the data of one extra sibling the typical variance-covariance matrix would

Path diagram depicting the extended twin model.

Notes: P = phenotype; T1 = twin 1 of a pair; T2 = twin 2 of a pair; SIB = singleton sibling; MZ = monozygotic; DZ = dizygotic; A = additive genetic influences; C = common environmental influences; E = unique environmental influences; a = additive genetic path coefficient; c = common environmental path coefficient; e = unique environmental path coefficient. Circles represent latent, unobserved variables; squares represent observed phenotypes; single-headed arrows represent influences of latent variables on observed variables; double-headed arrows represent (co)variances.

be extended as shown in Matrix 10.3 . Additional siblings can be added in the same way. Variances are on the diagonal highlighted in the darkest shade of gray, the intrapair covariances are a shade lighter on the off-diagonal, and the twin–sibling covariances are highlighted in the lightest shade of grey on the outermost row and column of the matrix.

The extended twin family model or the nuclear family model also allows for the estimation of more parameters and relaxed assumptions regarding mating and cultural transmission. For example, adding parental data to the model makes it possible to estimate effects from assortative mating, familial transmission, sibling environment, and the correlation between additive genetic effects and family environment ( Keller et al., 2009 ), as well as allowing for the simultaneous estimation of C and D influences.

Another method allowing for the estimation of A, C, D and E in the same model is the twin adoption design. Here, twins raised apart (with no shared environmental influences) are compared to twins raised together. This design has a great explanatory power to facilitate separation of biological from environmental influences ( Medland & Hatemi, 2009 ). However, because of ethical and legal hurdles, twin adoption studies are increasingly difficult to conduct. Also, modern adoption policies facilitate twins being adopted together, rapidly decreasing the number of twins reared apart. Finally, there are other methodological factors that have to be taken into account, such as contact with the biological family, age of adoption, time spent in state care or protective custody, and selective placement (i.e., matching of the infants’ biological and adoptive environments), each of which may bias the sample. As a result of these caveats, which are hard to overcome, the twin adoption design is used only rarely and will not be explained here in further detail.

Multivariate Modeling

The twin model can also be extended to include multiple phenotypes. In the case of a multivariate design the aim is to decompose the covariance between traits into that caused by A, C, and E in the same way as one would with the phenotypic variance of a single trait. A multivariate design allows us to investigate the extent to which common sets of genes (genetic correlation, r g ), shared environmental factors (common environmental correlation, r c ) or unshared environmental factors (unique environmental correlation, r e ) underlie correlations between phenotypes. Matrix 10.4 shows a schematic representation of the variance/covariance matrix for a bivariate model. The corresponding path diagram is shown in Figure 10.9 .

The model in Figure 10.9 employs Cholesky decomposition (named after its developer Andre-Louis Cholesky) and can be extended in a similar way to include many more phenotypes. In linear algebra, the Cholesky decomposition or Cholesky triangle is a decomposition of a symmetric, positive-definite matrix into the product of a lower triangular matrix and its conjugate transpose. Cholesky decomposition or triangular decomposition, illustrated in Figure 10.9 for two variables, can represent a multivariate analysis of simultaneously measured variables considered in some rationally defined order of priority ( Loehlin, 1996 ; Neale & Maes, 2004 ). The first latent additive genetic variable (A1) explains the genetic influences on the first phenotype (P1) and the correlated genetic influences on the second phenotype (P2). The second latent additive genetic variable (A2) is uncorrelated with A1 and explains the remaining heritability of P2. Similar latent structures are estimated for E and C or D. From this basic model, parameters can be dropped or equated to test specific hypotheses regarding those parameters. The goal is to explain the data with as few underlying factors as possible, by testing which paths are significant (i.e., by setting the path coefficients to zero and noting whether this results in a significant decrease in model fit). For a review on how to use SEM programs to perform Cholesky decomposition please see, for example, Raykov, Marcoulides, and Boyd (2003 ).

Multivariate modeling can accommodate numerous variables, and can be used for both exploratory and confirmatory factor analysis, as well as longitudinal and causal analyses. It should be emphasized that the final results depend on the ordering—if we had considered the latent variables in the reverse order, A2 would be a factor with paths to both variables, and A1 a residual. Only in the case of uncorrelated variables is the order of selection irrelevant ( Loehlin, 1996 ), but in that case multivariate modeling should not be used anyway.

One example application of multivariate twin modeling is the use of this method to examine genetic contributions to the comorbidity between psychiatric disorders. More than a dozen studies have revealed a shared genetic vulnerability between anxiety and depression, particularly between major depressive disorder and generalized anxiety disorder ( see Cerda, Sagdeo, Johnson, & Galea, 2010 , for a review).

Common Pathway Model

The common and independent pathway models can be considered submodels of the standard Cholesky decomposition. The common pathway model hypothesizes that the covariation between variables results from a single underlying “phe-notypic” latent variable. A frequent application of this model is the examination of symptom dimensions in complex, heterogeneous diseases. For example, van Grootheest et al. (2008 ) applied this model to obsessive-compulsive behavior and found that the three symptom dimensions—Rumination, Contamination, and Checking—share variation with a latent common factor, denoted obsessive-compulsive behavior. Variation in this common factor was explained by both genes (36%) and environmental factors (64%). Only the Contamination dimension was influenced by specific genes and seemed to be a relatively independent dimension. The results suggest that a broad obsessive-compulsive behavioral phenotype exists, influenced by both genes and unshared environment. However, the common pathway model, although it is conceptually attractive, often does not fit the observed data well because the amount of genetic and environmental variation transmitted from the latent factor is defined by the phenotypic correlation between the measured and latent variables ( Medland & Hatemi, 2009 ).

Path diagram depicting the bivariate twin model.

Notes: P1 + phenotype 1; P2 + phenotype 2; T1 + twin 1 of a pair; T2 + twin 2 of a pair; MZ + monozygotic; DZ + dizygotic; A1 + additive genetic influence 1; C1 + common environmental influence 1; E1 + unique environmental influence 1; A2 + additive genetic influence 2; C2 + common environmental influence 2; E2 + unique environmental influence 2; a + additive genetic path coefficient; c=common environmental path coefficient; e=unique environmental path coefficient. Circles represent latent, unobserved variables; squares represent observed phenotypes; single-headed arrows represent influences of latent variables on observed variables; double-headed arrows represent (co)variances.

Independent Pathway Model

On the other hand, the independent pathway model hypothesizes that the variance and covariance between the variables is expected to result from one (or sometimes two) common factor(s) with the residual variance reflecting variable-specific genetic and environmental effects. This is the case, for example, with cognitive domains and latency of event-related potentials ( Hansell et al., 2005 ; Luciano et al., 2004 ). Both the common and independent pathway models are nested within the previously described Cholesky decomposition. The fit of these models may therefore be compared to the “saturated model” using a likelihood ratio test, which is asymptotically distributed as x 2 with the degrees of freedom equal to the difference in the number of estimated parameters between the nested and saturated models.

Cross-Sectional Cohort and Longitudinal Designs

Once the role of genetic factors in the variance of a particular trait has been established, an additional question that can be addressed is whether the magnitude of these genetic influences is stable over time. Instead of a costly and time-consuming longitudinal study (which is another possibility; see below), this can be investigated with a cohort design , in which genetic and environmental estimates are obtained from different cohorts. In such a design, subjects from different age cohorts are assessed on one or more phenotypes. For example, Lyons et al. (1998 ) used a cohort design to examine the diagnosis of early-and late-onset major depression in men. Early-onset (before 30 years of age) and late-onset (after 30 years of age) major depression were both significantly influenced by genetic factors (early-onset: h 2 = 0.47; late-onset: h 2 = 0.10) and unique environmental factors (early-onset: e 2 = 0.53; late-onset: e 2 = 0.90), but early-onset major depression (95% CI: 0.32, 0.61) was significantly more heritable than late-onset major depression (95% CI: 0.01, 0.29). However, determining whether the same genes are involved at different stages of life is not possible with a cohort design. In addition, phenotypic differences resulting from age are confounded with any other differences between the cohorts.

With longitudinal twin data it is possible to estimate to what extent the relative contributions of genetic and environmental factors to the observed phenotypic variance are stable over time, and to what extent these genetic and environmental contributions are specific to a certain time of life. One use of the Cholesky decomposition is in temporal contexts ( Loehlin, 1996 ). For example, phenotypes P1 to P3 might represent measurements of a trait at three successive times. In this case, A1 would represent genetic influences present at time 1, affecting the observed trait at time 1 and on subsequent occasions; A2 would represent additional genetic influences that have arisen by time 2 and whose effects are added to those of A1; and, finally, A3 represents additional genetic influences, affecting only the third measurement (P3). To illustrate, studies on the heritability of cognitive abilities have repeatedly shown an increase in genetic influences and a decrease in common environmental influences over the life span ( Ando, Ono, & Wright, 2001 ; Bartels, Rietveld, van Baal, & Boomsma, 2002 ; Boomsma & van Baal, 1998 ; Luciano et al., 2001 ; Petrill et al., 2004 ; Plomin, 1999 ; Posthuma, de Geus, &Boomsma, 2001 ).

Increasing heritability over the life span could result from genes that are activated or become more active later in life, or may result from a decrease in the influence of environmental factors, as a result of which the relative contribution of genetic influences increases. Although it is possible to use a standard Cholesky decomposition for the purposes of a longitudinal study (as mentioned above), various longitudinal models have been described, including the genetic simplex model ( Boomsma & Molenaar, 1987 ; Eaves, Long, & Heath, 1986 ) and latent growth curve models ( Baker, Reynolds, & Phelps, 1992 ; McArdle, 1986 ; Neale & McArdle, 2000 ).

The genetic simplex model is based on the frequent observation that correlations are highest among adjoining occasions and that they fall away systematically as the distance between time points increases. Such a pattern is called a simplex structure after Guttman (1955 ). The genetic simplex design allows for modeling of changes in latent true scores over time by fitting autoregressive or Markovian chains. In autoregression each latent true score is predicted to be causally related to the immediately preceding latent true score in a linear fashion (linear regression of latent factor on the previous latent factor), while allowing for genetic/environmental change or innovation that is uncorrelated with the previous latent factor at each consecutive time point. Using this design Gillespie et al. (2004 ) were able to show that although female neuroticism shows a degree of genetic continuity, there are also age-specific genetic effects (genetic innovation), which could be related to developmental or hormonal changes during puberty and psychosexual development.

Growth curve models can be applied to assess the heritability of rate of change (increase or decrease) in a trait (e.g., cognitive abilities, brain volumes) throughout development. Reynolds et al. (2005 ) applied the growth curve model to a measure of cognitive abilities in adulthood. They examined sources of variability for ability level (intercept) and rate of change (linear and quadratic effects) for verbal, fluid, memory, and perceptual speed abilities. With the exception of one verbal and two memory measures, estimated variance components indicated decreasing genetic and increasing non-shared environmental variation over age, providing support for theories of the increasing influence of the environment on cognitive abilities with age.

Causal Models

When two correlated traits have rather different modes of inheritance (e.g., family resemblance is determined largely by family background, C, for one trait and by genetic factors, A or D, for the other trait), cross-sectional family data will allow for testing of unidirectional causal hypotheses ("A and B are correlated because A causes B” versus “because B causes A"), through the pattern of cross-twin cross-trait correlations ( Gillespie & Martin, 2005 ; Heath et al., 1993 ). This model makes it possible to model specific environmental risk factors. For example, proposing a twin-family model that incorporates childhood parental loss as a specific environmental risk factor, Kendler et al. (1996 ) examined how much of the association between childhood parental loss (through separation) and alcoholism was causal (i.e., mediated by environmental factors) versus non-causal (mediated by genetic factors, with parental loss serving as an index of parental genetic susceptibility to alcoholism). Both the causal-environmental pathway and non-causal genetic paths were significant for alcoholism. However, the causal-environmental pathway consistently accounted for most of the association, suggesting childhood parental loss is a direct and significant environmental risk factor for the development of alcoholism in women. De Moor et al. (2008 ) tested the hypothesis that exercise reduces symptoms of anxiety and depression, and found that although regular exercise is associated with reduced anxious and depressive symptoms in the population, the association is not because of causal effects of exercise.

Latent Class Analysis

Latent class analysis can be used to investigate whether distinct classes of disease subtypes can be identified, which can be used to refine genetic analyses. Using this approach, Althoff et al. (2006 ) were able to identify inattentive, hyperactive, or combined subtypes for ADHD based on the Child Behavior Check List. Latent class analysis allows for modeling of etiological heterogeneity in disease subtypes; for example, it compares a model that allows for genetic heterogeneity that is expressed only in individuals exposed to a high-risk “predisposing” environment (i.e., differential sensitivity of latent classes to measured covariates) with a model that allows the environment to differentiate two forms of the disorder in individuals of high genetic risk (i.e., GxE interaction; Eaves et al., 1993 ).

The genetic models described above and the related matrix algebra have been explained in more detail elsewhere, such as in Neale and Maes’ Methodology for Genetic Studies of Twins and Families (2004) . This book is downloadable free of charge at http://ibgwww.colorado.edu/workshop2006/cdrom/HTML/BOOK.HTM .

Twin Studies and Beyond

Twin studies have shown that almost every trait is heritable to some extent. Although the behavior genetics approach allows for the determination of the ratio of genetic and environmental influences, neither the number of genetic loci influencing a trait, nor the direction of these genetic effects, nor the location, nor identity of the loci can be determined with this approach. Thus, the next interesting step in genetic research is to identify specific genetic variants underlying the trait. Identification of specific genetic variants influencing complex traits provides knowledge about underlying biological mechanisms and identified genetic variants could potentially be used as biomarkers for screening, prevention, and medical treatment.

Linkage and candidate gene association studies were the first to search for underlying genetic variants. Linkage studies test for coinheritance of genetic markers and traits within families and are used to localize regions of the genome where a locus is harbored that regulates the trait. Candidate gene association studies test for a correlation between a specific genetic marker and the trait of interest in population samples. The markers tested generally have a known function that is hypothesized to influence the trait. Linkage and candidate gene studies have identified numerous potential regions and genes underlying complex traits, but they have not always been consistently replicated ( Bosker et al., 2011 ; Verweij et al.,2012 ).

Recent technological advances have enabled genome-wide association studies (GWAS), where single-nucleotide polymorphisms (SNPs) across the entire genome are systematically tested for association with the trait of interest. Genome-wide association studies do not take prior knowledge of gene function into account, so the approach is hypothesis-free. For complex traits, the results of GWAS are mixed. Genome-wide association studies have been successful in identifying genetic variants of large effect for a number of relatively rare disease traits ( Burton et al., 2007 ; Visscher & Montgomery, 2009 ). There have also been some successes in identifying many genetic variants of small effect underlying complex traits (i.e., schizophrenia, autism, and smoking; Liu et al., 2010 ; The International Schizophrenia Consortium, 2009 ; Wang et al., 2009 ).

Other technological advances, such as next-generation sequencing, assessment of copy number variation (CNV) and methylation rates will provide new opportunities. These approaches are promising, but only the future can tell us whether these methods will enable us to better unravel the genetic etiology of complex traits. A more in-depth description of linkage and association studies and their methodological background can be found in Chapter 11 .

Twin studies have contributed greatly to our knowledge about biological pathways. Although application of the twin model has revealed that almost every conceivable trait is partly genetically influenced, understanding the source of variance does not offer any indication of the number or location of genes influencing the trait. Twin studies provide one method of investigating the ongoing nature-nurture debate and are a very important and necessary first step in genetic analyses. In addition, multivariate twin analyses remain an important way to examine the nature and magnitude of covariation between traits and across time. Technological advances in both computational and laboratory techniques have led to the integration of variance component analyses with genetic information derived from DNA. The finding that a significant proportion of the variance in the trait of interest can be explained by genetic effects allows researchers to justify requesting funds to attempt to locate the genetic loci influencing the trait, as will be discussed in Chapter 11 .

Author Note

Gabriëlla A. M. Blokland, Miriam A. Mosing, Karin J. H.Verweij, Sarah E. Medland-Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, [email protected]

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Decoding Nature and Nurture: Insights From Twin Studies

Research finds genetics may help us distinguish between disgust and fear..

Posted March 15, 2024 | Reviewed by Tyler Woods

Twin study using brain imaging reveals genetic influence on cognition, with less impact on emotion processing.
One notable finding suggests genetics play a role in distinguishing between disgust and fear.
Understanding genetic and environmental interactions can inform mental health interventions.

The nature versus nurture conundrum is an eternal debate. A recent study of 175 identical and 88 fraternal adult twins explores some of the questions of how genes and the environment determine the fundamental aspects of the emotional and rational life of humans.

The study, led by Haeme Park at Neuroscience Research Australia and recently published in the Human Brain Mapping journal, used advanced brain imaging techniques to investigate cognitive and emotional processes. By examining data from twins, the researchers sought to unravel the relative influence of genes and the environment on brain function.

What Are Twin Studies?

Using structural equation modeling, it is possible to break down the total variability observed in a specific trait, like conscious emotion recognition or sustained attention , into different components that contribute to this variability. These components include genetic factors, shared environmental effects, and individual environmental effects. By understanding how much of the variance in a trait is due to genetics (heritability) versus environmental factors, researchers can gain insights into the underlying mechanisms influencing human behavior.

Twin studies involve comparing data from identical and fraternal twins to understand the role of genetics and environment on various traits. Identical twins share close to all of their genetic material, while fraternal twins only share about 50 percent, allowing for a comparison that highlights genetic influences. Because twins often grow up in the same place, there is also less variance in environmental factors.

The recent study by Park used data from the large TWIN-E cohort study, which includes 1,669 healthy Australian twin adults split almost evenly between identical and fraternal and male and female twin pairs. The goal of the ongoing TWIN-E study is to identify biomarkers that influence emotional brain health over time.

The researchers collected extensive data, including online assessments, electroencephalograms, functional magnetic resonance imaging (fMRI), and cognitive tasks. The fMRI data was obtained from a subset of 263 participants which were then included in Park’s study.

Cognitive and Emotional Tasks

Previous studies have determined that genetics play a significant role in the structural development of different regions of the brain, but few have looked at genetics and brain function using brain imaging while participants actively complete a task.

For the Park study, the twins completed five tasks while having their brains scanned using functional magnetic resonance imaging. Two tasks measured their emotional responses: a nonconscious processing of emotional faces task and a conscious processing of emotional faces task. The participants were shown standardized faces depicting anger , fear , sadness, disgust, happiness , or neutral expressions. For the nonconscious version, the emotional faces were shown for only ten milliseconds before being masked by a neutral face so that there would not be a conscious processing of the emotion. For the conscious version, the emotional face was presented for 500 milliseconds. The participants were asked at the end how many different emotions they observed for each task.

The other three tasks measured cognition : a working memory and sustained attention task, a response inhibition task, and a selective attention and novelty processing task.

The N-back test measured working memory and sustained attention by showing a letter on a screen for 200 milliseconds and asking participants to remember which letters were yellow.

The Go-NoGo task measured response inhibition and involved participants pressing on a green "go" stimulus but ignoring the red "NoGo" stimulus.

The Oddball task measured selective attention and novelty processing by asking participants to respond to audible tones presented at 1000 Hertz and ignoring the tones presented at 50 Hertz.

While participants worked on the tasks, the functional magnetic resonance imaging would light up, revealing which parts of the brain were activated. The researchers then measured the brain activation and compared them across participants.

Study Results

In order to quantify the associations of heritability and brain activity, the researchers used two different methods: a multivariate independent component analysis (ICA) approach and a univariate brain region-of-interest (ROI) approach.

Independent component analysis is a statistical analysis that involves separating data into independent components that represent different sources of information. Researchers can detect local functional connectivity networks within the brain and identify distinct patterns and structures within the data. The univariate region of interest approach allows researchers to focus on specific brain regions known to be involved in cognitive and emotional functions. This method involves analyzing the activity of these predefined brain regions to assess their heritability.

For the working memory, sustained attention, nonconscious processing of positive and negative emotional faces, and selective attention tasks, the participants’ brain function all showed a small to moderate genetic influence, while conscious processing of emotion and response inhibition showed no evidence of heritability. Overall, the functional networks related to executive functions showed the most prominent evidence of genetic influence.

The independent component analysis results showed that the heritability of brain function depended on the particular task. For subconscious emotion recognition, the brain network involving the superior temporal gyrus and insula showed a significant genetic influence when individuals were exposed to nonconscious disgust compared to neutral stimuli (26 percent) and nonconscious fear compared to happy stimuli (23 percent). For the working memory networks, including the fronto-parietal region and the inferior parietal lobule, a significant heritability estimate was found (27 percent). The sustained attention networks, including the superior temporal and precentral gyri, insula, pre- and post-central gyri, and the inferior parietal lobule, showed significant heritability (33 percent). Novelty processing networks had significant heritability in the superior and middle temporal gyri (33 percent) and the frontoparietal-temporal network (32 percent).

The brain region of interest approach had varying results. The ventral striatum showed 20 percent heritability for conscious facial emotion stimuli. The bilateral amygdala revealed a significant heritability contribution (right: 33 percent, left: 34 percent) elicited by nonconscious facial emotion stimuli. The selective attention and novelty processing task showed a significant contribution of heritability in the medial superior prefrontal cortex (29 percent). The working memory, sustained attention, and response inhibition tasks showed no significant contribution of heritability in the brain regions of interest.

One notable finding is that the results suggest genetics play a role in distinguishing between disgust and fear more so than positive emotions. The researchers state that this may be due to an evolutionary adaptation, as identifying threats is key to survival. In general, however, they speculate that environmental factors have a greater influence on the perception of emotional expressions since “the intentional (conscious) and accurate perception of others’ emotional expressions within a particular environmental context is a paramount skill for successful social interactions.” Because social expectations vary so widely across cultures, it follows that the environment and external influences play a greater role in shaping social and emotional interactions compared to genetics.

Future Directions

The study is one of the first to analyze the shared genetic and environmental correlations across heritable brain networks/regions across multiple tasks. The researchers used advanced technology and research methods to investigate the extent to which brain function elicited by executive function and emotion processing may be heritable.

The results are interesting, yet they do not provide definitive answers to the complex nature versus nurture debate. Twin studies can provide interesting new information and allow researchers to unravel genetic mysteries, but there are limitations to using twin models, including assumptions of equal environments and random mating . While uncommon, it is also possible for twins to have different biological fathers and share only 25 percent of their DNA. These limitations in twin research methods keep us from arriving at definitive conclusions regarding the influence of genetics on behavior.

Researchers continue to seek answers that may provide groundbreaking revelations. A recent twin study published in JAMA Psychiatry demonstrated the significant impact of the environment on mental health outcomes, studying twins who had adverse childhood experiences . Longitudinal studies tracking brain development over time could provide more insights into how genetic and environmental factors interact to influence cognitive and emotional processes. Additionally, advances in imaging technology and computational methods offer exciting opportunities to explore the neural mechanisms underlying genetic influences on brain function.

Understanding the genetic basis of cognitive and emotional processes could also have various practical implications, informing mental health treatment and intervention. Insights into the genetic underpinnings of emotional processing could inform therapeutic strategies for conditions such as anxiety and depression . By recognizing the role of both genetics and the environment in shaping brain function, clinicians can tailor interventions to meet the specific needs of each patient.

The study represents a significant step forward in our understanding of the genetic and environmental influences on brain function. By uncovering the complex relationship between genes, brain networks, and cognitive processes, the research opens new avenues for personalized approaches to mental health care and intervention. As we continue to unravel the mysteries of the human brain, studies like this provide valuable insights into the influence of biology on human behavior.

William A. Haseltine, Ph.D., is known for his pioneering work on cancer, HIV/AIDS, and genomics. He is Chair and President of the global health think tank Access Health International. His recent books include My Lifelong Fight Against Disease.

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The Brain Facts Book

Twin Studies: Histories and Discoveries in Neuroscience

Published 12 Jun 2019
Author Katie Scarlett Brandt
Source BrainFacts/SfN

Space travel changes the human body, but not so permanently that it can’t withstand long trips in space. That’s the conclusion NASA came to after Scott Kelly returned from 340 days aboard the International Space Station.

Kelly’s time in space changed the shape of his eyes, altered his gut bacteria, placed his immune system on high alert, and shifted the activity of his genes, among other things. But his body mostly returned to normal after his return from space. NASA knows this because Scott Kelly is a twin. And his twin, Mark Kelly, is a former astronaut who spent those same 340 days on Earth, providing a perfect comparison for how the body handles space.

While Scott and Mark Kelly may represent the most exotic comparison between twins to date, for over a century twins have been helping researchers understand how our genes and environment influence our susceptibility to disease. And, the value of that research is only increasing.

“Most twins love being in research, particularly identical twins. They feel like they really have something to contribute,” says Nancy L. Segal, director and founder of the Twin Studies Center at California State University, Fullerton.

Segal, a fraternal twin herself, turned her lifelong fascination in the marked differences between herself and her sister, now a lawyer, into a career exploring how genetics and environment intertwine to create each human’s experience.

In 1875, before scientists understood why some sets of twins appeared more similar than others, Sir Francis Galton — a scientist, statistician, and half-cousin of Charles Darwin — published the first twin study. In “The History of Twins”, Galton reported on the results of a questionnaire he’d given to families of twins. In it, he asked if the twins became more or less similar as they aged, irrespective of whether they were raised together or apart. Galton was trying to sort out whether a person’s nature, or genetics, played a greater role in who they became than the nurturing, or environment, they experienced.

Galton ultimately determined that “there is no escape from the conclusion that nature prevails enormously over nurture.” His resolute belief in the importance of heredity led him in 1883 to invent the term “ eugenics ” — a set of beliefs and practices aimed at increasing “desirable” human traits while decreasing “undesirable” ones. Perhaps well-intentioned, the science lacked rigor and the philosophy was used to propagate concepts of racial and class superiority.

Galton’s contribution to twin studies, however, remains to this day and has spawned an important field of study. Data from twin registries around the world help researchers answer a host of questions. Founded in 1959, the Swedish Twin Registry at the Karolinska Institute in Stockholm contains information on 194,000 twins born since 1886. The largest twin registry in the world, researchers have employed it to make important discoveries associated with cardiovascular disease, cancer, and aging. The TwinsUK Registry , which launched a database for studying arthritis, includes more than 14,000 twins, aged 16 to 100 years, from across the United Kingdom.

Twin studies compare two different types of twins: identical and fraternal. Identical twins possess the same set of genes entirely, while fraternal twins share about half of the same genes, on average — similar to siblings who didn’t share a womb. This difference enables scientists to explore how heredity contributes to illness and behavior. For example, if identical twins are both more likely to suffer from high or low cholesterol levels than fraternal twins, researchers can conclude that genes play an important role in the development of that trait. From there, they can search for any associated genes.

“Twin studies matter because we need to understand what influences our development. Behavior? Physical structure? Twin studies are perfectly poised to teach us that,” Segal says.

Into the 20th Century

In 1979, Thomas J. Bouchard, Jr., Segal’s post-doctoral advisor and now colleague, posed a simple question: Were twins separated in infancy and raised apart less similar than those raised in the same family? In other words, to what extent were the cognitive and psychological differences between people the result of nature and nurture? To answer the question, Bouchard, a psychologist at the University of Minnesota and ultimately the director of the Minnesota Center for Twin and Adoption Research, and his team launched what became a landmark twin investigation: The Minnesota Study of Twins Reared Apart.

The study included more than 137 pairs of separated identical and fraternal twins and triplets from around the world who participated in a battery of medical and psychological tests. Over the years, Bouchard reported that identical twins reared apart developed personalities and interests that showed about the same degree of resemblance as identical twins who were raised together. For example, one set of twins who had been separated at four weeks of age learned as adults that each had pursued law-enforcement training, performed better in math than in spelling, and suffered from tension headaches beginning at age 18. Much more about the origins, methods, findings, and implications of this study are available in Segal’s 2012 book, Born Together-Reared Apart .

What We’ve Learned

With robust databases, researchers around the world have employed twin studies to publish hundreds of papers on blood pressure and heart disease, kidney disease, diabetes, the gut microbiome, fatigue, rheumatic diseases, aging, cancer, and periodontal disease — just to name a few. In addition, researchers have used advanced imaging among twins to predict brain age , found links between solvents and Parkinson disease risk , and identified genes associated with depression .

“The value of twins to neuroscience is increasingly appreciated,” says William Iacono, a psychologist at the University of Minnesota and co-director of the Minnesota Center for Twin and Family Research, whose graduate advisor told him any study would be inherently more interesting if it included twins.

For example, one of his studies used twins to answer the question whether adolescent marijuana causes IQ to decrease or are adolescents prone to smoking marijuana also pre-disposed to seeing their IQ’s drop regardless. The researchers looked at twins where one twin used the drug and the other did not.

The researchers found that when IQ dropped in the marijuana using twin, it also dropped in the twin who didn’t use the drug. In other words, the IQ drop was the result of a vulnerability that was present before any exposure to the effects of marijuana. These types of findings make twin studies especially important in neuroscience.

“We wouldn’t be able to pinpoint causality without the use of these twins,” says Iacono. “That’s the element that the twin component brings to the table and why twins are important to the [research] design.”

The 21st Century & Beyond

Twins research is playing a critical role in the Adolescent Brain Cognitive Development (ABCD) study — the largest long-term study of brain development and child health in the United States. Funded by the National Institutes of Health, the 21 center, 10-year study has enrolled nearly 12,000 children ages nine to 10, including roughly 1,000 twin pairs.

Such a large study offers new opportunities in neuroscience research. “Ten years ago, it was common to report findings on only 10 people,” says Iacono. “We need larger samples in order to get reliable findings, and we can use these data for targeted hypotheses to help us understand the genetic basis of brain development.”

Iacono and his colleague, psychologist Monica Luciana, are leading the University of Minnesota effort, which is one of four centers with a special focus on twins. All participants in ABCD will have MRI scans, annual assessments, and behavioral testing. Twins will provide crucial clues to the genetics at play in development and vulnerability to substance misuse.

“We're able to assess kids’ behaviors, brain structure, and function before they have initiated risk-taking behaviors, such as substance use,” Luciana says. “A weakness of other studies is the inability to distinguish trait-based genetic vulnerabilities from environmental substance-based effects. With continued funding, we can follow these children well into adulthood to answer such questions.”

About the Author

Katie Scarlett Brandt

Katie Scarlett Brandt is a science writer drawn to stories about people who live their passions and fight for the causes in which they believe.

CONTENT PROVIDED BY

BrainFacts/SfN

Discussion Questions

Why are twin studies important to research on diseases and disorders?
What conclusion were neuroscientists able to draw from twin studies?
How do large studies and databases contribute to neuroscience research?

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Waller, J. C. (2012). Commentary: The birth of the twin study—a commentary on Francis Galton’s ‘The History of Twins.’ International Journal of Epidemiology , 41(4), 913–917. doi: 10.1093/ije/dys100

What is TwinsUK? - About Us. (n.d.). TwinsUK Registry. Retrieved from http://twinsuk.ac.uk/about-us/what-is-twinsuk/

Why Twin Studies? (n.d.). Michigan State University Twin Registry. Retrieved from https://msutwinstudies.com/why-twin-studies/

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Twin Studies

The classic twin design involves comparing the similarity of identical and fraternal twins. If identical twins are more alike in intelligence, personality, or physical skills this demonstrates that the trait is probably influenced by genetic factors. Some people have objected that identical twins are alike because people treat them alike, not because of their shared genes. However, careful studies have ruled out this criticism after finding that identical twins who are treated alike are not more similar than identical twins who are treated differently.

There are many ways to study twins. A powerful method is studying identical twins reared apart from birth. Reared-apart identical twins resemble one another only because of their shared genes. Interestingly, research shows that identical twins reared apart and together are about equally similar in personality traits such as aggression and traditionalism. The twin-family method includes identical twins, their spouses, and their children. The children of identical twins are cousins, but they are also “half-siblings” because they have a genetically identical parent. These children’s aunts and uncles are like their “mothers” and “fathers” because they are genetically identical to the children’s own parents. It is possible to compare the behavioral similarity of a twin mother and her daughter (who share genes and environments) and a twin aunt and her niece (who share genes but not environments). Research has shown that parent-child and aunt/uncle-niece/nephew similarity is the same on a spatial visualization test. A more recent research design uses a unique twin-like pair called virtual twins. Virtual twins are same-age individuals who are raised together, but are not genetically related. Virtual twins show modest similarity in intelligence, despite their shared environment, a finding that supports genetic influence.

The multiple birth rate (especially the fraternal twinning rate) has increased from 19.3 to 30.7 multiple births per 1,000 births in recent years. This is primarily due to new reproductive technologies but also to the fact that women are having children at older ages. The increased twinning rate is good news for researchers. However, the downside is that twins are more likely than non-twins to suffer from birth difficulties.

It is likely that twins will continue to play significant roles in psychological and medical research.

Identical twins differing in traits, such as novelty-seeking, schizophrenia, or breast cancer may help identify which genes are expressed and which genes are not expressed. Thus, twin studies can help clarify the origins of behavior in everyone else.

References:

Machin, G. A., & Keith, L. G. (1999). An atlas of multiple pregnancy: Biology and pathology. New York: Parthenon.
Segal, N. L. (2000). Entwined lives: Twins and what they tell us about human behavior. New York: Plume.
Segal, N. L. (2005). Indivisible by two: Lives of extraordinary twins. Cambridge, MA: Harvard University Press.
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Twin method

What have twin studies taught us about ESSENCE conditions?

About twin method

The issue of nature versus nurture has been debated for centuries. From the beginning of the 20 th century, the twin study design has helped us to shed light on this debate since it offers the possibility to disentangle the effects of genes (nature) and environment (nurture). The first formal twin registry was established in Denmark in 1954. As of 2019, there are more than 30 twin registries all over the world (1).

Lisa Dinkler

What twin studies tell us – and what they don’t tell us

Twin studies investigate whether differences between us (called individual differences or individual variation ) are influenced by differences in our genes or environments. More precisely, twin studies estimate the proportion of genetic and environmental influences on human characteristics (often called traits ), such as personality traits, cognitive traits and psychiatric disorders. Twin studies do not tell us which and how many genes that are involved in, for example, a psychiatric disorder. This is traditionally the subject of the field of molecular genetics and genomics.

Over the past five decades, twin studies have shown that all psychological traits are under substantial genetic influence (even things you never considered to be genetically influenced such as the act of voting (2)). Twin studies have also shown that genetics on average explain half of our individual differences in having psychiatric disorders (3, 4) , which has dramatically changed our understanding of psychiatric disorders and guided genomic research within psychiatry.

How does it work?

All humans share circa 99.9% of their DNA. The 0.1% that is not shared causes individual differences and are called segregating alleles *. Identical twin twins share 100% of their segregating alleles, because they develop from the same maternal egg, fertilised by a single sperm, which splits after fertilisation. These twins are therefore called monozygotic. Non-identical twins share on average 50% of their segregating alleles (just like any other couple of non-twin siblings), because two different eggs were fertilised by two different sperms (dizygotic twins).

Another special feature of twins is that both identical and non-identical twins grow up in the same home environment at the same age. Therefore, both types of twins share the home environment (making the twins more similar to each other) to the same extent. This is called the equal environments assumption and enables us to “control” for the environmental influences of the home environment (nurture) when estimating heritability (nature). In other words, identical and non-identical twins differ only in the genetic influences they share, but not in the environmental influences they share.

We estimate heritability by comparing the degree of similarity between identical and non-identical twins. If identical twins are more similar to each other than non-identical twins, we can conclude—due to the equal environments assumption—that this is due to genetic influence on the trait (i.e., the trait is heritable). The more similar identical twins are to each other and the less similar non-identical twins are, the higher the heritability. In the simplest twin study design, we estimate the proportions of heritability, shared environmental factors and non-shared environmental factors, based on the correlations between identical and non-identical twins.

What are “environmental factors”?

Environmental factors include all non-genetic influences and therefore comprise a very broad range of influences such as drug use during pregnancy, birth complications, parenting behaviours, media consumption, and exposure to toxins, just to name a few. Some environmental factors are usually shared between the twins (e.g., neighbourhood, parental education, parenting behaviours, or the amount of conflict in the household) and therefore make the twins more similar to each other. These factors are called shared environmental factors . Other environmental factors are not shared between the twins—especially as they become older—and therefore make the twins more different from each other. Examples are having different peers, teachers, and hobbies. These non-shared environmental factors are the reason that even identical twins are not completely similar in everything. If specific environmental factors are shared or non-shared between twins is very individual. While the neighbourhood is usually shared because the twins live in the same place, parenting behaviours can indeed be non-shared if the parents act very differently towards the twins.

Limitations of twin studies

As you can see, the twin study design is quite intriguing, but also has its limitations. For instance, genetic and environmental factors might interact and correlate with each other. Another problem is the assumption that identical twins always share 100% of their segregating alleles, as it is not always completely true. Certain mutations (called de novo mutations **) can happen after the fertilised maternal egg has split and therefore lead to small genetic differences between identical twins (5). In this case, heritability would be overestimated using the twin model described above.

Heritability

Twin studies and ESSENCE ****

The certainly most-studied conditions within the ESSENCE spectrum are autism and ADHD. Both also seem to have the highest heritabilities within the ESSENCE spectrum (ca. 74%), but the estimates differ considerably between studies and range between 60-90% (7, 8). When trying to interpret these estimates it can be helpful to bear in mind (a) that no psychological trait or psychiatric disorder is 100% heritable (which is why they are called complex traits and complex disorders) and (b) that on average, psychological traits have a heritability of 50% (3).

That autism and ADHD could be (largely) due to genetics has long been a taboo subject, until twin studies have shown over and over again that indeed most of the individual variation in autism and ADHD is due to genetic factors. This has certainly helped to remove the blame that was put on parents and their parenting styles, as in the case of the long-held belief that “refrigerator” mothers cause autism in their children (9).

The heritability of other ESSENCE conditions seems to be slightly lower than the heritability of autism and ADHD. Here are a few examples: developmental coordination disorder 70%, tic disorders 56%, conduct disorder 55%, oppositional defiant disorder 50-62%, and dyslexia 52-64% (4, 10-13).

The future of twin studies

By now, the heritability of most known psychological traits and psychiatric disorders has been estimated repeatedly and for many of them heritability estimates have even been summarised in meta-analyses (4). The classical (simple) twin model as described above might therefore be a bit outdated today, however, twin studies with more complex designs are still extremely valuable. Such extended designs comprise, for example: 1) studying whether the same genetic factors influence a trait at different stages of life (see point 3 above); 2) studying the genetic influence shared between traits/disorders (see point 4 above); 3) including data from other family members (parents, siblings, spouses or offspring) allowing for a much larger range of hypotheses to be tested; 4) studying identical twins who are discordant (i.e., not similar) for a certain trait or disorder, making it possible to investigate causal effects of environmental factors as well as epigenetics (changes in gene activity and gene expression), and 5) combining information on traits and disorders with DNA from blood or saliva and other biological materials (stool, hair, skin etc.) (14). Apart from enabling studies on a genetic level, twin studies are usually designed as long-term follow-up studies and therefore provide rich data on the development of traits and disorders over time for epidemiological studies.

Genes exists in several variant forms. An allele is one of the forms a gene can take.

A de novo mutation is a non-inherited genetic variant. It arises either in the parental germ cells or in the fertilised egg during early embryogenesis.

To be exact here, accidents/injuries are not “pure” environmental factors, but they are under some genetic influence, meaning that genes explain a small part of why people become involved in accidents/injuries. However, since it is only small part that is explained by genes, they can still be called environmental factors (6).

ESSENCE is an acronym for Early Symptomatic Syndromes Eliciting Neurodevelopmental Clinical Examinations that was coined by Christopher Gillberg in 2010. It is an umbrella term describing early symptoms of conditions such as autism and ADHD (but also many others such as intellectual disability, specific learning disorder, developmental coordination disorder, Tourette syndrome, etc.) that lead parents to seek clinical help for their children.

1. Sahu M, Prasuna JG. Twin Studies: A Unique Epidemiological Tool. Indian J Community Med. 2016;41(3):177-82.

2. Fowler JH, Baker LA, Dawes CT. Genetic Variation in Political Participation. American Political Science Review. 2008;102(2):233-48.

3. Plomin R, DeFries JC, Knopik VS, Neiderhiser JM. Top 10 Replicated Findings From Behavioral Genetics. Perspect Psychol Sci. 2016;11(1):3-23.

4. Polderman TJC, Benyamin B, de Leeuw CA, Sullivan PF, van Bochoven A, Visscher PM, et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet. 2015;47(7):702-9.

5. Vadgama N, Pittman A, Simpson M, Nirmalananthan N, Murray R, Yoshikawa T, et al. De novo single-nucleotide and copy number variation in discordant monozygotic twins reveals disease-related genes. Eur J Hum Genet. 2019;27(7):1121-33.

6. Salminen S, Vuoksimaa E, Rose RJ, Kaprio J. Age, Sex, and Genetic and Environmental Effects on Unintentional Injuries in Young and Adult Twins. Twin research and human genetics : the official journal of the International Society for Twin Studies. 2018;21(6):502-6.

7. Tick B, Bolton P, Happe F, Rutter M, Rijsdijk F. Heritability of autism spectrum disorders: a meta-analysis of twin studies. J Child Psychol Psychiatry. 2016;57(5):585-95.

8. Faraone SV, Larsson H. Genetics of attention deficit hyperactivity disorder. Mol Psychiatry. 2019;24(4):562-75.

9. Kanner L. Problems of nosology and psychodynamics of early infantile autism. Am J Orthopsychiatry. 1949;19(3):416–26.

10. Lichtenstein P, Carlstrom E, Rastam M, Gillberg C, Anckarsater H. The genetics of autism spectrum disorders and related neuropsychiatric disorders in childhood. Am J Psychiatry. 2010;167(11):1357-63.

11. Bornovalova MA, Hicks BM, Iacono WG, McGue M. Familial transmission and heritability of childhood disruptive disorders. Am J Psychiatry. 2010;167(9):1066-74.

12. Kerekes N, Lundström S, Chang Z, Tajnia A, Jern P, Lichtenstein P, et al. Oppositional defiant- and conduct disorder-like problems: neurodevelopmental predictors and genetic background in boys and girls, in a nationwide twin study. PeerJ. 2014;2:e359.

13. Grigorenko EL. Genetic bases of developmental dyslexia: A capsule review of heritability estimates. Enfance. 2004;56(3):273-88.

14. van Dongen J, Slagboom PE, Draisma HH, Martin NG, Boomsma DI. The continuing value of twin studies in the omics era. Nat Rev Genet. 2012;13(9):640-53.

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Twin Studies

What are twin studies.

Twin studies are used to investigate the roles of genetics and environment in various traits, behaviours and conditions. These studies involve examining the similarities and differences between identical (monozygotic) and fraternal (dizygotic) twins. Like any research approach, they come with pros and cons and if you're considering putting your twins into a study, make sure you think carefully before doing so.

Proponents of twin studies argue that:

Genetic Insights: Twin studies can provide valuable insights into the heritability of traits and conditions. By comparing identical twins (who share 100% of their genetic material) to fraternal twins (who share about 50% of their genetic material on average), researchers can estimate the extent to which genetics contribute to a particular trait or condition.
Longitudinal Studies: Twins can be followed over long periods, allowing researchers to track changes and developments in traits and conditions over time.
Clinical Applications: The findings from twin studies can have practical applications in fields like medicine and psychology. Understanding the genetic and environmental contributions to certain conditions can lead to better diagnostic tools and treatment strategies.
Nature vs Nurture: Twins often grow up in similar environments, especially if they are raised together, which can help researchers control for environmental factors and focus on genetic influences. This gives researchers a unique insight into the nature vs nurture discussion.

Critics of twin studies argue that:

Ethical Considerations: Conducting twin studies may raise ethical concerns, especially when involving children or vulnerable populations. Informed consent and privacy issues must be carefully addressed. See more below in the section on things to think about.
Generalisability: The results of twin studies may not always generalise to the broader population. Twins are not necessarily representative of all individuals.
Assumptions of Equal Environments: Twin studies often assume that identical and fraternal twins are raised in similar environments. However, this isn't always the case, which can affect studies' accuracy.
Twin Discordance: In cases where one twin has a particular condition or trait, while the other does not (discordance), researchers may find it challenging to identify the specific genetic and environmental factors at play.

Twin girls pull faces at the camera whilst standing by the seaside

Things to think about when considering twin studies

If you're considering putting your children into twin studies - or going into twin studies yourselves - there are several considerations to keep in mind:

Informed Consent: If your twins are minors, you'll need to provide informed consent on their behalf. Understand the study's purpose, procedures and potential risks or benefits before enrolling your twins.
Ethical Considerations: Ensure that the study is conducted ethically and that your twins' rights and privacy are protected. Be aware of the potential ethical issues associated with research involving children.
Study Objectives: Understand the specific goals of the twin study. What is the research trying to investigate or discover? Make sure you're comfortable with the study's objectives and its potential implications.
Time Commitment: Twin studies can span months or even years. Consider the time commitment required from both you and your twins and ensure it's feasible for your family.
Privacy and Data Security: Inquire about the measures in place to protect your family's privacy and the security of the data collected during the study. Understand how the data will be used and whether it will be anonymized.
Potential Risks and Benefits: Assess the potential risks and benefits of participation. Research studies can sometimes have unforeseen risks, so it's essential to weigh these against the potential benefits.
Voluntary Participation: Ensure that participation is entirely voluntary and you or your twins can withdraw from the study at any time without negative consequences.
Communication: Maintain open and clear communication with the researchers. Ask questions, express concerns and seek clarification about any aspect of the study that you find unclear or concerning.
Impact on Twins: Consider how participation may affect your twins. Will it disrupt their daily routines or cause them stress? Ensure that the study won't have a detrimental impact on their wellbeing.
Sibling Dynamics: Be aware of the potential impact on the relationship between your twins. Participating in a study may affect their interactions or create competition, so monitor their feelings and communication throughout the study.
Financial Compensation: Inquire about any compensation or incentives for participation. Ensure that you understand what is being offered and whether it's appropriate.
Long-Term Commitment: Some twin studies involve long-term follow-ups, even into adulthood. Be prepared for the possibility of continued involvement over an extended period.
Legal Rights: Familiarise yourself with any legal agreements or contracts associated with participation in the study. Ensure that your rights are protected and you have access to any relevant documentation.

Participating in a twin study can be a valuable contribution to scientific knowledge, but it's essential to make an informed and thoughtful decision that aligns with your family's values and priorities. Discuss your considerations with the research team and any experts you consult to ensure that you are comfortable with your decision.

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Review Article
Open access
Published: 03 June 2024

The effectiveness of digital twins in promoting precision health across the entire population: a systematic review

Mei-di Shen 1 ,
Si-bing Chen 2 &
Xiang-dong Ding ORCID: orcid.org/0009-0001-1925-0654 2

npj Digital Medicine volume 7 , Article number: 145 ( 2024 ) Cite this article

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Digital twins represent a promising technology within the domain of precision healthcare, offering significant prospects for individualized medical interventions. Existing systematic reviews, however, mainly focus on the technological dimensions of digital twins, with a limited exploration of their impact on health-related outcomes. Therefore, this systematic review aims to explore the efficacy of digital twins in improving precision healthcare at the population level. The literature search for this study encompassed PubMed, Embase, Web of Science, Cochrane Library, CINAHL, SinoMed, CNKI, and Wanfang Database to retrieve potentially relevant records. Patient health-related outcomes were synthesized employing quantitative content analysis, whereas the Joanna Briggs Institute (JBI) scales were used to evaluate the quality and potential bias inherent in each selected study. Following established inclusion and exclusion criteria, 12 studies were screened from an initial 1321 records for further analysis. These studies included patients with various conditions, including cancers, type 2 diabetes, multiple sclerosis, heart failure, qi deficiency, post-hepatectomy liver failure, and dental issues. The review coded three types of interventions: personalized health management, precision individual therapy effects, and predicting individual risk, leading to a total of 45 outcomes being measured. The collective effectiveness of these outcomes at the population level was calculated at 80% (36 out of 45). No studies exhibited unacceptable differences in quality. Overall, employing digital twins in precision health demonstrates practical advantages, warranting its expanded use to facilitate the transition from the development phase to broad application.

PROSPERO registry: CRD42024507256.

Digital twins for health: a scoping review

Digital twins in medicine

The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field

Introduction.

Precision health represents a paradigm shift from the conventional “one size fits all” medical approach, focusing on specific diagnosis, treatment, and health management by incorporating individualized factors such as omics data, clinical information, and health outcomes 1 , 2 . This approach significantly impacts various diseases, potentially improving overall health while reducing healthcare costs 3 , 4 . Within this context, digital twins emerged as a promising technology 5 , creating digital replicas of the human body through two key steps: building mappings and enabling dynamic evolution 6 . Unlike traditional data mining methods, digital twins consider individual variability, providing continuous, dynamic recommendations for clinical practice 7 . This approach has gained significant attention among researchers, highlighting its potential applications in advancing precision health.

Several systematic reviews have explored the advancement of digital twins within the healthcare sector. One rapid review 8 identified four core functionalities of digital twins in healthcare management: safety management, information management, health management/well-being promotion, and operational control. Another systematic review 9 , through an analysis of 22 selected publications, summarized the diverse application scenarios of digital twins in healthcare, confirming their potential in continuous monitoring, personalized therapy, and hospital management. Furthermore, a quantitative review 10 assessed 94 high-quality articles published from 2018 to 2022, revealing a primary focus on technological advancements (such as artificial intelligence and the Internet of Things) and application scenarios (including personalized, precise, and real-time healthcare solutions), thus highlighting the pivotal role of digital twins technology in the field of precision health. Another systematic review 11 , incorporating 18 framework papers or reviews, underscored the need for ongoing research into digital twins’ healthcare applications, especially during the COVID-19 pandemic. Moreover, a systematic review 12 on the application of digital twins in cardiovascular diseases presented proof-of-concept and data-driven approaches, offering valuable insights for implementing digital twins in this specific medical area.

While the existing literature offers valuable insights into the technological aspects of digital twins in healthcare, these systematic reviews failed to thoroughly examine the actual impacts on population health. Despite the increasing interest and expanding body of research on digital twins in healthcare, the direct effects on patient health-related outcomes remain unclear. This knowledge gap highlights the need to investigate how digital twins promote and restore patient health, which is vital for advancing precision health technologies. Therefore, the objective of our systematic review is to assess the effectiveness of digital twins in improving health-related outcomes at the population level, providing a clearer understanding of their practical benefits in the context of precision health.

Search results

The selection process for the systematic review is outlined in the PRISMA flow chart (Fig. 1 ). Initially, 1321 records were identified. Of these, 446 duplicates (446/1321, 33.76%) were removed, leaving 875 records (875/1321, 66.24%) for title and abstract screening. Applying the pre-defined inclusion and exclusion criteria led to the exclusion of 858 records (858/875, 98.06%), leaving 17 records (17/875, 1.94%) for full-text review. Further scrutiny resulted in the exclusion of one study (1/17, 5.88%) lacking health-related outcomes and four studies (4/17, 23.53%) with overlapping data. Ultimately, 12 (12/17, 70.59%) original studies 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 were included in the systematic review. Supplementary Table 1 provides a summary of the reasons for exclusion at the full-text reading phase.

Flow chart of included studies in the systematic review.

Study characteristics

The studies included in this systematic review were published between 2021 (2/12, 16.67%) 23 , 24 and 2023 (8/12, 66.67%) 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 . Originating from diverse regions, 4/12 studies (33.33%) were from Asia 13 , 14 , 21 , 24 , 5/12 (41.67%) from America 15 , 17 , 19 , 20 , 22 , and 3/12 (25.00%) from Europe 16 , 18 , 23 . The review encompassed various study designs, including randomized controlled trials (1/12, 8.33%) 14 , quasi-experiments (6/12, 50.00%) 13 , 15 , 16 , 18 , 19 , 21 , and cohort studies (5/12, 41.67%) 17 , 20 , 22 , 23 , 24 . The sample sizes ranged from 15 13 to 3500 patients 19 . Five studies assessed the impact of digital twins on virtual patients 15 , 16 , 18 , 19 , 20 , while seven examined their effect on real-world patients 13 , 14 , 17 , 21 , 22 , 23 , 24 . These patients included had various diseases, including cancer (4/12, 33.33%) 15 , 16 , 19 , 22 , type 2 diabetes (2/12, 16.66%) 13 , 14 , multiple sclerosis (2/12, 16.66%) 17 , 18 , qi deficiency (1/12, 8.33%) 21 , heart failure (1/12, 8.33%) 20 , post-hepatectomy liver failure (1/12, 8.33%) 23 , and dental issues (1/12, 8.33%) 24 . This review coded interventions into three types: personalized health management (3/12, 25.00%) 13 , 14 , 21 , precision individual therapy effects (3/12, 25.00%) 15 , 16 , 18 , 19 , 20 , 22 , and predicting individual risk (3/12, 25.00%) 17 , 23 , 24 , with a total of 45 measured outcomes. Characteristics of the included studies are detailed in Table 1 .

Risk of bias assessment

The risk of bias for the studies included in this review is summarized in Fig. 2 . In the single RCT 14 assessed, 10 out of 13 items received positive responses. Limitations were observed due to incomplete reporting of baseline characteristics and issues with blinding. Among the six quasi-experimental studies evaluated, five (83.33%) 13 , 15 , 16 , 18 , 21 achieved at least six positive responses, indicating an acceptable quality, while one study (16.67%) 19 fell slightly below this threshold with five positive responses. The primary challenges in these quasi-experimental studies were due to the lack of control groups, inadequate baseline comparisons, and limited follow-up reporting. Four out of five (80.00%) 17 , 20 , 22 , 23 of the cohort studies met or exceeded the criterion with at least eight positive responses, demonstrating their acceptable quality. However, one study (20.00%) 24 had a lower score due to incomplete data regarding loss to follow-up and the specifics of the interventions applied. Table 1 elaborates on the specific reasons for these assessments. Despite these concerns, the overall quality of the included studies is considered a generally acceptable risk of bias.

The summary of bias risk via the Joanna Briggs Institute assessment tools.

The impact of digital twins on health-related outcomes among patients

This review includes 12 studies that collectively assessed 45 outcomes, achieving an overall effectiveness rate of 80% (36 out of 45 outcomes), as depicted in Fig. 3a . The digital twins analyzed were coded into three functional categories: personalized health management, precision individual therapy effects, and predicting individual risks. A comprehensive analysis of the effectiveness of digital twins across these categories is provided, detailing the impact and outcomes associated with each function.

a The overall effectiveness of digital twins; b The effectiveness of personalized health management driven by digital twins; c The effectiveness of precision individualized therapy effects driven by digital twins; d The effectiveness of prediction of individual risk driven by digital twins.

The effectiveness of digital twins in personalized health management

In this review, three studies 13 , 14 , 21 employing digital twins for personalized health management reported an effectiveness of 80% (24 out of 30 outcomes), as shown in Fig. 3b . A self-control study 13 involving 15 elderly patients with diabetes, used virtual patient representations based on health information to guide individualized insulin infusion. Over 14 days, this approach improved the time in range (TIR) from 3–75% to 86–97%, decreased hypoglycemia duration from 0–22% to 0–9%, and reduced hyperglycemia time from 0–98% to 0–12%. A 1-year randomized controlled trial 14 with 319 type 2 diabetes patients, implemented personalized digital twins interventions based on nutrition, activity, and sleep. This trial demonstrated significant improvements in Hemoglobin A1c (HbA1C), Homeostatic Model Assessment 2 of Insulin Resistance (HOMA2-IR), Nonalcoholic Fatty Liver Disease Liver Fat Score (NAFLD-LFS), and Nonalcoholic Fatty Liver Disease Fibrosis Score (NAFLD-NFS), and other primary outcomes (all, P < 0.001; Table 2 ). However, no significant changes were observed in weight, Alanine Aminotransferase (ALT), Fibrosis-4 Score (FIB4), and AST to Platelet Ratio Index (APRI) (all, P > 0.05). A non-randomized controlled trial 21 introduced a digital twin-based Traditional Chinese Medicine (TCM) health management platform for patients with qi deficiency. It was found to significantly improve blood pressure, main and secondary TCM symptoms, total TCM symptom scores, and quality of life (all, P < 0.05). Nonetheless, no significant improvements were observed in heart rate and BMI (all, P > 0.05; Table 2 ).

The effectiveness of digital twins in precision individual therapy effects

Six studies 15 , 16 , 18 , 19 , 20 , 22 focused on the precision of individual therapy effects using digital twins, demonstrating a 70% effectiveness rate (7 out of 10 outcomes), as detailed in Fig. 3c . In a self-control study 15 , a data-driven approach was employed to create digital twins, generating 100 virtual patients to predict the potential tumor biology outcomes of radiotherapy regimens with varying contents and doses. This study showed that personalized radiotherapy plans derived from digital twins could extend the median tumor progression time by approximately six days and reduce radiation doses by 16.7%. Bahrami et al. 16 created 3000 virtual patients experiencing cancer pain to administer precision dosing of fentanyl transdermal patch therapy. The intervention led to a 16% decrease in average pain intensity and an additional median pain-free duration of 23 hours, extending from 72 hours in cancer patients. Another quasi-experimental study 18 created 3000 virtual patients with multiple sclerosis to assess the impact of Ocrelizumab. Findings indicated Ocrelizumab can resulted in a reduction in relapses (0.191 [0.143, 0.239]) and lymphopenic adverse events (83.73% vs . 19.9%) compared to a placebo. American researchers 19 developed a quantitative systems pharmacology model using digital twins to identify the optimal dosing for aggressive non-Hodgkin lymphoma patients. This approach resulted in at least a 50% tumor size reduction by day 42 among 3500 virtual patients. A cohort study 20 assessed the 5-year composite cardiovascular outcomes in 2173 virtual patients who were treated with spironolactone or left untreated and indicated no statistically significant inter-group differences (0.85, [0.69–1.04]). Tardini et al. 22 employed digital twins to optimize multi-step treatment for oropharyngeal squamous cell carcinoma in 134 patients. The optimized treatment selection through digital twins predicted increased survival rates by 3.73 (−0.75, 8.96) and dysphagia rates by 0.75 (−4.48, 6.72) compared to clinician decisions, with no statistical significance.

The effectiveness of digital twins in predicting individual risk

Three studies 17 , 23 , 24 employing digital twins to predict individual patient risks demonstrated a 100% effectiveness rate (5 out of 5 outcomes), as shown in Fig. 3d . A cohort study 17 used digital twins to forecast the onset age for disease-specific brain atrophy in patients with multiple sclerosis. Findings indicated that the onset of progressive brain tissue loss, on average, preceded clinical symptoms by 5-6 years among the 519 patients ( P < 0.01). Another study 23 focused on predicting postoperative liver failure in 47 patients undergoing major hepatectomy through mathematical models of blood circulation. The study highlighted that elevated Postoperative Portal Vein pressure (PPV) and Portocaval Gradient (PCG) values above 17.5 mmHg and 13.5 mmHg, respectively, correlated with the measured values (all, P < 0.0001; Table 2 ). These indicators were effective in predicting post-hepatectomy liver failure, accurately identifying three out of four patients who experienced this complication. Cho et al. 24 created digital twins for 50 adult female patients using facial scans and cone-beam computed tomography images to evaluate the anteroposterior position of the maxillary central incisors and forehead inclination. The analysis demonstrated significant differences in the position of the maxillary central incisors ( P = 0.04) and forehead inclination ( P = 0.02) between the two groups.

This systematic review outlines the effectiveness of digital twins in improving health-related outcomes across various diseases, including cancers, type 2 diabetes, multiple sclerosis, qi deficiency, heart failure, post-hepatectomy liver failure, and dental issues, at the population level. Distinct from prior reviews that focused on the technological dimensions of digital twins, our analysis shows the practical applications of digital twins in healthcare. The applications have been categorized into three main areas: personalized health management, precision individual therapy effects, and predicting individual risks, encompassing a total of 45 outcomes. An overall effectiveness of 80% was observed across these outcomes. This review offers valuable insights into the application of digital twins in precision health and supports the transition of digital twins from construction to population-wide implementation.

Digital twins play a crucial role in achieving precision health 25 . They serve as virtual models of human organs, tissues, cells, or microenvironments, dynamically updating based on real-time data to offer feedback for interventions on their real counterparts 26 , 27 . Digital twins can solve complex problems in personalized health management 28 , 29 and enable comprehensive, proactive, and precise healthcare 30 . In the studies reviewed, researchers implemented digital twins by creating virtual patients based on personal health data and using simulations to generate personalized recommendations and predictions. It is worth noting that while certain indicators have not experienced significant improvement in personalized health management for patients with type 2 diabetes and Qi deficiency, it does not undermine the effectiveness of digital twins. Firstly, these studies have demonstrated significant improvements in primary outcome measures. Secondly, improving health-related outcomes in chronic diseases is an ongoing, complex process heavily influenced by changes in health behaviors 31 , 32 . While digital twins can provide personalized health guidance based on individual health data, their impact on actual behaviors warrants further investigation.

The dual nature of medications, providing benefits yet potentially leading to severe clinical outcomes like morbidity or mortality, must be carefully considered. The impact of therapy is subject to various factors, including the drug attributes and the specific disease characteristics 33 . Achieving accurate medication administration remains a significant challenge for healthcare providers 34 , underscoring the need for innovative methodologies like computational precise drug delivery 35 , 36 , a example highlighted in our review of digital twins. Regarding the prediction of individual therapy effects for conditions such as cancer, multiple sclerosis, and heart failure, six studies within this review have reported partly significant improvements in patient health-related outcomes. These advancements facilitate the tailored selection and dosing of therapy, underscoring the ability of digital twins to optimize patient-specific treatment plans effectively.

Furthermore, digital twins can enhance clinical understanding and personalize disease risk prediction 37 . It enables a quantitative understanding and prediction of individuals by continuously predicting and evaluating patient data in a virtual environment 38 . In patients with multiple sclerosis, digital twins have facilitated predictions regarding the onset of disease-specific brain atrophy, allowing for early intervention strategies. Similarly, digital twins assessed the risk of liver failure after liver resection, aiding healthcare professionals in making timely decisions. Moreover, the application of digital twins in the three-dimensional analysis of patients with dental problems has demonstrated highly effective clinical significance, underscoring its potential across various medical specialties. In summary, the adoption of digital twins has significantly contributed to advancing precision health and restoring patient well-being by creating virtual patients based on personal health data and using simulations to generate personalized recommendations and predictions.

Recent studies have introduced various digital twin systems, covering areas such as hospital management 8 , remote monitoring 9 , and diagnosing and treating various conditions 39 , 40 . Nevertheless, these systems were not included in this review due to the lack of detailed descriptions at the population health level, which constrains the broader application of this emerging technology. Our analysis underscores the reported effectiveness of digital twins, providing unique opportunities for dynamic prevention and precise intervention across different diseases. Multiple research methodologies and outcome measures poses a challenge for quantitative publication detection. This systematic review employed a comprehensive retrieval strategy across various databases for screening articles on the effectiveness of digital twins, to reduce the omission of negative results. And four repeated publications were excluded based on authors, affiliation, population, and other criteria to mitigate the bias of overestimating the digital twins effect due to repeated publication.

However, there are still limitations. Firstly, the limited published research on digital twins’ application at the population level hinders the ability to perform a quantitative meta-analysis, possibly limiting our findings’ interpretability. We encourage reporting additional high-quality randomized controlled trials on the applicability of digital twins to facilitate quantitative analysis of their effectiveness in precision health at the population level. Secondly, this review assessed the effectiveness of digital twins primarily through statistical significance ( P -value or 95% confidence interval). However, there are four quasi-experimental studies did not report statistical significance. One of the limitations of this study is the use of significant changes in author self-reports as a criterion in these four quasi-experimental studies for identifying effectiveness. In clinical practice, the author’s self-reported clinical significance can also provide the effectiveness of digital twins. Thirdly, by focusing solely on studies published in Chinese and English, this review may have omitted relevant research available in other languages, potentially limiting the scope of the analyzed literature. Lastly, our review primarily emphasized reporting statistical differences between groups. Future work should incorporate more application feedback from real patients to expose digital twins to the nuances of actual patient populations.

The application of digital twins is currently limited and primarily focused on precision health for individual patients. Expanding digital twins’ application from individual to group precision health is recommended to signify a more extensive integration in healthcare settings. This expansion involves sharing real-time data and integrating medical information across diverse medical institutions within a region, signifying the development of group precision health. Investigating both personalized medical care and collective health management has significant implications for improving medical diagnosis and treatment approaches, predicting disease risks, optimizing health management strategies, and reducing societal healthcare costs 41 .

Digital twins intervention encompasses various aspects such as health management, decision-making, and prediction, among others 9 . It represents a technological and conceptual innovation in traditional population health intervention. However, the current content design of the digital twins intervention is insufficient and suggests that it should be improved by incorporating more effective content strategies tailored to the characteristics of the target population. Findings from this study indicate that interventions did not differ significantly in our study is from digital twins driven by personalized health management, which means that compared with the other two function-driven digital twins, personalized health management needs to receive more attention to enhance its effect in population-level. For example, within the sphere of chronic disease management, integrating effective behavioral change strategies into digital twins is advisable to positively influence health-related indicators, such as weight and BMI. The effectiveness of such digital behavior change strategies has been reported in previous studies 42 , 43 . The consensus among researchers on the importance of combining effective content strategies with digital intervention technologies underscores the potential for this approach to improve patient health-related outcomes significantly.

The applications of digital twins in precision health are mainly focused on model establishment and prediction description, with limited implementation in multi-center settings. A more robust and detailed data foundation is recommended to improve clinical decision-making and reduce the likelihood of imprecise treatments. This requires continuous updating and capturing of dynamic information by digital twins in the future, as well as the improvement of the data platform that facilitates mapping, interaction, and iterative optimization. Integrating digital twins effectively into clinical workflows can support clinical interventions, assist physicians in making informed decisions, and increase the standard of patient care 6 .

The accessibility of health data is a significant challenge for the clinical implementation of digital twins. Although the internet and information technology have significantly enhanced health data availability, health data, including information systems and electronic health records, remain heterogeneous and are difficult to share 44 . Health data often contains confidential patient information, as well as unreliable information, posing challenges for implementing digital twins in healthcare settings. The primary technology utilized in digital twins, artificial intelligence algorithms, demands high-performance hardware devices and software platforms for data analysis 45 , necessitating healthcare organizations to allocate increased investment and budget for computing infrastructure supporting digital twins’ application. Therefore, future research should be focused on the technical aspects of digital twins to resolve these challenges. The automated processing of health data using a large language model and the rapid conversion of complex natural language texts into comprehensive knowledge texts are encouraged. The development of high-performance computing technology is essential for cost-effective computing requirements, which can facilitate the application of digital twins in clinical practice 46 .

Overall, this systematic review offers a comprehensive overview of digital twins in precision health, examining their impact at the population level. The findings indicate a significant overall effectiveness rate of 80% for the measured outcomes, highlighting digital twins’ pivotal role in advancing precision health. Future research should broaden the application of digital twins across various populations, integrate proven content strategies, and implement these approaches in various healthcare settings. Such efforts will maximize the benefits of digital technologies in healthcare, promoting more precise and efficacious strategies, thereby elevating patient outcomes and improving overall healthcare experiences. While digital twins offer great promise for precision health, their broad adoption and practical implementation are still in the early stages. Development, and application are essential to unlock the full potential of digital twins in revolutionizing healthcare delivery.

This systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines 47 . The protocol for this systematic review was prospectively registered on PROSPERO, which can be accessed via the following link: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024507256 . The registered protocol underwent an update, which included polishing the title of the article, modifying the limitation of the control group and language in the inclusion/exclusion criteria, and refining the process of data synthesis and analysis to enhance that clarity and readability of this systematic review. These modifications were updated in the revision notes section of the PROSPERO.

Literature search strategy

Literature searches were conducted in PubMed, Embase, Web of Science, Cochrane Library, CINAHL, SinoMed, CNKI, and Wanfang Database, covering publications up to December 24, 2023. A comprehensive search strategy was developed using a combination of Medical Subject Headings terms and free-text terms, as detailed in Supplementary Table 2 . Furthermore, reference lists of articles and reviews meeting the inclusion criteria were reviewed for additional relevant studies.

Inclusion and exclusion criteria

The inclusion criteria for this systematic review included: 1) Population: Patients diagnosed with any diseases or symptoms; 2) Intervention: Any interventions involving digital twins; 3) Controls: Non-digital twin groups, such as standard care or conventional therapy, as well as no control group; 4) Outcomes: Health-related outcomes as the primary outcomes of interest; 5) Study design: All study designs that measured patient health-related outcomes after digital twins were included, including intervention studies and predictive cohort studies.

Initially, duplicates were removed. Exclusion criteria included: 1) Papers lacking original data, such as reviews, protocols, and conference abstracts; 2) Studies not in English or Chinese; 3) Surveys focusing on implementation and qualitative studies related to requirements. In cases of data duplication, the most comprehensive data report was included.

Study selection and Data extraction

Following the automatic removal of duplicates, two independent reviewers (MD.SHEN and SB.CHEN) conducted initial screenings of titles and abstracts against the predefined inclusion and exclusion criteria to identify potentially relevant studies. Afterward, the same reviewers examined the full texts of these shortlisted articles to confirm their suitability for inclusion. This process also involved checking the reference lists of these articles for any additional studies that might meet the criteria. Data from the included studies were systematically extracted using a pre-designed extraction form. Recorded information included the first author’s name, publication year, country of origin, type of study, sample size, study population, intervention, controls, measurements, and an appraisal of each study. Disagreements between the reviewers were resolved by consultation with a third senior reviewer (XD.DING), ensuring consensus.

Quality appraisal

The Joanna Briggs Institute (JBI) scales 48 were used to assess the quality and potential bias of each study included in the review, employing specific tools tailored to the type of study under evaluation. These tools feature response options of “yes,” “no,” “unclear,” or “not applicable” for each assessment item. For randomized controlled trials (RCTs), the JBI scale includes 13 items, with answering “yes” to at least six items indicating a high-quality study. Quasi-experimental studies were evaluated using a nine-item checklist, where five or more positive responses qualify the research as high quality. Cohort studies underwent evaluation through an 11-item checklist, with six or more affirmative responses indicating high quality. The assessment was independently carried out by two reviewers (MD.SHEN and SB.CHEN), and any disagreements were resolved through consultation with a third senior reviewer (XD.DING), ensuring the integrity and accuracy of the quality assessment.

Data synthesis and analysis

Given the heterogeneity in type of study and outcome measures, a meta-analysis was deemed unfeasible. Instead, a quantitative content analysis was employed to analyze all the selected studies 49 , 50 . Key information was extracted using a pre-designed standardized form, including the first author’s name, patient characteristics, intervention functional characteristics, measurements, results, effectiveness, and adverse events. Two reviewers (MD.SHEN and SB.CHEN) independently coded digital twin technology into three categories for descriptive analysis: personalized health management, precision individual therapy effects, and predicting individual risk, based on its functional characteristics. The Kappa statistic was applied to evaluate the inter-rater reliability during the coding process, yielding a value of 0.871, which signifies good agreement between the researchers 51 , 52 . The assessment of digital twins effectiveness was based on statistical significance ( P -value or 95% confidence interval). Outcomes with statistical significance were labeled as “resultful,” whereas those lacking statistical significance were deemed “resultless.” For quasi-experimental studies, significant changes in the authors’ self-reports were used to determine the effectiveness in the absence of reporting of statistical significance. The proportion of effectiveness was calculated as the number of “resultful” indicators divided by the total number of outcomes within each category.

Data availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Code availability

Code sharing is not applicable to this article as no codes were generated or analyzed during the current study.

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MD.SHEN contributed to the data collection, analysis and the manuscript writing. SB.CHEN contributed to the data collection and analysis. XD.DING contributed to the critical revision of the manuscript as well as the initial study conception. All authors read and approved the final manuscript, and jointly take responsibility for the decision to submit this work for publication.

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Shen, Md., Chen, Sb. & Ding, Xd. The effectiveness of digital twins in promoting precision health across the entire population: a systematic review. npj Digit. Med. 7 , 145 (2024). https://doi.org/10.1038/s41746-024-01146-0

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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On This Page:

Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

Famous Case Studies

Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

Studying the effectiveness of psychotherapy approaches with an individual patient
Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

Studying psychological development from birth through adolescence
Cases of learning disabilities, autism spectrum disorders, ADHD
Effects of trauma, abuse, deprivation on development

Types of Case Studies

Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

News/Media – News coverage of events related to the case study.
Academic articles – Journal articles, dissertations etc. that discuss the case.
Government reports – Official data and records related to the case context.
Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
Include client demographics like age and gender, information about social relationships, and mental health history.
Describe all physical, emotional, and/or sensory symptoms reported by the client.
Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
Present the results of the intervention,including any quantitative or qualitative data collected.
For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
Offer clinical implications, and suggest future research directions.

5. Additional Items

Thank specific assistants for writing support only. No patient acknowledgments.
References should directly support any key claims or quotes included.
Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
Provides detailed (rich qualitative) information.
Provides insight for further research.
Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

Lacking scientific rigor and providing little basis for generalization of results to the wider population.
Researchers’ own subjective feelings may influence the case study (researcher bias).
Difficult to replicate.
Time-consuming and expensive.
The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895). Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head. Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868). Recovery from the Passage of an Iron Bar through the Head . Publications of the Massachusetts Medical Society. 2 (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972). Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

Case Study Approach
Case Study Method
Enhancing the Quality of Case Studies in Health Services Research
“We do things together” A case study of “couplehood” in dementia
Using mixed methods for evaluating an integrative approach to cancer care: a case study

Research Methodology

Qualitative Data Coding

What Is a Focus Group?

Cross-Cultural Research Methodology In Psychology

What Is Internal Validity In Research?

Research Methodology , Statistics

What Is Face Validity In Research? Importance & How To Measure

Criterion Validity: Definition & Examples

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A new, nano-scale look at how the SARS-CoV-2 virus replicates in cells may offer greater precision in drug development, a Stanford University team reports in Nature Communications . Using advanced microscopy techniques, the researchers produced what might be some of the most crisp images available of the virus’s RNA and replication structures, which they witnessed form spherical shapes around the nucleus of the infected cell.

“We have not seen COVID infecting cells at this high resolution and known what we are looking at before,” said Stanley Qi , Stanford associate professor of bioengineering in the Schools of Engineering and of Medicine and co-senior author of the paper. “Being able to know what you are looking at with this high resolution over time is fundamentally helpful to virology and future virus research, including antiviral drug development.”

Blinking RNA

The work illuminates molecular-scale details of the virus’ activity inside host cells. In order to spread, viruses essentially take over cells and transform them into virus-producing factories, complete with special replication organelles. Within this factory, the viral RNA needs to duplicate itself over and over until enough genetic material is gathered up to move out and infect new cells and start the process over again.

The Stanford scientists sought to reveal this replication step in the sharpest detail to date. To do so, they first labeled the viral RNA and replication-associated proteins with fluorescent molecules of different colors. But imaging glowing RNA alone would result in fuzzy blobs in a conventional microscope. So they added a chemical that temporarily suppresses the fluorescence. The molecules would then blink back on at random times, and only a few lit up at a time. That made it easier to pinpoint the flashes, revealing the locations of the individual molecules.

Using a setup that included lasers, powerful microscopes, and a camera snapping photos every 10 milliseconds, the researchers gathered snapshots of the blinking molecules. When they combined sets of these images, they were able to create finely detailed photos showing the viral RNA and replication structures in the cells. “We have highly sensitive and specific methods and also high resolution,” said Leonid Andronov, co-lead author and Stanford chemistry postdoctoral scholar. “You can see one viral molecule inside the cell.”

The resulting images, with a resolution of 10 nanometers, reveal what might be the most detailed view yet of how the virus replicates itself inside of a cell. The images show magenta RNA forming clumps around the nucleus of the cell, which accumulate into a large repeating pattern. “We are the first to find that viral genomic RNA forms distinct globular structures at high resolution,” said Mengting Han, co-lead author and Stanford bioengineering postdoctoral scholar.

Video showing the different colored fluorescent labels blinking on and off, revealing more precise locations for individual molecules. | Leonid Andronov, Moerner Laboratory

The clusters help show how the virus evades the cell’s defenses, said W. E. Moerner , the paper’s co-senior author and Harry S. Mosher Professor of Chemistry in the School of Humanities and Sciences. “They’re collected together inside a membrane that sequesters them from the rest of the cell, so that they’re not attacked by the rest of the cell.”

Nanoscale drug testing

Compared to using an electron microscope, the new imaging technique can allow researchers to know with greater certainty where virus components are in a cell thanks to the blinking fluorescent labels. It also can provide nanoscale details of cell processes that are invisible in medical research conducted through biochemical assays. The conventional techniques “are completely different from these spatial recordings of where the objects actually are in the cell, down to this much higher resolution,” said Moerner. “We have an advantage based on the fluorescent labeling because we know where our light is coming from.”

Seeing exactly how the virus stages its infection holds promise for medicine. Observing how different viruses take over cells may help answer questions such as why some pathogens produce mild symptoms while others are life-threatening. The super-resolution microscopy can also benefit drug development. “This nanoscale structure of the replication organelles can provide some new therapeutic targets for us,” said Han. “We can use this method to screen different drugs and see its influence on the nanoscale structure.”

Indeed, that’s what the team plans to do. They will repeat the experiment and see how the viral structures shift in the presence of drugs like Paxlovid or remdesivir. If a candidate drug can suppress the viral replication step, that suggests the drug is effective at inhibiting the pathogen and making it easier for the host to fight the infection.

The researchers also plan to map all 29 proteins that make up SARS-CoV-2 and see what those proteins do across the span of an infection. “We hope that we will be prepared to really use these methods for the next challenge to quickly see what’s going on inside and better understand it,” said Qi.

For more information

Acknowledgements: Additional Stanford co-authors include postdoctoral scholar Yanyu Zhu, PhD student Ashwin Balaji, former PhD student Anish Roy, postdoctoral scholar Andrew Barentine, research specialist Puja Patel, and Jaishree Garhyan, director of the In Vitro Biosafety Level-3 Service Center . Moerner is also a member of Stanford Bio-X and the Wu Tsai Neurosciences Institute, and a faculty fellow of Sarafan ChEM-H . Qi is also a member of Bio-X, the Cardiovascular Institute , the Maternal & Child Health Research Institute (MCHRI), the Stanford Cancer Institute, and the Wu Tsai Neurosciences Institute, an institute scholar at Sarafan ChEM-H , and a Chan Zuckerberg Biohub – San Francisco Investigator.

This research was funded by the National Institute of General Medical Sciences of the National Institutes of Health. We also acknowledge use of the Stanford University Cell Sciences Imaging Core Facility.

Taylor Kubota, Stanford University: [email protected]

Digital twin on concepts, enabling technologies, and applications

Review Paper
Published: 03 June 2024
Volume 46 , article number 420 , ( 2024 )

Cite this article

Zhang Bing 1 ,
Michael Enyan ORCID: orcid.org/0000-0002-5382-1377 1 ,
Jesse Nii Okai Amu-Darko 2 , 3 ,
Eliasu Issaka 3 ,
Liu Hongyu 1 ,
Rao Junsen 1 &
Zhang Xinxing 1

The timely growth of data collection and virtual technology has led to advancements in digital twin (DT) technology, which has since become one of the primary research areas and provides enormous possibilities for various industry fields . Based on ultra-fidelity models, DT is an efficient method for realizing the merging of physical and virtual environments. Scholars investigated associated theories and modeling techniques, critical technologies for realizing continuous links and communication between physical and virtual entities, and other researchers concentrated on providing frameworks for the practical application of DT. This article aims to summarize common industrial cases to determine the present status of DT research. This paper discusses the concept of DT technology, the properties that define it, and the DT framework used in the industry. It also reviews the DT application and the findings of associated studies. Some present challenges in DT development, and potential DT prospects are discussed. Finally, we utilize the 6-degrees-of-freedom parallel robot as a case study to illustrate a future application of DT.

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Data sharing does not apply to this article as no datasets were generated or analyzed during the current study.

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This research was financially supported by the National Natural Science Foundation of China Grant No. 51805215, the National Natural Science Foundation of China, Grant No. 52075223, the National Natural Science Foundation of China, Grant No. 51975255, and College Student Innovation and Practice Fund of Industrial Center of Jiangsu University No. ZXJG2022046.

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Bing, Z., Enyan, M., Amu-Darko, J.N.O. et al. Digital twin on concepts, enabling technologies, and applications. J Braz. Soc. Mech. Sci. Eng. 46 , 420 (2024). https://doi.org/10.1007/s40430-024-04973-0

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Published: 29 May 2024

Exploring the use of body worn cameras in acute mental health wards: a mixed-method evaluation of a pilot intervention

Una Foye 1 , 2 ,
Keiran Wilson 1 , 2 ,
Jessica Jepps 1 , 2 ,
James Blease 1 ,
Ellen Thomas 3 ,
Leroy McAnuff 3 ,
Sharon McKenzie 3 ,
Katherine Barrett 3 ,
Lilli Underwood 3 ,
Geoff Brennan 1 , 2 &
Alan Simpson 1 , 2

BMC Health Services Research volume 24 , Article number: 681 ( 2024 ) Cite this article

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Body worn cameras (BWC) are mobile audio and video capture devices that can be secured to clothing allowing the wearer to record some of what they see and hear. This technology is being introduced in a range of healthcare settings as part of larger violence reduction strategies aimed at reducing incidents of aggression and violence on inpatient wards, however limited evidence exists to understand if this technology achieves such goals.

This study aimed to evaluate the implementation of BWCs on two inpatient mental health wards, including the impact on incidents, the acceptability to staff and patients, the sustainability of the resource use and ability to manage the use of BWCs on these wards.

The study used a mixed-methods design comparing quantitative measures including ward activity and routinely collected incident data at three time-points before during and after the pilot implementation of BWCs on one acute ward and one psychiatric intensive care unit, alongside pre and post pilot qualitative interviews with patients and staff, analysed using a framework based on the Consolidated Framework for Implementation Research.

Results showed no clear relationship between the use of BWCs and rates or severity of incidents on either ward, with limited impact of using BWCs on levels of incidents. Qualitative findings noted mixed perceptions about the use of BWCs and highlighted the complexity of implementing such technology as a violence reduction method within a busy healthcare setting Furthermore, the qualitative data collected during this pilot period highlighted the potential systemic and contextual factors such as low staffing that may impact on the incident data presented.

This study sheds light on the complexities of using such BWCs as a tool for ‘maximising safety’ on mental health settings. The findings suggest that BWCs have a limited impact on levels of incidents on wards, something that is likely to be largely influenced by the process of implementation as well as a range of contextual factors. As a result, it is likely that while BWCs may see successes in one hospital site this is not guaranteed for another site as such factors will have a considerable impact on efficacy, acceptability, and feasibility.

Peer Review reports

Body worn cameras (BWC) are mobile audio and video capture devices that can be secured to clothing allowing the wearer to record some of what they see and hear. In England, these have been introduced in the National Health Service (NHS) as part of a violence reduction strategy [ 1 ] which emphasises the reduction of aggression and violence against staff. The NHS Staff Survey 2022 found that 14.7% of NHS staff had experienced at least one incident of physical violence from patients, relatives or other members of the public in the previous 12 months. Violent attacks on staff were found to contribute to almost half of staff illness [ 2 ]. Levels of violence against staff working in mental health trusts remain much higher than other types of healthcare providers [ 3 ]. Numerous reports internationally highlight the increased risks faced by staff working in psychiatric care [ 4 ], though studies have reported that both ward staff and mental health patients experience violence and feeling unsafe on inpatient wards [ 5 , 6 ].

Body worn cameras have been in use for over a decade within law enforcement, where they hoped to provide transparency and accountability within use-of-force incidents and in the event of citizen complaints against police [ 7 ]. It was believed that video surveillance would help identify integral problems within the organisation, improve documentation of evidence, reduce use-of-force incidents, improve police-community relations, and provide training opportunities for officers [ 8 ]. However, a recent extensive international systematic review by Lum et al. [ 9 ], found that despite the successes noted in early evaluations, the way BWCs are currently used by police may not substantially affect most officer or citizen behaviours. Irrespective of these findings, other public services such as train operators have been implementing BWCs for security purposes, with reductions reported in the number of assaults on railway staff [ 10 ].

A recent systematic review of BWC use in public sector services established that there is a poor evidence base supporting the use of BWCs in the reduction of violence and aggression [ 11 ]. Yet, we are seeing a swift increase in the use of BWCs in mental health settings with that aim, with few studies conducted on the use of BWC technology in inpatient mental health wards, and even fewer studies exploring staff or patients’ views. Two evaluations conducted in England reported mixed results with both increases and decreases in violence and aggression found, and variation between types of wards. There is some suggestion of a reduction in more serious incidents and the use of restraint, but quality of evidence is low [ 12 , 13 ].

The use of BWCs in mental healthcare settings for safety and security remains a contentious topic due to the lack of evidence regarding the influence that such technology has on preventing violence and aggression and the complex philosophical and ethical issues raised, particularly where many patients may lack capacity and/or are detained under mental health legislation [ 14 ]. Additionally, there are concerns that BWCs may be used as a ‘quick fix’ for staff shortages rather than addressing the wider systemic and resourcing issues facing services [ 15 ]. With little independent evaluation of body-worn cameras in mental health settings, many of these concerns remain unanswered. There is also limited understanding of this technology from an implementation perspective. Therefore, in this study we aimed to conduct an independent evaluation of the introduction of BWCs as a violence reduction intervention on two inpatient mental health wards during a six-month pilot period to explore the impact of using the technology, alongside an exploration of the facilitators and barriers to implementation.

Research aim(s)

To evaluate the implementation of BWCs on two inpatient mental health wards, including the impact on incidents, the acceptability to staff and patients, the sustainability of the resource use and ability to manage the use of BWCs on these wards.

Patient and public involvement

The research team included a researcher and independent consultant, each with lived experience of mental health inpatient care. In addition, we recruited and facilitated a six member Lived Experience Advisory Panel (LEAP). This group was made up of patients and carers, some of whom had experienced the use of BWCs. Members were of diverse ethnic backgrounds and included four women and two men. The LEAP provided guidance and support for the research team in developing an understanding of the various potential impacts of the use of BWCs on inpatient mental health wards. Members contributed to the design of the study, development of the interview schedule, practice interviews prior to data collection on the wards, and supported the analysis and interpretation of the data, taking part in coding sessions to identify themes in the interview transcripts. The LEAP met once a month for two hours and was chaired by the Lived Experience Research Assistant and Lived Experience Consultant. Participants in the LEAP were provided with training and paid for their time.

The pilot introduction of the body worn cameras was conducted within a London mental health Trust consisting of four hospital sites with 17 acute wards. The research team were made aware of extensive preparatory work and planning that was conducted at a directorate and senior management level prior to camera implementation, including lived experience involvement and consultation, and the development of relevant policies and protocols inclusive of a human rights assessment and legal consultation.

The pilot period ran from 25th April to 25th October 2022. Reveal (a company who supply BWCs nationally across the UK) provided the Trust with 12 Calla BWCs for a flat fee that covered use of the cameras, cloud-based storage of footage, management software, and any support/maintenance required during the pilot period. Cameras were introduced to two wards based on two hospital sites, with six cameras provided to each of the wards on the same date. Training on using the BWCs was provided by the BWC company to staff working on both wards prior to starting the pilot period. Ward one was a 20-bed male acute inpatient ward, representing the most common ward setting where cameras have been introduced. Ward two was a ten-bed male Psychiatric Intensive Care Unit (PICU), representing smaller and more secure wards in which patients are likely to present as more unwell and where there are higher staff to patient ratios.

To answer our research questions, we used a mixed-methods design [ 16 ]. Using this design allowed us to investigate the impact of implementing BWCs in mental health settings on a range of quantitative and qualitative outcomes. This mixed methods design allows the study to statistically evaluate the effectiveness of using BWCs in these settings on key dependent variables (i.e., rates of violence and aggression, and incidents of conflict and containment) alongside qualitatively exploring the impact that the implementation of such technology has on patients and staff.

To ensure that the study was able to capture the impact and effect of implementation of the cameras, a repeated measures design was utilised to capture data at three phases on these wards:

Pre-pilot data: data prior of the implementation of the BWCs (quantitative and qualitative data).

Pilot period data: data collected during the six-month pilot period when BWCs were implemented on the wards (quantitative and qualitative data).

Post-pilot: data collected after the pilot period ended and cameras had been removed from the wards (quantitative data only).

Quantitative methods

Quantitative data was collected at all three data collection periods:

Pre-period: Data spanning six months prior to the implementation of BWCs (Nov 21 to May 22).

Pilot period: Data spanning the six months of the Trusts pilot period of using BWCs on the wards (June 22 to Nov 22).

Post-pilot: Data spanning the six months following the pilot period, when BWCs had been removed (Dec 22 to May 23).

Quantitative measures

To analyse the impact of BWC implementation, we collected two types of incident data related to violence and aggression and use of containment measures, including BWCs. Combined, these data provide a view of a wide range of incidents and events happening across the wards prior to, during, and after the implementation and removal of the BWCs.

The patient-staff conflict checklist

The Patient-staff Conflict Checklist (PCC-SR) [ 17 ] is an end of shift report that is completed by nurses to collate the frequency of conflict and containment events. This measure has been used successfully in several studies on inpatient wards [ 18 , 19 , 20 ].The checklist consists of 21 conflict behaviour items, including physical and verbal aggression, general rule breaking (e.g., smoking, refusing to attend to personal hygiene), eight containment measures (e.g., special observation, seclusion, physical restraint, time out), and staffing levels. In tests based on use with case note material, the PCC-SR has demonstrated an interrater reliability of 0.69 [ 21 ] and has shown a significant association with rates of officially reported incidents [ 22 ].

The checklist was revised for this study to include questions related to the use of BWCs ( e.g., how many uses of BWCs happened during the shift when a warning was given and the BWC was not used; when a warning was given and the BWC was used; when the BWC was switched on with no warning given ) in order to provide insight into how the cameras were being used on each ward (see appendix 1). Ward staff were asked to complete the checklist online at the end of each shift.

Routinely collected incident data (via datix system)

To supplement the PCC-SR-R, we also used routinely collected incident data from both wards for all three data collection phases. This data is gathered as part of routine practice by ward staff members via the Datix system Datix [ 23 ] is a risk management system used widely across mental health wards and Trusts in the UK to gather information on processes and errors. Previous studies have utilised routinely collect data via this system [ 24 , 25 ]. Incidents recorded in various Datix categories were included in this study (see Table 1 ). Incidents were anonymised before being provided to the research team to ensure confidentiality.

Routinely collected data included:

Recorded incidents of violence and aggression.

Recorded use of restrictive practices including seclusion, restraint, and intra-muscular medication/rapid tranquilisations.

Patient numbers.

Staffing levels.

Numbers of staff attending BWC training.

Quantitative data analysis

Incident reports.

Incident reports retrieved from Datix were binary coded into aggregate variables to examine violence and aggression, self-harm, and other conflict as outlined in Table 1 . Multivariate analyses of variance (MANOVA) were used to identify differences in type of incident (violence against person, violence against object, verbal aggression, self-harm, conflict) for each ward. MANOVA was also used to examine differences in incident outcomes (severity, use of restrictive practice, police involvement) across pre-trial, trial, and post-trial periods for each ward. Incident severity was scored by ward staff on a four-point scale (1 = No adverse outcome, 2 = Low severity, 3 = Moderate severity, 4 = Severe). Use of restrictive practice and police involvement were binary coded for presence or absence. Analyses were conducted using SPSS [ 26 ].

Patient-staff conflict checklist shift-report – revised (PCC-SR-R; )

Data were condensed into weeks for analysis rather than shifts to account for variability in PCC-SR-R submission by shift. Linear regressions assessed the relationship between BWC use and incident outcome (severity, use of restrictive practice, police involvement).

Qualitative methods

We used semi-structured qualitative interviews to explore participants’ experiences of BWCs on the ward to understand the impact of their use as well as to identify any salient issues for patients, staff and visitors that align with the measures utilised within the quantitative aspect of this study. These interviews were conducted at two time points: pre-pilot and at the end of the six-month pilot period.

Sample selection, eligibility, and recruitment

Convenience sampling was used to recruit staff and patients on wards. Researchers approached ward managers to distribute information sheets to staff, who shared that information with patients. Staff self-selected to participate in the study by liaising directly with the research team. Patients that were identified as close to discharge and having capacity to consent were approached by a clinical member of the team who was briefed on the study inclusion criteria (see Table 2 ). The staff member spoke with the patient about the study and provided them with a copy of the information sheet to consider. If patients consented, a member of the research team approached the participant to provide more information on the study and answer questions. After initial contact with the research team, participants were given a 24-hour period to consider whether they wanted to participate before being invited for an interview.

Participants were invited to take part in an interview within a private space on the ward. Interviews were scheduled for one hour with an additional 15 min before and after to obtain informed consent and answer any questions. Participation was voluntary and participants were free to withdraw at any time. To thank patients for their time, we offered a £10 voucher following the interview. Interviews were audio-recorded and saved to an encrypted server. Interview recordings were transcribed by an external company, and the research team checked the transcripts for accuracy and pseudonymised all participants. All transcripts were allocated a unique ID number and imported to MicroSoft Excel [ 27 ] for analysis.

Qualitative data analysis

Qualitative data were analysed using a framework analysis [ 28 ] informed by implementation science frameworks. Our coding framework used the Consolidated Framework for Implementation Research (CFIR) [ 29 ], which is comprised of five major domains including: Intervention Characteristics, Implementation Processes, Outer Setting, Inner Setting, and Characteristics of the Individual. Each domain consists of several constructs that reflect the evidence base of the types of factors that are most likely to influence implementation of interventions. The CFIR is frequently used to design and conduct implementation evaluations and is commonly used for complex health care delivery interventions to understand barriers and facilitators to implementation. Based on its description, the CFIR is an effective model to address our research question, particularly given the complexity of the implementation of surveillance technology such as BWCs in this acute care setting.

The initial analytic stage was undertaken by eight members of the study team with each researcher charting data summaries onto the framework for each of the interviews they had conducted on MicroSoft Excel [ 27 ]. Sub-themes within each broad deductive theme from our initial framework were then derived inductively through further coding and collaborative discussion within the research team, inclusive of Lived Experience Researcher colleagues. Pseudonyms were assigned to each participant during the anonymisation of transcripts along with key identifiers to provide context for illustrative quotes (e.g., P = patient, S = staff, A = acute ward, I = Intensive Care, Pre = pre-BWC implementation interview, Post = Post BWC implementation interview).

All participants gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Health Research Authority: London - Camden & Kings Cross Research Ethics Committee (IRAS Project ID 322,268, REC Reference 23/LO/0337).

Quantitative results

Exploring how body worn cameras were used during the pilot period.

Analysis of the PCC-SR-R provides information about how the BWCs were used on a day-to-day basis during the pilot period. Out of 543 total shift reports completed, BWC use was reported 50 times, indicating that BWCs were used on less than 10% of shifts overall; 78% of those deployments were on the Acute ward (see Figure 1 ). Overall, the majority of deployments happened as activations without a warning being given ( n = 30, 60% of activations), 19 times the BWC was deployed with a warning but the camera was not activated (38%), and only one was the camera activated without a warning being given (2%).

BWC use by ward per week of pilot (no data available before week 6 on Ward 1)

According to the PCC-SR-R, a total of 227 incidents of aggression occurred during the pilot period across both wards (see Table 3 ). Overall, there were small statistically significant correlations between BWC usage and certain types of conflict, aggression, and restrictive practice. Results found that BWC use was positively correlated with verbal aggression and use of physical restraint. BWC use was moderately positively correlated with verbal aggression ( r = .37, p < .001). This indicates that BWCs were more likely to be used in incidents involving verbal aggression, which do not tend to be documented in Datix. Similarly, BWC use was moderately positively correlated with physical restraint ( r = .31, p < .001) indicating that they were also more likely to be used alongside physical restraint.

Exploring the impact of BWCs utilising routinely collected ward data

Acute ward results.

Routine data collected via Datix records were used to examine differences in frequency of conflict and aggression, incident severity, and use of containment measures before, during, and after introduction of BWCs on each trial ward (see Table 4 ).

There was no effect of trial period on incident type ( F (10, 592) = 1.703, p = .077, Wilk’s Λ = 0.945), meaning there was no discernible difference in the type of incidents that occurred (E.g., verbal aggression, physical aggression) before, during, and after the pilot phase.

Incident outcomes

There was an effect of trial period on incident outcomes ( F (6, 596) = 10.900, p < .001, Wilk’s Λ = 0.812). Incident severity was statistically significantly higher in the trial and post-trial periods compared to the pre-trial period. Use of restrictive practice was significantly lower in the post-trial period compared to the pre-trial and trial period. Police involvement was also lower in the post-trial period compared to the pre-trial and trial periods (see Table 5 ).

Results for the psychiatric intensive care unit

There was an effect of trial period on incident type ( F (10, 490) = 4.252, p < .001, Wilk’s Λ = 0.847). Verbal aggression was statistically significantly higher in the post-trial period compared to the pre and trial periods. Self-harm was statistically significantly higher in the trial period compared to the pre-trial and post-trial periods. There were no differences in violence against a person ( p = .162), violence against an object or conflict behaviour (see Table 4 ).

There was a statistically significant difference in incident outcome across the trial periods ( F (6, 494) = 12.907, p < .001, Wilk’s Λ = 0.747). There was no difference in incident severity or police involvement. However, use of restrictive practice was statistically significantly higher in the pre-trial period, reducing in the test period, and reducing further in the post-trial period (see Table 5 ).

Qualitative findings

A total of 22 participants took part in interviews: five patients and 16 staff members. During the pre-pilot interviews a total of nine staff took part (five in the acute ward, four in the PICU ward) and two patients (both from the acute ward). After the pilot period, a total of eight staff took part (four from each ward) and three patients (all from the acute ward). Table 6 includes a full description of participants.

Below we have presented the key themes aligning to the five core CFIR categories of Intervention Characteristics, Characteristics of Individuals, The Process of Implementation, the Inner Setting, and The Outer Setting (see Table 7 ).

Intervention characteristics

Design and usability of wearing a bwc on the ward.

When discussing the use of the BWCs, staff noted a range of design issues related to the cameras that they said impacted on their use and acceptance of the cameras. This included the nature of the camera pulling on clothing necklines (a particular issue for female staff working on male wards), and overheating causing discomfort and irritation to skin, challenges with infection control, as well as the issue of cameras in a mental health setting where they can be easily grabbed, thrown and broken during an incident. Staff often cited these design issues as related to the lack of proactive use of the cameras on the wards.

There were issues around the devices getting overheated or about it going on your clothing, it pulls down the top… we had one person who was leading on it, whenever he was around, of course, the camera was being used, but if he wasn’t there, people weren’t as proactive in using the camera. Petra (f), Staff, A, Post.

There were also issues with staff forgetting to wear the cameras, forgetting to switch them on during incidents, and forgetting to charge them at the end of the shift, reducing the potential use of the cameras by other staff. These were perceived as key logistical issues prior to the pilot and were reported as issues at the end of the pilot by several staff on the wards.

The practicalities of will they actually turn it on in those sorts of incidents, I don’t know. Just little stuff as well, like if they don’t put it back on the docking station, so you think you’re charging it for next shift but then it’s not charged and the battery is dead, that’s one less camera to use, so little stuff. Jamal (m), Staff, A, Pre.

In relation to usability, staff noted that the cameras were small and easy to use given their simple single switch interface. It was felt that not having to upload and manage the data themselves made cameras more user friendly and usable by staff members. Protocols put into place such as signing the cameras in and out, and allocation for use during shifts were likened to procedures in place for other security measures therefore the implementation of this for the BWCs was viewed as easy for many staff.

It’s just like the ASCOM alarms that we wear. There’s a system to sign in and sign out, and that’s it. Alice (f), Staff, A, Pre.

While staff were generally positive about the usability of the cameras, some were cautious of with concerns for those less confident with technology.

… you have to be conscious that there’s some people – it’s quite easy to use, but I can say that because I’m alright using devices and all that but there’s some that are older age or not that familiar with using devices that may struggle with using it… they’re feeling a bit anxious and a bit scared, if they’re not familiar with it then they won’t use it. Jamal (m), Staff, A, Pre.

Evidence strength and quality: do BWCs change anything?

There were conflicting reports regarding the potential benefits of using BWCs on the wards, with both staff and patients reporting mixed perceptions as to whether the cameras might reduce violence and aggression. In the pre-pilot interviews, some staff reported feeling that the BWCs may have a positive impact on reducing physical violence.

I think it’s going to reduce violence and aggression on the ward…I don’t think they’ll want to punch you…they might be verbally abusive but in terms of physical that might reduce. Sarah (f), Staff, I, Pre.

Patients however noted that the cameras might hold staff to account of their own behaviours and therefore may improve care, however they felt that this impact would wear off after the first few months after which people might forget about the cameras being there.

Now they’ve got the body cams, it’s going to be a lot of changes. They’ll think, ‘Ooh well he’s on tape’. So, it might do something to their conscience, they actually start to listen to patients… until the novelty wears off and it might go back to square one again. Ian (m), Patient, A, Pre.

One staff member suggested that incident rates had reduced following introduction of the BWCs, but they remained unsure as to whether this was due to the cameras, reflecting that violence and aggression on wards can be related to many factors.

I know our violence and aggression has reduced significantly since the start of the cameras pilot… I don’t know, because obviously wearing the camera’s one thing, but if they weren’t in use, I don’t know maybe just the presence of the camera made a difference. But yeah, it’s hard to tell. Petra (f), Staff, A, Post.

In contrast, several staff reported that they had seen limited evidence for such changes.

I used it yesterday. He was aggressive and I used it, but he even when I was using [it] he doesn’t care about the camera… it didn’t make any difference… It doesn’t stop them to do anything, this camera does not stop them to do anything. Abraham (m), Staff, I, Post.

Some staff suggested that in some circumstances the cameras increased patient agitation and created incidents, so there was a need to consider whether the BWCs were going to instigate aggression in some circumstances.

There has been with a few patients because they will threaten you. They will tell you, ‘if you turn it on, I’m gonna smash your head in’. So incidents like that, I will not turn it on… Yeah, or some of them will just tell you, ‘if you come close by, I’m going to pull that off your chest’. So things like that, I just stay back. Ada (f), Staff, A, Post.

One rationale for a potential lack of effectiveness was noted by both staff and patients and was related to the levels of acute illness being experienced by patients which meant that for many they were too unwell to have insight into their own actions or those of staff switching on the cameras.

We’ve had instances where patients are so unwell that they just don’t care. You switch on the camera, whether you switch it on or not, it doesn’t really change the behaviour. ‘All right, okay, whatever switch it on’. They’re so unwell, they’re not really understanding. Petra (f), Staff, A, Post. It might make [staff] feel safer as a placebo effect, but I don’t think it would necessarily make them safer… I think the people that are likely to attack a member of staff are crazy enough that they’re not gonna even consider the camera as a factor. Harry (m), Patient, A, Pre.

This lack of evidence that the cameras were necessarily effective in reducing incident rates or severity of incidents may have had an impact on staff buy-in and the use of the cameras as a result. One staff member reflected that having feedback from senior management about the impact and evidence would have been useful during the pilot period to inform ward staff whether the cameras were influencing things or not.

Staff want feedback. I don’t think we’ve had any since we’ve had the cameras… it would be nice to get feedback from, I don’t know, whoever is watching it, and stuff like that. Ada (f), Staff, A, Post.

Relative advantage: are BWCs effective and efficient for the ward?

Due to a combination of personal beliefs related to BWCs, the lack of evidence of their impact on violence and aggression, and other elements of care and culture on the wards, a number of staff and patients explored alternative interventions and approaches that may be more beneficial than BWCs. Both staff and patients suggested that Closed Circuit Television (CCTV) as an intervention that provided the transparency of using cameras and video footage but with an independent perspective. This was felt by many to remove the bias that could be introduced in BWC use as the video capture didn’t require staff control of the filming.

I feel like [BWCs] puts all the power and trust into the hands of the staff and I feel that it would be better to have CCTV on the ward because CCTV is neutral. Harry (m), Patient, A, Pre. I have control over that [BWC recording] … It kind of gives that split as well between staff and patients. You can tell me or I can tell you when to switch it on. Whereas I feel like a CCTV camera is there all the time. Nobody’s asking to switch it on. It’s there. If you wanted to review the footage you can request it, anyone can request to view the footage for a legitimate reason. Whereas the camera can come across as if you’re threatening. Petra (f), Staff, A, Post.

In addition, some participants reflected that the nature and design of BWCs meant that unless staff were present for an incident it wouldn’t be captured, whereas CCTV has the advantage of being always present.

If there’s CCTV, then it’s the same thing, you get me. Like, if its body worn cameras that people can always do things away from staff. They can always go down to that corridor to have their fight or go to the side where staff ain’t gonna see them to have their fight, but with CCTV you can’t do that. Elijah (m), Patient, A, Post.

In addition to exploring technological and video-based interventions, many staff noted that the key tool to violence reduction had to be the use of de-escalation skills, noting that the use of communication and positive relationships had to be the primary tool before other interventions such as BWCs or CCTV.

We do a lot of verbal de-escalation. So we got our destress room now still open. That has a punch bag, and it’s got sensory tiles, and the aim and hope is that when people do get frustrated, because we’re all human. We all get annoyed at anything or many little things in life. There is the aim that they go into that room and start punching the bag instead of property and damaging furniture. But we also are working really hard on verbal de-escalation and actually trying to listen to patients and talk to them before anything else. And that’s helped a lot. And between this kind of shared, or role modelling, where while we’re showing staff, actually even spending an extra 20 min is okay. If it means you’re not going to end up having to restrain a patient. Petra (f), Staff, A, Post.

By using communication skills and de-escalation techniques skilfully, some staff felt there was no need to utilise the BWCs. One concern with the introduction of the BWCs for staff was that the use of this technology may negatively impact on trust and relationships and the use of de-escalation.

Some situations I feel like it can make a situation worse sometimes… I think a lot of situations can be avoided if you just talk with people…. Trying to find out why they’re angry, trying to just kind of see it from their point of view, understand them… I think maybe additional training for verbal de-escalation is needed first. Patrick (m), Staff, A, Post.

Characteristics of individuals

Staff and patients’ knowledge and beliefs about the intervention.

Overall, there were mixed views among both staff and patients as to whether cameras would reduce incidents, prior to and after the pilot period. When considering the possible impact on violence and aggressive incidents there was a view among staff that there was the need for a nuanced and person-centred view.

All the patients that come in, they’re different you know. They have different perceptions; they like different things… everyone is different. So, it just depends. We might go live, and then we have good feedback because the patients they are open and the understand why we have it, and then as they get discharged and new patients come in it might not go as well. It just depends. Serene (f), Staff, A, Pre.

As a result of the desire to be person-centred in the use of such interventions, one staff member noted that they weighed-up such consequences for the patient before using the BWC and would make decisions not to use the camera where they thought it may have a negative impact.

Actually, with this body worn camera, as I did mention, if a patient is unwell, that doesn’t, the patient will not have the capacity to I mean, say yes, you cannot just put it on like that. Yeah, I know it’s for evidence, but when something happens, you first have to attend to the patient. You first have to attend to the patient before this camera is, for me. Ruby (f), Staff, I, Post.

Some staff questioned the existing evidence and theories as to why BWCs work to reduce incidents, and instead noted that for some people it will instigate an incident, while others may be triggered by a camera.

I’m on the fence of how that is going to work because I know the evidence is that by telling a patient ‘look if you keep escalating I’m gonna have to turn this on’, but I know several of our patients would kind of take that as a dare and escalate just to spite so that you would turn it on. Diana (f), Staff, A, Pre.

In contrast, some staff felt the cameras helped them feel safer on wards due to transparency of footage as evidence for both staff and patients.

They [staff] need to use it for protection, for recording evidence, that type of thing… They can record instances for later evidence. Yeah, for them as well. Safer for them and for patients because you can also have the right to get them to record, because a patient might be in the wrong but sometimes it may be the staff is in the wrong position. And that’s achieving safety for patients as well. Yeah, I think it works both ways. Dylan (m), Patient, A, Post.

Positive buy-in was also related to the potential use of the intervention as a training, learning or reflective tool for staff to improve practice and care and promote positive staff behaviour.

If you know that your actions might be filmed one way or the other, that would make me to step up your behaviour to patients… if you know that your actions can be viewed, if the authority wants to, then you behave properly with patients so I think that will improve the quality of the care to patient. Davide (m), Staff, I, Pre.

While there were some positive attitudes towards the cameras, there remained considerable concerns among participants regarding the transparency of camera use to collate evidence in relation to incidents as it was widely noted that the cameras remain in staff control therefore there is an issue in relation to bias and power.

I do think my gut would say that it wouldn’t necessarily be well received. Because also I think people feel like prisoners in here, that’s how some of the patients have described their experience, so in terms of the power dynamic and also just – I think that can make one feel a bit, even worse, basically, you know? Leslie (m), Staff, A, Pre.

These issues lead to staff reporting they didn’t want to wear the camera.

I’d feel quite uncomfortable wearing one to be honest. Leslie (m), Staff, A, Pre.

The staff control of the cameras had a particular impact on patient acceptability of the intervention as it led to some patients viewing BWCs as being an intervention for staff advantage and staff safety, thus increasing a ‘them and us’ culture and leading to patient resistance to the cameras. This was particularly salient for those with prior negative experiences of police use of cameras or mistrust in staff.

I feel like the fact that the body worn cameras is gonna be similar to how the police use them, if a staff member has negative intent toward a patient, they would be able to instigate an incident and then turn the camera on and use the consequences of what they’ve instigated to expect restraint or injection or whatever else might happen. So, I feel like it would be putting all the power and trust into the hands of the staff and I feel that it would be better to have CCTV on the ward because CCTV is neutral. Whereas, the body worn camera, especially with some of the personality conflicts/bad attitudes, impressions I’ve had from certain members of staff since I’ve been here, I feel like body worn cameras might be abused in that way possible. Harry (m), Patient, A, Pre.

Perceived unintended consequences and impact on care

Prior to the implementation there were concerns from staff that the introduction of BWCs could have consequences beyond the intended use of reducing violence and aggression, unintentionally affecting a range of factors that may impact on the overall delivery of care. There was a key concern regarding the potential negative impact that cameras may have for patients who have paranoia or psychosis as well as for those who may have prior traumatic experiences of being filmed.

It might have negative impacts on these patients because I’m thinking about kind of patients with schizophrenia and things like that who already have paranoid delusions, thinking that people are after them, thinking that people are spying on them, people are watching them, and then seeing kind of cameras around. It might have negative impacts on them. Tayla (f), Staff, I, Pre. When I was admitted I was going through psychosis… I don’t want to be filmed and things like that. So you just see a camera, a guy with a camera on, you are like, are you filming me? Elijah (m), Patient, A, Post.

There was also a considerable concern among both staff and patients that the use of cameras would have a negative impact on the therapeutic relationship between staff and patients. This was felt to be related to the implication that the cameras enhanced a ‘them and us’ dynamic due to the power differential that staff controlling the cameras can create, likened to policing and criminalisation of patients. With the potential of a negative impact on relationships between staff and patients, staff suggested they may be disinclined to use BWCs if it would stop patients speaking to them or approaching them if they needed support.

Yeah, I think it would probably damage [the therapeutic relationship] because I think what’s probably quite helpful is things that maybe create less of a power difference. I think to some extent, [the BWC] might hinder that ability. Like for example imagine going to a therapist and them just like ‘I’ve got this camera in the corner of the room and it’s gonna be filming our session and just in case – or like, just in case I feel that you might get aggressive with me’. Um, I don’t think that’s going to help the therapeutic relationship! Jamal (m), Staff, A, Pre. When you get body worn cameras on there, the relationship as well between staff and patients, is just gonna instantly change because you’re looking like police! Elijah (m), Patient, A, Post.

In contrast, a minority of staff felt that the presence of cameras may improve relationships as they provide transparency of staff behaviour and would encourage staff to behave well and provide high quality care for patients.

It will also help how, improve the way we look at the patients… because if you know that your actions might be filmed one way or the other, that would make me to step up your behaviour you know… you behave properly with patients so I think that will improve the quality of the care to patient. More efficiently, more caring to patient. Davide (m), Staff, I, Pre.

The process of implementation

Planning: top-down implementation.

Staff perceived that BWC implementation directives had been given by senior management or policy stakeholders whom they felt viewed the process from a position of limited understanding due to a lack of ‘frontline’ mental health service experience. This led to a lack of faith amongst staff, and a perception that funds were being misspent.

They sit up there, they just roll it out and see how it works, how it goes. They waste a whole lot of money, millions or whatever, thousands of pounds in it, and then they see that ‘Oh, it’s not gonna work’. They take it back and all of that. Before coming out with it, you need to come speak to us… they just sit up there drinking tea and coffee, and then they’re just like, Oh, yeah, well, let’s do it this way…come stay with these people, work with them, for just I give you a 12 h shift, stay with them. Richard (m), Staff, I, Post.

This was exacerbated when staff felt there was a lack of consultation or explanation.

we don’t always get the ins and outs of certain things…We know that the cameras are coming in and stuff like that, but you know, and obviously it’s gone through every avenue to make sure that it’s fine. But then sometimes we don’t always know the ins and outs to then explain to people why we have the cameras. Patrick (m), Staff, A, Post.

It was also highlighted that due to multiple initiatives being implemented and directives handed down in parallel, staff felt negative towards interventions more widely, with the BWCs being ‘ just another thing to do’ , adding to workload for staff and reducing enthusiasm to use the cameras.

it’s not just to do with the camera, I just think there’s lots of changes happening at once, and there’s loads of new things being constantly introduced that people are just thinking oh it’s another thing. I think that’s what it is more than the camera itself. Alice (f), Staff, A, Pre.

Execution: training, Use and Ward Visibility

Overall, there was a lack of consistency amongst staff in their understanding of the purpose and processes of using the BWCs on the wards.

What do you do, do you record every single thing or, I don’t know. Do you record like, if a patient said, I want to talk to you, confidential, you go sit in a room, do you record things like those or is it just violence and aggression? Ada (f), Staff, A, Post.

The lack of clarity regarding the purpose of the intervention and the appropriate use of the cameras was felt to impact staffs’ attitudes and acceptance of using them and contributed to a lack of transparency or perhaps trust regarding the use of any subsequent video footage.

I think if the importance of the recording was explained a bit more…and how it would improve things, I think people would use it more… that’s why I don’t think it’s always used sometimes… if you’re not sure why some of it’s important, then you’re not going to see the value…I think if you’re gonna keep with them, it’s about updating the training, teaching staff when to use it, then where does that information go? How does that look in terms of improving? Just a bit of transparency, I think. But when you don’t know certain things it’s a bit hard to get behind something or back it, you know? Patrick (m), Staff, A, Post.

The lack of information about the purpose and processes related to the intervention was also seen among patients, with most patients noting that they hadn’t received information about the cameras during their admissions.

No information at all. I don’t think any of the patients know about it. Toby (m), Patient, A, Post.

While training was provided it was widely felt that it was insufficient to provide understanding about the purpose of the cameras or the more in-depth processes beyond operational aspects such as charging and docking. Several staff interviewed were unaware of the training, while others noted that they had an informal run-through by colleagues rather than anything formal.

What training are you talking about?… I wasn’t here, so I was taught by my colleague. I mean, from what I was taught, to operate the camera, and to give a warning to the patient that you’re going to use the camera. Nevis (f), Staff, A, Post.

Longer training with further details beyond operational use was felt to be needed by staff.

I think the training should have to be longer, even if it’s like an hour or something… Like what situations deem the camera to be… more information on the cameras, when to use it, why it’s used, and I think if the importance of the recording was explained a bit more and what it was doing and how that recording would go and how it would improve things. Patrick (m), Staff, A, Post.

Furthermore, there was a need for training to be on a rolling basis given the use of bank staff who were not trained to use the cameras or to understand the proper processes or purpose of using the BWCs, which could leave them vulnerable to misuse or abuse.

We have bank staff [who aren’t trained] so they say ‘I don’t know how to use that camera you are giving me’. Nevis (f), Staff, A, Post.

The inner setting

Ward context: acceptance of violence and aggression is part of the job.

It was widely believed by staff that the nature of working on a mental health ward included accepting that violence and aggression was part of the job. This was not seen as an acceptance of violence but more that the job was providing care for individuals who are mentally unwell, and confusion, fear, frustration and aggression can be part of that. As a result, there was an ambivalence among some staff that the introduction of cameras would change this.

I think like in this line of work, there’s always that potential for like risky behaviours to happen. I’m not sure if putting the camera on will make much difference. Patrick (m), Staff, A, Post.

Staff noted that because of the nature of the job, staff are used to managing these situations and they understood that it was part of the job; therefore, it was unlikely that they would record everything that on paper might be considered an incident.

There’s also enough things that happen here, so I don’t think they would record [the incidents] because it’s just another day here. You know what I’m saying… [staff] can just say, ‘Stop, go back to your room and leave it at that and that kind of be the end of it’. Dylan (m), Patient, A, Post. We are trained for it. Eveline (f), Staff, I, Pre.

This acceptance that incidents are a hazard of mental healthcare was linked to staff’s acknowledgment that many factors make up the complexity of violence and aggression including the nature of individual patients, acuity levels, ward atmosphere, staffing levels, access to activities, leave and outside space. The interplay of multiple factors creates a context in which frustrations and incidents are likely, thus become part of the everyday and ‘normal’ life on the ward for staff and patients alike.

I feel like, you know, how in GP services you say, zero tolerance to abusive language, or any kind of harassment. I don’t think there is that on a psychiatric ward you are kind of expected to take all the abuse and just get on with it. Petra (f), Staff, A, Post.

With staff reported having a higher threshold for these behaviours it was perceived that this was likely to impact on the efficiency of the intervention as staff would be less likely to consider a situation as violent but more ‘ part of the job’ .

Reactive nature of the ward and incidents

Most participants noted that the ward context is always changing with people being admitted and discharged, with daily staff changes and wider turnover of staff, so things are never static and can change at any point. This reflects the dynamic nature of the ward which creates a complex moving picture that staff need to consider and react to.

[the atmosphere] it’s very good at the moment. If you had asked me this two weeks ago, I would say, ‘Oh, my gosh’. But it changes… The type of patient can make your whole ward change… it depends on the client group we have at the time. Nevis (f), Staff, A, Post.

Staff noted that a key limitation of using the cameras to reduce incidents was the reactive nature of the environment and care being provided. This was felt to impact on the feasibility and use of the cameras as staff noted that they often react to what is happening rather than thinking to ‘ put the camera on first ’. It was felt by staff with experience of reacting to incidents that the failure to use BWCs during these processes were linked to staff’s instincts and training to focus on patients as a priority.

Say for instance, you’re in the office, and two patients start fighting, or a patient attacks someone and, all you’re thinking about is to go there to stop the person. You’re not thinking about putting on any camera. You understand? So sometimes it’s halfway through it, somebody might say, ‘Has anybody switched the camera on’? And that’s the time you start recording… If something happens immediately, you’re not thinking about the camera at that time, you’re just thinking to just go, so yeah. Nevis (f), Staff, A, Post.

Incidents happen quickly and often surprise staff, therefore staff react instantly so are not thinking about new processes such as recording on the cameras as this would slow things down or is not in the reactive nature needed by staff during such incidents.

When you’re in the middle of an incident and your adrenaline’s high, you’re focusing on the incident itself. It’s very difficult for you to now remember, remind yourself to switch on the camera because you’re thinking, patient safety, staff safety, who’s coming to relieve you? What’s going on? Who’s at the door? Petra (f), Staff, A, Post.

In addition, the need for an immediate response meant that it was felt that by the time staff remember to, or have the chance to, switch the camera on it was often too late.

Sometimes in the heat of moments and stuff like that, or if the situation’s happening, sometimes you don’t always think to, you know, put your camera on. Patrick (m), Staff, A, Post.

Outer setting

Resources: staffing.

Issues related to staffing were highlighted by several participants as a key problem facing mental health wards thus leading to staff having higher workloads, and higher rates of bank and agency staff being used on shift and feeling burnt-out.

Out of all the wards I’ve been on I’d say this is the worst. It’s primarily because the staff are overworked…it seems like they spend more time doing paperwork than they do interacting with the patients. Harry (m), Patient, A, Pre. We’re in a bit of a crisis at the minute, we’re really, really understaffed. We’re struggling to cover shifts, so the staff are generally quite burnt out. We’ve had a number of people that have just left all at once, so that had an impact… Staff do get frustrated if they’re burnt out from lack of staff and what have you. Alice (f), Staff, A, Pre.

It was noted by one participant that the link of a new intervention with extra workload was likely to have a negative impact on its acceptability due to these increasing demands.

People automatically link the camera to then the additional paperwork that goes alongside it. It’s like, ‘Oh god, if we do this, we’ve got to do that’, and that could play a part. Petra (f), Staff, A, Post.

One staff member noted that the staffing issue meant there were more likely to be bank staff on wards so the care of patients may be affected as temporary staff may be less able to build meaningful therapeutic relationships.

So obviously there is the basic impact on safety of not having adequate staffing, but then there’s the impact of having a lot of bank staff. So obviously when you have permanent staff they get to know the patients more, we’re able to give them the more individualised care that we ideally should be giving them, but we can’t do that with bank staff. Diana (f), Staff, A, Pre.

It was also suggested that staffing levels and mix often made it more difficult to provide activities or facilitate escorted leave which can lead to patients feeling frustrated and becoming more aggressive.

So you know there is enough staff to facilitate the actual shift, so you know when there’s less staff like you say you’ve got people knocking at the door, but then you don’t have staff to take people out on leave straight away, that all has a rippling effect! Serene (f), Staff, A, Pre.

Wider systemic issues

Overall, there was a concern that the introduction of BWCs would not impact on wider, underlying factors that may contribute to frustration, aggression and incidents on wards. Providing a more enhanced level of care and better addressing the needs of patients was felt to be central to helping people but also reducing the frustration that patients feel when on the ward.

… for violence and aggression, [focus on] the mental health side of things like therapy and psychology should be compulsory. It shouldn’t be something you apply for and have to wait three or four weeks for. I think every person should, more than three or four weeks even, months even… we need psychology and therapists. That’s what will stop most violence, because psychologists and a therapist can edit the way that they speak to people because they’ve been given that skill depending on the way the person behaves. So that’s what we need regularly… not like all this dancing therapy, yoga therapy. That’s a person, that you come and you actually sit down and talk through your shit with them. That will help! Elijah (m), Patient, A, Post. There’s a lack of routine and I think there’s a lack of positive interaction between the patient and the staff as well. The only time you interact with a member of staff is if you’re hassling them for something, you have to hassle for every little thing, and it becomes a sort of, frustration inducing and like I’m a very calm person, but I found myself getting very fucking angry, to be honest, on this ward just because out of pure frustration… there’s bigger problems than body worn cameras going on. Harry (m), Patient, A, Pre.

Staff agreed that there was a need to invest in staff and training rather than new technologies or innovations as it is staff and their skills behind the camera.

It’s not the camera that will do all of that. It’s not making the difference. It’s a very good, very beautiful device, probably doing its job in its own way. But it’s more about investing in the staff, giving them that training and making them reflect on every day-to-day shift. Richard (m), Staff, I, Post.

There was felt to be a need to support staff more in delivering care within wards that can be challenging and where patients are unwell to ensure that staff feel safe. While in some circumstances the cameras made some staff feel safer, greater support from management would be more beneficial in making staff feel valued.

In this study exploring the implementation and use of body-worn cameras on mental health wards, we employed two methods for collecting and comparing data on incidents and use of containment measures, including BWCs, on one acute ward and one psychiatric intensive care unit. We found no clear relationship between the use of BWCs and rates or severity of incidents on either ward. While BWCs may be used when there are incidents of both physical and verbal aggression, results indicate that they may also provoke verbal aggression, as was suggested during some interviews within this study. This should be a concern, as strong evidence that being repeatedly subject to verbal aggression and abuse can lead to burnout and withdrawal of care by staff [ 30 ]. These mixed findings reflect results that were reported in two earlier studies of BWCs on mental health wards [ 12 , 13 ]. However, the very low use of the cameras, on just 10 per cent of the shifts where data was obtained, makes it even more difficult to draw any conclusions.

While the data shows limited impact of using BWCs on levels of incidents, we did find that during the pilot period BWC use tended to occur alongside physical restraint, but the direction of relationship is unclear as staff were asked to use BWCs when planning an intervention such as restraint. This relationship with restraint reflected the findings on several wards in a previous study [ 13 ], while contrasting with those reported in a second study that found reductions in incidents involving restraint during the evaluation period [ 12 ]. Such a mix of findings highlights the complexity of using BWCs as a violence reduction method within a busy healthcare setting in which several interacting components and contextual factors, and behaviours by staff and patients can affect outcomes [ 31 ]. The qualitative data collected during this pilot period highlighted the potential systemic and contextual factors such as low staffing that may have a confounding impact on the incident data presented in this simple form.

The findings presented within this evaluation provide some insights into the process of implementing BWCs as a safety intervention in mental health services and highlight some of the challenges and barriers faced. The use of implementation science to evaluate the piloting of BWCs on wards helps to demonstrate how multiple elements including a variety of contextual and systemic factors can have a considerable impact and thus change how a technology may vary not only between hospitals, but even across wards in the same hospital. By understanding the elements that may and do occur during the process of implementing such interventions, we can better understand if and how BWCs might be used in the future.

Within this pilot, extensive preparatory work conducted at a directorate and senior management level did not translate during the process of implementation at a ward level, which appeared to impact on the use of BWCs by individuals on the wards. This highlights that there is a need to utilise implementation science approaches in planning the implementation of new technologies or interventions and to investigate elements related to behavioural change and context rather than just the desired and actual effects of the intervention itself.

While ward staff and patients identified the potential for BWCs to enhance safety on the wards, participants distrusted their deployment and expressed concerns about ethical issues and possible harmful consequences of their use on therapeutic relationships, care provided and patient wellbeing. These themes reflect previous findings from a national interview study of patient and staff perspectives and experiences of BWCs in inpatient mental health wards [ 14 ]. Given these issues, alternatives such as increasing de-escalation skills were identified by staff as possible routes that may be more beneficial in these settings. Furthermore, other approaches such as safety huddles have also been highlighted within the literature as potential means to improve patient safety by looking ahead at what can be attended to or averted [ 32 ].

Furthermore, it is important to consider that the presence of power imbalances and the pre-existing culture on the ward have considerable implications for safety approaches and must be considered, as exemplified by the preferences by both staff and patients in this evaluation for more perceived ‘impartial’ interventions such as CCTV. As identified within previous studies [ 14 ], BWCs can have different implications for psychological safety, particularly for vulnerable patients who already feel criminalised in an environment with asymmetrical power imbalances between staff and patients. This is particularly salient when considering aspects of identity such as race, ethnicity, and gender both in terms of the identities of the patient group but also in terms of the staff/patient relationship.

While preferences in this study note CCTV as more ‘impartial’, work by Desai [ 33 ] draws on the literature about the use of surveillance cameras in other settings (such as public streets) as well as on psychiatric wards and concludes that CCTV monitoring is fraught with difficulties and challenges, and that ‘watching’ patients and staff through the lens of a camera can distort the reality of what is happening within a ward environment. In her recently published book, Desai [ 34 ] develops this theme to explore the impacts of being watched on both patients and staff through her ethnographic research in psychiatric intensive care units. She highlights concerns over the criminalisation of patient behaviour, safeguarding concerns in relation to the way women’s bodies and behaviours are viewed and judged, and the undermining by CCTV of ethical mental health practice by staff who attempt to engage in thoughtful, constructive, therapeutic interactions with patients in face-to-face encounters. Appenzeller et al.’s [ 35 ] review found that whilst the presence of CCTV appeared to increase subjective feelings of safety amongst patients and visitors, there was no objective evidence that video surveillance increases security, and that staff may develop an over-reliance on the technology.

In addition, our findings add to the existing literature which notes that alternative interventions and approaches that address underlying contextual and systemic issues related to improving care on inpatient wards require attention to address the underlying factors related to incidents, e.g., flashpoints [ 36 ]. Evidence suggests that factors leading to incidents can be predicted; therefore, there is a need to enable staff to work in a proactive way to anticipate and prevent incidents rather than view incidents as purely reactive [ 37 , 38 , 39 ]. Such skills-based and relational approaches are likely to impact more on improving safety and reducing incidents by addressing the complex and multi-faceted issue of incidents on inpatient mental health wards [ 40 ].

These findings highlight that interventions such as BWCs are not used within a vacuum, and that hospitals are complex contexts in which there are a range of unique populations, processes, and microsystems that are multi-faceted [ 41 ]. As a result, interventions will encounter both universal, specific, and local barriers that will impact on its functioning in the real world. This is salient because research suggests that camera use inside mental health wards is based on a perception of the violent nature of the mental health patient, a perception that not only influences practice but also impacts how patients experience the ward [ 33 ]. As a result, there needs to be careful consideration of the use of any new and innovative intervention aimed at improving safety within mental health settings that have limited research supporting their efficacy.

Limitations

While the study provides important insights into the efficacy and acceptability of introducing BWCs onto inpatient mental health wards, there were several limitations. Firstly, the analysis of incident data is limited in its nature as it only presents surface level information about incidents without wider contextual information. Results using such data should be cautiously interpreted as they do not account for confounding factors, such as staffing, acuity, ward culture or ward atmosphere, that are likely to contribute to incidents of violence and aggression. For example, while there was a statistically significant decrease in restrictive practice on the PICU across the study period, we know that BWCs were not widely used on that ward, so this is likely due to a confounding variable that was not accounted for in the study design.

Secondly, the study faced limitations in relation to recruitment, particularly with patients. Researchers’ access to wards was challenging due to high staff turnover and high rates of acuity, meaning many patients were not deemed well enough to be able to consent to take part in the study. In addition, the low use of the cameras on wards meant that many patients, and some staff, had not seen the BWCs in use. Similarly, patients had been provided limited information about the pilot, so their ability to engage in the research and describe their own experiences with BWCs was restricted.

Thirdly, analysis captures the active use of the BWC, however it does not fully capture the impact of staff wearing the cameras even where they do not actively use them. While our qualitative analysis provides insight into the limitation of such passive use, it is likely that the presence of the cameras being worn by staff, even when turned off, may have an impact on both staff and patient behaviours. This may explain trends in the data that did not reach significance but warrant further investigation in relation to the presence of BWCs, nonetheless.

Finally, researchers had planned to collect quantitative surveys from staff and patients in relation to their experiences of the ward atmosphere and climate, views related to therapeutic relationships on the ward, levels of burnout among staff, views on care, and attitudes to containment measures. Due to issues related to staff time, patient acuity, and poor engagement from staff leading to challenges accessing the wards, the collection of such survey data was unfeasible, and this element of the study was discontinued. As a result, we have not reported this aspect in our paper. This limitation reflects the busy nature of inpatient mental health wards with pressures on staff and high levels of ill health among patients. As such, traditional methodologies for evaluation are unlikely to elicit data that is comprehensive and meaningful. Alternative approaches may need to be considered.

Future directions

With BWCs being increasingly used across inpatient mental health services [ 14 ], it is important that further research and evaluation is conducted. To date, there is limited data regarding the effectiveness of this technology in relation to violence reduction; however, there may be other beneficial uses in relation to safeguarding and training [ 13 ]. Future research should consider alternative methods that ensure contextual factors are accounted for and that patient voices can be maximised. For example, focus groups with patients currently admitted to a mental health ward or interviews with those who have recently been on a ward that has used the cameras, would bypass problems encountered with capacity to consent in the present study. Furthermore, ethnographic approaches may provide a deeper understanding of the implementation, deployment and impact that BWCs have on wards.

Overall, this research sheds light on the complexities of using BWCs as a tool for ‘maximising safety’ in mental health settings. The findings suggest that BWCs have a limited impact on levels of incidents on wards, something that is likely to be largely influenced by the process of implementation as well as a range of contextual factors, including the staff and patient populations on the wards. As a result, it is likely that while BWCs may see successes in one hospital site this is not guaranteed for another site as such factors will have a considerable impact on efficacy, acceptability, and feasibility. Furthermore, the findings point towards the need for more consideration to be placed on processes of implementation and the complex ethical discussions regarding BWC use from both a patient and a staff perspective.

In conclusion, while there have been advances in digital applications and immersive technologies showing promise of therapeutic benefits for patients and staff more widely, whether BWCs and other surveillance approaches are to be part of that picture remains to be seen and needs to be informed by high-quality, co-produced research that focuses on wider therapeutic aspects of mental healthcare.

Data availability

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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Acknowledgements

We would like to thank The Burdett Trust for Nursing for funding this work. We would also like to acknowledge our wider Lived Experience Advisory Panel and Project Advisory Panel for their contributions and support and would like to thank the staff and service users on the wards we attended for their warmth and participation.

Funding was provided by The Burdett Trust of Nursing. Funders were independent of the research and did not impact findings.

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All authors have read and approved the manuscript. Authors AS, UF, KW, GB created the protocol for the study. KW, JJ, UF conducted the recruitment for the study, and conducted the interviews. UF, JJ, JB, LMA, LU, SMK, KB, ET coded data, and contributed to the analysis. All authors supported drafting and development of the manuscript.

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Foye, U., Wilson, K., Jepps, J. et al. Exploring the use of body worn cameras in acute mental health wards: a mixed-method evaluation of a pilot intervention. BMC Health Serv Res 24 , 681 (2024). https://doi.org/10.1186/s12913-024-11085-x

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DOI : https://doi.org/10.1186/s12913-024-11085-x

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Proof-of-concept study pioneers new brain imaging technique through a transparent skull implant

by Keck School of Medicine of USC

In the first study of its kind, researchers from the Keck School of Medicine of USC and the California Institute of Technology (Caltech) designed and implanted a transparent window in the skull of a patient, then used functional ultrasound imaging (fUSI) to collect high-resolution brain imaging data through the window.

Their preliminary findings , published in Science Translational Medicine , suggest that this sensitive, non-invasive approach could open new avenues for patient monitoring and clinical research , as well as broader studies of how the brain functions.

"This is the first time anyone had applied functional ultrasound imaging through a skull replacement in an awake, behaving human performing a task," said Charles Liu, MD, Ph.D., a professor of clinical neurological surgery, urology and surgery at the Keck School of Medicine and director of the USC Neurorestoration Center.

"The ability to extract this type of information noninvasively through a window is pretty significant, particularly since many of the patients who require skull repair have or will develop neurological disabilities. In addition, 'windows' can be surgically implanted in patients with intact skulls if functional information can help with diagnosis and treatment."

The research participant, 39-year-old Jared Hager, sustained a traumatic brain injury (TBI) from a skateboarding accident in 2019. During emergency surgery , half of Hager's skull was removed to relieve pressure on his brain, leaving part of his brain covered only with skin and connective tissue. Because of the pandemic, he had to wait more than two years to have his skull restored with a prosthesis.

During that time, Hager volunteered for earlier research conducted by Liu, Jonathan Russin, MD, associate surgical director of the USC Neurorestoration Center, and another Caltech team on a new type of brain imaging called fPACT.

The experimental technique had been done on soft tissue, but could only be tested on the brain in patients like Hager who were missing a part of their skull. When the time came for implanting the prosthesis, Hager again volunteered to team up with Liu and his colleagues, who designed a custom skull implant to study the utility of fUSI—which cannot be done through the skull or a traditional implant—while repairing Hager's injury.

Before the reconstructive surgery, the research team tested and optimized fUSI parameters for brain imaging, using both a phantom (a scientific device designed to test medical imaging equipment) and animal models. They then collected fUSI data from Hager while he completed several tasks, both before his surgery and after the clear implant was installed, finding that the window offered an effective way to measure brain activity.

Functional brain imaging, which collects data on brain activity by measuring changes in blood flow or electrical impulses, can offer key insights about how the brain works, both in healthy people and those with neurological conditions.

But current methods, such as functional magnetic resonance imaging (fMRI) and intracranial electroencephalography (EEG) leave many questions unanswered. Challenges include low resolution, a lack of portability or the need for invasive brain surgery. fUSI may eventually offer a sensitive and precise alternative.

"If we can extract functional information through a patient's skull implant, that could allow us to provide treatment more safely and proactively," including to TBI patients who suffer from epilepsy, dementia, or psychiatric problems, Liu said.

A new frontier for brain imaging

As a foundation for the present study, Liu has collaborated for years with Mikhail Shapiro, Ph.D. and Richard Andersen, Ph.D., of Caltech, to develop specialized ultrasound sequences that can measure brain function, as well as to optimize brain-computer interface technology, which transcribes signals from the brain to operate an external device.

With these pieces in place, Liu and his colleagues tested several transparent skull implants on rats, finding that a thin window made from polymethyl methacrylate (PMMA)—which resembles plexiglass—yielded the clearest imaging results. They then collaborated with a neurotechnology company, Longeviti Neuro Solutions, to build a custom implant for Hager.

Before surgery, the researchers collected fUSI data while Hager did two activities: solving a "connect-the-dots" puzzle on a computer monitor and playing melodies on his guitar. After the implant was installed, they collected data on the same tasks, then compared the results to determine whether fUSI could provide accurate and useful imaging data.

"The fidelity of course decreased, but importantly, our research showed that it's still high enough to be useful," Liu said. "And unlike other brain-computer interface platforms, which require electrodes to be implanted in the brain, this has far less barriers to adoption."

fUSI may offer finer resolution than fMRI and unlike intracranial EEG, it does not require electrodes to be implanted inside the brain. It is also less expensive than those methods and could provide some clinical advantages for patients over non-transparent skull implants, said Russin, who is also an associate professor of neurological surgery at the Keck School of Medicine and director of cerebrovascular surgery at Keck Hospital of USC.

"One of the big problems when we do these surgeries is that a blood clot can form underneath the implant, but having a clear window gives us an easy way to monitor that," he said.

Refining functional ultrasound technology

In addition to better monitoring of patients, the new technique could offer population-level insights about TBI and other neurological conditions. It could also allow scientists to collect data on the healthy brain and learn more about how it controls cognitive, sensory, motor and autonomic functions.

"What our findings show is that we can extract useful functional information with this method," Liu said. "The next step is: What specific functional information do we want, and what can we use it for?"

Until the new technologies undergo clinical trials, fUSI and the clear implant are experimental. In the meantime, the research team is working to improve their fUSI protocols to further enhance image resolution . Future research should also build on this early proof-of-concept study by testing more participants to better establish the link between fUSI data and specific brain functions, the researchers said.

"Jared is an amazing guy," said Liu, who is continuing to collaborate with the study participant on refining new technologies, including laser spectroscopy, which measures blood flow in the brain. "His contributions have really helped us explore new frontiers that we hope can ultimately help many other patients."

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OpenSAFELY: Effectiveness of COVID-19 vaccination in children and adolescents

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Background Children and adolescents in England were offered BNT162b2 as part of the national COVID-19 vaccine roll out from September 2021. We assessed the safety and effectiveness of first and second dose BNT162b2 COVID-19 vaccination in children and adolescents in England.

Methods With the approval of NHS England, we conducted an observational study in the OpenSAFELY-TPP database, including a) adolescents aged 12-15 years, and b) children aged 5-11 years and comparing individuals receiving i) first vaccination with unvaccinated controls and ii) second vaccination to single-vaccinated controls. We matched vaccinated individuals with controls on age, sex, region, and other important characteristics. Outcomes were positive SARS-CoV-2 test (adolescents only); COVID-19 A&E attendance; COVID-19 hospitalisation; COVID-19 critical care admission; COVID-19 death, with non-COVID-19 death and fractures as negative control outcomes and A&E attendance, unplanned hospitalisation, pericarditis, and myocarditis as safety outcomes.

Results Amongst 820,926 previously unvaccinated adolescents, the incidence rate ratio (IRR) for positive SARS-CoV-2 test comparing vaccination with no vaccination was 0.74 (95% CI 0.72-0.75), although the 20-week risks were similar. The IRRs were 0.60 (0.37-0.97) for COVID-19 A&E attendance, 0.58 (0.38-0.89) for COVID-19 hospitalisation, 0.99 (0.93-1.06) for fractures, 0.89 (0.87-0.91) for A&E attendances and 0.88 (0.81-0.95) for unplanned hospitalisation. Amongst 441,858 adolescents who had received first vaccination IRRs comparing second dose with first dose only were 0.67 (0.65-0.69) for positive SARS-CoV-2 test, 1.00 (0.20-4.96) for COVID-19 A&E attendance, 0.60 (0.26-1.37) for COVID-19 hospitalisation, 0.94 (0.84-1.05) for fractures, 0.93 (0.89-0.98) for A&E attendance and 0.99 (0.86-1.13) for unplanned hospitalisation. Amongst 283,422 previously unvaccinated children and 132,462 children who had received a first vaccine dose, COVID-19-related outcomes were too rare to allow IRRs to be estimated precisely. A&E attendance and unplanned hospitalisation were slightly higher after first vaccination (IRRs versus no vaccination 1.05 (1.01-1.10) and 1.10 (0.95-1.26) respectively) but slightly lower after second vaccination (IRRs versus first dose 0.95 (0.86-1.05) and 0.78 (0.56-1.08) respectively). There were no COVID-19-related deaths in any group. Fewer than seven (exact number redacted) COVID-19-related critical care admissions occurred in the adolescent first dose vs unvaccinated cohort. Among both adolescents and children, myocarditis and pericarditis were documented only in the vaccinated groups, with rates of 27 and 10 cases/million after first and second doses respectively.

Conclusion BNT162b2 vaccination in adolescents reduced COVID-19 A&E attendance and hospitalisation, although these outcomes were rare. Protection against positive SARS-CoV-2 tests was transient.

Competing Interest Statement

BG has received research funding from the Laura and John Arnold Foundation, the NHS National Institute for Health Research (NIHR), the NIHR School of Primary Care Research, NHS England, the NIHR Oxford Biomedical Research Centre, the Mohn-Westlake Foundation, NIHR Applied Research Collaboration Oxford and Thames Valley, the Wellcome Trust, the Good Thinking Foundation, Health Data Research UK, the Health Foundation, the World Health Organisation, UKRI MRC, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies programme; he is a Non-Executive Director at NHS Digital; he also receives personal income from speaking and writing for lay audiences on the misuse of science. BMK is also employed by NHS England working on medicines policy and clinical lead for primary care medicines data. IJD has received unrestricted research grants and holds shares in GlaxoSmithKline (GSK).

Funding Statement

The OpenSAFELY Platform is supported by grants from the Wellcome Trust (222097/Z/20/Z); MRC (MR/V015757/1, MC_PC-20059, MR/W016729/1); NIHR (NIHR135559, COV-LT2-0073), and Health Data Research UK (HDRUK2021.000, 2021.0157). In addition, this research used data assets made available as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058). BG has also received funding from: the Bennett Foundation, the Wellcome Trust, NIHR Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, the Mohn-Westlake Foundation; all Bennett Institute staff are supported by BG's grants on this work. The views expressed are those of the authors and not necessarily those of the NIHR, NHS England, UK Health Security Agency (UKHSA) or the Department of Health and Social Care.

Funders had no role in the study design, collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This study was approved by the Health Research Authority (REC reference 20/LO/0651) and by the London School of Hygeine and Tropical Medicine Ethics Board (reference 21863).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Data Availability

All data were linked, stored and analysed securely using the OpenSAFELY platform, https://www.opensafely.org/ , as part of the NHS England OpenSAFELY COVID-19 service. Data include pseudonymised data such as coded diagnoses, medications and physiological parameters. No free text data was included. All code is shared openly for review and re-use under MIT open license [ https://github.com/opensafely/vaccine-effectiveness-in-kids ]. Detailed pseudonymised patient data is potentially re-identifiable and therefore not shared. Primary care records managed by the GP software provider, TPP were linked to ONS death data and the Index of Multiple Deprivation through OpenSAFELY.

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Twin research is an informative approach for understanding the genetic and environmental influences affecting behavioral, physical, and medical traits. The simple yet elegant logic of the twin method derives from the differences in genetic relatedness between the two types of twins. Identical (monozygotic or MZ) twins share 100 percent of their ...
Twin Studies
Twin studies are considered a key tool in quantitative behavioral genetic research methods, in which genetically informative data (i.e., data from sibling pairs, families, and pedigrees) are used to infer on genetic and environmental causes of individual differences in one or more measured variables (i.e., phenotypes).
Methodology of twin studies
Extending the twin design to include sibling data is a very useful method of assessing the generalizability of results from twin studies to singleton populations. 17 For example, comparing the prevalence of a trait in twins with that of their non-twin siblings allows one to examine firstly whether the experience of being a twin (including the ...
Classical twin studies and beyond
Twin studies have been a valuable source of information about the genetic basis of complex traits. To maximize the potential of twin studies, large, worldwide registers of data on twins and their ...
Twin Research for Everyone
Provides clear instruction on both basic and advanced twin research methods and study design; Features leading international experts in twin biology, genetics, health and psychology; Examines findings from recent twin studies across a broad array of health and behavioral studies; Details. ISBN. 978--12-821514-2. Language. English. Published.
Twins in Behavioral Science Research
One of the world's largest twin research studies is The Swedish Twin Registry at the Karolinska Institute. It has data on 194,000 twins, including identicals and fraternals.
Methodology of Twin Studies: A General Introduction
Abstract. The birthdate of twin research is usually considered to be the year 1875, when Francis Galton, in his paper, "The History of Twins as a Criterion of the Relative Powers of Nature and Nurture," first suggested the respective influences of heredity (nature) and environment (nurture) on any given trait or condition in man be assessed ...
Twin Studies and Behavior Genetics
Based on the differing genetic relatedness of monozygotic co-twins and dizygotic co-twins, the classical twin model allows for an estimation of the relative importance of these etiological factors. The classical twin model can be extended in multiple ways, depending on the phenotype, research question, and research design.
Key Study: The Minnesota Twin Study of Twins Reared Apart
Twin study by Bouchard et al. (1990) For this study, the average age of the twins when they participate in this study was 41, which is important because most twin research prior to this focused on adolescents. The twins spent an average of 5 months together before being separated and reunited (on average) around 30 years of age.
Decoding Nature and Nurture: Insights From Twin Studies
These limitations in twin research methods keep us from arriving at definitive conclusions regarding the influence of genetics on behavior. Researchers continue to seek answers that may provide ...
Behavioral Genetics--A second look at twin studies
As behavioral genetics enters a second century, the field's oldest research method remains both relevant and controversial. ... In the age of molecular genetics, meanwhile, the classical twin study design is only one aspect of genetics research. Twin studies estimate the heritability of a trait, but molecular genetics attempts to pinpoint the ...
Twin Studies: Histories and Discoveries in Neuroscience
Funded by the National Institutes of Health, the 21 center, 10-year study has enrolled nearly 12,000 children ages nine to 10, including roughly 1,000 twin pairs. Such a large study offers new opportunities in neuroscience research. "Ten years ago, it was common to report findings on only 10 people," says Iacono.
Why Twin Studies?
Twin studies allow researchers to examine the overall role of genes in the development of a trait or disorder. Comparisons between monozygotic (MZ or identical) twins and dizygotic (DZ or fraternal) twins are conducted to evaluate the degree of genetic and environmental influence on a specific trait. MZ twins are the same sex and share 100% of ...
Twin Studies (SOCIAL PSYCHOLOGY)
Reared-apart identical twins resemble one another only because of their shared genes. Interestingly, research shows that identical twins reared apart and together are about equally similar in personality traits such as aggression and traditionalism. The twin-family method includes identical twins, their spouses, and their children.
Twin method
About twin method. The issue of nature versus nurture has been debated for centuries. From the beginning of the 20 th century, the twin study design has helped us to shed light on this debate since it offers the possibility to disentangle the effects of genes (nature) and environment (nurture). The first formal twin registry was established in Denmark in 1954.
Twins Trust
Twin studies are used to investigate the roles of genetics and environment in various traits, behaviours and conditions. These studies involve examining the similarities and differences between identical (monozygotic) and fraternal (dizygotic) twins. Like any research approach, they come with pros and cons and if you're considering putting your ...
The effectiveness of digital twins in promoting precision ...
The impact of digital twins on health-related outcomes among patients. This review includes 12 studies that collectively assessed 45 outcomes, achieving an overall effectiveness rate of 80% (36 ...
Case Study Research Method in Psychology
Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews). The case study research method originated in clinical medicine (the case history, i.e., the patient's personal history). In psychology, case studies are ...
A new way to see viruses in action
Acknowledgements: Additional Stanford co-authors include postdoctoral scholar Yanyu Zhu, PhD student Ashwin Balaji, former PhD student Anish Roy, postdoctoral scholar Andrew Barentine, research ...
Digital twin on concepts, enabling technologies, and applications
The timely growth of data collection and virtual technology has led to advancements in digital twin (DT) technology, which has since become one of the primary research areas and provides enormous possibilities for various industry fields. Based on ultra-fidelity models, DT is an efficient method for realizing the merging of physical and virtual environments. Scholars investigated associated ...
Exploring the use of body worn cameras in acute mental health wards: a
The study used a mixed-methods design comparing quantitative measures including ward activity and routinely collected incident data at three time-points before during and after the pilot implementation of BWCs on one acute ward and one psychiatric intensive care unit, alongside pre and post pilot qualitative interviews with patients and staff ...
A lightweight tomato leaf disease identification method based on shared
On the Shared-twin network, there is a special experimental method, which proposes to use the majority vote method to improve the identification accuracy of tomato diseases. The tomato leaf data from Plant-Village and Taiwan region were used to compare the two groups of experimental data to verify the theory and method of this project.
Proof-of-concept study pioneers new brain imaging technique through a
Credit: CC0 Public Domain. In the first study of its kind, researchers from the Keck School of Medicine of USC and the California Institute of Technology (Caltech) designed and implanted a ...
OpenSAFELY: Effectiveness of COVID-19 vaccination in children and
Methods With the approval of NHS England, we conducted an observational study in the OpenSAFELY-TPP database, including a) adolescents aged 12-15 years, and b) children aged 5-11 years and comparing individuals receiving i) first vaccination with unvaccinated controls and ii) second vaccination to single-vaccinated controls. We matched vaccinated individuals with controls on age, sex, region ...

Twin Studies: A Unique Epidemiological Tool

Josyula G Prasuna

Introduction

Evolution of Twin Studies

Twin Registries: Unique Database

Indian Scenario

Methods Used in Twin Research

Tetrachoric correlations

Co-twin control analyses: Disease-discordant twins

Co-twin control analyses: Exposure-discordant twins

Statistical methods and analysis

Advantages of twin studies

Limitations of twin studies

Financial support and sponsorship

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Twin Studies by Nancy L. Segal LAST REVIEWED: 19 March 2013 LAST MODIFIED: 19 March 2013 DOI: 10.1093/obo/9780199828340-0101

10 Twin Studies and Behavior Genetics

Introduction

The Classical Twin Model

Structural Equation Modeling

Assumptions of the Classical Twin Model

Generalizability

Random Mating

The Degree of Genetic Similarity Between MZ Twins

Equal Environments

Genotype-Environment Interaction

Genotype-Environment Correlation

Extensions to the Classical Twin Model

Sex Limitation

Liability Threshold Model

Including Data from Additional Family Members

Multivariate Modeling

Common Pathway Model

Independent Pathway Model

Cross-Sectional Cohort and Longitudinal Designs

Causal Models

Latent Class Analysis

Twin Studies and Beyond

Author Note

This Feature Is Available To Subscribers Only

Decoding Nature and Nurture: Insights From Twin Studies

What Are Twin Studies?

Cognitive and Emotional Tasks

Study Results

Future Directions

Core Concepts

Twin Studies: Histories and Discoveries in Neuroscience

Into the 20th Century

What We’ve Learned

The 21st Century & Beyond

About the Author

CONTENT PROVIDED BY

Discussion Questions

Also In Genes & Molecules

Research & Discoveries

SUPPORTING PARTNERS

Twin Studies

References:

Twin method

About twin method

What twin studies tell us – and what they don’t tell us

How does it work?

What are “environmental factors”?

Limitations of twin studies

Heritability

Twin studies and ESSENCE ****

The future of twin studies

Twin Studies

Proponents of twin studies argue that:

Critics of twin studies argue that:

Things to think about when considering twin studies

The effectiveness of digital twins in promoting precision health across the entire population: a systematic review

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