Resilience in the Ranks: Trait Mindfulness and Self-Compassion Buffer the Deleterious Effects of Envy on Mental Health Symptoms among Public Safety Personnel
Bibliographic record
Abstract
Public safety personnel (PSP) face frequent stressors that increase their risk of developing symptoms of depression and anxiety. In addition to being exposed to potentially traumatic events, PSP trainees may face a compounded risk of developing mental health symptoms, as their training environments are conducive to social comparisons and the resultant painful emotion of envy. Envy is associated with numerous negative health and occupational outcomes. Fortunately, there are several individual difference factors associated with increased emotional regulation, and such factors may offer resilience against the damaging mental health effects of envy. In this study, we examined the interplay between dispositional mindfulness, self-compassion, and dispositional envy in predicting job satisfaction, stress, experience of positive and negative emotions, subjective resilience, and symptoms of depression and anxiety in a sample of police trainees (n = 104). A substantial minority of trainees reported clinically significant symptoms of depression (n = 19:18.3%) and anxiety (n = 24:23.1%) in accordance with the cut-off scores on screening measures. Consistent with hypotheses, dispositional envy was associated with lower job satisfaction, greater stress, and greater anxiety and depression. Furthermore, envy was associated with higher negative emotions, lower positive emotions, and lower subjective resilience. Dispositional mindfulness and self-compassion were associated with greater job satisfaction, lower stress, and reduced symptoms of depression and anxiety. Moreover, mindfulness and self-compassion were both associated with lower negative emotions, higher positive emotions, and subjective resilience. The associations between envy and the relevant job and mental health outcomes were significantly diminished after controlling for mindfulness and self-compassion. This suggests that these protective traits may serve as transdiagnostic buffers to the effects of envy on mental health. The results of this study confirmed the damaging effects of envy and suggested the potential remediation of these effects through the cultivation of mindfulness and self-compassion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".