ABSTRACT
Objectives:
to examine the association between burnout and sociodemographic, occupational, and health-related factors among Brazilian Military Police officers.
Methods:
cross-sectional study conducted between November and December 2024 with 1,028 participants. Burnout was assessed using the Burnout Assessment Tool, with descriptive and inferential analyses.
Results:
most participants were men (81.9%) and Brown (pardo) (49.6%); mean age was 41.9 ± 6.5 years. Burnout ranged from moderate to very high in 75.4%. Age, years of service, and physical inactivity were negatively correlated with burnout. Scores were significantly higher among women, White participants, those with a college degree, fixed shifts, physical inactivity, long-term medication use, prior psychological care, and addiction.
Conclusions:
burnout reflects an imbalance between high job demands and limited institutional resources, consistent with the Job Demands-Resources model. Findings underscore the need for interdisciplinary policies, healthy workplaces, and mental health care aligned with SDGs 3 and 8, reinforcing nursing’s strategic role.
Descriptors: Burnout, Occupational Stress, Police, Technology, Health, Occupational Health.
RESUMEN
Objetivos:
analizar la asociación entre burnout y factores sociodemográficos, laborales y de salud en policías militares brasileños.
Métodos:
estudio transversal realizado entre noviembre y diciembre de 2024 con 1.028 participantes. El burnout se evaluó mediante el Burnout Assessment Tool, con análisis descriptivos e inferenciales.
Resultados:
en el 75,4% de los participantes, el burnout osciló entre moderado y muy alto. La edad, los años de servicio y la inactividad física se correlacionaron negativamente con el burnout. Se observaron medias significativamente más altas en mujeres, personas blancas, participantes con educación superior, turno fijo, inactividad física, uso continuado de medicación, antecedentes de atención psicológica y adicción.
Conclusiones:
los hallazgos evidencian un desequilibrio entre demandas laborales y escasez de recursos institucionales, en consonancia con el modelo de demandas y recursos laborales. Urgen políticas interdisciplinarias, entornos saludables y atención a la salud mental, alineadas con los ODS 3 y 8, con protagonismo de la enfermería.
Descriptores: Burnout, Estrés Laboral, Policía, Tecnología para la Salud, Salud Laboral.
INTRODUCTION
Work-related mental disorders are currently among the leading causes of illness among professionals in complex organizational settings, posing major challenges to public health and occupational health and safety in the 21st century(1). Burnout stands out among them and is characterized by exhaustion, mental distance, and impaired cognitive and emotional functioning resulting from chronic exposure to occupational stress(2).
Since its inclusion in the International Classification of Diseases (ICD-11) by the World Health Organization (WHO) in 2022, burnout has been officially recognized as an occupational phenomenon, underscoring the need for institutional strategies focused on workplace mental health surveillance, prevention, and care(3). Despite these conceptual advances, applied studies examining burnout in occupations highly exposed to psychosocial risks, such as public safety, remain scarce.
Brazilian Military Police (Polícia Militar, PM) - a state-level uniformed patrol force responsible for maintaining public order - represents one of the occupational groups most vulnerable to psychosocial strain. PMs are daily exposed to adverse conditions such as irregular work schedules, frequent violence, resource shortages, and organizational tensions, which affect not only individual well-being but also institutional performance and, consequently, public safety(4-6). Illness among PMs also affects social stability, the quality of public services, and public trust in public safety institutions(7).
To understand this scenario, theoretical frameworks are needed that can account for the multiple dimensions of work. In this regard, the Job Demands-Resources (JD-R) model, proposed by Demerouti et al.(8) and later expanded by Bakker and Demerouti(9), is particularly useful. According to this model, burnout arises from an imbalance between job demands (emotional, physical, and cognitive) and the resources available to cope with them (e.g., institutional support, autonomy, and recognition)(10). This approach allows an integrated analysis of the interplay between the individual and organizational factors involved in occupational distress.
Based on this framework, the Burnout Assessment Tool (BAT) was developed as a more comprehensive alternative to the classic Maslach Burnout Inventory (MBI). The BAT organizes burnout into four core dimensions (Exhaustion, Mental Distance, Cognitive Impairment, and Emotional Impairment) and two secondary dimensions (Psychological complaints and Psychosomatic complaints), providing a more integrated understanding of work’s psychosocial effects on individuals(2,11). In addition, by incorporating Mental Distance, Cognitive Impairment, and Emotional Impairment as components of burnout, the BAT reflects a contemporary theoretical framework and addresses the limitations of the MBI(12).
In this study, we used the BAT-33, work-related version, because it is well suited to the occupational context and can assess symptoms linked to job demands and working conditions(2,11). This choice also reflects the need to generate evidence to inform public and institutional policies, recognizing mental health as an inseparable component of occupational health and strengthening prevention, comprehensive care, and recognition of PMs’ work. A key strength of this study is the use of the BAT-33, a more comprehensive and theoretically consistent instrument than the traditional MBI because it encompasses cognitive and emotional dimensions that remain underexplored in the Brazilian literature. By identifying vulnerable groups and factors associated with burnout among Brazilian PMs, this study broadens the scientific debate and makes a novel contribution to the development of evidence-based strategies to address burnout.
OBJECTIVES
To analyze the association between burnout and sociodemographic, occupational, and health related factors among Brazilian Military Police officers.
METHODS
Ethical aspects
The study was conducted in accordance with national and international ethical guidelines and was approved by the Research Ethics Committee of the Federal University of Health Sciences of Porto Alegre (UFCSPA). The study fully complied with Brazilian National Health Council Resolution No. 466/2012(13), which governs research involving human participants. It also followed specific recommendations for online research, as well as the privacy and personal data protection principles outlined in Law No. 13,709/2018 (Brazil’s General Data Protection Law [LGPD])(14).
Study design, period, and setting
This was a cross-sectional study with a quantitative, descriptive, and analytical approach. The study was reported in accordance with the Strengthening the reporting of observational studies in epidemiology (STROBE) guidelines. It was conducted through the online scientific outreach platforms of the Research Group on Technology, Management, Education, and Occupational Safety (TeGEST), affiliated with UFCSPA and registered in the CNPq Directory of Research Groups (DGP CNPq). Recruitment was carried out through the group’s Facebook® page, active since January 2019, and its official Instagram® profile. The invitation was posted with the group deputy leader’s written authorization.
Population and inclusion and exclusion criteria
The study population consisted of 1,574 Brazilian PMs. The sample was recruited by convenience sampling using snowball sampling, beginning with invitations posted on TeGEST’s social media accounts and encouraging participants to share them with colleagues in the profession. In addition, electronic messages were sent to Public Security Secretariats, General Commands, Casas Militares, and associations representing officers and enlisted personnel in all Brazilian states, requesting support in disseminating the study among personnel in the state Military Police forces. Participants were eligible if they were career PMs, were on active duty, and held permanent employment status. Retired PMs, those on temporary leave for more than 30 consecutive days (for reasons such as sick leave, vacation, or similar leave), temporarily hired personnel, and those still in their probationary period were excluded. After the eligibility criteria were applied and response completeness was verified, the final sample consisted of 1,028 PMs from multiple Brazilian states.
Study protocol
The questionnaire was made available online (https://bit.ly/PMQuestBR) and via QR code. The form included the eligibility criteria and the Informed Consent Record (Registro de Consentimento Livre e Esclarecido [RCLE]), with an option to download the full document. Participation was confirmed through electronic consent recorded in the form.
Data were collected between November and December 2024 using an online questionnaire with two sections: (1) Burnout, assessed with the BAT-33, work-related version; and (2) PMs’ sociodemographic, occupational, and health characteristics. The BAT was translated and adapted for use in Brazil, with evidence of validity and reliability reported in a Brazilian sample of workers (n = 2,217) from multiple occupational groups as part of a cross-cultural study that also included Portuguese workers (n = 886). The instrument comprises 33 items across four core dimensions (Exhaustion, Mental distance, Cognitive impairment, and Emotional impairment) and two secondary dimensions (Psychological complaints and Psychosomatic complaints)(2). The work-related version was selected because it is well suited to the occupational context and allows assessment of how job demands and working conditions affect mental health. Its use has also been recommended for occupational groups exposed to high demands and stress, which supports its applicability to the population under study(2,15).
Data analysis and statistics
Data were stored in Google Drive® as a Google Sheets® spreadsheet and exported as a Microsoft Excel® file to a local computer, ensuring anonymity and protection of sensitive data. Variables were coded according to a study-specific coding manual to ensure consistency and standardize selected responses. The dataset was then imported into Statistical Package for the Social Sciences® for descriptive and inferential analyses. Variables were summarized using absolute and relative frequencies, measures of central tendency and dispersion, and percentiles, depending on the data type and distribution. Normality was assessed with the Kolmogorov-Smirnov test (p < 0.05). Pearson’s correlation coefficient and the independent-samples t test were used for inferential analyses, with statistical significance set at 5%.
RESULTS
The study included 1,028 PMs from 225 municipalities across 20 Brazilian federal units. The North Region accounted for the largest share of participants (491; 47.8%), followed by the South Region (284; 27.6%), Central-West Region (134; 13.0%), Northeast Region (111; 10.8%), and Southeast Region (7; 0.7%); one participant did not report their region of origin (1; 0.1%). Most participants were men (842; 81.9%) and heterosexual (996; 96.9%), with a mean age of 41.9 ± 6.5 years (range: 23 to 60 years). Regarding race/ethnicity, participants self-identified as Brown (pardo) (510; 49.6%), White (387; 37.6%), Black (118; 11.5%), Asian (5; 0.5%), and Indigenous (4; 0.4%); 4 (0.4%) did not report this information. Regarding marital status, 807 (78.5%) were married or living with a partner. The predominant educational attainment was a college degree (817; 79.5%), followed by high school (177; 17.2%), technical and vocational education (24; 2.3%), and elementary school (8; 0.8%); 2 (0.2%) did not report this information. Table 1 shows the PMs’ occupational and health characteristics.
Table 1. Occupational and health characteristics of Brazilian Military Police, Brazil, 2025.
| Occupational and health characteristics | n (%) |
|---|---|
| Rank | |
| Sergeant | 438 (42.5) |
| Corporal | 158 (15.4) |
| Private | 127 (12.3) |
| Lieutenant | 85 (8.3) |
| Major | 58 (5.6) |
| Lieutenant colonel | 53 (5.2) |
| Subtenente (warrant officer) | 52 (5.1) |
| Captain | 39 (3.8) |
| Colonel | 15 (1.5) |
| Did not report | 3 (0.3) |
| Tempo de atuação (em anos) | 17.6 (7.7) * |
| Role | |
| Administrative duties | 450 (43.8) |
| Patrol duties | 416 (40.5) |
| Administrative and patrol duties | 48 (4.7) |
| Other duties | 90 (8.7) |
| Did not report | 24 (2.3) |
| Work shift | |
| Rotating | 492 (47.9) |
| Morning and afternoon | 314 (30.4) |
| Afternoon | 124 (12.1) |
| Morning | 84 (8.2) |
| Night | 12 (1.2) |
| Did not report | 2 (0.2) |
| Weekly working hours | 43.8 (9.9) * |
| Federal unit | |
| Pará | 307 (29.8) |
| Santa Catarina | 161 (15.7) |
| Rio Grande do Sul | 123 (11.9) |
| Goiás | 109 (10.6) |
| Bahia | 79 (7.7) |
| Tocantins | 74 (7.2) |
| Rondônia | 60 (5.8) |
| Acre | 24 (2.3) |
| Alagoas | 20 (1.9) |
| Roraima | 15 (1.5) |
| Mato Grosso | 13 (1.3) |
| Amazonas | 11 (1.1) |
| Distrito Federal | 8 (0.8) |
| Rio de Janeiro | 6 (0.6) |
| Sergipe | 6 (0.6) |
| Maranhão | 4 (0.4) |
| Mato Grosso do Sul | 4 (0.4) |
| São Paulo | 1 (0.1) |
| Pernambuco | 1 (0.1) |
| Rio Grande do Norte | 1 (0.1) |
| Não informou | 1 (0.1) |
| Physical activity (yes) | 849 (82.6) |
| Physical activity frequency (days) | 3.3 (1.4) * |
| Long-term medication use (yes) | 332 (32.3) |
| Psychological care (yes) | 452 (44) |
| Care received within the corporation | 185 (40.9) |
| Prefer not to say | 68 (6.5) |
| Any addiction (yes) | 212 (20.6) |
| Substances used | 1.2 (0.5) * |
Mean ± standard deviation.
Most PMs (860; 83.6%) held lower ranks, including private, corporal, sergeant, subtenente (warrant officer), and lieutenant. Years of service ranged from 1 to 40 years, with most PMs having served up to 19 years in the force, and 534 (51.9%) were assigned to fixed shifts. Among the 90 participants classified under “Other roles”, 23 (25.5%) worked in health services; 20 (22.3%) in Casa Militar; 12 (13.3%) in Civil Defense; 9 (10.1%) as intelligence agents; 8 (8.9%) in guard duty; 6 (6.7%) in educational units; 3 (3.3%) in the Emergency Center; 3 (3.3%) in the Cavalry; 2 (2.2%) as armorers; 2 (2.2%) in the Artistic Unit; and 2 (2.2%) in Special Operations. Among participants reporting addiction, only 149 (70.2%) specified the substance used, yielding 192 responses and a mean of 1.2 ± 0.5 substances per respondent. The most commonly reported substances were alcohol (87; 45.3%), followed by tobacco (38; 19.8%), compulsive eating (26; 13.5%), nonprescription medication use (16; 8.3%), and marijuana (1; 0.5%). Of note, 24 (12.6%) participants chose to report other addictions, although marijuana, cocaine, ecstasy, and crack were listed as response options. Another 63 (29.8%) participants who reported having an addiction preferred not to disclose the type of addiction or did not answer this item. Table 2 presents the prevalence of burnout symptoms.
Table 2. Prevalence of burnout symptoms among Brazilian Military Police, Brazil, 2025.
| Dimensions and domains | Mean (SD * ) | Low n (%) |
Moderate n (%) |
High n (%) |
Very high n (%) |
IC 95% Cronbach’s α |
|---|---|---|---|---|---|---|
| BAT-33 | 2.2 (0.7) | 253 (24.6) | 516 (50.2) | 206 (20) | 53 (5.2) | 1.65-3.14 0.968 |
| Core symptoms | 2.2 (0.7) | 268 (26.1) | 506 (49.2) | 202 (19.6) | 52 (5.1) | 1.65-2.90 0.958 |
| Exhaustion | 2.6 (0.8) | 253 (24.6) | 504(49) | 228 (22.2) | 43 (4.2) | 2.22-2.90 0.930 |
| Mental distance | 1.9 (0.9) | 308 (30) | 464 (45.1) | 207 (20.1) | 49 (4.8) | 1.70-2.44 0.873 |
| Cognitive impairment | 2.1 (0.8) | 267 (26) | 517 (50.2) | 200 (19.5) | 44 (4.3) | 1.91-2.54 0.886 |
| Emotional impairment | 1.8 (0.7) | 329 (32) | 450 (43.7) | 198 (19.3) | 51 (5.0) | 1.65-2.18 0.904 |
| Secondary symptoms | 2.4 (0.8) | 292 (28.4) | 499 (48.5) | 187 (18.2) | 50 (4.9) | 1.77-3.14 0.921 |
SD - standard deviation.
Age was weakly, negatively, and significantly correlated with all BAT-33 dimensions and domains, indicating slightly lower burnout scores with increasing age: BAT-33 (r = -0.114; p < 0.001), core symptoms (r = -0.111; p < 0.001), Exhaustion (r = -0.128; p < 0.001), Mental Distance (r = -0.070; p = 0.024), Cognitive Impairment (r = -0.100; p = 0.001), Emotional Impairment (r = -0.071; p = 0.022), and secondary symptoms (r = -0.105; p = 0.001). Years of service as a PM showed a negative correlation with Exhaustion (r = -0.085; p = 0.007), suggesting lower exhaustion among more experienced officers. No significant associations were found between weekly working hours and BAT-33 scores (p > 0.05).
Weekly frequency of physical activity showed negative and significant correlations with all BAT-33 dimensions and domains: BAT-33 (r = -0.149; p < 0.001), core symptoms (r = -0.138; p < 0.001), Exhaustion (r = -0.145; p < 0.001), Mental Distance (r = -0.088; p = 0.009), Cognitive Impairment (r = -0.118; p < 0.001), Emotional Impairment (r = -0.127; p < 0.001), and secondary symptoms (r = -0.151; p < 0.001). By contrast, the number of substances consumed by participants reporting addiction was positively correlated with all BAT-33 dimensions and domains: BAT-33 (r = 0.325; p < 0.001), core symptoms (r = 0.316; p < 0.001), Exhaustion (r = 0.319; p < 0.001), Mental Distance (r = 0.240; p = 0.003), Cognitive Impairment (r = 0.224; p = 0.006), Emotional Impairment (r = 0.305; p < 0.001), and secondary symptoms (r = 0.308; p < 0.001). Table 3 shows the associations between the BAT-33 dimensions and domains and PMs’ sociodemographic, occupational, and health variables.
Table 3. Association between burnout and Military Police officers’ sociodemographic, occupational, and health characteristics, Brazil, 2025.
| Variables | BAT-33 | Core symptoms | Exhaustion | Mental distance |
Cognitive impairment |
Emotional impairment |
Secondary symptoms |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean (SD * ) |
p value† | Mean (SD * ) |
p value† | Mean (SD * ) |
p value† | Mean (SD * ) |
p value† | Mean (SD * ) |
p value† | Mean (SD * ) |
p value† | Mean (SD * ) |
p value† | |
| Sex | ||||||||||||||
| Male | 2.2(0.7) | 0.008 | 2.1(0.7) | 0.097 | 2.6(0.8) | 0.238 | 1.9(0.9) | 0.925 | 2.1(0.8) | 0.001 | 1.8(0.7) | 0.105 | 2.3(0.8) | <0.001 |
| Female | 2.4(0.7) | 2.2(0.6) | 2.7(0.7) | 1.9(0.8) | 2.3(0.8) | 1.9(0.8) | 2.6(0.8) | |||||||
| Race/ethnicity | ||||||||||||||
| Brown. Black, Indigenous, and Asian | 2.1(0.7) | < 0.001 | 2.1(0.7) | < 0.001 | 2.5(0.8) | 0.014 | 1.8(0.8) | < 0.001 | 2.0(0.8) | < 0.001 | 1.7(0.7) | < 0.001 | 2.3(0.8) | < 0.001 |
| White | 2.4(0.7) | 2.3(0.7) | 2.7(.0.8) | 2.0(0.9) | 2.3(0.8) | 1.9(0.8) | 2.5(0.8) | |||||||
| Educational attainment | ||||||||||||||
| High school | 2.1(0.7) | < 0.001 | 2.0(0.7) | < 0.001 | 2.4(0.8) | 0.002 | 1.8(0.8) | 0.058 | 1.9(0.8) | < 0.001 | 1.7(0.7) | 0.002 | 2.2(0.8) | < 0.001 |
| College degree | 2.3(0.7) | 2.2(0.7) | 2.6(0.8) | 1.9(0.9) | 2.2(0.8) | 1.8(0.8) | 2.4(0.8) | |||||||
| Rank | ||||||||||||||
| Lower ranks | 2.2(0.7) | 0.221 | 2.2(0.7) | 0.226 | 2.6(0.8) | 0.228 | 2.0(0.9) | 0.002 | 2.1(0.9) | 0.371 | 1.8(0.8) | 0.535 | 2.4(0.9) | 0.278 |
| Higher ranks | 2.2(0.6) | 2.1(0.6) | 2.5(0.7) | 1.8(0.8) | 2.1(0.7) | 1.8(0.7) | 2.3(0.7) | |||||||
| Years of service | ||||||||||||||
| ≤ 19 anos | 2.2(0.7) | 0.277 | 2.2(0.7) | 0.270 | 2.6(0.8) | 0.014 | 1.9(0.9) | 0.540 | 2.1(0.8) | 0.833 | 1.8(0.7) | 0.918 | 2.4(0.8) | 0.355 |
| ≥ 20 anos | 2.2(0.7) | 2.1(0.7) | 2.5(0.8) | 1.9(0.9) | 2.1(0.8) | 1.8(0.7) | 2.3(0.8) | |||||||
| Work shift | ||||||||||||||
| Fixed | 2.3(0.7) | 0.159 | 2.2(0.7) | 0.264 | 2.6(0.8) | 0.748 | 1.9(0.8) | 0.509 | 2.2(0.8) | < 0.001 | 1.8(0.7) | 0.235 | 2.4(0.8) | 0.070 |
| Rotating | 2.2(0.7) | 2.1(0.7) | 2.6(0.8) | 1.9(0.9) | 2.0(0.8) | 1.8(0.8) | 2.3(0.8) | |||||||
| Physical activity | ||||||||||||||
| No | 2.4(0.7) | < 0.001 | 2.3(0.7) | 0.001 | 2.8(0.8) | < 0.001 | 2.1(0.9) | 0.002 | 2.3(0.8) | 0.004 | 2.0(0.8) | 0.009 | 2.7(0.8) | < 0.001 |
| Yes | 2.2(0.7) | 2.1(0.7) | 2.6(0.8) | 1.9(0.9) | 2.1(0.8) | 1.8(0.7) | 2.3(0.8) | |||||||
| Long-term medication use | ||||||||||||||
| No | 2.1(0.6) | < 0.001 | 2.0(0.6) | < 0.001 | 2.5(0.8) | < 0.001 | 1.8(0.8) | < 0.001 | 2.0(0.7) | < 0.001 | 1.7(0.7) | < 0.001 | 2.2(0.7) | < 0.001 |
| Yes | 2.5(0.7) | 2.4(0.7) | 2.8(0.8) | 2.1(0.9) | 2.4(0.9) | 2.0(0.8) | 2.7(0.8) | |||||||
| Psychological care | ||||||||||||||
| No | 1.9(0.5) | < 0.001 | 1.9(0.5) | < 0.001 | 1.9(0.5) | < 0.001 | 1.6(0.7) | < 0.001 | 1.8(0.7) | < 0.001 | 1.5(0.5) | < 0.001 | 2.0(0.6) | < 0.001 |
| Yes | 2.6(0.7) | 2.5(0.7) | 2.5(0.8) | 2.2(0.9) | 2.5(0.8) | 2.1(0.8) | 2.8(0.8) | |||||||
| Addiction | ||||||||||||||
| No | 2.2(0.7) | < 0.001 | 2.1(0.7) | < 0.001 | 2.5(0.8) | < 0.001 | 1.8(0.8) | < 0.001 | 2.0(0.8) | < 0.001 | 1.7(0.7) | < 0.001 | 2.3(0.8) | < 0.001 |
| Yes | 2.5(0.8) | 2.4(0.8) | 2.8(0.8) | 2.2(1.0) | 2.4(0.9) | 2.1(0.9) | 2.6(0.9) | |||||||
Standard deviation; †significance level (p < 0.05).
The analysis of factors associated with burnout among PMs showed greater vulnerability among women, who had higher mean scores on the BAT-33, Cognitive Impairment, and secondary symptoms. White officers also had higher scores across all BAT-33 dimensions and domains, suggesting possible sociocultural and occupational influences. Officers with a college degree had higher mean scores in most dimensions, except Mental distance, which may reflect greater awareness of or exposure to occupational stressors.
Rank was significantly associated with Mental distance, particularly among lower-ranking personnel (privates, corporals, sergeants, warrant officers, and lieutenants), possibly because of heavier workloads and lower autonomy. Exhaustion was more pronounced among PMs with up to 19 years of service, suggesting greater strain during midcareer stages. Fixed shifts were associated with Cognitive impairment, suggesting that rigid work schedules may negatively affect occupational health.
Regular physical activity was a protective factor, with lower scores across all BAT-33 dimensions and domains. By contrast, long-term medication use was associated with higher mean scores, possibly reflecting comorbidities or less effective coping strategies. Officers receiving psychological care also had higher scores, suggesting higher stress levels. Substance use was associated with greater psychosocial impairment, highlighting risk behaviors linked to burnout. No statistically significant associations were found between the BAT-33 dimensions and domains and the variables “age over 40 years”, “marital status”, and “availability of psychological care within the corporation” (p > 0.05), suggesting that these factors did not directly influence burnout levels.
DISCUSSION
The findings can be interpreted through the lens of the JD-R model, which conceptualizes burnout as the result of an imbalance between high job demands and limited institutional and personal resources. In policing, these demands include exposure to risk, hierarchical pressure, long working hours, and high emotional demands, whereas resources such as social support, recognition, and autonomy remain limited. The BAT makes the effects of this imbalance visible across measurable dimensions, such as Exhaustion, Mental distance, Cognitive impairment, and Emotional impairment, allowing burnout to be understood as both an individual and a structural phenomenon and underscoring the need for institutional policies that strengthen coping resources and protect PMs’ mental health(16,17).
related effects on mental health and acknowledging the psychosocial complexity of occupational distress(2,10,18). In this regard, cognitive Impairment, manifested in memory lapses and slowed information processing, underscores the importance of preventive and strategic interventions to preserve PMs’ operational capacity(5,19-22). The instrument also reframes cynicism as Mental distance, understood as a process of progressive cognitive and affective detachment associated with a loss of meaning and professional engagement(2,15,18). Finally, by assessing secondary symptoms such as sleep disturbances, tachycardia, headaches, muscle pain, and gastrointestinal discomfort, the instrument captures manifestations of chronic stress that are often normalized in everyday police work(2,15,18).
The sample was predominantly male, with a mean age above 40 years, reflecting an aging workforce within a rigid hierarchical structure. Women appear more vulnerable to burnout, especially in relation to exhaustion, which may be intensified by male-dominated environments that render occupational distress invisible(5,23,24). Age and years of service are also relevant factors, as they reflect cumulative wear and prolonged exposure to stress(25). Most participants serve in lower ranking positions, work rotating shifts, and take on multiple duties, a combination that increases the risk of exhaustion and mental distance(6,26). Dissatisfaction with the hierarchical structure and the overload borne by lower-ranking personnel suggest that illness stems not only from individual factors, but also from the scarcity of coping resources provided by the organizational model.
Having a college degree does not necessarily translate into career advancement, which can lead to frustration and low professional fulfillment(27). Recognition from superiors positively influences mental health, whereas its absence contributes to occupational stress(4,27-29). White PMs had higher burnout scores, possibly because of greater visibility, institutional demands, and self imposed pressure, whereas Black PMs may report less distress because emotional suffering is more often normalized or because they distrust the institution’s ability to preserve confidentiality(30-32).
Severe burnout symptoms are associated with intentions to leave the profession prematurely, work overload, and low organizational support, pointing to a risk to retention(33). A similar study conducted with police officers in Thailand found that work overload, combined with hierarchical rigidity and lack of recognition, has intensified psychological exhaustion and the desire to leave the profession(34). In settings marked by high demands and low subjective return, burnout contributes to illness and demotivation, undermining mental health and retention in the profession(16,17).
Continuous exposure to pain, violence, and vulnerability leads to emotional depletion and affective exhaustion, fostering the pattern of mental distance identified among PMs as a strategy of self-preservation(35). This mental distance, often expressed as indifference or cynicism, does not necessarily indicate contempt but rather a way of coping with chronic stress(2,11,15,18).
Although many PMs reported being in good health, the data also show medication use, psychological care-seeking, and reports of addiction, suggesting a mismatch between perceived health and the reality of psychological distress. In military settings, where emotional toughness is highly valued, acknowledging vulnerability may be seen as weakness, which contributes to institutional denial of illness and delays access to appropriate care(36). Studies show that, in the absence of safe spaces for emotional expression, many PMs resort to individual strategies such as self-medication, substance use, and isolation, which, although palliative, tend to worsen burnout and mental distance(37,38).
However, these findings do not necessarily indicate that institutional care policies are in place. On the contrary, they may point to a lack of structural responses and to the individualization of responsibility for mental health(39). One study found that, despite the high prevalence of mental disorders, most PMs rely on self-directed care without adequate institutional support(40). Barriers such as stigma and distrust of services provided by the corporation itself limit help-seeking, while the accumulation of everyday stressors heightens psychological vulnerability(41). This scenario underscores the need for systematic and ongoing interventions that go beyond individual-level responsibility.
Mental health continues to be treated as an individual responsibility, while institutional responses remain limited, and stigma and distrust within the corporation restrict access to appropriate care and engagement in self-care practices within a culture of invulnerability(5,35). Lack of institutional support may discourage PMs from seeking help, thereby worsening symptoms of stress and exhaustion and increasing the risk of conditions such as post-traumatic stress disorder (PTSD)(42). By contrast, structured mindfulness-based interventions have shown promise in fostering mindfulness, improving emotional regulation, and reducing burnout, especially when implemented in hierarchical settings with organizational support(43-45).
The inclusion of PMs from different regions, with strong representation from the North and South, together with the study’s sample size, adds robustness to the findings and suggests that burnout among PMs is a systemic problem. Recurrent exposure to violence, reduced work ability, and alcohol use were associated with poorer mental health and a higher risk of burnout, confirming convergent findings in the Brazilian literature, which identifies work overload and risk behaviors as central elements in illness among police personnel(36,46). Perceived quality of life is directly related to institutional support and adequate working conditions. Thus, burnout stems not only from high demands but also from an organizational model that weakens psychosocial protection, requiring concrete institutional measures that go beyond individual-level responsibility(21,47,48).
Strategies to prevent burnout should prioritize women PMs and those with longer years of service, with emphasis on work reorganization, effective institutional support, and the promotion of psychosocially healthy environments. This context points to the need for structural changes in public safety, including greater recognition of these professionals and a reconfiguration of operational roles. It also calls for an intersectional approach that takes into account race/ethnicity, rank, symbolic exposure, and mechanisms of institutional silencing in analyses of PMs’ mental health(6,49). Mindfulness-based interventions also appear promising for promoting mental health and underscore the importance of institutional investment in culturally sensitive support measures to address stress.
Study limitations
The cross-sectional design precludes causal inference and allows only associations to be identified. The sample was recruited through convenience sampling, and the use of a self-report instrument may have introduced response bias, including social desirability bias, especially in a population that may be reluctant to acknowledge signs of psychological distress.
Contributions to the field
This study contributes to nursing in the fields of occupational health and public health. Identifying burnout among PMs broadens understanding of psychological distress in high-risk occupational settings and supports efforts to promote mental health, prevent adverse outcomes, and implement psychosocial interventions. These findings can inform occupational health surveillance strategies and foster comprehensive, humanized care for public safety professionals.
CONCLUSIONS
The findings reaffirm that burnout among Brazilian PMs reflects the mismatch between high job demands and limited institutional resources described by the Job Demands-Resources model. Exhaustion, mental distance, cognitive impairment, and emotional impairment capture the human cost of work overload, hierarchical rigidity, and the invisibility of psychological distress. Burnout thus emerges as a collective phenomenon, pointing to organizational weaknesses and to a management model that continues to normalize occupational wear and tear. Addressing this scenario requires institutional and intersectoral policies that expand protective resources and promote psychosocially healthy work environments. Alignment with SDGs 3 and 8 places these recommendations within a broader agenda of well-being, decent work, and safer, more equitable societies. In this context, nursing stands out as a strategic actor in public safety surveillance and policy development.
Funding Statement
This study was supported by the Brazilian National Council for Scientific and Technological Development (CNPq), through the Institutional Program for Scientific Initiation Scholarships (PIBIC), and by the Federal University of Health Sciences of Porto Alegre (UFCSPA), through its Scientific Initiation Program (PIC/UFCSPA). Additional support was provided by CNPq through the Productivity Fellowship in Technological Development and Innovative Extension (DT-C).
Footnotes
FUNDING: This study was supported by the Brazilian National Council for Scientific and Technological Development (CNPq), through the Institutional Program for Scientific Initiation Scholarships (PIBIC), and by the Federal University of Health Sciences of Porto Alegre (UFCSPA), through its Scientific Initiation Program (PIC/UFCSPA). Additional support was provided by CNPq through the Productivity Fellowship in Technological Development and Innovative Extension (DT-C).
AVAILABILITY OF DATA AND MATERIAL
The research data are available within the article.
REFERENCES
- 1.Santos EA, Coutinho AF, Monteiro C, Masson LOA, Saba T. Diretrizes diagnósticas e terapêuticas para transtornos mentais relacionados ao trabalho. Goiânia: Subsecretaria de Vigilância em Saúde da Secretaria de Estado da Saúde de Goiás;; 2025. [cited 2025 Apr 26]. p. 79. [Internet] Available from: https://goias.gov.br/saude/wp-content/uploads/sites/34/2019/05/diretrizes-portaria-1128-72c.pdf . [Google Scholar]
- 2.Schaufeli WB, Witte H, Desart S. Version 2.0. Leuven (Belgium): KU Leuven;; 2020. [cited 2025 Apr 26]. Handleiding Burnout Assessment Tool (BAT) [Internet] Available from: https://burnoutassessmenttool.be/ [Google Scholar]
- 3.World Health Organization (WHO) Social determinants of mental health. Geneva (CH): World Health Organization;; 2023. [cited 2025 Apr 26]. [Internet] Available from: https://www.who.int/publications/i/item/9789240003927 . [Google Scholar]
- 4.Santos TBRD, Souza EA, Alves FR. Lack of professional recognition: main reason for stress in military police. Rev Bras Med Trab. 2022;20(3):438–444. doi: 10.47626/1679-4435-2022-749. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Ribeiro BMSS, Scorsolini-Comin F, Robazzi MLCC, Santos SVM, Terra FS, Dalri RCMB. Factors associated with Burnout Syndrome in police officers: a scoping review. Rev Bras Enferm. 2024;77(2):e20230444. doi: 10.1590/0034-7167-2023-0444. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Alves L, Abreo L, Petkari E, Costa MP. Psychosocial risk and protective factors associated with burnout in police officers: a systematic review. J Affect Disord. 2023;332:283–298. doi: 10.1016/j.jad.2023.03.081. [DOI] [PubMed] [Google Scholar]
- 7.Gavin P, Porter CN. Understanding the impact of organisational and operational stressors on the mental health of police officers in Ireland. Police Pract Res. 2025;26(1):90–100. doi: 10.1080/15614263.2024.2364247. [DOI] [Google Scholar]
- 8.Demerouti E, Bakker AB, Nachreiner F, Schaufeli WB. The job demands-resources model of burnout. J Appl Psychol. 2001;86(3):499–512. doi: 10.1037/0021-9010.86.3.499. [DOI] [PubMed] [Google Scholar]
- 9.Bakker AB, Demerouti E. Job demands-resources theory: taking stock and looking forward. J Occup Health Psychol. 2017;22(3):273–285. doi: 10.1037/ocp0000056. [DOI] [PubMed] [Google Scholar]
- 10.Schaufeli WB. Burnout: a short socio-cultural history. In: Nekel S, Schaffner A, Wagner G, editors. Burnout, fatigue, exhaustion: an interdisciplinary perspective on a modern affliction. Cham (CH): Palgrave Macmillan; 2017. pp. 105–127. [DOI] [Google Scholar]
- 11.Santin LJ, Júnior, Martins BG, Campos JADB, Vazquez ACS, Marziale MHP, Mendes IAC, et al. Psychometric properties of the Burnout Assessment Tool - General version in nursing workers. Rev Latino-Am Enferm. 2025;33:e4426. doi: 10.1590/1518-8345.7367.4425. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Villacura-Herrera C, Acosta-Antognoni H, Maldonado J, Arriaza F, Cancino-Letelier N, Nvo-Fernández M, et al. Burnout Assessment Tool: a reliability generalisation meta-analysis. Work Stress. 2025;39(2):169–196. doi: 10.1080/02678373.2025.2484758. [DOI] [Google Scholar]
- 13.Conselho Nacional de Saúde (CNS) Diretrizes e normas regulamentadoras de pesquisas envolvendo seres humanos. Diário Oficial da União; Brasília: 2013. [cited 2025 Apr 26]. Resolução nº 466, de 12 de dezembro de 2012. [Internet] Available from: https://conselho.saude.gov.br/resolucoes/2012/Reso466.pdf . [Google Scholar]
- 14.Presidência da República (BR) Lei nº 13.853, de 8 Jul 2019. Altera a Lei nº 13.709, de 14 de Agosto de 2018, para dispor sobre a proteção de dados pessoais e para criar a Autoridade Nacional de Proteção de Dados, e dá outras providências. Diário Oficial da União; Brasília: 2019. [cited 2025 Apr 26]. Secretaria-Geral. Subchefia para Assuntos Jurídicos. [Internet] Available from: https://www.planalto.gov.br/ccivil_03/_ato2019-2022/2019/lei/l13853.htm . [Google Scholar]
- 15.Sinval J, Vazquez ACS, Hutz CS, Schaufeli WB, Silva S. Burnout Assessment Tool (BAT): validity evidence from Brazil and Portugal. Int J Environ Res Public Health. 2022;19(3):1344. doi: 10.3390/ijerph19031344. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Bakker AB, Xanthopoulou D, Demerouti E. How does chronic burnout affect dealing with weekly job demands? A test of central propositions in JD-R and COR-theories. Appl Psychol. 2023;72(1):389–410. doi: 10.1111/apps.12382. [DOI] [Google Scholar]
- 17.Lambert EG, Qureshi H, Frank J, Anand V, Santhanam N, Grover A. Testing the Job Demands-Job Resources Model for Police Officer Job Burnout in a Sample of Indian Police Officers. Int Criminol. 2022;2(2):188–205. doi: 10.1007/s43576-022-00046-1. [DOI] [Google Scholar]
- 18.Redelinghuys K, Morgan B. Psychometric properties of the Burnout Assessment Tool across four countries. BMC Public Health. 2023;23(1):824. doi: 10.1186/s12889-023-15604-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Khammissa RAG, Nemutandani S, Feller G, Lemmer J, Feller L. Burnout phenomenon: neurophysiological factors, clinical features, and aspects of management. J Int Med Res. 2022;50(9):03000605221106428. doi: 10.1177/03000605221106428. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Bayes A, Tavella G, Parker G. The biology of burnout: causes and consequences. World J Biol Psychiatry. 2021;22(9):686–698. doi: 10.1080/15622975.2021.1907713. [DOI] [PubMed] [Google Scholar]
- 21.Torres-Vences IN, Mayoral EPC, Mayoral M, Pérez-Campos EL, Martínez-Cruz M, Torres-Bravo I, et al. Burnout syndrome and related factors in Mexican police workforces. Int J Environ Res Public Health. 2022;19(9):5537. doi: 10.3390/ijerph19095537. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Allison P, Tiesman HM, Wong IS, Bernzweig D, James L, James SM, et al. Working hours, sleep, and fatigue in the public safety sector: a scoping review of the research. Am J Ind Med. 2022;65(11):878–897. doi: 10.1002/ajim.23407. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Gibbons C. Stress, coping, burnout and mental health in the Irish Police Force. J Police Crim Psych. 2024;39:348–357. doi: 10.1007/s11896-023-09638-7. [DOI] [Google Scholar]
- 24.Renner MN, Gnacinski SL, Porter FJ, Cornell DJ. The influence of age and dynamic balance on functional movement among active-duty police officers. J Sport Rehabil. 2022;32(3):1–6. doi: 10.1123/jsr.2022-0046. [DOI] [PubMed] [Google Scholar]
- 25.Lima EC, Góis JÁ, Barreto FL, Tapioca TSC, Rodrigues EP, Tironi MOS, et al. Burnout syndrome in military police officers from a large city in the state of Bahia. Med Res Arch. 2025;13(5):1–6. doi: 10.18103/mra.v13i5.6541. [DOI] [Google Scholar]
- 26.Queirós C, Passos F, Bártolo A, Faria S, Fonseca SM, Marques A, et al. Job stress, burnout and coping in police officers: relationships and psychometric properties of the organizational police stress questionnaire. Int J Environ Res Public Health. 2020;17(18):6718. doi: 10.3390/ijerph17186718. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Souza NG. Avaliação de atitudes de supervisores sobre o ensino superior para praças policiais militares. Rev Ciênc Polícia. 2020;5(2):36–56. doi: 10.59633/2316-8765.2019.106. [DOI] [Google Scholar]
- 28.Johnson TL, Johnson NN, Sevigny EL. The college shield: examining the role of officer education in violent police encounters. Psychol Violence. 2022;12(4):260–269. doi: 10.1037/vio0000407. [DOI] [Google Scholar]
- 29.Alahiane L, Zaam Y, Abouqal R, Belayachi J. Factors associated with recognition at work among nurses and the impact of recognition at work on health-related quality of life, job satisfaction and psychological health: a single-centre, cross-sectional study in Morocco. BMJ Open. 2023;13(5):e051933. doi: 10.1136/bmjopen-2021-051933. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Paoline EA, Sloan JJ. Race, ethnicity and basic law enforcement training non-completion: a national-level examination of police academies. Police Q. 2024;27(2):158–186. doi: 10.1177/10986111231188429. [DOI] [Google Scholar]
- 31.Wright JE, Headley AM. Police use of force interactions: is race relevant or gender germane? ARPA. 2020;50(8):851–864. doi: 10.1177/0275074020919908. [DOI] [Google Scholar]
- 32.Rosenberger JS, Dierenfeldt R. Media and confidence in the police: differences across race/ethnicity. Am J Crim Justice. 2022;47:589–613. doi: 10.1007/s12103-020-09603-8. [DOI] [Google Scholar]
- 33.Gomes GP, Ribeiro N, Gomes DR. The impact of burnout on police officers’ performance and turnover intention: the moderating role of compassion satisfaction. Adm Sci. 2022;12(3):92. doi: 10.3390/admsci12030092. [DOI] [Google Scholar]
- 34.Samersri P. The Burnout Syndrome of police officers in Thailand. Acad J Interdiscip Stud. 2023;12(3):400. doi: 10.36941/ajis-2023-0087. [DOI] [Google Scholar]
- 35.Navarrete J, García-Salvador M, Cebolla A, Baños R. Impact of mindfulness training on Spanish police officers’ mental and emotional health: a non-randomized pilot study. Mindfulness. 2022;13:695–711. doi: 10.1007/s12671-022-01827-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Barreto CR, Carvalho FM, Lins-Kusterer L. Factors associated with health-related quality of life of military policemen in Salvador, Brazil: cross-sectional study. Health Qual Life Outcomes. 2021;19(1):21. doi: 10.1186/s12955-020-01661-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Singo C, Shilubane HN. How do police officers cope with stress? A qualitative study. J Police Crim Psych. 2022;37:984–992. doi: 10.1007/s11896-022-09556-0. [DOI] [Google Scholar]
- 38.Krishnan N, Steene LMB, Lewis M, Marshall D, Ireland JL. A systematic review of risk factors implicated in the suicide of police officers. J Police Crim Psych. 2022;37:939–951. doi: 10.1007/s11896-022-09539-1. [DOI] [Google Scholar]
- 39.Jetelina KK, Molsberry RJ, Gonzalez JR, Beauchamp AM, Hall T. Prevalence of mental illness and mental health care use among police officers. JAMA Netw Open. 2020;3(10):e2019658. doi: 10.1001/jamanetworkopen.2020.19658. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Newell C, Ricciardelli R, Czarnuch S, Martin K. Police staff and mental health: barriers and recommendations for improving help-seeking. Police Pract Res. 2021;23(1):111–124. doi: 10.1080/15614263.2021.1979398. [DOI] [Google Scholar]
- 41.Giessing L, Oudejans R, Hutter V, Plessner H, Strahler J, et al. Acute and chronic stress in daily police service: a three-week n-of-1 study. Psychoneuroendocrinology. 2020;122:104865. doi: 10.1016/j.psyneuen.2020.104865. [DOI] [PubMed] [Google Scholar]
- 42.Kerswell NL, Strodl E, Johnson L, Konstantinou E. Mental health outcomes following a large-scale potentially traumatic event involving police officers and civilian staff of the Queensland Police Service. J Police Crim Psych. 2020;35(1):64–74. doi: 10.1007/s11896-018-9310-0. [DOI] [Google Scholar]
- 43.Márquez M, Galiana L, Oliver A, Sansó N. The impact of a mindfulness-based intervention on the quality of life of Spanish national police officers. Health Soc Care Community. 2021;29:1491–1501. doi: 10.1111/hsc.13209. [DOI] [PubMed] [Google Scholar]
- 44.Hoeve M, Bruin EI, Van Rooij F, Bögels SM. Effects of a mindfulness-based intervention for police officers. Mindfulness. 2021;12:1672–1684. doi: 10.1007/s12671-021-01631-7. [DOI] [Google Scholar]
- 45.Krick A, Felfe J. Who benefits from mindfulness? The moderating role of personality and social norms for the effectiveness on psychological and physiological outcomes among police officers. J Occup Health Psychol. 2020;25(2):99–112. doi: 10.1037/ocp0000159. [DOI] [PubMed] [Google Scholar]
- 46.Fonseca PM, Jaffe CB, Verissimo A. Public policy factors associated with effectiveness of working environment and quality of life among military policemen in Brazil. J Public Policy Governam. 2022;6(3):14–22. doi: 10.53819/81018102t4107. [DOI] [Google Scholar]
- 47.Laureano-Morales L, Saldaña-Santiago N, Malave-Velez N, Quiles-Aponte J, Travieso-Perez S, Diaz-Algorri Y, et al. Work stress and burnout among active correctional officers in Puerto Rico: a cross-sectional study. PLoS One. 2024;19(10):e304886. doi: 10.1371/journal.pone.0304886. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Bezie A, Yenealem DG, Belay AA, Abie AB, Abebaw T, Melaku C, et al. Prevalence of work-related burnout and associated factors among police officers in central Gondar zone, Northwest Ethiopia, 2023. Front Public Health. 2024;12:1355625. doi: 10.3389/fpubh.2024.1355625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Rauschmayr S, Schleicher K, Dohnke B. Job Resources in the Police: Main and Interaction Effects of Social and Organizational Resources. J Police Crim Psych. 2023;38(3):716–727. doi: 10.1007/s11896-023-09592-4. [DOI] [Google Scholar]
