Categories
We undertook this survey with the aim of confirming or improving the prior recommended sets of terms [ 21 ] by using findings from a survey of people experienced in an OSH-related field and enrolled in an online graduate level course in industrial hygiene.
2.1. the survey instrument.
An online survey was developed for this project. It asked respondents to rate various terms using a 100-point semantic differential scale available in the survey platform Qualtrics (Provo, Utah). It involved a linear rating scale with a mouse-controlled slide for indicating a rating from zero to 100. The end points were labeled with the bipolar descriptors below.
The survey instrument was designed to present sequential screens known as blocks. Figure 5 depicts how the blocks were arranged. Respondents were instructed to respond to a single item before advancing to another item. Respondents were not allowed to go backward to reconsider a term already rated.
Organisation of survey instrument.
Two surveys, identified as A and B, were created with identical material in Blocks 1 through 10. The terms rated were the same in both surveys with one unintended exception. One survey used minor harm, the other used minor damage. Within the categories (likelihood/probability, severity, and extent of exposure), the order of presentation was randomized for each survey. For example, the severity terms in Survey A were presented in random order, and the severity terms in Survey B were determined by a different random order.
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the University of Montana (protocol code 39-21, dated 21 February 2021). The approval was under the exempt category according to the U. S. Code of Federal Regulations, Part 42, section 104 (d).
The terms selected for this follow-on survey included a mix or identical terms, different terms, and some modified words. Table 2 lists the probability-based terms on the left and the likelihood terms on the right. Three probability-based terms were highly probable, probable, and improbable. The fourth term, remote, was in both surveys but, in the first survey, it was among the extent of exposure terms using a scale with end points No exposure and Constant exposure. In addition to remote, this second survey had six terms not previously studied. The term almost incredible was omitted from both lists for two reasons. One was that incredible means not credible and, according to Baybutt [ 8 ], events that are not credible should be excluded from risk analysis. Two, the prior study [ 21 ] found incredible had a very large standard deviation resulting from confusion among respondents as to whether it means near zero or near 100. In search of terms to replace almost incredible, we added extremely unlikely and extremely improbable to the second survey. In the prior survey, the lowest mean rating for a probability scale (14.3) was highly improbable. We sought an alternative term that would receive lower ratings, so we added extremely improbable, and, to mirror that on the high end of the rating scale, we added extremely probable.
Probability-based terms and likelihood-based terms in the survey and whether the terms are the same or different from the prior survey by Jensen and Hansen [ 21 ].
Probability Terms | Likelihood Terms | ||||
---|---|---|---|---|---|
Term Studied | Same | Different | Term Studied | Same | Different |
Highly probable | X | Highly likely | X | ||
Probable | X | Likely | X | ||
Improbable | X | Somewhat likely | X | ||
Remote | X | Somewhat unlikely | X | ||
Fairly normal | X | Unlikely | X | ||
Moderately probable | X | Certain | X | ||
Extremely probable | X | Almost certain | X | ||
Extremely improbable | X | Extremely unlikely | X | ||
Somewhat probable | X | Extremely likely | X | ||
Somewhat improbable | X | Moderately likely | X | ||
Fairly normal | X | ||||
Very unlikely | X | ||||
Very likely | X |
Table 3 lists severity terms on the left and extent of exposure terms on the right. All severity terms were the same in both surveys with minor modifications. Among the extent of exposure terms in Table 3 , a group of five were modified by adding “ly” to the end. A second group of four terms were modified by adding “exposed” to clarify that the intended meaning was how often exposure to the hazard occurred.
Terms in the survey for severity of harm and extent of exposure along with indicating if same or changed from prior survey by Jensen and Hansen [ 21 ].
Severity Terms | Extent of Exposure Terms | ||
---|---|---|---|
Current Study Term | Prior Study | Current Study Terms | Prior Study Terms |
Catastrophic | Same | Very frequently | Very frequent |
Medical treatment case | Same | Frequently | Frequent |
Severe | Same | Somewhat frequently | Somewhat frequent |
Moderate | Same | Infrequently | Infrequent |
Minor damage | Same | Very infrequently | Very infrequent |
Insignificant | Same | — | — |
Serious | Same | Regularly exposed | Regularly |
Severe loss | Same | Occasionally exposed | Occasionally |
Major damage | Same | Seldom exposed | Seldom |
Negligible | Same | Rarely exposed | Rarely |
Permanent injury/illness | Same | — | — |
Critical | Same | Annually | Same |
Minor | Same | Monthly | Same |
Death of a person | Same | Weekly | Same |
First aid only case | Same | Daily | Same |
Marginal | Same |
1 Prior survey used the term “Death of one person”.
A third group of exposure terms consisted of four calendar-related terms (daily, weekly, monthly, annually). These were unchanged, because the authors of the earlier paper suggested that mixing these terms randomly within all the other extent of exposure terms might have influenced rating. In order to check this, the four terms were presented together as the final four rating items. Survey A and Survey B presented these four terms in different orders.
An invitation to participate in a survey was extended to 98 individuals who were: (i) taking a Montana Technological University online course in industrial hygiene during spring semester 2021, (ii) engaged in a Master of Science program in industrial hygiene, and (iii) met the admission requirement of having at least two years of experience working in an occupational safety and health related job. In order to increase the response rate, the course instructors emailed their enrollees to watch for an invitation. None of the online courses were being taught by any of the researchers.
About two days after the notification emails, each student was sent a personal email invitation from the researchers to participate. The invitation did not contain any inducement to participate, such as points in their course grade, money, or other. Six or seven days after the invitation emails, the course instructors sent a second email to all their enrollees reminding them to consider participating if they had not already done so.
The 98 individuals were listed in a numbered order. Those with an odd number were sent a link to Survey A, while those with an even number were sent a link to Survey B. The individuals who chose to participate took the survey online. After starting the survey, respondents could stop at any point and their ratings were retained in the data set.
Analyses included reporting means, standard deviations, and medians for each term. Ratings for identical terms used in both surveys were compared using the Mann–Whitney test of medians [ 25 ]. The null hypothesis was the two data sets had equal medians while the alternate hypothesis was the two medians were not equal.
The survey contained questions asking respondents for information about their personal attributes, most experience area of practice, and their present employment sector. For the personal attribute questions, items asked for first language, gender, and the ethnicity they most identify with. The age distribution, in decades, is provided in the left side of Table 4 . The ages ranged from 26 to 60 with a mean of 38.9. For the question asking about language, 34 of 37 (91.1%) reported having English as their first language. For the three who reported other than English, their reported languages were Spanish, Chinese, and Yoruba.
Attributes of respondents.
Age | N | Prct. | Gender | N | Prct. | Ethnicity or Race | N | Prct. |
---|---|---|---|---|---|---|---|---|
60–69 | 1 | 02.7 | Male | 25 | 69.4 | White/Caucasian | 27 | 75.0 |
50–59 | 5 | 13.5 | Female | 11 | 30.6 | Hispanic/Latinx | 4 | 11.1 |
40–49 | 11 | 29.7 | Decline | 1 | NA | Asian | 3 | 8.3 |
30–39 | 12 | 32.4 | Native American | 1 | 2.8 | |||
20–29 | 8 | 21.6 | Other (African) | 1 | 2.8 | |||
Total | 37 | 99.9 | 37 | 100.0 | 36 | 100.0 |
1 The category included native Americans and native Alaskans. 2 Not precisely 100.0 due to rounding.
When asked what ethnicity they identified with, the options were White/Caucasian, Hispanic/Latinx, Asian, Black/African-American, Native American/Native Alaskan, Hawaiian/Pacific Islander, and Other. One respondent provided no answer making a total of 36. A respondent who chose “Other” reported being African. No respondents chose Black/African American or Hawaiian/Pacific Islander. The numbers and percentages are listed in the right side of Table 4 .
For their OSH-related work experience, the survey asked respondents for the practice area where they had the most experience. Responses are in the left side of Table 5 . The first three experience areas listed in Table 5 are traditional categories of practice of occupational safety and health. These three accounted for 29 of the 37 (78.4%) respondents. Six others chose environmental protection. The survey category “Responder” was further defined in the survey to include emergency medical technicians, police, and firefighters. One respondent selected this area of practice.
Most experience area of practice and current employment sector.
Most Experience | N | Prct. | Sector Employed | N | Prct. |
---|---|---|---|---|---|
Occupational Safety | 5 | 13.5 | Private Industrial | 9 | 25.0 |
Industrial Hygiene | 12 | 32.4 | Private Commercial | 5 | 13.9 |
Occupational S&H Combined | 12 | 32.4 | Education | 4 | 11.1 |
Environmental Protection | 6 | 16.2 | Federal Military | 3 | 8.3 |
Responder | 1 | 2.7 | Federal Non-Military | 7 | 19.4 |
Other (not specified) | 1 | 2.7 | Non-Federal Government | 7 | 19.4 |
Other | 1 | 2.8 | |||
Total | 37 | 99.9 | Total | 36 | 99.9 |
1 Not precisely 100.0 due to rounding.
The survey asked respondents about their current sector of employment. Results are in the right side of Table 5 . The government category included Federal military (3) and Federal Non-Military (7). The latter consisted of six in other-than-public health and one in public health. The employment category Non-Federal Government had seven respondents, three employed in local (city/county) and four in state/provincial governments. The survey had options for healthcare and for environmental restoration that received zero responses. When asked about experience participating on a risk-assessment team, 27 of 37 (73.0%) reported having served on a risk-assessment team.
Rating of the terms are in Table 6 , Table 7 , Table 8 and Table 9 for severity terms, probability terms, likelihood terms, and extent of exposure terms, respectively. All tables list the number of ratings (N), mean, standard deviation, and median. The order is according to the median. Where terms had equal medians, their order is according to mean rating.
Ratings of severity terms ordered by median.
Term Rated | N | Mean | St. Dev. | Median |
---|---|---|---|---|
Death of a person | 32 | 99.7 | 1.4 | 100.0 |
Catastrophic | 33 | 96.4 | 6.5 | 100.0 |
Permanent Injury/Illness | 33 | 87.3 | 18.9 | 92.0 |
Severe Loss | 34 | 77.1 | 11.8 | 85.0 |
Critical | 34 | 78.9 | 13.4 | 81.0 |
Severe | 34 | 77.1 | 11.8 | 80.0 |
Serious | 34 | 71.0 | 13.8 | 70.0 |
Major Damage | 30 | 71.3 | 17.0 | 70.5 |
Medical Treatment Case | 34 | 57.4 | 19.1 | 60.0 |
Moderate | 34 | 44.9 | 12.6 | 50.0 |
First Aid Only Case | 34 | 25.9 | 16.4 | 24.5 |
Marginal | 33 | 26.4 | 12.8 | 21.0 |
Minor Damage | 33 | 22.9 | 8.7 | 20.0 |
Minor | 33 | 20.6 | 10.1 | 20.0 |
Negligible | 29 | 21.3 | 26.0 | 10.0 |
Insignificant | 26 | 10.5 | 16.5 | 5.5 |
1 All ratings for Death of a person were 100 or 99 except one extreme outlier of 3 was removed from the data set prior to analyses.
Ratings for probability terms ordered by median.
Term Rated | N | Mean | St. Dev. | Median |
---|---|---|---|---|
Certain | 31 | 95.1 | 12.4 | 100.0 |
Extremely Probable | 31 | 93.9 | 4.9 | 95.0 |
Almost Certain | 33 | 92.1 | 7.0 | 94.0 |
Highly Probable | 30 | 87.8 | 7.9 | 88.5 |
Probable | 31 | 65.4 | 16.8 | 67.0 |
Moderately Probable | 30 | 61.1 | 14.2 | 57.5 |
Somewhat Probable | 28 | 57.3 | 15.0 | 56.0 |
Fairly Normal | 31 | 53.5 | 22.7 | 51.0 |
Somewhat Improbable | 31 | 28.5 | 14.2 | 22.0 |
Remote | 30 | 25.1 | 22.4 | 16.5 |
Improbable | 27 | 14.1 | 9.3 | 10.0 |
Extremely Improbable | 25 | 15.2 | 24.9 | 6.0 |
Ratings for likelihood terms ordered by median.
Term Rated | N | Mean | St. Dev. | Median |
---|---|---|---|---|
Certain | 31 | 95.1 | 12.4 | 100.0 |
Almost Certain | 33 | 92.1 | 7.0 | 94.0 |
Extremely Likely | 30 | 87.0 | 16.4 | 90.0 |
Highly Likely | 31 | 84.2 | 9.4 | 81.0 |
Likely | 31 | 67.2 | 16.9 | 65.0 |
Moderately Likely | 31 | 56.9 | 12.5 | 55.0 |
Fairly Normal | 31 | 53.5 | 22.7 | 51.0 |
Somewhat Likely | 31 | 45.5 | 16.4 | 40.0 |
Somewhat Unlikely | 32 | 24.8 | 13.0 | 25.5 |
Unlikely | 27 | 20.8 | 12.3 | 20.0 |
Remote | 30 | 25.1 | 22.4 | 16.5 |
Extremely Unlikely | 28 | 15.9 | 26.7 | 7.0 |
Ratings of extent of exposure ordered by median.
Term Rated | N | Mean | St. Dev. | Median |
---|---|---|---|---|
Daily | 30 | 90.1 | 12.2 | 94.0 |
Very Frequently | 31 | 80.8 | 17.0 | 82.0 |
Regularly Exposed | 30 | 75.1 | 18.7 | 77.5 |
Frequently | 31 | 72.7 | 16.2 | 75.0 |
Weekly | 30 | 64.6 | 21.4 | 70.5 |
Somewhat Frequently | 31 | 56.7 | 16.2 | 60.0 |
Monthly | 31 | 42.4 | 18.3 | 44.0 |
Occasionally exposed | 31 | 39.2 | 24.8 | 31.0 |
Somewhat Infrequently | 31 | 30.1 | 17.6 | 27.0 |
Infrequently | 30 | 22.2 | 16.1 | 20.5 |
Annually | 30 | 21.9 | 17.7 | 19.0 |
Seldom Exposed | 31 | 17.4 | 19.3 | 11.0 |
Very Infrequently | 29 | 14.7 | 21.0 | 10.0 |
Rarely Exposed | 25 | 9.6 | 11.4 | 6.0 |
1 Calendar-based Terms.
Four terms were included in both Table 6 and Table 7 because these terms have meanings equally applicable to likelihood and probability. These terms were Certain, Almost Certain, Remote, and Fairly Normal.
Terms in each survey for extent of exposure are listed in Table 9 Four terms are expressed in terms of typical exposures (regularly exposed, occasionally exposed, seldom exposed, and rarely exposed). Five terms are for calendar-based exposures (daily, weekly, monthly, and annually). Four terms are for frequency-based exposures (very frequently, somewhat frequently, somewhat infrequently, infrequently, and very infrequently).
A consideration for selecting terms for likelihood and probability scales may include using one or more of the seven pairs of terms having parallel versions. All seven pairs of terms were rated using the same rating scale. The horizontal bar chart in Figure 6 provides a visual comparison, with the upper bar (gray) for the likelihood term and the lower bar (blue) for the comparable probability term. Four of the seven terms had closely matched medians.
Bar chart comparing median ratings of likelihood and probability terms obtained in two surveys.
The three parallel terms listed below had medians that were not as closely matched as the four above.
Comparisons between median ratings from the undergraduates in the prior study [ 21 ] with ratings of corresponding terms in the present survey are provided in three tables— Table 10 for severity, Table 11 for probability and likelihood terms, and Table 12 for extent of exposure terms. Each table includes term-specific means, medians, difference in medians, and percentage difference, The Mann–Whitney test of medians identified different medians using the 0.05 level of significance (adjusted for ties) [ 25 ]. The order of terms in each table was based on difference in medians. For terms with equal differences, the order was based on largest to smallest p -value from the Mann–Whitney test. Each table presents term-specific means, medians, difference in medians, and percentage difference.
Ratings for severity terms from the prior survey of undergraduates by Jensen and Hansen [ 21 ] compared to present survey of experienced graduate students, ordered by difference (∆) in median rating.
Terms for Severity of Harm | Previous Survey: Undergraduates | Present Survey: Experienced | ∆ Medians | % Diff | ||
---|---|---|---|---|---|---|
Mean | Median | Mean | Median | |||
Minor | 21.8 | 20 | 20.6 | 20 | 0.0 | 0.0 |
Catastrophic | 96.8 | 100 | 96.4 | 100 | 0.0 | 0.0 |
Minor damage | 25.0 | 20 | 22.3 | 20 | 0.0 | 0.0 |
Negligible | 15.7 | 10 | 21.3 | 10 | 0.0 | 0.0 |
Moderate | 48.9 | 50 | 44.9 | 50 | 0.0 | 0.0 |
Death of one person | 97.1 | 100 | 99.8 | 100 | 0.0 | 0.0 * |
Serious | 74.9 | 74 | 71.0 | 70 | 4.0 | −5.4 |
Permanent Injury/illness | 94.4 | 96 | 87.3 | 92 | 4.0 | −4.2 |
Severe | 83.8 | 84 | 77.1 | 80 | 4.0 | −4.8 * |
Insignificant | 12.6 | 10 | 10.5 | 5.5 | 4.5 | −45.0 * |
Severe loss | 86.9 | 90 | 85.1 | 85 | 5.5 | −5.6 * |
Critical | 84.5 | 90 | 78.9 | 81 | 9.0 | −10.0 * |
Marginal | 32.9 | 31 | 24.8 | 21 | 10.0 | −32.3 * |
First aid only case | 41.8 | 37.5 | 25.9 | 24.5 | 13.0 | −34.7 * |
Medical treatment case | 74.0 | 74 | 57.4 | 60 | 14.0 | −18.9 * |
Major damage | 81.7 | 86 | 71.3 | 70.5 | 15.5 | −18.0 * |
1 Previous survey median minus present survey median. 2 Percent difference = 100 ((Median1 − Median2)/Median1). 3 Present survey used “Death of a person” whereas prior survey used “Death of one person”. This may be the reason the difference tested significant. * indicates significant difference at p < 0.05 according to Mann–Whitney test of medians.
Ratings for likelihood and probability terms from the prior survey of undergraduates by Jensen and Hansen [ 21 ] compared to present survey of experienced graduate students, ordered by difference (∆) in median rating.
Terms for Likelihood and Probability | Previous Survey: Undergraduates | Present Survey: Experienced | ∆ Medians | % Diff | ||
---|---|---|---|---|---|---|
Mean | Median | Mean | Median | |||
Certain | 94.9 | 100.0 | 95.1 | 100.0 | 0.0 | 0.0 |
Highly Likely | 80.7 | 80.5 | 84.2 | 81.0 | −0.5 | −0.6 |
Unlikely | 24.9 | 21.0 | 20.8 | 20.0 | 1.0 | 4.8 |
Probable | 67.4 | 70.0 | 65.4 | 67.0 | 3.0 | 4.3 |
Likely | 65.2 | 70.0 | 67.2 | 65.0 | 5.0 | 4.8 |
Highly Probable | 81.7 | 82.0 | 87.8 | 88.5 | −6.5 | −7.9 * |
Somewhat Unlikely | 34.4 | 34.0 | 24.8 | 25.5 | 8.5 | 25.0 * |
Almost Certain | 81.4 | 85.0 | 92.1 | 94.0 | −9.0 | −10.6 * |
Improbable | 18.7 | 20.0 | 14.1 | 10.0 | 10.0 | 50.0 * |
Somewhat Likely | 53.4 | 60.0 | 45.5 | 40.0 | 20.0 | 33.3 * |
1 Previous survey median minus present survey median. 2 Percent difference = 100 ((Median1 − Median2)/Median1). * indicates significant difference at p < 0.05 according to Mann–Whitney test of medians.
Ratings for extent of exposure terms from the prior survey of undergraduates by Jensen and Hansen [ 21 ] compared to present survey of experienced graduate students, ordered by difference (∆) in median rating.
Term for Extent of Exposure | Previous Survey: Undergraduates | Present Survey: Experienced | ∆ Medians | % Diff | ||
---|---|---|---|---|---|---|
Mean | Median | Mean | Median | |||
Very Infrequently | 15.0 | 10.0 | 14.7 | 10.0 | 0.0 | 0.0 |
Infrequently | 23.1 | 20.0 | 22.2 | 20.5 | −0.5 | −2.5 |
Weekly | 65.9 | 70.0 | 62.5 | 70.5 | −0.5 | −0.7 |
Somewhat Frequently | 54.0 | 59.5 | 56.7 | 60.0 | −0.5 | −0.8 |
Regularly Exposed | 74.1 | 74.0 | 75.1 | 77.5 | −3.5 | −4.7 |
Frequently | 72.0 | 72.5 | 72.7 | 75.0 | −2.5 | −3.4 |
Remote | 16.7 | 14.0 | 25.1 | 16.5 | −2.5 | −17.9 |
Daily | 86.8 | 90.0 | 90.1 | 94.0 | −4.0 | −4.4 |
Occasionally exposed | 39.6 | 36.0 | 39.2 | 31.0 | 5.0 | 13.9 |
Monthly | 49.3 | 50.0 | 42.4 | 44.0 | 6.0 | 12.0 |
Very Frequently | 85.0 | 88.5 | 80.8 | 82.0 | 6.5 | 7.3 |
Seldom Exposed | 19.7 | 18.0 | 17.4 | 11.0 | 7.0 | 38.9 * |
Rarely Exposed | 15.6 | 14.0 | 9.6 | 6.0 | 8.0 | 57.1 * |
Annually | 36.2 | 29.5 | 21.9 | 19.0 | 10.5 | 35.6 * |
1 Previous survey median minus present survey median. 2 Percent difference = 100 ((Median1 − Median2)/Median1). 3 Remote rated on likelihood scale in previous survey, but on extent of exposure scale in present survey. * indicates significant difference at p < 0.05 according to Mann–Whitney test of medians.
This study was undertaken with the primary aim of confirming or improving the initial sets of terms [ 21 ] recommended for naming the rows and columns of risk assessment matrices by using findings from a survey of people experienced in an OSH-related field and enrolled in a graduate level course in industrial hygiene. Their recommendations were based on a survey of undergraduate OSH students. In contrast, this follow-on study was used to survey a sample of people with OSH-related experience. Based on findings of the follow-on survey, the authors (i) discuss their rationale for selectively removing some terms from further consideration due primarily to weak consistency between the two surveys (ii) considering calendar-based terms, and (iii) commenting on limitations of the investigation.
A desirable attribute of terms to recommend for RAMs is consistency among different populations. For this study, a measure of consistency is the difference in medians between the prior and the present surveyed populations. Medians have an advantage over means by minimizing the contribution of outlier ratings. To help make decisions about retaining or removing terms, results of the two surveys were compared with a view toward consistency. Data in Table 10 , Table 11 and Table 12 show results of comparing the two surveys. Although there is no natural difference in medians for separating those consistent versus inconsistent, after examining the comparison in those tables, the authors used judgment to sort terms into strong, moderate, and weak consistency, with the goal of removing those with weak consistency from recommendations.
Severity terms are in Table 10 along with term-specific differences in median (∆). Severity terms we classified as strongly consistent are: minor, catastrophic, minor damage, negligible, moderate, death of a person, serious, permanent injury/illness, severe, insignificant, and severe loss. These terms had differences in medians in the 0–5 range. Terms with moderate consistency were: critical and marginal with differences of nine and ten, respectively. Terms with weak consistency were: first aid only case (∆ = 13) , medical treatment case (∆ = 14) , and major damage (∆ = 16) with a difference greater than ten. We elected to remove the weak consistency terms for labeling the columns in a RAM. In addition, the terms major damage and minor damage were removed, however, if major damage is omitted, there is no need to retain minor damage, because it is redundant to the term minor as both have medians of 20.
Likelihood terms and probability terms used in both surveys are in Table 11 . Terms we classified as strongly consistent were: certain, highly likely, unlikely, probable, likely and remote. These terms had differences in medians in the 0–5 range. Terms we classified as moderately consistent were: highly probable, somewhat unlikely, almost certain, and improbable. These terms had median differences in the 6–10 range. The only term in Table 11 considered weak in consistency, somewhat likely, had median ratings of 60 in the prior survey and 40 in the present survey (∆ = 20). This term was not preferred but was retained among terms to consider if no suitable alternative is identified.
The four terms that express extent of exposure using calendar-based terms (daily, weekly, monthly, and annually) are appropriately considered as a group rather than being intermixed with other terms. The findings from the present survey show consistent spacing between these terms, specifically, the space between daily and weekly was 23.5, between weekly and monthly 26.5, and between monthly and annually 25. The authors of the prior paper [ 21 ] suggested that these terms might be rated differently if presented as a group, as was done in this survey. Table 13 provides comparative results. The difference supports consistency in order of medians and substantial consistency in median values. Differences between categories in the prior study were consistently 20 and 21. Those in the present survey were in the mid-twenties (23–27). It is concluded that these terms could be used to label a RAM with four categories and doing so would create acceptable spacing between categories.
Comparison of median ratings from the prior survey by Jensen and Hansen [ 21 ] and this follow-on survey for calendar-based terms.
Term | Prior Survey Median | Present Survey Median | Difference |
---|---|---|---|
Daily | 90.0 | 94.0 | −4.0 |
Weekly | 70.0 | 70.5 | 0.0 |
Monthly | 50.0 | 44.0 | 6.0 |
Annually | 29.5 | 19.0 | 10.5 |
The survey described in this paper, and the prior survey, were based on target populations of people taking university courses. Because of that, we cannot generalize the findings to the diverse population of employed people who perform risk assessments in industry. For those actively involved in industrial risk assessment, their experience will have been influenced by their understanding of risk-related terminology. Moreover, because the risk-assessment terminology used in different industrial sectors is not uniform, we have no basis for expecting experienced risk assessors to have uniform or consistent understanding of the terms used in RAMs.
Another limitation is the number or respondents ( n = 37). We have no way of knowing if those who responded are representative of the 98 invited to take the survey. What we do know is the 37 who responded are, as a group, more experienced in OSH-related jobs than the undergraduates who typically have an internship or no experience working in OSH. The findings that the two responder groups were, for the most part, consistent in their median rating of most terms adds confidence in the recommendations developed from the prior study.
Recommendations are presented in Table 14 , Table 15 , Table 16 and Table 17 for severity terms, likelihood terms, probability terms, and extent of exposure terms, respectively. Each table lists the recommended sets of terms from the survey of undergraduates [ 21 ], the mean the median of each term, the mean and median found in the present survey findings, and recommendations from the authors on each set. For severity sets in Table 14 , findings from this follow-on survey are consistent with those of the prior survey [ 21 ], Two changes for consideration are: in the second set replace severe loss with severe, and in the third set replace major damage with severe loss.
Sets of three, four, and five terms for severity as recommended in prior paper [ 21 ] compared to present survey with comments by the research team. Prior survey data adapted from Jensen and Hansen [ 21 ].
Sets of Terms from Prior Survey | Prior Survey | Survey of Graduates | Recommendations | ||
---|---|---|---|---|---|
Mean | Median | Mean | Median | ||
Severe | 83.8 | 84 | 77.1 | 85.0 | Recommended with no change |
Moderate | 48.9 | 50 | 44.9 | 50.0 | |
Minor | 21.8 | 20 | 20.6 | 20.0 | |
Severe loss | 86.9 | 85 | 77.1 | 85.0 | Recommended but replace severe loss with severe |
Moderate | 48.9 | 50 | 44.9 | 50.0 | |
Minor | 21.8 | 20 | 20.6 | 20.0 | |
Major damage | 81.9 | 86 | 71.3 | 70.5 | Recommended for equipment, facilities, environment but not for human safety and health. |
Moderate | 48.9 | 50 | 44.9 | 50.0 | |
Minor damage | 25.6 | 20 | 22.9 | 20.0 | |
Catastrophic | 96.9 | 100 | 96.4 | 100.0 | Recommended with no change |
Serious | 74.9 | 74 | 71.0 | 70.0 | |
Marginal | 32.9 | 31 | 26.4 | 21.0 | |
Negligible | 15.7 | 10 | 21.3 | 10.0 | |
Catastrophic | 96.9 | 100 | 96.4 | 100.0 | Recommended with no change |
Severe | 83.3 | 84 | 77.1 | 80.0 | |
Moderate | 48.9 | 50 | 44.9 | 50.0 | |
Marginal | 32.9 | 31 | 26.4 | 21.0 | |
Insignificant | 12.6 | 10 | 10.5 | 5.5 | |
Catastrophic | 96.9 | 100 | 96.4 | 100.0 | Recommended with no changes |
Serious | 74.9 | 74 | 71.0 | 70.0 | |
Moderate | 48.9 | 50 | 44.9 | 50.0 | |
Marginal | 32.9 | 31 | 26.4 | 21.0 | |
Insignificant | 12.6 | 10 | 10.5 | 5.5 |
Sets of three, four, five and six terms for likelihood recommended in prior paper [ 21 ] compared to present survey with recommendations by the research team. Prior survey data adapted from Jensen and Hansen [ 21 ].
Sets of Terms from Prior Survey [ ] | Prior Survey | Survey of Graduates | Recommendations | ||
---|---|---|---|---|---|
Mean | Median | Mean | Median | ||
Highly likely | 80.7 | 80.5 | 84.2 | 81.0 | Recommended with options to consider in footnotes 1 and 2 |
Somewhat likely | 53.6 | 60.0 | 45.5 | 40.0 | |
Very unlikely | 14.6 | 11.0 | No match | No match | |
Highly likely | 80.7 | 80.5 | 84.2 | 81.0 | Recommended with options to consider in footnotes 1 and 2 |
Somewhat likely | 53.6 | 60.0 | 45.5 | 40.0 | |
Somewhat unlikely | 34.4 | 34.0 | 24.8 | 25.5 | |
Highly unlikely | 13.3 | 10.0 | No match | No match | |
Certain | 96.0 | 100 | 95.1 | 100.0 | Recommended with options to consider in footnotes 1 and 2 |
Highly likely | 80.7 | 80.5 | 84.2 | 81.0 | |
Somewhat likely | 53.6 | 60.0 | 45.5 | 40.0 | |
Somewhat unlikely | 34.4 | 34.0 | 24.8 | 25.5 | |
Highly unlikely | 13.3 | 10.0 | No match | No match | |
Highly likely | 80.7 | 80.5 | 84.2 | 81.0 | Recommended with options to consider in footnotes 1 and 2 |
Likely | 66.0 | 70.0 | 67.2 | 65.0 | |
Somewhat likely | 53.6 | 60.0 | 45.5 | 40.0 | |
Somewhat unlikely | 34.4 | 34.0 | 24.8 | 25.5 | |
Unlikely | 24.6 | 22.0 | 20.8 | 20.0 | |
Highly unlikely | 13.3 | 10.0 | No match | No match |
1 A concern with the term somewhat likely is it had inconsistent ratings from the two survey populations (medians of 60 and 40). If an alternative is desired, the term moderately likely (mean 56.9, median 55) would be suitable. 2 A term for the lowest likelihood category in a RAM could be any of three: very unlikely (11), extremely unlikely (7), or highly unlikely (10). Median ratings are in parentheses. The authors see no clear preference.
Sets of three, four, five, and six terms for probability recommended in prior paper [ 21 ] compared to present survey with comments by the research team. Prior survey data adapted from Jensen and Hansen [ 21 ].
Sets of Terms from Prior Survey | Prior Survey | Survey of Graduates | Recommendations | ||
---|---|---|---|---|---|
Mean | Median | Mean | Median | ||
Highly probable | 81.7 | 82 | 87.8 | 88.5 | Recommended with options to consider footnotes 1 and 2 |
Occasionally | 40.2 | 36 | No match | No match | |
Highly improbable | 14.3 | 10 | No match | No match | |
Highly probable | 81.7 | 82 | 87.8 | 88.5 | Recommend with options to consider in footnotes 1 and 2. |
Probable | 68.2 | 70 | 65.4 | 67.0 | |
Occasionally | 40.2 | 36 | No match | No match | |
Highly improbable | 14.3 | 10 | No matcch | No match | |
Highly probable | 81.7 | 82 | 87.8 | 88.5 | Recommend with comments: Replace possible with somewhat probable (mean 57.3, median 56). Replace occasionally with somewhat improbable (mean 28.5, median 22). |
Probable | 68.2 | 70 | 65.4 | 67.0 | |
Possible | 59.4 | 60 | No match | No match | |
Occasionally | 40.2 | 36 | No match | No match | |
Highly improbable | 14.3 | 10 | No match | No match | |
Certain | 96.0 | 100 | 95.1 | 100.0 | Recommend with options to consider in footnotes 1 and 2 |
Highly probable | 81.7 | 82 | 87.8 | 88.5 | |
Probable | 68.2 | 70 | 65.4 | 67.0 | |
Possible | 59.4 | 60 | No match | No match | |
Occasionally | 40.2 | 36 | No match | No match | |
Highly improbable | 14.3 | 10 | No match | No match |
1 The term occasionally is a better fit for extent of exposure than it is for probability. For the probability sets, the authors recommend somewhat improbable with median 22. 2 The term highly improbable had a median of 10 in the prior survey. If an alternative is desired, either improbable (10) or extremely improbable (6) would be suitable.
Sets of two and three terms for extent of exposure recommended in prior paper [ 21 ] compared to present survey with recommendations by the present research team. Prior survey data adapted from Jensen and Hansen [ 21 ].
Sets of Terms from Prior Survey | Prior Survey | Survey of Graduates | Recommendations | ||
---|---|---|---|---|---|
Mean | Median | Mean | Median | ||
Regularly | 74.1 | 74.0 | 75.1 | 77.5 | Recommended with minor word change |
Seldom | 19.7 | 18.0 | 17.4 | 11.0 | |
Regularly | 74.1 | 74.0 | 75.1 | 77.5 | Recommended with minor word change |
Occasionally | 40.2 | 36.0 | 39.2 | 31.0 | |
Rarely | 15.8 | 14.0 | 9.6 | 6.0 | |
Very frequent | 85.0 | 88.5 | 80.8 | 82.0 | Recommended with minor word change |
Somewhat frequent | 54.7 | 59.5 | 56.7 | 60.0 | |
Very infrequent | 15.0 | 10.0 | 14.7 | 10.0 |
1 Added in present survey “exposed” after Regularly, Seldom, Occasionally, and Rarely. 2 Added in present survey “ly” to the words frequent and infrequent.
For severity terms, nine of the 15 terms in Table 11 had median differences in the 0–5 range while six had large differences. Undergraduate rating of severity was higher than those of the graduate students for all difference over five. Three terms are not recommended: first aid cases (15.9), medical treatment cases (16.6), and major damage (12.9).
The ratings for likelihood terms in the prior and the present survey are presented in Table 15 . Each of the sets included highly likely. It had similar ratings from both surveyed populations for means (80.7 and 84.2) and medians (80.5 and 81.0). The term somewhat likely appears to fill a gap in the middle range of likelihood. A concern about this term is the inconsistent rating between the prior survey and present survey, with means of 53.6 and 45.5 and medians of 60 and 40, respectively. In the set of three, there was no better term in these survey for naming the middle category of a likelihood axis in a RAM. The lowest term in the set of three (very unlikely) was among those recommended in the prior paper. A footnote indicates there are three terms suitable for the lowest category of a likelihood scale. The three terms with their medians are very unlikely (11),highly unlikely (10), and extremely unlikely (7). The research team suggests any of the three would be suitable. The sets of four and five in Table 16 have desirable spacing between them. The set of six, however, has two terms with minimal spacing, somewhat unlikely (25.5) and unlikely (20). The conclusion of the research team is that terms recommended in the prior paper are suitable for sets of three, four, and five. The set for six categories is sufficient, but not as well spaced as those in the other likelihood sets.
The ratings for probability terms in the prior and the present survey are presented in Table 16 . The prior survey had only five probability terms (highly probable, probable, possible, improbable, and highly improbable). One consequence of that was lack of a probability term for the middle range. The prior authors decided to borrow the term occasionally from the extent of exposure terms. It had a mean rating of 40.2 using the extent of exposure rating scale. This was not an ideal solution. For the present survey, occasionally exposed was kept among the extent of exposure terms. In order to find terms to fill mid-range of the 100-point scale, the present survey included fairly normal, somewhat probable, and somewhat improbable. These terms are mentioned in the Recommendations column of Table 16 .
The primary conclusion of the research team is that probability terms recommended in the prior paper had insufficient options for creating categories with appropriate spacing. The rational for improvements are provided in Table 16 .
The ratings for extent of exposure terms in the prior and the present survey are presented in Table 17 . Minimal modifications to the prior recommended terms were made before conducting the present survey. One such modification was adding the word ”exposed” after regularly, seldom, occasionally, and rarely. The reason was to help survey respondents think about how the term is to be used. The other modification was to add “ly” to the words frequent and infrequent. Other than those changes, the prior sets of terms were confirmed and supported by findings from the present study. The set of two would be suitable as a third axis in a RAM. It could be operationalized as two traditional RAMs set side by side, one for regularly exposed and one for seldom exposed. The sets of three could also be operationalized in that way as well. The present authors agree with the prior authors that extent of exposure is best regarded as a set of only two or three categories.
Findings for severity indicated a few terms that should not be used for naming the rows and columns of risk assessment matrices. Do not use first aid case only or medical treatment case because ratings of these terms appear to be influenced by reporting requirement and workers’ compensation laws. These terms would fit better in the text descriptions of the severity categories.
Findings for likelihood indicated the adjectives “very” and “extremely” have similar meanings when used to modify likely and probable. Therefore, using one of these but not both is recommended. Some adjectives produced similar effects when used to modify the terms likely and probable. Extremely improbable and extremely unlikely produce ratings of 6 and 7. Moderately probable and moderately likely received median ratings of 67 and 65. Somewhat improbable and somewhat unlikely received median ratings of 22 and 25.5. Highly probable and highly likely had median ratings of 88.5 and 80.5. The bar chart in Figure 6 facilitates comparison.
The aim of this project was to confirm or improve the prior recommended word sets for headers of the columns and rows in RAMs. Findings led to the following conclusions.
The following are available online at https://www.mdpi.com/article/10.3390/ijerph19052763/s1 , Table S1: Ratings of Probability and Likelihood Terms, Table S2: Ratings of Exposure Terms, Table S3: Ratings of Severity Terms.
The quantitative risk matrix used in the system safety profession has rows with numerical values for probability defined to fit the situation of concern. The columns have numerical values of consequence, commonly in expected dollar value of loss, or, in some domains, consequence may be in number of lives lost. In the practice of occupational safety and health, the values required for both probability and severity are imprecise estimates made by people. For example, should the probability of a particular hazardous event be 10 −3 or 10 −6 ? What amount should be used for the death of one employee? What is needed for OSH is a RAM formatted to accommodate human estimates of both axes.
The RAM in Figure 1 of the main article is based on a framework with both axes having a 0–10 range, and the whole space divided into cells based on the intersection of row and columns. Tony Cox explained the mathematical and statistical rationale in a 2008 paper [ 13 ]. An attempt to explain the rationale in a less rigorous manner follows.
Figure A1 depicts three planes analogous to a three-floor building. The ground floor represents the underlying quantitative relationship between probability and severity as an X-Y graph. A plot of the X-Y space on log-log paper can be used to plot lines of equal risk using Equation (1). These iso-risk lines run straight from the upper left toward the lower right.
A 3-floor building analogy depiction of how an underlying quantitative relationship using logarithmic scaling (ground floor) may be normalized to form a quantitative matrix using linear scaling (middle floor). The top floor is carpeted using rectangular pieces of carpeting colored red, yellow, and green, arranged in a pattern to identify spaces of similar risk.
The next floor up is based on changing the logarithmic axis scales into linear scales by normalizing each to a specified range. The linear range of each axis described by Cox was 0–1. Equivalent scales may use 0–10 or 0–100. On this floor, bands of similar risk are defined by curved iso-risk lines plotted in this X-Y space like those shown in Figure 1 of the main article. For example, the iso-risk line at 45 in Figure 1 defines a space above and right of the line as a high-risk region, and the iso-risk line 20 defines the space to its left and below as the low-risk region. This is all good technically, but a typical risk assessment team in industry using this approach needs to reach agreement on numerical values for both axes in order to determine the point in the X-Y space where a particular hazard belongs. This could take a lot of time and possibly lead to bickering among the team members. For that reason, a RAM format that is more accommodating for human judgment is desirable.
The upper floor in the building represents the usable risk matrix for assessing hazards. It uses the same axes as the floor below, including the iso-risk lines. The building owner may retain a RAM designer to install rectangular pieces of colored carpet to lay in a grid pattern. If carpet colors are red, yellow, and green, the pattern could mirror the layout in Figure 1 , or a different pattern preferred by the building owner or RAM designer.
Conceptualization, R.C.J.; methodology, R.C.J., R.L.B. and. B.W.N.; software, R.L.B. and B.W.N.; validation, R.C.J.; formal analysis, R.C.J.; investigation, R.L.B. and B.W.N.; resources, R.C.J.; data curation, R.C.J.; writing—original draft preparation, R.C.J.; writing—review and editing, R.L.B. and B.W.N.; visualization, R.C.J.; supervision, R.C.J.; project administration, R.C.J.; funding acquisition, R.C.J. All authors have read and agreed to the published version of the manuscript.
This research received no external funding. Internal funding was through Montana Technological University’s Research Assistant Mentorship Program.
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board of the University of Montana (protocol code 39-21, dated 21 February 2021). The approval was under the exempt category according to the U. S. Code of Federal Regulations, Part 42, section 104 (d).
Informed consent was obtained from all subjects involved in the study.
Conflicts of interest.
The authors declare no conflict of interest. No funders had a role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Published on: 28/02/2012
Latest update: 20/09/2022
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Workers should be protected from occupational risks they could be exposed to. This could be achieved through a risk management process, which involves risk analysis, risk assessment and risk prevention and control practices. In order to carry out an effective risk management process, it is necessary to have a clear understanding of the legal context, concepts, risk analysis, assessment and prevention and control processes and the role played by all involved. It is also desirable to base risk management on solid and tested methodologies.
Employers have to take the necessary measures for the safety and health protection of workers, including prevention of occupational risks. This is a basic legal obligation in all EU Member States. This basic legal obligation is stated in Council Directive of 12 June 1989 on the introduction of measures to encourage improvements in the safety and health of workers at work (Framework Directive 89/391/EEC [1] ), which was transposed by Member States’ into national laws. It should be noted that Member States can introduce more rigorous provisions to protect their workers.
For preventing occupational accidents and ill health, employers must carry out a risk assessment, and decide on prevention measures and, if necessary, to use personal protective equipment . It is recommended to review the risk assessment on a regular basis and in particular each time a change occurs at the workplace, e.g. the use of new work equipment or chemicals , changes in the work processes or modifications to the work organisation.
Risk assessment is not only a legal duty but also good for business. Avoiding and reducing risks reduces work-related accidents and health problems, leading to cost benefits and improved productivity. Risk assessment is a dynamic process that allows companies and organisations to put in place a proactive policy for managing occupational risks. Therefore, risk assessment constitutes the basis for implementation of appropriate preventive measures and, according to the Directive; it must be the starting point of any Occupational Safety and Health (OSH) Management system. An OSH Management system should be integrated in the company’s management system. An OSH Management system allows to develop a systematic approach to OSH [2] . Risk assessment is a step in the OSH risk management process.
Basic concepts in risk management are the definitions of hazard and risk.
Hazard: source or situation with a potential to cause injury and ill-health i.e. an adverse effect on the physical, mental or cognitive condition of a person [2] . Examples of physical hazardous sources or situations can be working on a ladder, handling chemicals or walking on a wet floor. Examples of psychosocial hazardous sources or situations are job content, job insecurity, isolation, bullying or harassment.
Risk: effect of uncertainty. Occupational health and safety risk: combination of the likelihood of occurrence of a work-related hazardous event or exposure(s) and the severity of injury and ill health that can be caused by the event or exposure s. [2]
A psychosocial risk is defined as a combination of the likelihood of occurrence of exposure to work-related hazard(s) of a psychosocial nature and the severity of injury and ill-health that can be caused by these hazards [3] . Hazards of a psychosocial nature include aspects of work organisation, social factors at work, work environment, equipment and hazardous tasks.
Risk assessment can be defined as the process of evaluating the risk to the health and safety of workers while at work arising from the circumstances of the occurrence of a hazard at the workplace [4] . This definition stems from the EU guide elaborated by the EU Commission to provide practical assistance for the implementation of the risk assessment requirements from the framework directive. However, it should be noted that the concept of risk assessment is not only used within the context of OSH but it can also relate to financial, environmental, socio-economic, technical and other aspects. A general framework on the risk assessment process is provided in standard ISO 31001. This standard describes risk assessment as the overall process of (1) risk identification, (2) risk analysis and (3) risk evaluation:
Following the methodology PDCA (Plan-Do-Check-Act) risk management is a systematic process that includes the examination of all characteristics of the work system where the worker operates, namely, the workplace, the equipment/machines, materials, work methods/practices and work environment. The aim of risk management is to identify what could go wrong, i.e. finding what can cause injury or harm to workers, and to decide on measures to prevent injuries and ill-health and implement the measures.
It is important that employers know where the risks are in their organisations and prevent or keep them under control to avoid putting employees, customers and the organisation itself at risk. The main goal of risk management is to eliminate or at least to reduce the risks according to the ALARP (as low as reasonably practicable) principle. A key aspect in risk management is that it should be carried out with an active participation/involvement of the entire workforce. Carrying out risk management requires a step-by-step approach.
The preparation of the risk management process involves several activities, namely:
Several means can be used to support these activities. For instance:
As referred, according to EU legislation employers are responsible for performing risk assessment regarding safety and health at work. Therefore, the overall responsibility for identifying, assessing and preventing risks at the workplace lies with the employer, who must guarantee that the occupational safety and health (OSH) risk management activities are properly executed.
The employer can delegate this function (not the responsibility) to occupational health and safety specialists and occupational physicians. The specialists may be part of the company staff (internal services) or be contracted outside (external services).
The participation of workers in the process of risk management in the field of safety and health at work is of fundamental importance, as workers have the best knowledge of their tasks and the associated risks. Participation also improves acceptance of the measures and facilitates their application in practice.
The risk analysis activities involve:
Risk assessment is the process of evaluation of the risks arising from a hazard, taking into account the adequacy of any existing controls. Several methods to perform risk assessment are available ranging from expert to participatory methodologies and from simple to complex methods. Which method for assessing risks is applied will depend on the nature of the workplace, the type of the tasks and work processes, and the technical complexity [4] . An overview and some guidance on risk assessment techniques can be found in IEC/ISO Standard 31010:2019 Risk management - Risk assessment techniques https://www.iso.org/standard/72140.html . Risk assessment involves evaluating, ranking, and classifying risks.
Risk evaluation involves the determination of a quantitative or qualitative value for the risk. Quantitative risk evaluation requires calculations of the two components of the risk: the probability that the risk will occur, and the severity of the potential consequences. This approach is seldom applied in practice.
Qualitative risk evaluation is more common and usually adopts a methodology based on a matrix. A risk assessment matrix consists of a two-dimensional grid with categories of harmful effects on one axis and categories of probability or likelihood on the other axis. The cells within the grid are used to indicate risk [6] . An example is shown in table 1.
Based on the risk values obtained during the risk evaluation phase, risks should be sorted and ranked according to their severity.
A decision whether or not a risk is acceptable results from the comparison of the obtained risk value with acceptability criteria based on legal requirements, principles of the hierarchy of prevention , standards, recommendations, evidence-based information on risks, adapting to innovation, etc.
It should be highlighted that a particularly careful assessment of individual risk exposure should be performed to workers of special groups (for example, vulnerable groups such as new or inexperienced workers), or to those most directly involved in the highest risk activities (i.e. the most exposed group of workers) [8] .
This risk classification is the baseline for selecting actions to be implemented and when defining the timescale, i.e. the urgency of the implementation of the corrective measures. As an example, table 1 includes a simple risk categorisation in 3 broad categories indicating a priority ranking for actions.
To have a consistent base for all risk assessments the company should first establish the acceptability criteria. This should involve consultation with workers representatives and other stakeholders and should take account of legislation and regulatory agency guidance, where applicable [8] .
At this stage actions are identified and implemented to avoid or reduce risks having in mind the protection of workers’ health and safety, as well as their monitoring over time. The measures implemented should be the ones that best protect everyone exposed to the risk. However, it is important not to forget that additional or different measures may be required to protect workers belonging to special groups, namely workers with special needs (such as pregnant women, young workers, aging workers and workers with disabilities) and maintenance workers, cleaners, contractors and visitors .
It is very important to take account of the number of individuals exposed to the risk when setting priorities and the timeline for the implementation of prevention and control measures. The risk prevention and control strategy includes the design, planning and implementing of adequate measures, as well as training and informing workers.
The first step is the design of the measures to eliminate risks. The risks that cannot be avoided or eliminated should be reduced to an acceptable level, i.e. the residual risk shall be minimised according to the ALARP (as low as reasonably practicable) principle. This means employers must perform a cost-benefit analysis to balance the cost (including money, time, trouble and effort) they could have to reduce a risk against the degree of risk [9] . It should be demonstrated that the cost involved in reducing the risk further would be grossly disproportionate to the benefit gained. The residual risk should be controlled.
The measures to be implemented should be based on up-dated technical and/or organisational knowledge, and good practices using the following hierarchy order [10] [11] :
Mitigation measures.
The aim of implementation of prevention measures is to reduce the likelihood of injuries or ill-health. Several examples, also in hierarchical order, that can be used to achieve this objective are:
a) Using engineering or technical measures to act directly on the risk source, in order to
These measures are more efficient and economical when accomplished during the workplace design phase.
b) Using organisational or administrative measures for changing of behaviours and attitudes and promote a safety culture :
Implementation of Protection measures should consider, first, collective measures and then individual measures. Several examples of measures (sorted by priority) that can be used to achieve this objective are:
a) Collective Protection measures:
b) Individual Protection - use of Personnel Protective Equipment (PPE) to protect worker from the residual risk. The worker should participate in the selection of PPE and should be trained in its use.
When despite prevention and protective measures incidents, an injury or a cases of ill-health occurs, the company needs to be prepared (emergency preparedness) by implementing mitigation measures. The aim of mitigation measures is to reduce the severity of any damage to facilities and harm to employees and public. Several examples of measures that can be used to achieve this aim are: emergency plans, evacuation planning, warning systems (alarms, flashing lights), test of emergency procedures, exercises and drills , fire-extinguishing system, or a return-to-work plan.
Managers must know the risk their workers are exposed to. Workers must know the risks they are exposed to. Providing information and training courses to workers is a legal requirement in EU.
The risk management process should be reviewed and updated regularly, for instance every year, to ensure that the prevention measures implemented are adequate and effective. Additional measures might be necessary if the improvements do not show the expected results. This is also a highly recommendable procedure since workplaces are dynamic due to change in equipment, machines, substances or work procedures that could introduce new hazards in the workplace. Another reason is that new knowledge regarding risks can emerge ; either leading to the need of an intervention or offering new ways of avoiding or controlling the risk. The review of the risk management process should consider a variety of types of information and draw them from a number of relevant perspectives (e.g. staff, management, stakeholders).
In EU it is a legal obligation that employers make an assessment of the risks to safety and health at work, including those facing groups of workers exposed to particular risks (Framework Directive 89/391/EEC) and document the process. Documentation should provide an overview of the identified hazards, respective risks and subsequent measures implemented .
The risk management process plays a central role for any to ensure occupational health and safety and to prevent workplace injuries and ill-health. But, companies, especially smaller ones, sometimes lack the expertise and the resources to carry out risk assessments. The need for a simple, clear and cost-effective way to ensure compliance with the legislation and to foster a positive safety and health culture has led to the development and use of web-based tools. To assist Member States, EU-OSHA has created the OiRA tool , a web-based platform that enables the creation of sectoral risk assessment tools in any language in an easy and standardised way. The OiRA tool generator is provided free of charge to sectoral social partners and national authorities at EU and national level. All the OiRA tools are available on oiraproject.eu https://oiraproject.eu/en and can be used by workplaces to carry out risk assessments.
[1] Directive 89/391/EEC of 12 June 1989 on the introduction of measures to encourage improvements in the safety and health of workers at work (Framework Directive). Available at: https://osha.europa.eu/en/legislation/directives/the-osh-framework-directive/1
[2] ISO 45001:2018 Occupational health and safety management systems — Requirements with guidance for use
[3] ISO 45003:2021 Occupational health and safety management - Psychological health and safety at work - Guidelines for managing psychosocial risks
[4] EC - European Commission, Guidance on Risk Assessment at Work, Luxembourg, 1996. Available at: http://osha.europa.eu/en/topics/riskassessment/guidance.pdf .
[5] Nunes, I. L., 'Risk Analysis for Work Accidents based on a Fuzzy Logics Model', 5th International Conference of Working on Safety - On the road to vision zero? Roros. Norway, 2010.
[6] Jensen RC, Bird RL, Nichols BW. Risk Assessment Matrices for Workplace Hazards: Design for Usability. Int J Environ Res Public Health. 2022 Feb 27;19(5):2763. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8910355/
[7] BAuA. Schritt 3: Gefährdungen beurteilen. Available at: https://www.baua.de/DE/Themen/Arbeitsgestaltung-im-Betrieb/Gefaehrdungsbeurteilung/Grundlagenwissen/Prozessschritte-der-Gefaehrdungsbeurteilung/Autorenbeitraege/Schritt3.html
[8] BSI - British Standard Institutions, Occupational health and safety management systems — Guide, BS 8800, 2004.
[9] HSE - Health and Safety Executive, Principles and guidelines to assist HSE in its judgements that duty-holders have reduced risk as low as reasonably practicable, 2011. Available at: http://www.hse.gov.uk/risk/theory/alarp1.htm#P14_1686
[10] NSW - New South Wales Government, Six steps to Occupational Health and Safety. Available at: http://www.une.edu.au/od/files/OHSSixsteps.pdf
[11] Harms-Ringdahl, L., Safety Analysis: Principles and Practice in Occupational Safety, Taylor & Francis, 2001.
EU-OSHA - European Agency for Safety and Health at Work, Risk assessment essentials. Available at: https://osha.europa.eu/en/publications/risk-assessment-essentials/view
EU-OSHA - European Agency for Safety and Health at Work, Management Leadership in Occupational Safety and Health – a practical guide. Available at: https://osha.europa.eu/en/publications/management-leadership-occupational-safety-and-health-practical-guide
EU Commission, Health and safety at work is everybody’s business. Available at: https://op.europa.eu/en/publication-detail/-/publication/cbe4dbb7-ffdc-11e6-8a35-01aa75ed71a1/language-en/format-PDF/source-85839760
ILO - International Labour Organisation, How can occupational safety and health be managed? Available at: https://www.ilo.org/global/topics/labour-administration-inspection/resources-library/publications/guide-for-labour-inspectors/how-can-osh-be-managed/lang--en/index.htm
IEC/ISO 31010:2019 Risk management - Risk assessment techniques https://www.iso.org/standard/72140.html .
ISO/TR 14121-2:2012 Safety of machinery — Risk assessment — Part 2: Practical guidance and examples of methods https://www.iso.org/standard/57180.html
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Aditya Jain
Karla Van den Broek
Isabel Nunes
The humble Risk Assessment Matrix (RAM) comes in for a lot of criticism. Whilst some of this may be justified, some arises more from a misunderstanding of the purpose and intended use of the RAM. There are strong views expressed on both sides of the argument (see Ref. 1 example). Here, we provide practical guidance on some of the more common issues.
A RAM is a matrix that is used during risk assessment to define the various levels of risk as the combination of probability and consequence categories. Figure 1, derived from ISO 17776, shows a typical example. A RAM is a simple tool intended to increase visibility of risks and assist decision-making.
The key benefit of a RAM is to give a rapid and consistent appreciation of the risk levels and, hopefully, to encourage a discussion and common understanding of how severe hazardous scenarios can be and how often they could occur. The RAM risk level scores are there to help make an informed decision as to the acceptability of that risk. The actual cell chosen should not be too critical, and if the decision-making process is indelibly tied to the exact position on the RAM, then a more detailed assessment method would be appropriate.
RAMs come in many different shapes and sizes, ranging from 3×3 to 10×10. Too small a RAM may not give sufficient resolution, whilst too large may take longer to use and it is questionable whether this level of granularity is really needed. The most common tend towards the 6×4, 5×5 or 6×6 type.
However, don’t assume that because there are only two axes and 25 cells, that everyone will use the RAM in the same way. What is important is consistency and that that there is clear guidance on its use.
One contentious area that commonly results in poor use of the RAM is in assessing residual risk. Residual risk, when combined with the initial unmitigated risk scores, has the advantage of showing a moving score on the RAM. Unfortunately this allows some people to claim, falsely, that this proves risk levels have been reduced as low as reasonably practicable (ALARP).
Part of the problem lies with the difficulty in determining the unmitigated risk. This answers the question, “If nothing works, how bad could it be?” The acceptance of residual risk then relies on assessing whether “given the controls we have in place, is that good enough?” But it’s not always practical to completely discount controls in gauging the unmitigated risk. You might argue that the unmitigated risk of driving a car should consider an unlicensed driver in a car with no mechanical integrity on unmade roads, but is this realistic? But if we allow for a licensed driver in a roadworthy car on a freeway, why then should we not claim the seat belts and airbags as well? The solution to this conundrum is to define at the outset precisely what is meant by unmitigated and residual risk.
A RAM gives point risk scores for individual scenarios. Whilst it is often useful to prepare heat maps showing the relative distribution of events across the RAM, this isn’t the same as determining a cumulative risk score. Individual events may affect different groups of people, and may also lead to multiple consequences occurring simultaneously.
Should an entire company employ a single common RAM, or should each department have its own specific one? The former allows for a consistent approach but can lead to increased RAM size to handle risk assessments ranging from workplace hazards to events threatening the corporation. The latter allows for simple, highly targeted assessments, but managing consistency across an organisation becomes more difficult.
The RAM provides a simple, well-used approach to risk assessment with considerable benefits in promoting discussion and achieving a common understanding of the risks. Despite its simplicity it is still open to abuse both unconsciously (“It’s simple so I don;t have to think very hard”) and consciously (“I can use this to my advantage”) from people ascribing greater accuracy than the matrix can achieve or using it to uphold a decision that has already been made, rather than using the ALARP process.
1. Cox, L.A., What’s wrong with risk matrices? 2008. 2. Talbot, J., What’s right with risk matrices?
This article first appeared in RISKworld issue 30
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In this class, Alejandro Orrego, CEO at Pirani, teaches us about key components of a Risk Assessment Matrix, impact variables, measure risks, and risk management strategies.
A Risk Assessment Matrix is a tool used in risk management to evaluate and prioritize potential risks by categorizing them based on their likelihood and impact.
It provides a visual representation that helps in assessing the severity of risks and deciding which ones need attention.
IMPACT: Impact refers to the potential consequences or effects of a risk event on an organization's objectives. The impact can be positive (an opportunity) or negative (a threat) and can affect various aspects of the organization, such as financial performance, reputation, safety, or environmental factors.
LIKELIHOOD: Likelihood refers to the probability or chance of a risk event occurring. It is a measure of the frequency or occurrence of the risk and can be expressed qualitatively (e.g., low, medium, high) or quantitatively (e.g., a percentage or frequency rate).
This How It Works:
The Purpose:
1. centralized data management.
Risk management software provides a centralized platform for storing and managing all risk-related data. This reduces the risk of data being scattered across multiple spreadsheets and ensures consistency and accuracy.
These tools often come with built-in analytics and reporting features that allow for more sophisticated risk analysis and visualization. You can generate reports and dashboards that offer insights into risk trends and metrics that are more difficult to create manually in spreadsheets.
Risk management software typically supports real-time updates and collaborative features, allowing multiple users to work on risk assessments simultaneously. This is more efficient than coordinating changes across different versions of spreadsheets.
Many risk management tools include automation features that can calculate risk scores, prioritize risks, and even suggest mitigation strategies based on predefined criteria. This reduces manual effort and potential errors.
Modern risk management software is designed with user experience in mind, offering intuitive interfaces that make it easier to navigate and use compared to complex and often unwieldy spreadsheets.
As your organization grows, managing risks through spreadsheets can become cumbersome and error-prone. Risk management software is designed to scale with your needs, handling larger datasets and more complex risk management processes efficiently.
Risk management software often includes audit trails that track changes and updates made to the risk data. This can be crucial for accountability and understanding the history of risk management decisions.
Spreadsheets are prone to human errors, such as formula mistakes or data entry issues. Risk management software reduces these risks through standardized processes and automated checks.
Dedicated software often includes features to help ensure compliance with industry regulations and standards. This can be particularly important for industries with strict compliance requirements.
These software solutions often integrate with other business systems (like ERP, CRM, or project management tools), which helps in consolidating risk information from various sources and maintaining a comprehensive risk profile.
Learn everything you need to know about Risk Management with our experts. Next class: How to use risk management software
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https://www.nist.gov/publications/guide-conducting-risk-assessments
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Is audit in practice: managing the practical risk assessment.
Jane smiled as she signed the contract—it had been a long time coming. Data availability and data integrity for her organization’s advocacy work had always been an issue. Available public information was controlled by the entities her organization was trying to monitor. Detail was lacking, timeliness was nonexistent. Now their watchdog group would change all that by developing their own data analytics tool for fact-based evidence that could be acted upon. Not that Jane was ready to toast the occasion yet. Although the new contract for a vendor-developed custom data tool would bring the organization from conversation to action, she knew the project posed risk to the tiny advocacy group. Did they have the know-how to pull this off, even with a savvy software vendor? What if the budget projections were off and more capital was needed? And, what if, after all the data collection, the results were inconclusive, or the data integrity was suspect? How would they even know how to detect errors? Jane knew they had taken a huge leap and a risk that everyone was ready to accept, but did they all understand what that risk really was? She thought of the old saying, “be careful what you wish for.”
ISACA ® professionals know that all risk is not the same. Industry dynamics, enterprise culture, and department risk tolerance all impact what an organization is willing to do. But risk is more than a willingness to take something on. Risk needs to be reviewed and scored based on the organization’s objectives, while fact checking the objectives against market trends, regulatory requirements, and more. So how can a risk professional help someone like Jane?
Successful risk management is all about operational acceptance and feasibility. Industry culture plays a significant role in determining risk priorities, and having a structured risk assessment approach is crucial, regardless of industry or organization size. That said, the structure must be tailored to suit the audience. Oftentimes, the leadership teams inadvertently make risk decisions without careful deliberation on benefits and consequences. To an IT professional familiar with the rigor of methodical development, business continuity, and other technology disciplines, it seems inconceivable that planning based on prioritized value and need might be overlooked, but it often is. The standard portfolio of risk categories must be outlined and assigned ratings of importance, including these categories:
It seems like a lot of work to research and discuss up front, which is why many organizations do a less than thorough job of building a risk framework. Business ideas are raised, teams get excited, and risk isn’t reviewed. Yet doing nothing to assess risk is the biggest risk of all.
Overcoming barriers to successful risk management.
ISACA professionals can help organizations overcome the major barriers to risk profiling by providing and executing a risk framework that’s feasible and practical for each organization. A feasible framework is one that the organization can execute because it has the tools and resources to perform the risk evaluation. A practical framework is one that provides enough value to the organization to merit using resources and tools versus using them on something else. Using resources, whether budget or manpower that is best used elsewhere, only devalues the benefit of the risk assessment. It is an extra step, but understanding what else is going on, what money can be spent, and what the organization’s expectations are will help right-size the risk framework used. The example of Jane’s advocacy group shows what must be considered by the ISACA professional to ensure that the risk assessment itself is valued and prioritized. Taking the following steps for Jane’s not-for-profit can help:
Jane did end up hiring a risk professional after signing the data analytics contract. Practically speaking, she knew this was a huge opportunity for her organization to become a trusted advisor to the communities impacted by the big business Jane’s organization monitored. Success required a solid financial assessment, especially for add-on features and functionality they might want. Data integrity was paramount, so a thorough review of security and operational risk were also key priorities for project success. All information used was public, and her organization was a small advocacy group, but the organization they monitored was regulated and Jane wasn’t sure how to tackle compliance risk. It made sense to bring in a knowledgeable professional to not only educate the team and vendor on risk management, but also to help operationalize a risk plan, with appropriate controls and auditing. The result was that risk was prioritized adequately from the start and corrective action was taken in a timely manner for the high priority areas. It was worth the risk of taking on a risk consultant.
Is Conservation Manager for Friends of Belle Isle Marsh. She works with environmental organizations, the community, and with developers to promote compliance for a green and resilient environment for the only remaining salt marsh in the city of Boston, Massachusetts. Her work also involves collaboration with municipal and state officials to move legislation forward with the innovation that green technology provides. Baxter is pleased that technology has allowed her to reinvent her career and continue learning at every step. She had the privilege of learning technology and managing Fortune 100 client relationships at AT&T. Baxter then applied her expertise as an IT operations director at Johnson & Johnson before moving to compliance and risk management roles at AIG and State Street Corporation. Baxter continues to accept select consulting assignments through her business What’s the Risk LLC, focusing on environmental risk management, inspection, and compliance enforcement. Baxter is pleased to serve as Operations Officer on the ISACA New England Chapter and is a board member on the Nantucket Lightship LV-112 Museum.
Background Cerebral arteriovenous malformation (AVM) is a cerebrovascular disorder posing a risk for intracranial hemorrhage. However, there are few reliable quantitative indices to predict hemorrhage risk accurately. This study aimed to identify potential biomarkers for hemorrhage risk by quantitatively analyzing the hemodynamic and morphological features within the AVM nidus.
Methods This study included three datasets comprising consecutive patients with untreated AVMs between January 2008 to December 2023. Training and test datasets were used to train and evaluate the model. An independent validation dataset of patients receiving conservative treatment was used to evaluate the model performance in predicting subsequent hemorrhage during follow-up. Hemodynamic and morphological features were quantitatively extracted based on digital subtraction angiography (DSA). Individual models using various machine learning algorithms and an ensemble model were constructed on the training dataset. Model performance was assessed using the confusion matrix-related metrics.
Results This study included 844 patients with AVMs, distributed across the training (n=597), test (n=149), and validation (n=98) datasets. Five hemodynamic and 14 morphological features were quantitatively extracted for each patient. The ensemble model, constructed based on five individual machine-learning models, achieved an area under the curve of 0.880 (0.824–0.937) on the test dataset and 0.864 (0.769–0.959) on the independent validation dataset.
Conclusion Quantitative hemodynamic and morphological features extracted from DSA data serve as potential indicators for assessing the rupture risk of AVM. The ensemble model effectively integrated multidimensional features, demonstrating favorable performance in predicting subsequent rupture of AVM.
Data are available upon reasonable request. The data that support the findings of this study are available from the corresponding author on reasonable request.
https://doi.org/10.1136/jnis-2024-022208
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Contributors All authors made substantial contributions to the conception and design of the study. Material preparation, data collection, and analysis were performed by LL and HZ. Formal analysis and investigation were performed by SL, XF and CM. YC, LZ, and YS performed manuscript review and editing. CJ and YZ performed supervision. HZ and JZ wrote the first draft of the manuscript, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. CJ is the guarantor for this study.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
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A risk assessment matrix is a visual chart that prioritizes and tracks project risks. Of more than a dozen different categories of risk, the four most important for a project manager to account for are management, organizational, technical, and external risks. Building a risk assessment matrix should be a core element of your overall approach ...
A risk assessment matrix, also known as a Probability and Severity or Likelihood and Impact risk matrix, is a visual tool depicting potential risks affecting a business. ... To avoid confusion, the company's risk assessment matrix methodology should be formally documented in policy and procedure documents, including any weighting and any ...
A risk assessment determines the likelihood, consequences and tolerances of possible incidents. "Risk assessment is an inherent part of a broader risk management strategy to introduce control measures to eliminate or reduce any potential risk- related consequences." 1 The main purpose of risk assessment is to avoid negative consequences related to risk or to evaluate possible opportunities.
Limitations of Risk Matrix. A risk matrix is useful in risk management but has some limitations. These limitations are: Inefficient Decision-Making: Sometimes, poor categorization of risk can cause poor assessment of risks, leading to poor decision-making. Biased Assessment: Many times, due to biases in risk assessment, risk levels can be miscalculated, and it can affect the risk management plan.
The risk assessment matrix will help your organization identify and prioritize different risks, by estimating the probability of the risk occurring and how severe the impact would be if it were to happen. ... Other organizations use a weighting methodology to bring greater attention to the responses by participants with subject matter expertise ...
A 5×5 risk matrix is a type of risk matrix that is visually represented as a table or a grid. It has 5 categories each for probability (along the X axis) and impact (along the Y axis), all following a scale of low to high. As a comprehensive tool used by organizations during the risk assessment stage of project planning, operations management ...
A risk assessment matrix (sometimes called a risk control matrix) is a tool used during the risk assessment stage of project planning. It identifies and captures the likelihood of project risks and evaluates the potential damage or interruption caused by those risks. The risk assessment matrix offers a visual representation of the risk analysis ...
Seven risk assessment methodologies. A comprehensive guide to using a risk assessment matrix. Risk management automation: A how-to guide for optimizing your processes. ... A risk assessment matrix is a grid-based, typically color-coded visualization of the potential risks an entity faces, graded against the likelihood of each risk scenario as ...
A risk matrix is a risk analysis tool to assess risk likelihood and severity during the project planning process. Once you assess the likelihood and severity of each risk, you can chart them along the matrix to calculate risk impact ratings. These ratings will help your team prioritize project risks and effectively manage them.
There are options on the tools and techniques that can be seamlessly incorporated into a business' process. The four common risk assessment tools are: risk matrix, decision tree, failure modes and effects analysis (FMEA), and bowtie model. Other risk assessment techniques include the what-if analysis, failure tree analysis, Layer of ...
A risk assessment matrix (also called a probability and severity risk matrix) is a visual tool project managers use to assess a risk's potential impact on their project. A risk matrix is a project management grid, with the probability of a risk represented on the left, and the severity of the risk represented on the top.
Risk assessment matrix is a simple methodology. Perfect for highlighting and rating risk severity. Risk assessment matrices are flexible and offer several systematic approaches to problem-solving. ISO 31000 certified methodology. Moving over to the actual implementation part, the Risk Assessment matrix methodology "CAN" turns out to be a ...
Risk Assessment. The risk assessment step, i.e. evaluating the risk item versus the Risk Assessment Criteria is often initially done as part of the risk identification process. As part of the risk ID meeting, allow the identifier of the risk event also characterize their risk by placing it on a 3' X 4' version of the Risk Priority Matrix (ref ...
To use a risk assessment matrix during the risk evaluation process effectively, take the following steps: 1. Identify all potential risks. The first step in the risk assessment process is to identify potential risks. To maintain a structure that is easy to manage, the risk assessment process offers a way to prioritize risks by evaluating ...
Risk assessment is one of the key stages in the Risk Management Process and involves specific steps: identifying hazards, analyzing and evaluating all possible risks. Several methods are developed to assess risks in the literature. A risk matrix method, also called "decision matrix risk assessment (DMRA) technique", is a systematic approach ...
Since its inception, the risk matrix has become one of the most widely used qualitative risk assessment technique that has been well adopted by the industries for its simplicity, yet, effectiveness. The risk matrix has been described as a semi-quantitative approach by many scholars (Ni, Chen, & Chen, 2010; Ruge, 2004). However, if both the ...
1.1 Purpose of the "risk matrix" methodology The risk matrix methodology is a practical model to quickly visualize the level of risk and decide whether further actions should be taken. This simplistic assessment model has been proven to be widely used in many domains, including aviation,
A tool used for assessing and evaluating risks is referred to in the OSH field as a risk table, risk grid, risk matrix, or (our preference) risk assessment matrix (RAM) [2,3,5,6,7,8,9,10,11]. RAMs appear as a two-dimensional grid with one axis having categories of harmful consequence and the other axis with categories for likelihood or probability.
Qualitative risk evaluation is more common and usually adopts a methodology based on a matrix. A risk assessment matrix consists of a two-dimensional grid with categories of harmful effects on one axis and categories of probability or likelihood on the other axis. The cells within the grid are used to indicate risk [6]. An example is shown in ...
The humble Risk Assessment Matrix (RAM) comes in for a lot of criticism. Whilst some of this may be justified, some arises more from a misunderstanding of the purpose and intended use of the RAM. There are strong views expressed on both sides of the argument (see Refs. 1 and 2 for example). Here, we provide practical guidance on some of the more common issues.
A Risk Assessment Matrix is a tool used in risk management to evaluate and prioritize potential risks by categorizing them based on their likelihood and impact. It provides a visual representation that helps in assessing the severity of risks and deciding which ones need attention.
an alternative risk matrix or methodology may be used. For example, the chemical risk assessment ... The University risk assessment methodology requires an analysis/score for both the inherent risk and the residual risk. safety.unimelb.edu.au HEALTH & SAFETY: RISK ASSESSMENT METHODOLOGY 3
Risk assessment involves the evaluation of risks taking into consideration the potential direct and indirect consequences of an incident, known vulnerabilities to various potential threats or hazards, and general or specific threat/hazard information. This resource document introduces various methodologies that can be utilized by communities to ...
This document provides guidance for carrying out each of the three steps in the risk assessment process (i.e., prepare for the assessment, conduct the assessment, and maintain the assessment) and how risk assessments and other organizational risk management processes complement and inform each other. [Supersedes SP 800-30 (July 2002): http ...
Using resources, whether budget or manpower that is best used elsewhere, only devalues the benefit of the risk assessment. It is an extra step, but understanding what else is going on, what money can be spent, and what the organization's expectations are will help right-size the risk framework used. The example of Jane's advocacy group ...
Background Cerebral arteriovenous malformation (AVM) is a cerebrovascular disorder posing a risk for intracranial hemorrhage. However, there are few reliable quantitative indices to predict hemorrhage risk accurately. This study aimed to identify potential biomarkers for hemorrhage risk by quantitatively analyzing the hemodynamic and morphological features within the AVM nidus. Methods This ...
For correct allergen risk management by industry, retail and food safety authorities, sensitive and reliable fast allergen detection methods are required, even more when precautionary allergen labelling based on reference doses will be implemented in legislation.This study aimed to perform a comparative assessment of three commercially available quantitative or qualitative test kits, for DNA ...