Work addiction risk, stress and well-being at work: testing the mediating role of sleep quality
Bibliographic record
Abstract
Introduction: Attention to work addiction risk is growing; however, more studies are needed to explore the possible impact of work addiction risk on various aspects of employees' work and life domains. Although several studies have considered the antecedents or consequences of work addiction risk, this study particularly focuses on sleep quality as a potential explanatory underlying mechanism in the relation between work addition risk and three outcome variables including stress at home, stress at work and well-being. Method: The data was collected using an online platform and participants consisted of 188 French employees who were selected using simple random sampling method. Participants responded to the survey including the Work Addiction Risk Test (WART), stress at work, well-being, and sleep quality. The data was analyzed using JASP and SPSS-26 programs. Results: The results revealed that there are significant positive relationships between work addiction risk and both stress at home and at work and negative relationships between work addiction risk and both sleep quality and well-being. In addition, the analyses of the mediation paths suggest the significant mediation role of sleep quality for the link between work addition risk and stress at work as well as the link between work addiction risk and well-being. Discussion: Given the verified mediating role of sleep quality in the relationship between work addiction, stress and wellbeing, it is recommended that organizations and companies pay particular attention to their employees' sleep quality.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".