Arthritis and employment: An examination of behavioral coping efforts to manage workplace activity limitations
Bibliographic record
Abstract
OBJECTIVE: To examine ways in which individuals with arthritis manage their employment and health by focusing on the type and determinants of diverse behavioral coping strategies used to manage activity limitations, and to examine the relationship between coping behaviors and participation in employment. METHODS: The study group comprised 492 patients with osteoarthritis or rheumatoid arthritis. All participants were employed, and all participants were administered an in-depth, structured questionnaire. The study used an inductive approach and distinguished among 4 categories of coping behaviors as follows: adjustments to time spent on activities; receipt of help; modification of behaviors; and anticipatory coping. RESULTS: Fewer coping behaviors were reported at the workplace than outside of the workplace. Anticipatory coping was used most often in the workplace. Workplace activity limitations were related to increased reports of all types of coping. Women, those with more joints affected, and people expecting to remain employed reported more anticipatory coping. Expectations of continued employment were also related to modifications of activities, as was longer disease duration and discussing arthritis with one's employer. Help from others was associated with talking to an employer and positive job perceptions. Compared with work, reports of a greater number of coping behaviors used at home were associated with changes in overall work participation (e.g., absenteeism). CONCLUSION: These results expand our understanding of the experience of having a chronic illness and working and highlight the ways in which people accommodate to workplace limitations by using a variety of different behavioral coping efforts to remain employed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".