[Employment specialists' views on hiring people with mental disorders: International cross-sections on employers' perceptions].
Bibliographic record
Abstract
Introduction and objectives The professional reintegration of people with mental disorders has become a global concern, resulting in a diversity of individualised support practices. These practices require a profound reorganisation of support strategies, where employers become key partners with whom employment advisers must establish enduring relationship. These practices allow the development of a supportive and interface relationship between employment counselors and employers and contribute to the continued employment of these people.This international qualitative study explores not only the perceptions of employment specialists regarding employers' apprehensions, benefits and risk associated with hiring people with mental disorders but also collects insights from 5 employment specialist/job coaches in Belgium, Canada, France, Luxembourg and Switzerland. Methods This study is part of an international survey conducted by the Community of Practice in Mental Health and Work (CoP-SMT in French), which examined the perspectives of 181 employment specialists on hiring people with mental disorders. The qualitative data (verbatims) were manually coded into codes, sub-themes, themes, major themes and occurrences. Additionally, a one-hour workshop was held with 5 female employment specialists to explore the findings in greater depth. Results According to the perceptions of employment advisers, employers' apprehensions are based on the personal characteristics of the future employee (e.g. lack of consistency). Despite the advantages that this employee brings (e.g. maturity, efficiency), what would push an employer to take the risk of hiring these profiles are the experiences that the employee has had (e.g. someone in their network with a mental disorder), their lack of knowledge of mental illness, as well as their own qualities (e.g. sensitivity). The employment counsellors also felt that the organization should modify its policies and practices (e.g. deconstructing preconceived ideas, employee well-being) to provide the person with a framework for job retention. To expand on these results, five employment counsellors stated during the CoP-SMT workshop that employers are looking for a person who is competent and causes as few problems as possible. In addition, the way in which the employment counsellor introduces the employee to the employer, the decision to disclose and the employer's awareness of the situation beforehand also play a role in the employer's openness to hiring. Conclusion The employment counsellor plays a major role in employers' openness to hiring a person with mental disorders, because they want to know how the person performs at work, his or her cognition and speed of task execution, without changing their organizational practices. The study also suggests avenues for further research in this area, such as cross-referencing these results with those of the employers or looking at the support and skills of the employment counsellor in the hiring process.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".