Job Satisfaction and Psychological Distress among Help-Seeking Men: Does Meaning in Life Play a Role?
Bibliographic record
Abstract
Men's low job satisfaction has been shown to be associated with greater symptoms of psychological distress. Meaning in life may be an important factor in this relationship, but its role as a mediator has not been reported. The present study investigated meaning in life as a mediator in the relationship between job satisfaction and psychological distress among men. A total of 229 employed Canadian men participated in a cross-sectional survey, completing measures of depression and anxiety symptoms, anger severity, job satisfaction, and the presence of meaning in life. Zero-order correlations were calculated, and regression with mediation analyses were conducted; two models were tested: one for anxiety/depression symptoms and one for anger, as the dependent variables. Both mediation models emerged as significant, revealing a significant mediating effect for job satisfaction on the symptoms of psychological distress (anxiety/depression symptoms, anger) through meaning in life, even while controlling for salient confounding variables including COVID-related impacts. Lower job satisfaction was associated with less meaning in life, which in turn was associated with more symptoms of depression, anxiety, and anger. The findings highlight the importance of job satisfaction in the promotion of a sense of meaning in life among men, leading to improved psychological well-being both inside and outside of the workplace.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".