Occupational Stressors and Mental Health Disorders: A National Study of Correctional Service Providers in Canada's Provincial and Territorial Systems

Abstract

Correctional workers (CWs) experience organizational (e.g., staff shortages, administrative burdens) and operational stressors (e.g., exposure to potentially psychologically traumatic events [PPTEs]) when completing their occupational responsibilities. In the current Canadian study, we assessed the average stress levels for diverse organizational and operational stressors among CWs across occupational groups (e.g., institutional operational, correctional officers, community operations, management, and administrators), provincial and territorial jurisdictions, and pre versus during COVID-19. We examined the relationships between 40 work-related stressors, including PPTE exposures and prevalence of positive screens for several mental health disorders (e.g., posttraumatic stress disorder, major depressive disorder, general anxiety disorder, panic disorder, alcohol use disorder). Results further evidence organizational and operational stressors beyond PPTE as being correlates of mental health challenges among CWs. Reducing organizational stress by increasing staffing and leadership training, improving communication and access to specialized treatment resources, mitigating PPTE exposures, and supporting collegial relationships may all potentiate improvements for the mental health of CWs.

Keywords

organizational stressors operational stressors correctional workers potentially psychologically traumatic events mental health disorders

Introduction

Correctional service providers or correctional workers (CWs) have physically, socially, and emotionally strenuous occupational responsibilities, whether working in correctional institutions (e.g., prisons), the community (e.g., reporting-centers), or headquarters (e.g., administrative spaces; Butler et al., 2019; Norman & Ricciardelli, 2022; Ricciardelli, 2019). CWs operate largely out of public view, which obscures their perspectives and experiences, minimizes recognition of their contributions and challenges (Johnston & Ricciardelli, 2024; Ricciardelli, 2019), yet subjects them to intense public scrutiny (Johnston & Ricciardelli, 2025). In Canada, CWs are recognized as first responders and public safety professionals (PSP) who provide critical services for everyone. CW responsibilities include being accountable for the rehabilitative and daily living needs of incarcerated people, while ensuring the safety, security, and care of incarcerated people, staff, the institution, and the public (Ricciardelli, 2019). Canadian provincial and territorial CWs have described their occupation as a vocation tied to wider pursuits of social and transformative justice for incarcerated people (Ricciardelli et al., 2023). CWs have unique, diverse, and sometimes-conflicting occupational roles, responsibilities, and work environments, all receiving increased focus from contemporary scholars working to understand interactions with mental health outcomes in correctional work (e.g., Regehr et al., 2021; Ricciardelli et al., 2024), including parole work (e.g., Norman & Ricciardelli, 2022).

How mental health is measured and conceptualized has been inconsistent across scholarship assessing CW wellness, and with the exception of recent studies in Canada (Ricciardelli et al., 2024), Switzerland (Isenhardt & Hostettler, 2020), and Italy (Lazzari et al., 2020), the literature tends to focus on the mental health and well-being of sworn security staff (i.e., correctional officers [COs]) rather than other CWs such as educators, medical staff, social workers, and so forth. In the Canadian context, recent research has examined the prevalence of mental health disorder(s) symptoms among diverse occupational groups of CWs to operationalize CW wellness, including posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and generalized anxiety disorder (GAD), which often arise from exposure to potentially psychologically traumatic events (PPTEs)¹ in correctional workspaces (Carleton et al., 2019; Regehr et al., 2021; Ricciardelli et al., 2024, 2025).

Occupational stressors among PSP include operational stressors (i.e., exposure to violence, threats, self-injury, death, fatal accidents) often inherent to the job and organizational stressors (i.e., structural aspects of the organization such as staff shortages or excessive workload) that may be more readily mitigated,² all of which appear associated with mental health outcomes (Carleton et al., 2020). Research with a sample of CWs from the Canadian province of Ontario—which the current study replicates on a national scale—evidenced average occupational stress scores as correlated with increased odds of positive screens for several mental health disorders (i.e., PTSD, MDD, GAD, Panic Disorder, or any mental health disorder; Konyk et al., 2021). The same study evidenced interactions between occupational stress, total PPTE exposures, and mental health symptoms, suggesting (at least in one jurisdiction) that mitigating occupational stressors may moderate mental health challenges (Konyk et al., 2021). Relatedly, in their recent national study of CW mental health disorder prevalence across every provincial and territorial correctional system in Canada, Ricciardelli et al. (2024) found 58% of CWs screened positive for at least one mental health disorder, with COs reporting a higher prevalence than other CW occupational groups; notably, the prevalence of mental health disorders was similar in pre- and post-COVID-19 periods, despite strong evidence indicating the unique challenges COVID-19 posed to prisons internationally (i.e., lack of medical supplies, understaffing, testing and tracing challenges, issues with containing contagion, physical and mental health risks of segregation; Williams et al., 2020).

In the current study, we extend the findings of Konyk et al. (2021) across all provincial and territorial correctional services in Canada, group participants into consistent occupational categories, and add a semi-comparison, where approximately half the data were collected before the COVID-19 pandemic and the other half during the COVID-19 pandemic. Regarding the former—the participant occupational groupings—most previous research aggregated participants across occupational categories within CW samples; however, recent research has evidenced potentially foundational differences between occupational categories of CWs in Canada (Ricciardelli et al., 2024). In terms of the latter, our study examines potential differences in occupational stressors that could be attributed to the impacts of the pandemic and associated public health measures. The current study is necessary, including for replication, but also for several other reasons: (a) day-to-day stressors have not been examined among CWs (the focus has been on COs specifically) in Canada; (b) former results stem from a single province (Konyk et al., 2021) limiting generalizability to the rest of the country due to differences and variability in systems across Canada; (c) more information is required on stressors as they are likely more actionable and can be changed (overtime, staff shortages, red tape, etc.) to improve mental health and well-being.

We begin the article by summarizing previous scholarship on occupational stressors and mental health challenges amongst CWs. We then describe our research methods, present our results, and discuss how our contributions further conceptualize individual experiences of occupational stressors, including but not limited to PPTE exposures. We further discuss the study limitations as well as recommendations for future research, policy, and practice in correctional services, with a focus on Canada.

CW Occupational Stressors and Exposure to PPTEs

Since the Oliphant (2016) report was published by the Government of Canada, there is a growing body of scholarship underscoring the prevalence of PPTE exposures and occupational stress among PSP, and how both are related to mental health disorder symptoms, with results applying to CWs or PSP more broadly (Carleton et al., 2020; Fusco et al., 2021; Jaegers et al., 2019; Ricciardelli, 2019). Associations between occupational stressors and mental health challenges appear robust (Butler et al., 2019); yet, there is no Canadian or international research to date examining mental health in relation to PPTEs and other occupational stressors across diverse CW occupations.

Much of the earlier work on occupational stressors among CWs (COs in particular) has occurred in the United States and focused on role conflict, ambiguity, and overload (Lambert & Hogan, 2018). This research on CWs has highlighted concerns tied to role overlap, supervision needs, work-family conflict, (threat of) victimization, and omnipresent unpredictable risk for violence (Lambert & Hogan, 2018); however, variability in research tools and methods has limited understandings of the relationships between occupational stressors and mental health (Lambert et al., 2015). The former, role conflict, may emerge, for instance, when there is overlap or differentiation in how COs are able to meet the rehabilitative needs of incarcerated people versus the security demands of the institution (Arnold, 2017). Role ambiguity occurs when there is a lack of clarity surrounding how to conduct oneself at work and the occupational responsibilities of which one is to complete (Arnold, 2017; Lambert & Hogan, 2018). Role overload refers to how an excessive workload can result in tension, stress, and strain (Lambert & Hogan, 2018). However, either individually or collectively, role challenges can accumulate in burnout and/or job stress (Lambert et al., 2015) that may subsequently tie to PTSD and other mental health disorders (James & Todak, 2018).

Although supervision is less studied in relation to its association with mental health disorders, scholars have found lower self-reported symptoms of PTSD when relations with supervisors are positive (James & Todak, 2018). Though beyond the scope of the current analysis, work-family conflict has also been tied to overlaps between roles and responsibilities at home as work is a documented source of personal stress for CWs (Armstrong et al., 2015; Lambert et al., 2017; Lambert & Hogan, 2018; Liu et al., 2017). This phenomenon has been tied to increased prevalence of MDD symptoms (Obidoa et al., 2011) as well as, for female CWs specifically, emotional burnout (Lambert et al., 2010). There is also much challenge between the transition from working in correctional services to home life, as hypervigilance, which is one example, extends to home life and shift work creates challenges for meeting familial responsibilities and expectations (e.g., Armstrong et al., 2015; Liu et al., 2020).

As described in Canadian research, violence is inherent to the occupational work of many CWs (Carleton et al., 2018; Ricciardelli & Power, 2020) and influences how safe one feels at work and outside of work. To evidence the realities of workplace violence for CWs in Canada, Carleton et al. (2019) found high percentages of CWs were exposed to PPTEs, including physical assault (88.7%), sudden violent death (85.6%), sudden accidental death (80.6%), assault with a weapon (78.8%), and life threating illness or injury (77.9%). PTSD is one of many possible outcomes from a PPTE exposure as there are comorbid conditions as well as the potential for other disorders (e.g., MDD and GAD) to develop (American Psychiatric Association, 2013). However, there is a necessary connection between PPTE exposures and mental health challenges, particularly PTSD (Andersen et al., 2019; Carleton et al., 2018, 2019, 2020). Studying COs in Denmark, Andersen et al. (2019) found, while noting how difficult capturing variation in PPTEs can be in the workplace, that verbal threats at work increased the potentiality of developing PTSD because of the psychological impact of such experiences—despite the immediacy in the effects of physical violence. Further, the idea that incarcerated people pose the sole source of risk in prisons stereotypes them as a priori unsafe (Kunst, 2011) and may distract from the challenges between colleagues, who federal COs in Canada have reported as the most influential source of stress (Cassiano & Ricciardelli, 2023). Earlier research warned psychological harm results from colleagues harassing or intimidating COs (Bourbonnais et al., 2007), with peer aggression correlating with PTSD prevalence (Kunst et al., 2009).

Overall, there remains a strong association internationally and in Canada between occupational stressors and compromised mental health. This relationship has been supported by prior Canadian research on diverse PSP (see Carleton et al., 2020); specifically, after controlling for PPTE exposures, occupational stress remained significantly associated with positive screens for mental health disorders, particularly among CWs, leading the authors to underscore the relative importance of occupational stressors other than PPTE exposures. To elaborate, Regehr et al. (2021) conducted a systematic review of CO prevalence of mental health disorders, finding COs reported higher rates of mental health concerns than the general public, including “over three times the relevant national lifetime prevalence for PTSD” (p. 8). In a Canadian study from 2018 that grouped all CWs under one umbrella, Carleton et al. (2018) determined a mental health disorder prevalence of 54.6%, which is much higher than the diagnostic prevalence for the general population (Statistics Canada, 2013; see also Ricciardelli et al., 2024). Thus, CWs in Canada experience high rates of occupational stress and compromised mental health.

Current Study

In the current study, we replicate and extend previous results with new data from provincial and territorial CWs across Canada. Specifically, we analyzed data from 13 studies that collectively represent a national sample, disaggregated by occupational groupings of CWs, with half the data collected prior to the COVID-19 pandemic and the other half during the pandemic. We examine similarities and differences in average stress levels for all occupational stressors and for item-level differences in both organizational (i.e., job context) and operational (i.e., job content) stressors as evidenced by each occupational group and across jurisdictions. We complement our analyses with an examination of the association between overall scores for occupational stressors, PPTEs, and prevalence of mental health disorders. We expected statistically significant positive correlations between measures of occupational stress and positive screens for a mental health disorder. We expected the variance accounted for by occupational stressors other than PPTE would be greater than the variance accounted for by PPTE. We also expected more positive screens for mental health disorders among CWs who participated ‘during COVID-19’.

Method

Participants

This study obtained ethics approval from the Research Ethics Boards at the University of Regina (file #2017–098) and Memorial University of Newfoundland (file #20201330-EX) and followed ethical guidelines for research involving human participants. Data were collected from the Canadian Provincial and Territorial Correctional Worker Mental Health and Well-Being Study. The original survey was launched in Ontario (Konyk et al., 2021) with 12 replications from December 2017 to May 2023, collectively creating a national sample. The surveys were deployed using Qualtrics across every provincial and territorial correctional system in Canada, included the same core of self-report mental health measures, and were then tailored as needed for local context, jargon, and explicit needs expressed by a provincial or territorial representative. Data were collected in Ontario (n = 1084), Manitoba (n = 602), Saskatchewan (n = 605), New Brunswick (n = 27), Nova Scotia (n = 156), Newfoundland and Labrador (n = 69), and the Yukon (n = 47) before the onset of COVID-19 pandemic. Data collection stopped with the onset of the COVID-19 pandemic and restarted 18 months later in Alberta (n = 395), British Columbia (n = 422), Quebec (n = 241), Northwest Territories (n = 18), Nunavut (n = 11), and Prince Edward Island (n = 63).

Participants were recruited using the email listservs of the Ministry or Department that oversees correctional services in the province or territory or through their union listserv. Given the listservs overlap, we cannot definitively determine the response rate or sampling frame. Recruitment involved the service and/or union distributing an invitation for survey participation that included information about the study with a link to the informed consent documents which, once read, linked to the survey itself. Further creating ambiguity about the sampling frame, the solicitation email could be forwarded to other email addresses.

Only participants who proceeded far enough into the survey to complete the mental health disorders sections were included in analyses. Specifically, in total, 5,212 respondents logged into the survey; however, only 3,740 (71.9%) respondents completed the sections of the survey required for the current analyses. Participants could start and pause the survey, rather than answer all questions in one sitting. Thus, the reduced response rate as the survey progressed was likely due to length and fatigue. There were some statistically significant differences in sociodemographic covariates and occupational categories noted between included or excluded participants from the current analyses (see supplementary online Table S1). In short, participants who were female, younger, lower income, with 4‒9 years of service, working in community operations or as program officers, or from British Columbia or the Northwest Territories were more likely to be excluded from the final analytic sample. Sociodemographic characteristics of the sample by province/territory have been published elsewhere (Ricciardelli et al., 2024).

Participants were categorized by region and occupation: Administrative Headquarters (e.g., people working at the regional headquarters); Institutional Management/Administration (e.g., managers, superintendents, administrative supports in prisons); Institutional Operational (e.g., program officers, healthcare providers, instructors); COs; Youth CWs (e.g., community or institutional CWs working with youth who are criminalized); Community Operational (e.g., probation officers, caseworkers); Community Administration (e.g., administrative supports in community correctional spaces).

Measures

Occupational stressors. We assessed occupational stressors using the 20-item Organizational Police Stress Questionnaire (PSQ-Org) and the 20-item Operational Police Stress Questionnaire (PSQ-Op; McCreary & Thompson, 2006). Although the PSQ-Org and the PSQ-Op were developed to assess occupational stress in policing, items are not specific to the police environment and these measures have been used to assess occupational stress in other public safety groups, including CWs (e.g., Carleton et al., 2020; Konyk et al., 2021). The PSQ-Org measures stressors related to fulfilling occupational responsibilities (e.g., interpersonal relationships with colleagues, understaffing, abundance of administrative responsibilities). The PSQ-Op measures organizational (including cultural) stressors related to how the occupational role is enacted, including the collateral effects of the work on social and family living (e.g., fatigue, being on shift, relationships outside of the workplace). The literature has established how the PSQ-Op can be useful to identify the sources of stress among CWs because CWs, like police officers, face occupational stressors with negative implications for their health and well-being, including workplace safety concerns (Laureano-Morales et al., 2024). The complete list of items is presented in Table 1. We assessed each item using a 7-point ordinal scale ranging from 1 = no stress at all to 7 = a lot of stress. We computed the average item scores for each of the PSQ-Org and PSQ-Op. Cronbach's alpha was .936 for the PSQ-Org and .940 the PSQ-Op.

Table 1.

Associations Between Data Collection Period (Pre-COVID vs. During-COVID) and Type of Occupational Stressors.

Occupational Stressor	Pre-COVID Provinces/Territories% (n)	During-COVID Provinces/ Territories% (n)	OR (95% CI)^a
Organizational stressors
Dealing with co-workers	93.3 (2036)	87.6 (823)	0.51 (0.39, 0.66)***
The feeling that different rules apply to different people (e.g., favoritism)	90.3 (1972)	83.5 (786)	0.55 (0.44, 0.68)***
Feeling like you always have to prove yourself to the organization	85.0 (1858)	81.8 (771)	0.79 (0.65, 0.97)*
Excessive administrative duties	76.7 (1675)	79.6 (749)	1.19 (0.99, 1.43)
Constant change in policy/legislation	88.0 (1921)	83.6 (787)	0.70 (0.56, 0.87)**
Staff shortages	87.8 (1918)	86.2 (811)	0.87 (0.69, 1.09)
Bureaucratic red tape	85.7 (1865)	82.7 (777)	0.80 (0.65, 0.98)*
Too much computer work	70.0 (1527)	70.4 (662)	1.02 (0.86, 1.20)
Lack of training on new equipment	71.9 (1567)	70.7 (666)	0.94 (0.80, 1.12)
Perceived pressure to volunteer free time	40.9 (894)	43.6 (411)	1.12 (0.96, 1.30)
Dealing with supervisors	81.9 (1788)	73.0 (687)	0.60 (0.50, 0.71)***
Inconsistent leadership style	87.0 (1900)	80.4 (756)	0.61 (0.50, 0.75)***
Lack of resources	87.2 (1899)	81.6 (766)	0.65 (0.53, 0.80)***
Unequal sharing of work responsibilities	85.0 (1850)	77.3 (727)	0.60 (0.50, 0.73)***
If you are sick or injured your co-workers seem to look down on you	58.5 (1277)	51.9 (488)	0.76 (0.66, 0.89)**
Leaders over-emphasize the negatives (e.g., supervisor evaluations, public complaints)	76.1 (1658)	66.8 (627)	0.63 (0.54, 0.75)***
Internal investigations	62.7 (1364)	51.9 (487)	0.64 (0.55, 0.75)***
Dealing with the court system	55.9 (1219)	61.0 (574)	1.24 (1.06, 1.44)**
The need to be accountable for doing your job	77.9 (1701)	72.1 (678)	0.73 (0.61, 0.87)***
Inadequate equipment	73.9 (1614)	65.7 (618)	0.68 (0.57, 0.80)***
Operational stressors
Shift work	58.5 (1305)	40.9 (384)	0.49 (0.42, 0.57)***
Working alone at night	33.7 (752)	27.2 (255)	0.73 (0.62, 0.87)***
Over-time demands	45.7 (1021)	42.9 (403)	0.89 (0.77, 1.04)
Risk of being injured on the job	76.0 (1699)	62.4 (586)	0.53 (0.45, 0.62)***
Work-related activities on days off (e.g., court, community events)	37.6 (840)	36.6 (343)	0.96 (0.82, 1.12)
Potentially psychologically traumatic events (e.g., motor vehicle accidents, domestics, death, injury)	55.8 (1245)	53.3 (500)	0.90 (0.78, 1.05)
Managing your social life outside of work	72.1 (1607)	63.2 (593)	0.66 (0.57, 0.78)***
Not enough time available to spend with friends and family	76.3 (1703)	66.4 (624)	0.61 (0.52, 0.73)***
Paperwork	74.3 (1660)	70.2 (661)	0.82 (0.69, 0.97)*
Eating healthy at work	80.9 (1806)	68.0 (639)	0.50 (0.42, 0.60)***
Finding time to stay in good physical condition	86.7 (1935)	79.0 (743)	0.58 (0.47, 0.70)***
Fatigue (e.g., shift work, over-time)	100 (2232)	100 (939)	—
Occupation-related health issues (e.g., back pain)	78.9 (1760)	74.7 (701)	0.79 (0.66, 0.94)**
Lack of understanding from family and friends about your work	75.3 (1682)	63.6 (597)	0.57 (0.49, 0.67)***
Making friends outside the job	62.9 (1402)	56.3 (528)	0.76 (0.65, 0.89)**
Upholding a “higher image” in public	59.6 (1328)	53.7 (504)	0.79 (0.68, 0.92)**
Negative comments from the public	67.7 (1509)	58.7 (551)	0.68 (0.58, 0.79)***
Limitations to your social life (e.g., who your friends are, where you socialize)	67.9 (1513)	58.8 (552)	0.67 (0.58, 0.79)***
Feeling like you are always on the job	70.1 (1563)	60.9 (572)	0.66 (0.57, 0.78)***
Friends/family feel the effects of the stigma associated with your job	67.4 (1504)	53.5 (503)	0.56 (0.48, 0.65)***

Note. OR = odds ratio; CI = confidence interval. Pre-COVID provinces/territories include Ontario, Manitoba, New Brunswick, Newfoundland and Labrador, Yukon, Saskatchewan, and Nova Scotia. During-COVID provinces/territories include Prince Edward Island, Alberta, British Columbia, Quebec, Northwest Territories, and Nunavut.

Pre-COVID provinces are the reference category with an odd of 1.00.

*p < .05; **p < .01; ***p < .001.

Mental health disorder symptoms. We used multiple validated self-report screening measures to determine mental health disorder symptoms. PTSD symptoms were assessed using the Life Events Checklist for the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (LEC-5; Blevins et al., 2015; Weathers et al., 2013) and the PCL-5 (Weathers et al., 2013). Participants chose an index PPTE (i.e., their worst single PPTE, the PPTE that was most distressing, or the PPTE currently resulting in the most distress) to anchor their past-month symptom ratings on the PCL-5 items. A positive screen on the PCL-5 required participants to endorse each PTSD cluster and have a total score >32 (Weathers et al., 2013). We assessed MDD symptoms using the nine-item Patient Health Questionnaire (PHQ-9), which uses a past 14-day timeframe (Kroenke et al., 2001, 2010; Löwe et al., 2004). Participants screened positive for MDD if their PHQ-9 total score was > 9 (Manea et al., 2015). We assessed GAD symptoms using the seven-item GAD scale (GAD-7) based on a prior 14-day period (Beard & Björgvinsson, 2014; Kroenke et al., 2010; Spitzer et al., 2006). Participants screened positive for GAD if their GAD-7 total score was > 9 (Swinson, 2006). We assessed PD symptoms using the seven-item Panic Disorder Symptoms Severity scale (PDSS) based on a prior 7-day period (Furukawa et al., 2009; Shear et al., 1997, 2001). Participants screened positive for PD if their PDSS total score was > 7 (Shear et al., 1997). We assessed AUD symptoms using the Alcohol Use Disorders Identification Test (AUDIT) based on a prior 12-month period (Gache et al., 2005; Saunders et al., 1993). Participants screened positive screen for AUD if their AUDIT total score was > 15 (Gache et al., 2005). We also asked participants to self-report having ever been diagnosed with any other mental health disorders including social anxiety disorder, obsessive-compulsive disorder, persistent depressive disorder, bipolar I, bipolar II, and cyclothymic disorder. Self-reported diagnosed disorders were only included in the dichotomous ‘any positive mental disorder screen’ variable due to the relatively infrequent reporting of these disorders. Any positive mental health disorder screen was computed as positive (i.e., ‘yes’) if the participant screened positive on one or more of the screening tools and/or self-reported a mental health disorder diagnosis.

Total number of types of PPTE exposures. The LEC-5 (Blevins et al., 2015; Weathers et al., 2013) was used to measure the lifetime exposure of participants to 16 PPTEs (e.g., life-threatening natural disaster; fire or explosion; serious transportation accident). We computed the total number of types of PPTE exposures by adding exposures across the 16 items. Participant responses were coded as having a specific PPTE exposure when a participant reported the exposure: (a) it happened to them personally; (b) they witnessed it happen to someone else; (c) they learned about it happening to a close family member or close friend; and/or (d) they were exposed to it as part of their jobs as first responders. We allowed up to two missing values in the calculation of the total number of types of PPTE exposures variable, likely resulting in a slightly more conservative estimate of the total prevalence of exposure to PPTEs in the sample. The mean number of types of PPTE exposures was 9.89 (SD = 4.28) in the sample.

Sociodemographic covariates. We report the sociodemographic covariates of sex (male or female), age (i.e., 19‒29 years, 30‒39 years, 40‒49 years, 50‒59 years, or 60 years and older), marital status (i.e., married/common-law, remarried, separated/divorced/widowed, or single), education (i.e., high school or less, some postsecondary less than 4-year college/university program, or university degree/4-year college or higher), total years of service (i.e., less than 4 years, 4‒9 years, 10‒15 years, or more than 15 years), and occupational category (i.e., institutional operational, institutional management/administrative, community operational, community administrative, CO, headquarters administrative, youth correctional services).

Procedure

Statistical analyses. First, we calculated mean scores for the two occupational stress measures (i.e., organizational and operational), as well as for each individual item within those scales. We then used Bonferroni post-hoc tests following a one-way ANOVA to assess differences across various province/territory and occupational groups, both for the overall scale scores and for the individual items. Second, logistic regression models were estimated to assess differences in the types of occupational stressors between regions where data collection occurred before versus after the onset of COVID-19.

Third, multivariate logistic regression models were estimated to test the associations between both the overall organizational and operational scores, as well as each of the individual occupational stressors, and a positive screen for each specific type of mental health disorder and the any positive mental health disorder screen variable. The multivariate logistic regression analyses adjusted for sociodemographic covariates (i.e., sex, age, marital status, education, total years of service, occupational group, and provinces), and the total number of types of PPTE exposures.

Fourth, a series of nested multivariate logistic regression models were computed to investigate the independent and combined effects of mean organizational and operational stress scores, along with the total number of types of PPTE exposures, on each type of positive mental health disorder screen and any positive mental health disorder screen. The nested multivariate logistic regression models calculated adjusted odds ratios (AORs) to explore the relationships between positive screens for each assessed disorder and the total number of types of PPTE exposures (model 1), the mean organizational stress score (model 2), and the mean operational stress score (model 3). Models 1, 2, and 3 serve as baseline evaluations of the individual effects between each of the three predictors, analyzed separately for each criterion. Model 4 serves as the main analysis, identifying the unique associations for each predictor while controlling for the other two predictors, also separately for each criterion. Models 4 and 5 further explore the statistical interaction between PPTE and each occupational stress measure, separately for each criterion.

Results

Across the entire sample, the mean for organizational stress scale items was 3.64 (SD =1.35). The highest mean levels of stress associated with specific organizational stressors were the feeling that different rules apply to different people (4.51), staff shortages (4.50), inconsistent leadership style (4.50), bureaucratic red tape (4.33), constant change in policy/legislation (4.28), lack of resources (4.22), and dealing with co-workers (4.21). There were many statistically significant differences on individual items across the provinces/territories (see Supplementary Online Table S2 for detailed information on provincial/territorial differences). For example, Prince Edward Island and Nunavut tended to report the lowest mean organizational stress scores, while New Brunswick and Ontario tended to report the highest mean organizational stress scores (see Supplementary Online Table S2).

Across the entire sample, the mean for operational stress items was 3.09 (SD = 1.31). The mean for the operational stressor scale items (mean score 3.09) was statistically significantly lower (t = 27.58, p < .01, r² = .43) than the mean for the organizational stress scale items (mean score 3.64). Across the entire sample, the operational stressors associated with the highest mean levels of stress were fatigue (5.42), finding time to stay in good physical condition (4.05), occupation-related health issues (3.66), eating healthy at work (3.56), not enough time available to spend with friends and family (3.51), and lack of understanding from family and friends about your work (3.38). Again, several significant differences on individual items were noted across provinces/territories (see Supplementary Online Table S2). Overall, across operational stressors, Nunavut, Prince Edward Island, and Alberta tended to report the lowest mean stress scores across operational stressors, whereas New Brunswick, Manitoba, and Ontario tended to report the highest mean stress scores across operational stressors (see Supplementary Online Table S2).

The mean stress levels associated with the organizational and operational stressors, across occupational group as a function of overall averages and on an item basis, are provided in the Supplementary Online Table S3. There were many statistically significant differences across occupational groups as a function of each item for both organizational and operational stressors. Overall, participants working in Headquarters Administration tended to report the lowest mean scores, whereas COs tended to report the highest mean scores (see Supplementary Online Table S3 for detailed comparisons across occupational categories).

Table 1 presents results from comparing organizational and operational stress scores from data collected before the COVID-19 pandemic to data collected during/after the COVID-19 pandemic. There were statistically significant differences in the prevalence of many types of organizational and operational stressors in provincial/regional data before and during/after the COVID-19 pandemic. CWs who participated in the survey before the onset of the COVID-19 pandemic tended to report a lower prevalence of specific types of organizational (significantly lower odds found for 14 of the 20 organizational stressors assessed) and operational (significantly lower odds found for 16 of the 20 organizational stressors assessed) stressors than CWs who participated in the survey after the onset of the COVID-19 pandemic (see Table 1). Dealing with the court system was the only type of occupational stressor where a significantly higher prevalence was reported by CWs who participated in the survey before the onset of the COVID-19 pandemic compared to CWs who participated in the survey after the onset of the COVID-19 pandemic (55.9% vs. 61.0%, odds ratio = 1.24, 95% confidence interval [CI] = 1.06, 1.44, p < .01). Nonparametric tests were also conducted to examine these comparisons, but since they yielded similar results to the parametric tests mentioned above, we refrain from presenting their results here.

Table 2 shows the relationships between organizational and operational stress scores, by the overall subscale score and by individual items, and each type of positive mental health disorder screen, as well as with any positive mental health disorder screen. The results are presented as odds ratios after adjustment for sociodemographic covariates, the total number of types of PPTE exposures, occupational group, and provinces (except for AUD and PD, in which province is removed from their covariates). The overall mean scale scores for organizational (AOR ranged from 1.30 to 2.02) and operational (AOR ranged from 1.46 to 2.78) stress were both associated with increased odds of positive screens for each disorder. Each individual organizational and operational stressor was associated with increased odds of positive screens for PTSD (AORs ranged from 1.18 to 1.68), MDD (AORs ranged from 1.22 to 1.80), GAD (AORs ranged from 1.17 to 1.85), PD (AORs ranged from 1.17 to 1.74), and any mental health disorder (AORs ranged from 1.23 to 1.89). There were 31 of 40 organizational and operational stressors (significant AORs ranged from 1.09 to 1.34) associated with increased odds of a positive screen for AUD. Among all the stressors, the largest AOR was related to managing your social life outside of work and the smallest AOR was related to internal investigations (except for PD).

Table 2.

Relationship Between Occupational Stressors and Positive Mental Disorder.

Occupational Stressor	PTSDAOR (95% CI)	MDDAOR (95% CI)	Generalized AnxietyAOR (95% CI)	Panic DisorderAOR (95% CI)	Alcohol Use DisorderAOR (95% CI)	Any Mental DisorderAOR (95% CI)
Organizational stressors
Mean organizational stress score	1.91*** (1.77, 2.07)	1.91*** (1.78, 2.05)	1.79*** (1.66, 1.93)	1.78*** (1.63, 1.94)	1.30*** (1.13, 1.50)	2.02*** (1.87, 2.18)
Dealing with co-workers	1.32*** (1.25, 1.39)	1.35*** (1.29, 1.42)	1.38 *** (1.31, 1.45)	1.32 *** (1.25, 1.40)	1.24*** (1.12, 1.37)	1.40*** (1.33, 1.47)
The feeling that different rules apply to different people (e.g., favoritism)	1.35*** (1.29, 1.42)	1.39*** (1.33, 1.45)	1.31*** (1.25, 1.38)	1.33*** (1.26, 1.41)	1.13** (1.03, 1.25)	1.39*** (1.33, 1.45)
Feeling like you always have to prove yourself to the organization	1.36*** (1.30, 1.43)	1.40*** (1.34, 1.46)	1.39*** (1.33, 1.45)	1.38*** (1.31, 1.46)	1.09 (1.00, 1.18)	1.46*** (1.39, 1.52)
Excessive administrative duties	1.26*** (1.21, 1.32)	1.28*** (1.23, 1.34)	1.23*** (1.18, 1.28)	1.22*** (1.16, 1.28)	1.12* (1.03, 1.22)	1.30*** (1.25, 1.36)
Constant change in policy/legislation	1.31*** (1.25, 1.38)	1.30*** (1.24, 1.35)	1.26*** (1.20, 1.32)	1.27*** (1.21, 1.35)	1.14** (1.04, 1.25)	1.35*** (1.29, 1.42)
Staff shortages	1.29*** (1.23, 1.35)	1.29*** (1.24, 1.35)	1.27*** (1.21, 1.33)	1.22*** (1.15, 1.28)	1.05 (0.96, 1.15)	1.30*** (1.25, 1.36)
Bureaucratic red tape	1.33*** (1.26, 1.39)	1.28*** (1.22, 1.33)	1.29*** (1.23, 1.35)	1.26*** (1.20, 1.33)	1.12* (1.03, 1.23)	1.34*** (1.28, 1.40)
Too much computer work	1.18*** (1.13, 1.24)	1.23*** (1.18, 1.28)	1.19*** (1.14, 1.25)	1.17*** (1.11, 1.23)	1.08 (0.99, 1.19)	1.24*** (1.18, 1.30)
Lack of training on new equipment	1.28*** (1.22, 1.34)	1.28*** (1.23, 1.34)	1.26*** (1.20, 1.32)	1.24*** (1.17, 1.30)	1.09 (1.00, 1.19)	1.34*** (1.28, 1.40)
Perceived pressure to volunteer free time	1.30*** (1.23, 1.36)	1.30*** (1.24, 1.37)	1.25*** (1.19, 1.31)	1.28*** (1.21, 1.35)	1.08 (0.98, 1.19)	1.36*** (1.29, 1.44)
Dealing with supervisors	1.35*** (1.29, 1.41)	1.36*** (1.30, 1.41)	1.30*** (1.24, 1.36)	1.33*** (1.27, 1.40)	1.15** (1.06, 1.26)	1.38*** (1.32, 1.44)
Inconsistent leadership style	1.31*** (1.25, 1.38)	1.33*** (1.27, 1.38)	1.24*** (1.19, 1.30)	1.28*** (1.21, 1.35)	1.17** (1.07, 1.29)	1.32*** (1.27, 1.38)
Lack of resources	1.34*** (1.28, 1.41)	1.33*** (1.27, 1.39)	1.29*** (1.24, 1.35)	1.25*** (1.19, 1.32)	1.07 (0.98, 1.17)	1.36*** (1.30, 1.42)
Unequal sharing of work responsibilities	1.29*** (1.24, 1.35)	1.29*** (1.24, 1.35)	1.25*** (1.20, 1.30)	1.23*** (1.17, 1.29)	1.14** (1.04, 1.24)	1.31*** (1.25, 1.36)
If you are sick or injured your co-workers seem to look down on you	1.31*** (1.26, 1.36)	1.33*** (1.28, 1.39)	1.32*** (1.26, 1.37)	1.35*** (1.29, 1.41)	1.16*** (1.07, 1.25)	1.40*** (1.33, 1.46)
Leaders over-emphasize the negatives (e.g., supervisor evaluations, public complaints)	1.30*** (1.25, 1.35)	1.32*** (1.27, 1.37)	1.28*** (1.23, 1.33)	1.25*** (1.19, 1.31)	1.12** (1.03, 1.21)	1.36*** (1.31, 1.42)
Internal investigations	1.26*** (1.21, 1.31)	1.22*** (1.17, 1.26)	1.17*** (1.12, 1.22)	1.22*** (1.16, 1.27)	1.14** (1.05, 1.23)	1.23*** (1.18, 1.28)
Dealing with the court system	1.26*** (1.19, 1.32)	1.28*** (1.22, 1.34)	1.25*** (1.18, 1.31)	1.27*** (1.20, 1.34)	1.10 (1.00, 1.21)	1.28*** (1.21, 1.35)
The need to be accountable for doing your job	1.26*** (1.21, 1.32)	1.26*** ()1.21, 1.31	1.25*** (1.20, 1.31)	1.20*** (1.15, 1.27)	1.09* (1.00, 1.19)	1.27*** (1.22, 1.33)
Inadequate equipment	1.28*** (1.22, 1.34)	1.26*** (1.20, 1.31)	1.22*** (1.16, 1.27)	1.20*** (1.15, 1.26)	1.06 (0.97, 1.16)	1.29*** (1.23, 1.35)
Operational stressors
Mean operational stress score	2.59*** (2.37, 2.83)	2.58*** (2.37, 2.81)	2.49*** (2.28, 2.71)	2.22*** (2.03, 2.43)	1.46*** (1.27, 1.67)	2.78*** (2.53, 3.06)
Shift work	1.30*** (1.24, 1.36)	1.27*** (1.21, 1.33)	1.28*** (1.22, 1.34)	1.23*** (1.17, 1.29)	1.18*** (1.08, 1.29)	1.32*** (1.26, 1.38)
Working alone at night	1.28*** (1.22, 1.34)	1.24*** (1.18, 1.30)	1.24*** (1.18, 1.30)	1.20*** (1.14, 1.26)	1.12* (1.02, 1.22)	1.28*** (1.21, 1.35)
Over-time demands	1.33*** (1.27, 1.39)	1.30*** (1.24, 1.36)	1.29*** (1.23, 1.35)	1.20*** (1.15, 1.26)	1.08 (0.99, 1.17)	1.34*** (1.27, 1.41)
Risk of being injured on the job	1.49*** (1.42, 1.57)	1.41*** (1.35, 1.48)	1.43*** (1.36, 1.51)	1.43*** (1.35, 1.51)	1.16** (1.06, 1.28)	1.45*** (1.38, 1.53)
Work-related activities on days off (e.g., court, community events)	1.45*** (1.37, 1.54)	1.37*** (1.30, 1.45)	1.34*** (1.27, 1.42)	1.34*** (1.27, 1.42)	1.14* (1.03, 1.26)	1.38*** (1.30, 1.48)
Potentially psychologically traumatic events (e.g., motor vehicle accidents, domestics, death, injury)	1.49*** (1.42, 1.56)	1.37*** (1.31, 1.44)	1.42*** (1.36, 1.49)	1.46*** (1.39, 1.53)	1.19*** (1.09, 1.29)	1.46*** (1.38, 1.54)
Managing your social life outside of work	1.68*** (1.59, 1.78)	1.80*** (1.71, 1.90)	1.85*** (1.75, 1.96)	1.74*** (1.64, 1.84)	1.34*** (1.22, 1.47)	1.89*** (1.78, 2.01)
Not enough time available to spend with friends and family	1.48*** (1.41, 1.55)	1.53*** (1.46, 1.60)	1.55*** (1.48, 1.63)	1.43*** (1.36, 1.51)	1.21*** (1.11, 1.32)	1.57*** (1.50, 1.65)
Paperwork	1.33*** (1.27, 1.40)	1.32*** (1.27, 1.38)	1.33*** (1.27, 1.40)	1.25*** (1.19, 1.32)	1.14** (1.04, 1.25)	1.31*** (1.25, 1.37)
Eating healthy at work	1.35*** (1.29, 1.41)	1.45*** (1.39, 1.51)	1.35*** (1.29, 1.41)	1.35*** (1.28, 1.42)	1.15** (1.05, 1.25)	1.41*** (1.35, 1.48)
Finding time to stay in good physical condition	1.36*** (1.30, 1.43)	1.54*** (1.47, 1.62)	1.43*** (1.36, 1.50)	1.38*** (1.31, 1.46)	1.18** (1.07, 1.29)	1.47*** (1.40, 1.54)
Fatigue (e.g., shift work, over-time)	1.62*** (1.51, 1.74)	1.78*** (1.67, 1.90)	1.66*** (1.55, 1.78)	1.51*** (1.40, 1.63)	1.25** (1.09, 1.43)	1.68*** (1.58, 1.78)
Occupation-related health issues (e.g., back pain)	1.45*** (1.38, 1.52)	1.48*** (1.42, 1.55)	1.51*** (1.44, 1.59)	1.49*** (1.41, 1.57)	1.16** (1.06, 1.26)	1.54*** (1.47, 1.62)
Lack of understanding from family and friends about your work	1.49*** (1.42, 1.57)	1.49*** (1.43, 1.56)	1.48*** (1.42, 1.55)	1.40*** (1.33, 1.47)	1.20*** (1.10, 1.31)	1.53*** (1.46, 1.61)
Making friends outside the job	1.50*** (1.43, 1.57)	1.55*** (1.49, 1.62)	1.51*** (1.44, 1.57)	1.43*** (1.36, 1.50)	1.20*** (1.10, 1.30)	1.60*** (1.52, 1.68)
Upholding a “higher image” in public	1.44*** (1.37, 1.50)	1.39*** (1.33, 1.45)	1.34*** (1.29, 1.40)	1.36*** (1.30, 1.43)	1.16*** (1.07, 1.26)	1.46*** (1.39, 1.54)
Negative comments from the public	1.38*** (1.32, 1.44)	1.34*** (1.29, 1.40)	1.31*** (1.25, 1.36)	1.30*** (1.24, 1.37)	1.13** (1.04, 1.23)	1.35*** (1.29, 1.42)
Limitations to your social life (e.g., who your friends are, where you socialize)	1.49*** (1.42, 1.56)	1.47*** (1.40, 1.53)	1.44*** (1.37, 1.50)	1.42*** (1.35, 1.49)	1.29*** (1.18, 1.40)	1.52*** (1.45, 1.60)
Feeling like you are always on the job	1.51*** (1.45, 1.58)	1.44*** (1.38, 1.50)	1.46*** (1.40, 1.53)	1.41*** (1.35, 1.49)	1.21*** (1.11, 1.31)	1.48*** (1.41, 1.55)
Friends/family feel the effects of the stigma associated with your job	1.59*** (1.51, 1.67)	1.54*** (1.47, 1.61)	1.55*** (1.48, 1.63)	1.46*** (1.39, 1.54)	1.26*** (1.16, 1.38)	1.62*** (1.53, 1.71)

Notes. PTSD = post-traumatic stress disorder; AOR = odds ratio adjusted for sex, age, marital status, education, total years of service, occupational group, and provinces; MDD = major depressive disorder; AUD = alcohol use disorders. AORs related to AUD and panic disorder are without provinces as covariate.

*p < .05; **p < .01; ***p < .001.

Table 3 presents the independent and interactive effects of mean organizational and operational stress total scores on positive mental health screens. The results provide baseline estimates of the associations between positive screens for each of the assessed mental health disorders, each of the total number of types of PPTE exposures (Model 1), the mean organizational stress score (Model 2), and the mean operational stress score (Model 3). Except for the relationship between the total number of PPTE types and positive screens for AUD, the total number of PPTE types (AORs ranged from 1.08 to 1.13), the mean organizational stress (AORs ranged from 1.31 to 2.02), and the mean operational stress (AORs ranged from 1.49 to 2.80) scores were all associated with positive screens for each mental health disorder category and for the category containing any mental health disorder when entered into the models independently (i.e., Models 1, 2, and 3).

Table 3.

Relationship Between the Total Number of Types of PPTE Exposures, Occupational Stressors, and Any Positive Mental Disorder.

Mental Disorder	PTSDAOR (95% CI)	MDDAOR (95% CI)	Generalized AnxietyAOR (95% CI)	Panic DisorderAOR (95% CI)	Alcohol Use DisorderAOR (95% CI)	Any Mental DisorderAOR (95% CI)
Model 1
Total number of types of PPTE exposures	1.13*** (1.10, 1.16)	1.08*** (1.06, 1.11)	1.08*** (1.05, 1.10)	1.11*** (1.08, 1.14)	1.01 (0.96, 1.06)	1.08*** (1.06, 1.11)
Model 2
Mean organizational stress score	1.91*** (1.76, 2.07)	1.93*** (1.79, 2.07)	1.81*** (1.67, 1.96)	1.78*** (1.63, 1.94)	1.31*** (1.14, 1.52)	2.02*** (1.87, 2.19)
Model 3
Mean operational stress score	2.55*** (2.32, 2.80)	2.66*** (2.43, 2.90)	2.56*** (2.34, 2.81)	2.27*** (2.06, 2.49)	1.49*** (1.29, 1.72)	2.80*** (2.54, 3.08)
Model 4
Total number of types of PPTE exposures	1.07*** (1.03, 1.10)	1.01 (0.99, 1.04)	1.01 (0.98, 1.04)	1.05** (1.02, 1.08)	0.97 (0.93, 1.02)	1.02 (0.99, 1.04)
Mean organizational stress score	1.18** (1.06, 1.32)	1.25*** (1.13, 1.38)	1.12* (1.01, 1.25)	1.18** (1.05, 1.33)	0.98 (0.79, 1.21)	1.29*** (1.16, 1.43)
Mean operational stress score	2.20*** (1.95, 2.48)	2.28*** (2.04, 2.55)	2.38*** (2.11, 2.69)	2.01*** (1.78,2.28)	1.60*** (1.30,1.98)	2.28*** (2.02, 2.58)
Model 5
Total number of types of PPTE exposures by organizational stress interaction term	1.00 (0.98, 1.02)	1.02 (1.00, 1.04)	1.01 (0.99, 1.03)	1.01 (0.99, 1.03)	0.99 (0.96, 1.03)	1.02* (1.00, 1.05)
Model 6
Total number of types of PPTE exposures by operational stress interaction term	0.99 (0.97, 1.02)	1.01 (0.99, 1.03)	1.01 (0.99, 1.04)	1.01 (0.99, 1.03)	0.99 (0.95, 1.02)	1.03* (1.00, 1.05)

Notes. AOR = odds ratio adjusted for sociodemographic covariates (sex, age, marital status, education, total years of service, occupational group, and provinces. AORs related to AUD and Panic Disorder are without provinces as covariate); PTSD = post-traumatic stress disorder; MDD = major depressive disorder; AUD = alcohol use disorders; PPTEs = potentially psychologically traumatic events. Model 1: The total number of types of potentially psychologically traumatic event exposures entered and adjusted for covariates. Model 2: The mean organizational stress score entered and adjusted for covariates. Model 3: The mean operational stress score entered and adjusted for covariates. Model 4: The total number of types of potentially psychologically traumatic event exposures, the mean organizational stress score, and the mean operational stress score entered the same model simultaneously and adjusted for covariates. Model 5: Model 4 with the main effects of the total number of types of potentially psychologically traumatic event exposures, the mean organizational stress score, and the interaction term for the total number of types of potentially psychologically traumatic event exposures × the mean organizational stress score and adjusted for covariates and the mean operational stress score. Model 6: Model 4 with the main effects of the total number of types of potentially psychologically traumatic event exposures and the mean operational stress score and the interaction term for the total number of types of potentially psychologically traumatic event exposures × the mean operational stress score and adjusted for covariates and the mean organizational stress score.

*p < .05; **p < .01; ***p < .001.

Model 4 was used to assess associations between PPTEs, organizational stressors, operational stressors (i.e., independent variables), and mental health (i.e., dependent variables), with each individual analysis controlling for sociodemographic factors. By entering the total number of PPTE types and mean organizational and operational stress scores simultaneously in logistic regression models (i.e., Model 4), the total number of PPTE types, the mean organizational stress scores, and the mean operational stress scores remained independently associated with increased odds of positive screens for PTSD (AORs were 1.07, 1.18, and 2.20, respectively) and PD (AORs were 1.05, 1.18, and 2.01, respectively). In addition, mean organizational and mean operational stress scores were also independently associated with positive screens for MDD (AORs = 1.25 and 2.28, respectively), GAD (AORs = 1.12 and 2.38, respectively), and any mental health disorder (AORs = 1.29 and 2.28, respectively). The mean operational stress score was also statistically significantly associated with increased odds of a positive AUD screen (AOR = 1.60).

Models 5 and 6 examined whether occupational stress and the number of PPTEs interacted to influence the associations with the mental health variables. Except for any mental health disorder, neither of the total number of PPTE types by mean organizational or operational stress score interaction terms were statistically significant.

Discussion

There were several substantial differences in organizational and operational stress scores among services in the provinces and territories; however, on average, participating CWs described organizational stressors as more stressful than operational. The results appear consistent with recent qualitative and quantitative scholarship on CW mental health and wellness (Cassiano & Ricciardelli, 2023; Konyk et al., 2021; Ricciardelli et al., 2024). More specifically, Konyk et al. (2021) initially found in Ontario, Canada that the organizational stressors most strongly associated with mental health challenges for CWs were staff shortages, bureaucratic red tape, feeling that different rules apply to different people, lack of resources, constant changes in policy and legislation, and dealing with co-workers. In the current national study, across provincial and territorial jurisdictions, stressors such as fatigue, finding time to stay in good physical condition, occupation-related health issues, eating healthily at work, not enough time available to spend with friends and family, and lack of understanding from family and friends about your work were associated with the highest average stress scores. Thus, the current results continue to evidence multifactorial associations between occupational stressors and CW mental health (Konyk et al., 2021). We also emphasize jurisdictional variability, further shaped by pre- and post-COVID-19, as CWs from Nunavut and Prince Edward Island tended to report the lowest organizational and operational stress scores, compared to New Brunswick and Ontario, which tended to report the highest mean scores organizational and operational stress scores; as such, potential remedies and responses to mental health and wellness needs must take into account the different governance, cultural, and operational realities of each correctional service. We emphasize how provincial and territorial systems in Canada are marked by jurisdictional variability and differences, and yet we found similar challenges across correctional services which indicates a need to do better to alleviate current stresses among CWs and discover more tangibly what organizational responses are working and what are not.

On that note, CWs in Canada have reported qualitatively how mental health and well-being could be improved and stress reduced in their organizations through systematic changes (Johnston et al., 2022), with a focus on enhancing access to specialized mental health services that are immediately available and comprehensive in nature, as well as improvements to work and schedule structures (i.e., consistent shift rotations, less on-call hours, more job security, more mental health sick leave), improved manager-staff relations, and key changes to the physical prison environment (i.e., access to positive spaces for meditation, exercise, and decompression). While more research is necessary to determine the efficacy of service delivery for CWs, further considerations include strengthening and reviewing Employee and Family Assistance Programs (McKendy et al., 2023) and other operating programs in Canada meant to decrease mental health stigma in correctional services, build coping skills, and develop mental health resiliency and preparedness, such as Road to Mental Readiness (Johnston et al., 2023) and AMStrength (Ricciardelli & Adorjan, 2020). Though understudied among CWs, Foley and Ricciardelli (2023) found peer supports apps (i.e., PeerConnect) have had minimal success in being viewed positively by PSP, primarily for its effectiveness in reducing mental health stigma around peer support use and raising awareness around concerns for mental health and wellness. These ideas are not exhaustive, but demonstrate change is happening within correctional services across Canada, with a need for more scientific inquiry and work to bolster potential solutions, going forward. We put forth however, given the prevalence of organizational stress tied to relationships with colleagues and management, that efforts be made to reduce gossip, increase kindness, and remind all to not make assumptions about others – all factors which are socially possible and would do much to reduce these stressors.

The onset of COVID-19 was associated with statistically significant differences in the prevalence of organizational and operational stressors. With some exceptions (i.e., dealing with the court system), most organizational stressors decreased significantly during/after the pandemic period. We also found this to be the case with operational stressors, which challenges our hypothesis and points to the complexity of how correctional systems were managed during the abrupt changes and disruption the pandemic produced. Explanation of these findings relate to some qualitative studies on CWs and COVID-19, which show that decarceration during COVID-19, in some cases, improved operational capacities within provincial correctional services and thus reduced perceptions and experiences with stress (Johnston et al., 2024). With decarceration, overcrowding was reduced as was, in select jurisdictions, staff shortages, which suggest more staff and less people who are incarcerated would do much to reduce all occupational stressors – areas worthy of future inquiry and considerations for reform.

With the exception of the relationship between the total number of PPTE types and positive screens for AUD, the total number of PPTE types, the mean organizational stress, and the mean operational stress scores were all associated with positive screens for each mental health disorder category and for the category containing any mental health disorder when entered into the models independently. These results further demonstrate that PPTE exposures remain significantly associated with mental health disorders, but occupational stressors account for variance in mental health. Preventing PPTEs in correctional workspaces is impossible and interventions may prove difficult (Konyk et al., 2021) but, nonetheless, PPTE exposures cannot be ignored and must be further understood across both Canadian and international jurisdictions and in connection with the numerous other occupational stressors that necessitate further scholarly and clinical attention.

Limitations

Several factors limit the current study. First, the respondents in the CW sample self-selected, which potentially limits generalizability of the findings. Second, given responses to the survey are anonymous, there is opportunity for limitations associated with missing, erroneous, or biased data. Also, given sample recruitment methods, individuals could have possibly completed the survey more than once, which would violate the independence assumption underlying the statistical methods utilized in this paper. However, no incentives were provided to complete the survey, so the likelihood of duplicate submissions is low. Third, we employed self-report screening measures to assess mental health – not diagnostic tools – thus, we support a future study using clinical interviews that allow for diagnostic assessments for more robust results. Fourth, we also relied on self-report to determine type of PPTE exposures, which relied on participant recall and its attendant limitations. Fifth, we failed to measure the prevalence and effects of family-based stressors or individualized variables, which we encourage future researchers to assess to determine if such factors interact with mental health status. Sixth, we encourage researchers to examine interaction effects between indirect and direct types of PPTE exposures to generate more robust understandings. Seventh, since our data are cross-sectional, we cannot assess with confidence risk and causality. There is a need for longitudinal studies to determine causality. Eight, COVID-19 was an unprecedented challenge, yet the literature shows mixed findings in terms of how these factors affected CWs across the globe (Johnston et al., 2024; Williams et al., 2020). There is a need for future researchers to re-survey pre-COVID jurisdictions to fully determine the impact of COVID on participant mental health and wellness. Finally, although this work comprises a national study with consistent occupational groupings, it is only a starting point—there are further nuances and differences between correctional services in different provinces and territories (and internationally); these nuances must be identified and unpacked in future research to better understand jurisdictional variability in CW mental health outcomes.

Conclusion

In the current study, we build on preliminary CW mental health and wellness literature by examining the relationships between 40 work-related stressors, including PPTE exposures and prevalence of positive screens for several mental health disorders. These findings provide a roadmap for developing and implementing interventions for CWs across jurisdictions and occupational groupings that may help mitigate compromised mental health. In closing, we wish to emphasize the need for more tailored efforts to mitigate PPTE exposure frequency and more research on PPTE types that are most strongly associated with mental health challenges. Correctional organizations providing access to evidence-informed resources after a PPTE exposure, at the discretion of the exposed CW, may help to mitigate mental health injuries and related stress (Ricciardelli et al., 2025). As Ricciardelli et al. (2025) described, greater understanding of the relationship between PPTE exposures and mental health may increase public attention of the problem (and subsequently government resources) and provides further insight into required treatment resources for CWs. While our study finds PPTE exposures will interact with other occupational stressors, future research is needed to (especially qualitatively) unpack how PPTE exposures and stress interact among CWs and often produce trying mental health outcomes.

Supplemental Material

sj-docx-1-icj-10.1177_10575677251356450 - Supplemental material for Occupational Stressors and Mental Health Disorders: A National Study of Correctional Service Providers in Canada's Provincial and Territorial Systems

Supplemental material, sj-docx-1-icj-10.1177_10575677251356450 for Occupational Stressors and Mental Health Disorders: A National Study of Correctional Service Providers in Canada's Provincial and Territorial Systems by R. Ricciardelli, M. S. Johnston, S. Dorniani, T. L. Taillieu, T. O. Afifi and R. N. Carleton in International Criminal Justice Review

Footnotes

Acknowledgments

Special thanks for recruitment support provided by the diverse Correctional Services in each Canadian Province and Territory, as well as their overseeing Ministries or Departments and associated unions.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Tracie O. Afifi's research is supported by a CIHR Foundation Scheme Award and a Tier 1 Canada Research Chair in Childhood Adversity and Resilience. This research was also funded in part by a CIHR Catalyst Grant (FRN: 162545).

Ethics Approval and Consent to Participate

Research ethics boards at the University of Regina (REB #2017–098) and Memorial University of Newfoundland (ICEHR #20201330-EX) approved the data collection for the current study. We complied with Canadian Psychological Association ethical standards in the treatment of our sample. The survey was available for voluntary participation from December 2017 to June 2023. We directed all interested persons to a website with study details and participants were required to explicitly indicate consent before proceeding.

Consent to Publish

There are no details, images, or videos relating to an individual person presented in the current manuscript.

Availability of Data and Materials

The datasets generated and/or analyzed during the current study are not publicly available due to guarantees made in the data collection consent form regarding protections to ensure participant confidentiality.

ORCID iD

M. S. Johnston

Supplemental Material

Supplemental material for this article is available online.

Notes

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