Retaining and supporting employees with mental illness through inclusive organizations: lessons from five Canadian case studies
Bibliographic record
Abstract
Purpose Although awareness is growing of the importance of employee mental health and the value of inclusive work practices, less is known about how to support employees with mental illness (MI). We aimed to explore organizational strategies and work practices that promote retention and support of employees living with MI in relation to past theory-driven research by building and extending current theory. Design/methodology/approach We adopted a qualitative case-study approach focussed on organizations that have taken steps towards promoting workplace inclusion for employees with MI. Five diverse Canadian organizations were recruited based on their efforts to build psychologically safe and healthy workplaces, and actively support employees with MI. Data collection in each organization consisted of onsite observation and interviews with workplace stakeholders, including employees with MI, their co-workers, supervisors/managers and human resource professionals. Thirty interviews were conducted from across the five organizations. Data analysis was informed by interpretive description to identify challenges and opportunities. Findings Two key themes were noted in depictions of supportive workplaces: (1) relationship-focussed workplaces and (2) flexible, inclusive work practices. Originality/value These practices highlight how organizations support employees with MI. Despite our focus on organizations working towards inclusion, the stigma associated with MI and the rigidity of some workplace processes continue to limit support and retention. Our findings suggest that organizations should focus on communication processes, support mechanisms, how they reinforce flexibility, inclusion and oversight of employees with MI.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.031 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.008 |
| Research integrity | 0.000 | 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 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".