Suicidal ideation and mental health care: Predisposing, enabling and need factors associated with general and specialist mental health service use in France
Bibliographic record
Abstract
BACKGROUND: Population-based studies have shown that less than one in two individuals reporting suicidal ideation also report past-year mental health service use. Only a few studies have looked at different types of providers consulted. There is a need to better understand the factors associated with different provider combinations of mental health service use in representative samples of individuals with suicidal ideation. AIMS: The aim of the current study is to assess, using Andersen's model of healthcare seeking behaviors, the predisposing, enabling and need factors associated with type of mental health service use in adults with past-year suicidal ideation. METHODS: Data were drawn from the 2017 Health Barometer survey, a representative sample of the general population aged 18 to 75 years, among whom 1,128 respondents had reported suicidal ideation in the past year were analyzed. Past-year outpatient mental health service use (MHSU) was categorized into mutually exclusive groups as no use, general practitioner (GP) only; mental health professional (MHP) only; and both GP and MHP. Multinomial regression analyses were used to model mental health service use as a function of predisposing, enabling and need factors. RESULTS: Overall, 44.3% reported past-year MHSU and this was higher in females than males (49.0% vs. 37.6%). Prevalence of GP only use in the overall sample was 8.7%, consulting with GP and MHP was 21.3%, consulting with MHP only was 14.3%. Higher education was associated with increased MHP use. Residing in a rural area was associated with increased GP only use. Presence of a suicide attempt within the year, a major depressive episode and role impairment were associated with consulting a GP and MHP, and MHP only, but not GP only. CONCLUSIONS: When controlling for need and predisposing factors, socio-economic factors related to employment and income were associated with higher levels of consulting with mental health professionals.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".