Barriers and facilitators to primary care for people with mental health and/or substance use issues: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Mental health and/or substance use issues are associated with significant disparities in morbidity and mortality. The aim of this study was to identify the mechanisms underlying poor primary care access for this population. METHOD: This was a community-based participatory action qualitative study, in which 85 adults who self-identified as having a serious mental health and/or substance use issue and 17 service providers from various disciplines who worked with this population participated in a semi-structured interview. RESULTS: Client, service provider and health system barriers to access were identified. Client factors, including socioeconomic and psychological barriers, make it difficult for clients to access primary care, keep appointments, and/or prioritize their own health care. Provider factors, including knowledge and personal values related to mental health and substance use, determine the extent to which clients report their specific needs are met in the primary care setting. Health system factors, such as models of primary care delivery, determine the context within which both client and service provider factors operate. CONCLUSIONS: This study helps elucidate the mechanisms behind poor primary health care access among people with substance use and/or mental health issues. The results suggest that interdisciplinary, collaborative models of primary healthcare may improve accessibility and quality of care for this population, and that more education about mental health and substance use issues may be needed to support service providers in providing adequate care for their clients.
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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 | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".