Self-referrers to community workshops: Who are they and why do some participants not consult with their GP about their mental health difficulties?
Bibliographic record
Abstract
BACKGROUND: Self-referring is an important pathway to care that is being used increasingly by services, but little research has been conducted in this area. AIMS: To examine whether self-referrers would (i) be representative of the local community; (ii) be significantly psychologically distressed; (iii) be demographically similar to GP consulters and (iv) to investigate non-consulters' attitudinal reasons for not consulting their GPs. METHOD: The study is a cross-sectional analysis of 442 self-referrers who attended one of six one-day Cognitive Behavioural Therapy workshop programmes in the community. Socio-demographic details and information about past contact with GP services and attitudes towards non-consulting were collected. Parametric and non-parametric tests and logistic regressions were used to analyse the data. RESULTS: Self-referrers were representative of the local population although a disproportionate number of participants were unemployed and unoccupied. Over a quarter (26.5%) had not consulted their GPs. GP consulters had significantly higher clinical outcome in routine evaluation scores, though the scores of both groups were in the clinical range. Non-consulters tended to be from black, minority and ethnic groups and male. Attitudinal reasons for not consulting their GP were independently categorised as Perception of Services, Perception of Illness and Self-coping. CONCLUSIONS: Self-referral offers access to services to people who have been previously reluctant to consult.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".