Role Overload and Perceived Stress in U.S. Police Officers: A Replication Study
Bibliographic record
Abstract
The current study sought to replicate a prior study (Duxbury & Halinski, 2018), conducted with Canadian police officers, to further explore the generalizability of their theoretical model of work- and family-role overload as sources of stress for male and female police officers in the United States. The Canadian study supported the proposed relationships between work-role overload, including four antecedents (Competing Demands, Outside Work of One’s Mandate, Non-supportive Culture, Employed Hours Worked), family-role overload (Dependent Care Hours), and police officer stress. A total of 357 United States law enforcement officers participated in the present study. A multivariate analysis was conducted utilizing SmartPLS 4 (Ringle et al., 2024) for PLS-SEM algorithm and bootstrapping procedures to analyze the measurement and structural model. Results demonstrated a significant positive relationship between role overload (work and family) and perceived stress. Three of the four proposed antecedents also had significant positive relationships with work-role overload (Competing Demands, Non-supportive Culture, and Employed Hours Worked). Contrary to the proposed structural model, the relationship between hours spent in dependent care and family-role overload and the relationship between feeling pressured to perform outside of one’s mandate and work-role overload were not significant. These results may assist law enforcement recruiters, law enforcement organizations, police policy makers, interdisciplinary researchers, and counseling and police psychologists in better understanding the antecedents of role overload and their connection to officer stress and mental health. Future research may consider further exploring the importance of gender, context, and culture as variables potentially impacting law enforcement stress.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".