Unmet needs in the community:can existing services meet them?
Bibliographic record
Abstract
OBJECTIVE: This prospective study of community cases examined: (a) needs for care; (b) whether services meet the needs; and (c) personal factors associated with unmet needs. METHOD: Two separate 'Needs for Care Assessment Schedule Community version' evaluations identified 38 subjects with No Need (NN), 19 with Met Needs (MN) and 25 with Unmet Needs (UNM). Other instruments included the Diagnostic Interview Schedule-Abridged Version (DISSA) and repeated measures of symptoms and social functioning. RESULTS: (a) Cases did not equate needs. (b) Services utilization did not equate having met needs. (c) Respondents with UNM were more likely to present high rates of lifetime DSM-II-R disorders, no marital relationship ever, no employment, high rates of life events, and physical or sexual abuse in childhood. They have worse outcome in terms of distress and social functioning. CONCLUSION: Personal factors may prevent respondents from seeking, engaging and benefiting from treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".