Disclosure Decisions of Workers Living with a Chronic Health Condition Causing Disability at Work: Are Decisions to Disclose to Co-workers and Supervisors Different?
Bibliographic record
Abstract
PURPOSE: Individuals living with chronic physical or mental health/cognitive conditions must make decisions that are sometimes difficult about whether to disclose health information at work. This research investigated workers' decisions to not to disclose any information at work, disclosure to a supervisor only, co-workers only, or to both a supervisor and co-workers. It also examined personal, health, and work factors associated with disclosure to different groups compared to not disclosing information. METHODS: Employed workers with a physical or mental health/cognitive condition were recruited for a cross-sectional survey from a national panel of Canadians. Respondents were asked about disclosure decisions, demographics, health, working experience, work context, and work perceptions. Multinomial logistic regressions examined predictors of disclosure. RESULTS: There were 882 respondents (57.9% women). Most had disclosed to both co-workers and supervisors (44.2%) with 23.6% disclosing to co-workers only and 7% to a supervisor only. Age, health variability, and number of accommodations used were significant predictors of disclosure for all groups. Job disruptions were associated with disclosure to supervisors only and pain and comfort sharing were associated with co-worker disclosure. CONCLUSION: The findings highlight that disclosure to co-workers is common despite being an overlooked group in workplace disclosure research. Although many similar factors predicted disclosure to different groups, further research on workplace environments and culture would be useful in efforts to enhance workplace support.
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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 | 0.022 |
| 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 | 0.001 |
| 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".