Disclosure dilemmas: how people with a mental health condition perceive and manage disclosure at work
Bibliographic record
Abstract
PURPOSE: Little research has explored the process of disclosure decision-making from antecedents to outcomes. This paper presents a model of decision-making about disclosure of a mental health condition to the immediate supervisor in the workplace shortly after starting a new job. METHODS: A qualitative descriptive design was employed to explore participants' experiences of the disclosure decision-making process, the disclosure event itself (if applicable), and their perceptions of the impact of the decision on personal, interpersonal, and organizational outcomes. The transcripts were coded and analyzed using directed content analysis. RESULTS: Twenty-eight participants were purposively selected to represent different disclosure decisions, sex, diagnoses, and maintenance of employment. Analysis identified goals and conditions/context were important antecedents for the disclosure decision. All participants discussed concerns about prejudice and discrimination if they disclosed, and, for those who chose to disclose, high stress and anxiety were described during the disclosure event; however, supervisor reactions were generally described as positive. CONCLUSIONS: Regardless of the disclosure strategy adopted, participants reported that their disclosure decision helped to support their self-acceptance and recovery. For those who disclosed, most perceived a positive response by their supervisor. However, the pervasive concerns of prejudice indicate there is still much work to be done.IMPLICATIONS FOR REHABILITATIONDecision-making about disclosure of a mental health condition to the immediate supervisor in the workplace is a complex process.Disclosure goals, the relationship with the supervisor and the workplace context are important antecedents to the disclosure decision.Careful consideration should be given to the planning of disclosure, particularly related to what information will be shared, how it will be shared, and an appropriate level of emotional content to enhance the likelihood of a positive response from the supervisor.Disclosure planning should take the supervisor's style and organizational norms into account.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| 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".