Striking a Balance: Work-Health-Personal Life Conflict in Women and Men with Arthritis and its Association with Work Outcomes
Bibliographic record
Abstract
PURPOSE: To examine men and women's perceptions of inter-role balance/imbalance in work, arthritis, and personal roles and its association with demographic, health and employment factors, including job stress, career satisfaction, job disruptions, absenteeism and perceived productivity losses. METHODS: Participants were employed, aged ≥40 years and diagnosed with osteoarthritis or inflammatory arthritis. They were recruited through community advertising and rheumatology clinics in two Canadian provinces. Respondents completed a 35-45 min telephone interview and a 20-min self-administered questionnaire assessing role perceptions [(arthritis negatively impacts work (A → W); work/personal life negatively impact arthritis (W/P → A); work as a positive role (W +))], demographic, health and work context information. Analyses included exploratory factor analysis and multivariate regressions. RESULTS: Findings revealed similarities between men (n = 104) and women (n = 248) in health, work and role perceptions, although women reported more benefits of working with arthritis (W+) than men. Some gender differences were found in factors associated with inter-role perceptions highlighting the importance of children, fatigue, unpredictable work hours, job control, and workplace activity limitations. Role perceptions were associated with work outcomes but only one perception, W/P → A, interacted with gender. Among men, greater perceptions that work and personal demands interfered with managing arthritis were associated with more job disruptions. CONCLUSIONS: This study revealed negative and positive inter-role perceptions related to working with a chronic illness and associations with work outcomes. It highlights potentially modifiable factors that could assess risk and inform interventions to improve role balance and working experiences.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".