1 Assignment 1: Quantitative Journal Article Review Kylie Chernenkoff Yorkville University PSYC6213 Research Methodology Dr. Stacia Alexander July 30, 2023 Classification: Protected A 2 Declaration of chosen Topic for the Final Project For the final project, I have chosen to explore the impact of shift work schedules on mental health. Quantitative Journal Article for Review Peterson, S. A., Wolkow, A. P., Lockley, S. W., O'Brien, C. S., Qadri, S., Sullivan, J. P., Czeisler, C. A., Rajaratnam, S. M. W., & Barger, L. K. (2019). Associations between shift work characteristics, shift work schedules, sleep and burnout in North American police officers: a cross-sectional study. BMJ open, 9 (11), e030302. Statement of Problem This study addresses the potential harm that a shift work schedule has on an employee’s mental health. A high percentage of the shift work population are first responders, who exhibit more prevalent psychological health conditions than other careers (Horan et al., 2021). The questions Peterson et al. (2019) explore include: “Are there any associations between shift work characteristics and schedules on burnout in police? Are sleep duration and sleepiness associated with burnout?” By showing burnout as a negative effect of shift work, the researchers encourage improved scheduling in police professions. Literature Review For police officers, shift work is one of the leading contributors to occupational stress due to irregular schedules, sleep disorders, and psychological disorders (Vila, 2006 in Peterson et al., 2019). Occupational stress leads to burnout which has negative psychological consequences and, subsequently, affects overall work quality and productivity (McGreedy, 1974 in Peterson et al., 2019). Classification: Protected A 3 Hypotheses To Be Tested In the words of the experimenters, the hypotheses of this study are: “a greater frequency of night shifts is more strongly associated with burnout compared with lower frequencies; and more variable shift work is related to high burnout” (Peterson et al., 2019). Method Research Design Designed for “population-based surveys” and to “assess the prevalence of diseases in clinic-based samples”, this cross-sectional study provides information regarding outcomes and exposures (Setia, 2016). Further, as a correlational study, two or more characteristics are measured for the subsequent analysis of correlation (Woodworth, 1938 in Goodwin & Goodwin, 2017). Participants In a cross-sectional study, inclusion and exclusion criteria is developed for the selection of participants (Setia, 2016). In Peterson et al. (2019), participants were acquired through a volunteer process that was advertised in police magazines and newsletters, on law enforcement websites, and in police department meetings (Peterson et al., 2019). The response of interest and consent came from 4957 sworn North American police officers who agreed to participate in an online or on-site survey (Peterson et al., 2019). Materials To assess burnout in participants, the Maslach Burnout Inventory- Human Services Survey (MBI–HSS) was used. This survey has high reliability because it has been repeated for over 35 years (Soares et al., 2022). As it was designed for human service professionals, it holds high validity because it measures exactly what it is supposed to measure: burn-out in police Classification: Protected A 4 officers. “Emotional exhaustion (EE), depersonalization (DP), and personal accomplishment (PA)” are three features of burnout that were assessed and rated with high reliability (0.76-0.90) (Peterson et al., 2019). Using a Likert scale to measure for low, moderate, or high risk scores, burnout was deemed to be present if participants scored high in EE and DP, “with or without low PA” (Peterson et al., 2019). Sleepiness of participants was measured using the Epworth Sleepiness Scale (ESS). The ESS “measures levels of daytime sleepiness” by participants rating their tendency to become sleepy during eight common daily activities (Boyes et al., 2017). With consistent reports of testretest reliability (0.81 and 0.93), the ESS is widely used in the medical field as a subjective measure of sleepiness, which proves commendable validity (Boyes et al., 2017). Procedure This correlational study followed a simple procedure of a statement of hypotheses, collection of data utilizing survey-based methods, the acquired data is then analyzed for correlation, and subsequent results are discussed. Statistics First, variables which differed significantly from other points of data were averaged out using the winsorizing method, where the smallest and largest variables are replaced by the observations closest to them (Lien & Balakrishnan, 2005). Winsorizing promotes reliable results by eliminating “erroneous conclusions” (Lien & Balakrishnan, 2005). Next, multiple logistic regression models were used for “the cross-sectional analysis of associations between shift work (shift work characteristics and schedules), sleep duration, sleepiness, and burnout” (Peterson et al., 2019). This model “estimates the effects on a dependent Classification: Protected A 5 variable by changing one variable, while holding the other explanatory variables constant” (Uyanik & Guler, 2013). Lastly, confounding variables were selected based on prior studies, adjusted, then individually tested with the outcome being burnout (Peterson et al., 2019). Only significant (p<0.10) variables were then included in step one of a hierarchical logistic regression model; the second step then included the confounding factors that made it through selection (Peterson et al., 2019). The statistical analyses of this study “were conducted using SPSS V.24.0 (IBM) and significance set at p<0.05” (Peterson et al., 2019). Results Implications for Counselors, Clients, and Counselling The implications of the findings are that shift work personnel are more prone to burnout and subsequent mental health issues. Although causality could not be proven, strong inference is. For counsellors to improve their practice, this study offers insight on how a client is affected by their shift work schedule, providing a clearer depiction of the worldview of a shift worker. Summary The main results of this study indicate that “higher numbers of long shifts/night shifts, mandatory overtime/short sleep, and sleepiness raise the risk of burnout in police” (Peterson et al., 2019). These findings align with the original hypotheses that “a greater frequency of night shifts would be more strongly associated with burnout compared with lower frequencies and more variable shift work would be related to high burnout” (Peterson et al., 2019). Classification: Protected A 6 Interpretation The conclusions made by the author are warranted as the findings align with the hypotheses. Possible alternative explanations for the results could be something related to PTSD symptoms because the population of shift workers being studied are police officers. The strengths of the study include reliability and validity of measures, which are major points of interest to affirm a study’s results (Goodwin & Goodwin, 2017). Due to the nature of the collection of data, ethical considerations were easily facilitated. The effort to control confounding variables was successful using a hierarchical logistic regression model. The limitation of this study includes potential subjectivity of survey reports, as they can be influenced by participant bias. A causal conclusion could not be drawn due to this being a non-experimental correlational study. The generalizability of the study applies to the population subgroup of police officers, however given the nature of the research being conducted on shift work schedules these findings can apply to other shift-working professionals. For Further Study While shift work is inevitable in the human service profession, a means to lower burnout should be explored and incorporated. With lower levels of burnout, this would improve mental health and energy levels in staff, improving overall job performance (Peterson et al., 2019). This research can be further developed by using a longitudinal design which would permit researchers to “detect developments or changes in the characteristics of the target population at both the group and the individual level” (Caruana et al., 2015). The findings support future research to prevent irregular schedules in vulnerable shift worker populations such as police officers. Classification: Protected A 7 References Boyes, J., Drakatos, P., Jarrold, I., Smith, J., & Steier, J. (2017). The use of an online Epworth Sleepiness Scale to assess excessive daytime sleepiness. Sleep & breathing = Schlaf & Atmung, 21(2), 333–340. https://doi.org/10.1007/s11325-016-1417-x Caruana, E. J., Roman, M., Hernández-Sánchez, J., & Solli, P. (2015). Longitudinal studies. Journal of thoracic disease, 7(11), E537–E540. https://doi.org/10.3978/j.issn.2072-1439.2015.10.63 Goodwin, K. A., & Goodwin, C. J. (2017). Research in psychology: Methods and designs (8th ed.). Hoboken, NJ: John Wiley & Sons. Horan, K. A., Marks, M., Ruiz, J., Bowers, C., & Cunningham, A. (2021). Here for My Peer: The Future of First Responder Mental Health. International journal of environmental research and public health, 18(21), 11097. https://doi.org/10.3390/ijerph182111097 Lien, D. & Balakrishnan, N. (2005). On regression analysis with data cleaning via trimming, winsorization, and dichotomization. Communications in Statistics - Simulation and Computation, 34:4, 839-849. https://doi.org/10.1080/03610910500307695 McGreedy K. (1974). Selection practices and the police role. Police Chief, 41, 41–3. Peterson, S. A., Wolkow, A. P., Lockley, S. W., O'Brien, C. S., Qadri, S., Sullivan, J. P., Czeisler, C. A., Rajaratnam, S. M. W., & Barger, L. K. (2019). Associations between shift work characteristics, shift work schedules, sleep and burnout in North American police officers: a cross-sectional study. BMJ open, 9 (11), e030302. Rajaratnam S.M.W., Barger L.K., Lockley S.W., Shea, S.A., Wang, W., Landrigan, C.P., Classification: Protected A 8 O’Brien, C.S., Qadri, S., Sullivan, J.P., Cade, B.E., Epstein, L.J., White, D.P., & Czeisler, C.A. (2011). Sleep Disorders, Health, and Safety in Police Officers. JAMA, 306(23):2567–2578. doi:10.1001/jama.2011.185 Setia M. S. (2016). Methodology Series Module 3: Cross-sectional Studies. Indian journal of dermatology, 61(3), 261–264. https://doi.org/10.4103/0019-5154.182410 Soares, J. P., Lopes, R. H., Mendonça, P. B. S., Silva, C. R. D. V., Rodrigues, C. C. F. M., & Castro, J. L. (2022). Use of the Maslach Burnout Inventory Among Public Health Care Professionals: Protocol for a Scoping Review. JMIR research protocols, 11(11), e42338. https://doi.org/10.2196/42338 Uyanik, G. K & Guler, N. (2013). A Study on Multiple Linear Regression Analysis. Procedia – Social and Behavioral Sciences, 106, 234-240. https://doi.org/10.1016/j.sbspro.2013.12.027. Vila, B. (2006). Impact of long work hours on police officers and the communities they serve. American Journal of Industrial Medicine, 49, 972–80. https://doi.org/10.1002/ajim.20333 Classification: Protected A