“Should I tell my employer and coworkers I have arthritis?” A longitudinal examination of self‐disclosure in the work place
Bibliographic record
Abstract
OBJECTIVE: To examine arthritis self-disclosure at work, factors associated with disclosure, and prospective relationships of self-disclosure and work place support with changes to work place interactions, work transitions, and work place stress. METHODS: Using a structured questionnaire, participants with osteoarthritis or inflammatory arthritis were interviewed at 4 time points, 18 months apart. At time 1, all participants (n = 490; 381 women, 109 men) were employed. Of the entire sample, 71% were retained throughout the study. Respondents were recruited using community advertising and from rheumatology and rehabilitation clinics. Self-disclosure and perceived support from managers and coworkers was assessed, as well as demographic, illness, work-context, and psychological variables. Generalized estimating equations modeled associations of disclosure and support on changes at work (e.g., job disruptions, work place stress). RESULTS: At each time point, 70.6-76.6% of participants had self-disclosed arthritis to their manager and 85.2-88.1% had told a coworker. Intraindividual variability in disclosure was considerable. Factors associated with self-disclosure were often inconsistent over time, with the exception of variables assessing the need to self-disclose (e.g., activity limitations) and perceived coworker support. Self-disclosure was not associated with changes to work. However, coworker support was related to fewer job disruptions, help with work tasks, and being less likely to reduce hours. Perceived managerial support was associated with less work place stress. CONCLUSION: Greater awareness is needed about issues related to self-disclosing arthritis at work. This study emphasizes the importance of a supportive work place, especially supportive coworkers, in decisions to discuss arthritis at work and in changes to work that might enable people 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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".