Identifying the Variables Contributing to At- Risk

Journal of Organizational Behavior Management

ISSN: 0160-8061 (Print) 1540-8604 (Online) Journal homepage: http://www.tandfonline.com/loi/worg20

Identifying the Variables Contributing to AtRisk Performance: Initial Evaluation of the Performance Diagnostic Checklist–Safety (PDCSafety) Brandon Martinez-Onstott, David Wilder & Sigurdur Sigurdsson To cite this article: Brandon Martinez-Onstott, David Wilder & Sigurdur Sigurdsson (2016) Identifying the Variables Contributing to At-Risk Performance: Initial Evaluation of the Performance Diagnostic Checklist–Safety (PDC-Safety), Journal of Organizational Behavior Management, 36:1, 80-93, DOI: 10.1080/01608061.2016.1152209 To link to this article: https://doi.org/10.1080/01608061.2016.1152209

Published online: 20 Mar 2016.

Submit your article to this journal

Article views: 390

View Crossmark data

Citing articles: 2 View citing articles

Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=worg20

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT 2016, VOL. 36, NO. 1, 80–93 http://dx.doi.org/10.1080/01608061.2016.1152209

Identifying the Variables Contributing to At-Risk Performance: Initial Evaluation of the Performance Diagnostic Checklist–Safety (PDC-Safety) Brandon Martinez-Onstott, David Wilder, and Sigurdur Sigurdsson Florida Institute of Technology, Melbourne, Florida, USA ABSTRACT

KEYWORDS

We adapted the Performance Diagnostic Checklist to analyze the environmental events contributing to safe and at-risk behaviors by employees in organizations. We then used the resulting tool, the Performance Diagnostic Checklist–Safety (PDC-Safety), to identify variables contributing to unsafe equipment usage by 3 members of a landscaping crew at a private university. Based on PDC-Safety results, an intervention consisting of graphic feedback was implemented. The intervention increased safe performance for all participants.

Behavioral safety; performance analysis; Performance Diagnostic Checklist–Safety (PDC-Safety)

In the United States, injuries and deaths resulting from workplace incidents cost companies and the federal government billions of dollars each year (Occupational Safety and Health Administration, 2014). Behavioral safety is the application of principles of behavior to improve safe performance; its focus is the analysis and modification of the social and physical environment to decrease at-risk behaviors and increase safe behaviors (McSween, 2003; Sulzer-Azaroff, 1978). More than 40 decades of research in behavioral safety has examined a variety of safe practices across many industries and settings, including the use of universal precautions (Luke & Alavosius, 2011), safe lifting procedures (Nielsen, Sigurdsson, & Austin, 2009), and flight checklist completion among pilots (Rantz & Van Houten, 2011). Assessment in behavioral safety often takes the form of a comprehensive description of the number, severity, type, and nature of accidents in an organization during a given time period. This type of assessment is essential to analyzing the factors contributing to unsafe performance. Specifically, a safety assessment consists of reviewing an organization’s safety data, conducting interviews with key organizational members, observing safety meetings and practices, analyzing the information obtained and developing a safety improvement plan, and reporting the recommendations to management (McSween, 2003, pp. 41–49; Sulzer-Azaroff & Fellner, 1984). Assessment in organizational behavior CONTACT David Wilder [email protected] 150 W. University Blvd., Melbourne, FL 32901, USA. Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/worg. © 2016 Taylor & Francis

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

81

management (OBM), which has been termed performance analysis, is broader and has generally focused on one of three levels of analysis: the individual level, the process level, or the systems level (Austin, 2000; Gilbert, 1978). At the individual level, which is the focus of the current study, assessment in OBM involves identification of the environmental events that are correlates of, or enter into a functional relationship with, a specific employee behavior. Individual assessments generally fall into three categories: informant assessment, descriptive assessment, and experimental analysis. One of the most utilized methods of individual assessment in the OBM literature is the informant method. Specifically, the Performance Diagnostic Checklist (PDC), which was introduced by Austin (2000), is among the most commonly described methods of assessing individual performance and its relationship to environmental events. The PDC has been used in a number of settings. For example, it has been used to identify the variables contributing to poor performance in a pizza restaurant (Amigo, Smith, & Ludwig, 2008), an autism treatment center (Carr, Wilder, Majdalany, Mathisen, & Strain, 2013), an outdoor sports retailer (Doll, Livesey, McHaffie, & Ludwig, 2007), a large department store (Eikenhout & Austin, 2004), a coffee shop (Pampino, Heering, Wilder, Barton, & Burson, 2004), a university-affiliated clinic (Gravina, VanWagner, & Austin, 2008), a retail framing and art store (Pampino, MacDonald, Mullin, & Wilder, 2004), and two sites of a restaurant franchise (Rodriguez et al., 2006). Despite its use in a variety of settings across many industries, only one study (Lebbon, Austin, Rost, & Stanley, 2011) has used the PDC to identify the environmental variables that affect safe and at-risk behaviors. In addition, no formal tool specifically designed to examine the environmental variables that may be responsible for safe and at-risk performance currently exists in the behavior analysis literature; such a tool could prove useful for safety managers, consultants, insurance companies, and researchers if it is accompanied by a comprehensive safety assessment as described previously. In the current study, we adapted the PDC to address variables related to safety. We adapted the PDC, rather than using the original tool, because the language of safety and the variables impacting safety are sufficiently different from mainstream OBM to warrant special consideration when informants provide their input. We then used the PDC-Safety to identify the variables contributing to at-risk performance among three landscape employees at a private university. In addition, we evaluated an intervention based on PDC-Safety results.

Method Participants and setting

Observers collected data on the grounds of a medium-size, private university in the southeastern United States. The climate in the area is humid

82

B. MARTINEZ-ONSTOTT ET AL.

subtropical; the flora found on the campus grows very quickly, requiring daily maintenance. Fifteen employees worked in the Grounds Department at the university; three of these employees (one male, two females) participated in the study. The participants were Henry, Abby, and Barbara. At the time of the study, they ranged in age from 42 to 53. They had a mean of 16 years of experience doing landscaping work, with a range of 12 to 22 years. Materials

The PDC-Safety (see the Appendix) was used with informants to identify the potential variables contributing to at-risk performance on the job. PDC-Safety questions focused on employee failure to adhere to personal protective equipment (PPE) requirements while working, as this was the concern described by supervisors (see “General Procedure”). When developing the PDC-Safety, we retained the four major domains described in the original PDC (antecedents, equipment and processes, knowledge and skills, and consequences). However, we did make a number of modifications to the original PDC based on comments and suggestions by safety experts in the field. Specifically, the first author sent the original version of the PDC-Safety (which was identical to the original PDC except for a changed focus from performance to safe performance) to six behavioral safety experts (i.e., individuals currently employed as behavioral safety consultants or managers) and asked each expert to make comments and suggestions for revision. Each of these experts had been practicing in the area of behavioral safety for 10 to 30 years. All six experts provided suggestions. Questions were modified, added, or removed based on the feedback provided. In addition, a Likert scale and formal scoring instructions were added. General procedure

First, we conducted a review of the organization’s injury data and safety practices. Based on this, appropriate PPE usage was identified as the target performance and the three participants described here were identified as participants. Next, baseline data on appropriate PPE usage were collected for the three participants. Next, the PDC-Safety was administered to two supervisors responsible for managing the three participants (baseline data are typically collected before PDC-Safety administration to learn more about the problem before interviewing supervisors). An intervention was then selected based on the PDC-Safety results. Finally, the selected intervention was evaluated using a nonconcurrent multiple baseline design. Dependent variable At an annual meeting that took place a few months before data collection began, supervisors for all three participants informed the participants that

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

83

gloves should be used when working with flora or tools and earplugs should be worn when working with motorized equipment. This information was also written in the employee handbook, which each participant received on initial employment and annually thereafter. Lack of PPE usage was defined as working with flora or tools such as shovels, hoes, and brooms without wearing cutproof gloves, and PPE usage was defined as engaging in the aforementioned activities while wearing gloves. Proper PPE usage for Barbara, who worked primarily with motorized equipment, was using in-ear or over-ear protection while working with motorized equipment. Glove and earplug use were targeted because the results of the safety review identified a history of cuts on hands and some hearing loss among previous employees. Data collection Each graduate student observer used a laptop or tablet to collect data and was trained in data collection until an interobserver agreement score greater than 90% was obtained for two successive observation sessions. Once trained, data collectors visited the site at least twice a week and collected data for a minimum of a 1-hr period. Data collectors, whom the participants had never met, collected data as unobtrusively as possible (e.g., they observed performance from windows or around corners of buildings). The first author also assisted with data collection during baseline but never collected data once intervention sessions began in order to reduce reactivity. Data were collected over 6 months. Employees on the site were informed about and agreed to participate in a study on safety, but they were not informed about specific dependent variables. The university’s institutional review board approved this arrangement. In addition, on days during which data collection took place, employees were asked their general location on the university campus and informed via a text message that their performance might be observed by data collectors. Data collectors used a partial interval recording system. Each 10-min observation session was divided into 10 observation intervals of 1 min each. If there was any occurrence of activities requiring PPE, but PPE was not used, the interval was marked electronically with an X. If there was proper PPE usage, the interval was marked with a checkmark even if PPE usage was not required for the entire interval. If there was no opportunity for PPE usage during the interval, the interval was left blank. Data on safe and at-risk behavior were calculated as percentage of overall intervals safe and percentage of overall intervals at risk when engaging in qualifying activities. Interobserver agreement A second observer collected data during a minimum of 31% of sessions across baseline and intervention phases for each participant. Each interval was compared across observers on an interval-by-interval basis to determine whether the observers agreed on intervals safe, at risk, or absent.

84

B. MARTINEZ-ONSTOTT ET AL.

Interobserver agreement data were scored for each session by dividing the number of intervals with agreement by the number of intervals with and without agreement and multiplying by 100. Mean agreement per session was then calculated by adding the agreement scores and dividing by the number of sessions. This number was then converted to a percentage. Mean agreement for Henry was 99% (range = 90%–100%). Mean agreement for Abby was 99% (range = 88%–100%). Mean agreement for Barbara was 100%. Experimental design A nonconcurrent multiple baseline design across participants was used to evaluate the intervention. Data were collected at different times for each participant, but the length of each baseline phase varied. Data were also collected at geographically dissimilar sites. That is, participants worked in different areas of campus, out of sight of one another. During baseline, data on safe and at-risk behavior were collected. After baseline, the first author administered the PDC-Safety. The PDC-Safety identified a lack of effective consequences as a contributor to at-risk behavior. The intervention implemented, graphic and oral feedback, was based on the results of the PDC-Safety (Sulzer-Azaroff & Fellner, 1984). That is, because employees received no programmed consequences for engaging in safe versus unsafe practices, we added feedback on safe performance. Independent variable The intervention consisted of graphic feedback, delivered by the experimenter, on participants’ adherence to PPE usage. Individual graphic feedback was delivered at the end of every three sessions. The graph depicted both baseline and intervention sessions; each participant was only provided with the graphic feedback that corresponded to his or her individual performance (i.e., he or she did not see other participants’ data). In addition to showing the participant the graph, the experimenter vocally explained the data displayed on the graph to the participant. No formal mastery criterion was used; feedback was delivered until performance was stable. Independent variable integrity data were also collected. A procedural checklist was used to record whether graphic feedback was properly delivered (i.e., delivered after every three intervention sessions, vocal explanation provided) to participants during the intervention. Independent variable integrity data were collected during a minimum of 24% of sessions across all participants; the mean independent variable integrity value was 100%.

Results and discussion Table 1 depicts the results of the administration of the PDC-Safety to two supervisors. A higher score on a domain of the PDC-Safety indicates that

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

85

Table 1. Percentage Scores From Each Performance Diagnostic Checklist–Safety Category Across Supervisors. Supervisor 1 2

Antecedents and information 26% 13%

Equipment and processes 7% 2%

Knowledge and skills 11% 11%

Consequences 40% 40%

Note. Higher percentages correspond to increased problems.

employee safety problems may be due to deficits in that area or domain and that an intervention targeting that domain is appropriate. The PDC-Safety identified a lack of effective consequences as contributing to participant safety problems. For both supervisors, the Consequences section produced a score of 40%, which was the highest overall score (note that the last step of scoring is to reverse-score each domain—see the scoring instructions in the Appendix). Figure 1 depicts the results of the intervention evaluation. Henry did not use gloves while working; graphic feedback increased performance to a mean of 100% of intervals with glove use. Abby also did not use gloves while working; graphic feedback increased her performance to a mean of 75% of intervals with the use of gloves. Abby went on vacation for 10 days immediately following the delivery of feedback after Session 15; when she returned to work she did not use the PPE properly (Sessions 16–18). It is hypothesized that the time between delivery of feedback and the opportunity to engage in the target behavior (10 days) was responsible for this decrease in performance. Alternatively, it is possible that feedback was not effective to maintain Abby’s performance. Future research should examine the variables contributing to inadequate maintenance of performance. The experimenter was not given notification that Abby was taking time off until after the feedback was delivered. After Session 18, Abby received feedback and her safe performance increased. Barbara did not wear hearing protection during baseline; graphic feedback increased her safe performance to a mean of 88% of intervals wearing hearing protection. The PDC-Safety was administered to two supervisors to identify potential variables contributing to lack of PPE usage by three landscape employees at a private university. The PDC-Safety suggested that a lack of effective consequences contributed to poor PPE usage. Based on these results, graphic feedback was then implemented. PPE usage increased after the intervention was implemented with each participant. These data suggest that the PDC-Safety identified important variables affecting safety equipment usage and assisted in appropriate treatment selection. This is congruent with Gilbert’s (1978) behavioral engineering diagnostic model in that it suggests that data/information provided to the performer is often the logical first step of intervention. This study adds to the literature by extending the original PDC (Austin, 2000) to the area of safety via an adapted tool. One of the advantages of the PDC-Safety is that it is easy to administer; it took approximately 20 min per supervisor. The PDC-Safety might be useful as an adjunct to a

Figure 1. Percentage of intervals with proper personal protective equipment (PPE) usage for Henry, Abby, and Barbara. The arrows represent feedback delivery.

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

87

comprehensive safety assessment, but it is not a substitute for a comprehensive assessment. The PDC-Safety might be conducted immediately before direct observation of an organization’s safety meetings and practices (see the description of safety assessment steps in the introduction) as part of a comprehensive assessment. Completing this prior to collection of baseline data may enhance the data collection by including measurement of contextual variables correlating with target behaviors in the observation protocol. Several limitations of this study should be noted. First, because only one area of the PDC-Safety was identified as problematic, only one type of intervention was examined. The intervention addressed a lack of effective consequences; interventions that address problems correlated with other domains covered by the PDC-Safety, such as equipment and processes and knowledge and skills, were not examined in the present study. Second, it is possible that alternative interventions that addressed the lack of effective consequences would have been equally useful. Other consequence-based interventions, such as selfmonitoring, peer observation/feedback, or the delivery of preferred items contingent on improved safety, could later be examined as independent variables. Third, although the Consequences section of the PDC-Safety was clearly the section with the highest score in the current study, no specific score was determined a priori to designate a PDC-Safety domain as problematic. Future researchers might explore the establishment of specific scores that indicate that an intervention is warranted. Fourth, we used a nonconcurrent multiple baseline design; a concurrent design would have been stronger, but because of scheduling conflicts we were unable to start participants at the same time. Fifth, no follow-up data were collected. Finally, it is possible that other interventions not identified by the PDC-Safety would have been equally effective at increasing PPE usage. Future research should compare the effectiveness of interventions identified via the PDC-Safety to that of interventions suggested by other assessment methods to further examine the tool’s utility. In conclusion, the PDC-Safety adds to the behavioral safety and performance analysis literatures by providing an easy-to-administer assessment tool that practitioners and researchers in the field can use to gather information about the environmental variables that might affect safe performance by individual employees. The PDC-Safety may also assist in directing practitioners to effective interventions, possibly reducing time spent evaluating interventions selected arbitrarily that may not directly target the variables responsible for a lack of safe performance. References Amigo, S., Smith, A., & Ludwig, T. (2008). Using task clarification, goal setting, and feedback to decrease table busing times in a franchise pizza restaurant. Journal of Organizational Behavior Management, 28(3), 176–187. doi:10.1080/01608060802251106

88

B. MARTINEZ-ONSTOTT ET AL.

Austin, J. (2000). Performance analysis and performance diagnostics. In J. Austin & J. Carr (Eds.), Handbook of applied behavior analysis (pp. 304–327). Reno, NV: Context Press. Carr, J., Wilder, D., Majdalany, L., Mathisen, D., & Strain, L. (2013). An Assessment-based solution to a human-service employee performance problem: An initial evaluation of the Performance Diagnostic Checklist–Human Services. Behavior Analysis in Practice, 6, 17– 32. Doll, J., Livesey, J., McHaffie, E., & Ludwig, T. D. (2007). Keeping an uphill edge. Journal of Organizational Behavior Management, 27(3), 41–60. doi:10.1300/J075v27n03_04 Eikenhout, N., & Austin, J. (2004). Using goals, feedback, reinforcement, and a performance matrix to improve customer service in a large department store. Journal of Organizational Behavior Management, 24(3), 27–62. doi:10.1300/J075v24n03_02 Gilbert, T. (1978). Human competence: Engineering worthy performance. New York, NY: McGraw-Hill. Gravina, N., VanWagner, M., & Austin, J. (2008). Increasing physical therapy equipment preparation using task clarification, feedback and environmental manipulations. Journal of Organizational Behavior Management, 28(2), 110–122. doi:10.1080/01608060802100931 Lebbon, A., Austin, J., Rost, K., & Stanley, L. (2011). Improving safe consumer transfers in a day treatment setting using training and feedback. Behavior Analysis in Practice, 4(2), 35–43. Luke, M. M., & Alavosius, M. (2011). Adherence with universal precautions after immediate, personalized performance feedback. Journal of Applied Behavior Analysis, 44, 967–971. doi:10.1901/jaba.2011.44-967 McSween, T. (2003). The values-based safety process: Improving your safety culture with behavior-based safety (2nd ed.). Hoboken, NJ: Wiley. Nielsen, D., Sigurdsson, S. O., & Austin, J. (2009). Preventing back injuries in hospital settings: The effects of video modeling on safe patient lifting by nurses. Journal of Applied Behavior Analysis, 42, 551–561. doi:10.1901/jaba.2009.42-551 Occupational Safety and Health Administration. (2014). Fact sheet. Retrieved from https:// www.osha.gov/ Pampino, R., Heering, P., Wilder, D. A., Barton, C., & Burson, L. (2003). The use of the performance diagnostic checklist to guide intervention selection in an independently owned coffee shop. Journal of Organizational Behavior Management, 23, 5–19. Pampino, R. N., MacDonald, J. E., Mullin, J. E., & Wilder, D. A. (2004). Weekly feedback vs. daily feedback. Journal of Organizational Behavior Management, 23(2–3), 21–43. doi:10.1300/J075v23n02_03 Rantz, W. G., & Van Houten, R. (2011). A feedback intervention to increase digital and paper checklist performance in technically advanced aircraft simulation. Journal of Applied Behavior Analysis, 44, 145–150. doi:10.1901/jaba.2011.44-145 Rodriguez, M., Wilder, D. A., Therrien, K., Wine, B., Miranti, R., Daratany, K., . . . Rodriguez, M. A. (2006). Use of the Performance Diagnostic Checklist to select an intervention designed to increase the offering of promotional stamps at two sites of a restaurant franchise. Journal of Organizational Behavior Management, 25(3), 17–35. doi:10.1300/ J075v25n03_02 Sulzer-Azaroff, B. (1978). Behavioral ecology and accident prevention. Journal of Organizational Behavior Management, 2, 11–44. doi:10.1300/J075v02n01_02 Sulzer-Azaroff, B., & Fellner, D. (1984). Searching for performance targets in the behavior analysis of occupational safety: An assessment strategy. Journal of Organizational Behavior Management, 6(53), 53–65. doi:10.1300/J075v06n02_09

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

89

Appendix Performance Diagnostic Checklist–Safety Company Name: ____________________________ Interviewer: ________________________________ Interviewee:________________________________ Date: ________________ Time: ____________ Job Title: __________________________________ Answer each of the following questions to the best of your ability. At the end of the questionnaire please note any OSHA requirements that are currently in place. (1) Antecedents and Information –Do personnel receive formal safety training before they are allowed to begin their job? None A little Some 1 2 3 4 5

Fair amount

A lot

–Is there a safety manual in the employee’s work environment? Yes No –Are there safety prompts in the employee’s work environment? None A little Some 1 2 3 4 5

Fair amount

A lot

–Are there any safety programs or processes currently taking place? None A little Some 1 2 3 4 5

Fair amount

A lot

–Are managers involved in any of the safety programming? None A little Some 1 2 3 4 5

Fair amount A lot

–Is there a challenging yet attainable safety goal set? Can the employee tell you what this goal is? None A little Some 1 2 3 4 5

Fair amount A lot

–Does the organization have a safety mission that is clearly stated? Not clear Kind of clear 1 2 3 4 5

Somewhat clear Pretty clear

Very clear

90

B. MARTINEZ-ONSTOTT ET AL.

–Are safety values clearly established? Not clear Kind of clear 1 2 3 4 5

Somewhat clear

Pretty clear

Very clear

–Are employees involved in the safety process in any way? None A little Some Fair amount A lot 1 2 3 4 5 Total: ______/ 40 (Bullet 2 does not accrue points) (1) Equipment and Processes –If equipment is required, does it conform to safety inspections? Not at all A little Some 1 2 3 4 5

Most

Completely

–Are there medical resources available in case they are needed? None A little Some 1 2 3 4 5

Fair amount

A lot

–Is any Personal Protective Equipment (PPE) required? Yes

No

Unsure

–If applicable, is the Personal Protective Equipment accessible? None A little Some 1 2 3 4 5

Fair amount

A lot

–Is the work area generally free from environmental hazards? Not at all A little 1 2 3 4 5

Some

Most

Completely

–How quickly are safety concerns addressed, such as equipment problems or hazards in work area? Never Within a month Within a week 1 2 3 4 5

Within 24 hours Same day

–Is the equipment ergonomically correct and does it encourage safe use? Not at all A little 1 2 3 4 5

Some

Most

Completely

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

91

–Are employees required to demonstrate fluency in safe performance before beginning work? Not at all A little 1 2 3 4 5

Some

Most

Completely

–Are there any obstacles that are keeping the employee from completing the task safely? A lot Fair amount Some A little None 1 2 3 4 5 Total: ______/ 35 or 40 (Bullet 3 does not accrue points: If answer to Bullet 3 is Yes, 40 is denominator; If answer to Bullet 3 is No, 35 is denominator) (1) Knowledge and Skills –Can all employees physically demonstrate safety routines required for their job? Not at all A little 1 2 3 4 5

Some

Most

Completely

–How often are safety incidents reported? Never Rarely Sometimes 1 2 3 4 5

Almost always Always

–Are injury reports collected and analyzed? Not at all A little 1 2 3 4 5

Some

Most

Completely

–Are safety assessments conducted? None A little Some 1 2 3 4 5

Fair amount

A lot

–Is there a safety manager/department? Yes No

Unsure

–Can the employee recite the mission or values (as they relate to safety) of the company? Not at all A little 1 2 3 4 5 Total: ______/25

Some

Most

Completely

(1) Consequences –Are accidents investigated and, if something can be changed to prevent future accidents, are changes made?

92

B. MARTINEZ-ONSTOTT ET AL.

None A little Some 1 2 3 4 5

Fair amount

A lot

–Are there consequences delivered contingent on safe behaviors? None 1 2

A little 3 4

Some 5

Fair amount A lot

–Are consequences delivered contingent on being free from accidents? For example, if employees go X amount of days without injury, are there consequences? A lot 1 2

Fair amount 3 4 5

Some

A little

None

–Are there any safety incentive programs currently in use? None A little 1 2 3 4

Some 5

Fair amount

A lot

–Are there any competing contingencies supporting unsafe task performance? A lot Fair amount Some 1 2 3 4 5

A little

None

–Are managers present to give feedback on safe behaviors? Not at all 1 2 3

A little 4 5

Some

Most

Completely

–Is there a response effort associated with performing a task safely? A lot Fair amount Some A little None 1 2 3 4 5 Total: ______/35 OSHA Requirements: _______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ To Calculate / Score: Add up the score in each section A through D and record below. Then divide the number of points earned by total number of points for each section, multiply by 100 and convert to a percentage. Ex. 36/40 = .9 × 100 = 90%. Next, reverse-score for each section (e.g., 90% = 10%, 80% = 20%, etc.). This indicates the extent of the problem for a given section.

JOURNAL OF ORGANIZATIONAL BEHAVIOR MANAGEMENT

93

To obtain a ranking, place the number 1–4 according to the numerical order of the percentage calculated. Place a 1 next to the highest percentage a 2 for second highest and so on. Total Percentage Reverse Score Ranking (A) (B) (C) (D)

_____/ _____/ _____/ _____/

40 40 25 35

= = = =

______% ______% ______% ______%

______ ______ ______ ______

______ ______ ______ ______