Emotional self-efficacy and psychological health of police officers
Bibliographic record
Abstract
Purpose The evaluation of emotional management in police environments has impacts on their health and on their interventions (Monier, 2014; Van Hoorebeke, 2003). There are significant costs related to occupational diseases in the police force: absenteeism, turnover, deterioration of the work climate (Al Ali et al., 2012). Considering that policing involves a high level of emotional control and management (Monier, 2014; Al Ali et al., 2012; Dar, 2011) and that no study has yet examined the relationship between police officers’ emotional competencies and their psychological health at work (PHW), the purpose of this paper is to explore the relationship and influence of emotional self-efficacy (ESE) on PHW in policing. Design/methodology/approach PHW results from psychological distress at work (PDW) (irritability, anxiety, disengagement) and psychological well-being at work (PWBW) (social harmony, serenity and commitment at work) (Gilbertet al., 2011). ESE is defined as the individual’s belief in his or her own emotional skills and effectiveness in producing desired results (Bandura, 1997), conceptualized through seven emotional skills: the use of emotions; the perception of one’s own emotions and that of others; the understanding of one’s emotions and that of others; and the management of one’s emotions and that of others (Deschênes et al., 2016). A correlational estimate was used with a sample of 990 employed police officers, 26 percent of whom were under 34 years of age and 74 percent over 35. The ESE scales (a=0.97) of Deschênes et al. (2018) and Gilbertet al.(2011) on PWBW (a=0.91) and PDW (a=0.94) are used to measure the concepts under study. Findings The results of the regression analyses confirm links between police officers’ emotional skills and PHW. The results show that self-efficacy in managing emotions, self-efficacy in managing emotions that others feel, self-efficacy in using emotions and self-efficacy in understanding emotions partially explain PWBW (R2=0.30,p<0.001). On the other hand, self-efficacy in perceiving the emotions that others feel, self-efficacy in using emotions and self-efficacy in managing emotions partially explain PDW (R2=0.30,p<0.001). Originality/value This study provided an understanding of the correlation between police officers’ feelings of ESE and their PHW, particularly with PWBW. Beyond the innovation and theoretical contribution of such a study on the police environment, the results reveal the scope of the consideration of emotional skills in this profession.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".