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Assignment 1: Quantitative Journal Article Review
Kylie Chernenkoff
Yorkville University
PSYC6213 Research Methodology
Dr. Stacia Alexander
July 30, 2023
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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).
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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
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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
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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).
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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.
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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.,
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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
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