Client experiences of structural stigma in mental healthcare settings
Bibliographic record
Abstract
Structural stigma in mental healthcare is reflected in organizational cultures of care that are experienced by service recipients as negative and disempowering. This includes pathways to care, clinical practices, shared ways of thinking, patterns of communications, and patterns of interaction. We report on (a) the prevalence of structural stigma experienced by a national sample of 818 clients 18 years of age or older receiving mental or substance use care in the past two years, and (b) the testing of two new scales to assess structural stigma in mental healthcare settings; The Coercive Care Scale and the Person-centred Scale. Structural stigma experiences were drawn from a prior focus group study. Survey respondents for psychometric testing were sampled from a large Canadian polling firm using a national sample. Exploratory and confirmatory factor analyses were performed on random split halves of the sample. Respondents reported a wide range of experiences indicative of structural stigma. Over half reported a punitive or coercive care experience and almost half reported care that was not person-centred. Factor analyses resulted in two sub-scales: one measuring 12 aspects of coercive care (The Coercive Care Scale, alpha = .92) and the other measuring 8 aspects of person-centred care (The Person-centred Scale, alpha = .86), both with excellent reliability. These scales are unique in that they are grounded in the personal experiences of service users and characterize an entire episode of care (rather than a specific provider/client interaction) from the perspective of the individual receiving care. Items can be used to target specific issues for quality improvement initiatives or aggregated into their sub-scales to monitor cultural change over time. Tools such as these can foster efforts to identify and reduce structural stigma in mental healthcare settings and assess the effectiveness of anti-stigma interventions designed to improve stigma cultures.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".