Integrated Treatment Programme for Young Adults with Concurrent Disorders
Bibliographic record
Abstract
Background: The incidence of substance use, abuse and dependence seem to be increasing (1). It is probable that underlying mental illness, may reinforce individual's continuing substance indulgence (2), and If not intervened early, the consequence of this not only affects individual health, but also poses the threat of them procreating future sufferers. Objective: To detect mental illness at an early stage, in young adults with drug indulging behavior, and early intervention could be attempted. Method: A pilot project has been undertaken, for young adults (16-20 years) with concurrent disorder providing integrated intensive treatment program for six months. 12 patients were enrolled the study and 8 patients completed the study. A questionnaire has been devised to detect the probable existence of concurrent disorders. Assessment in all tridimensional spheres and intervened concurrently by the multidisciplinary team members. The outcome measures with the patients and the personnel were assessed by an independent assessor. The sensitivity and specificity of the devised questionnaire, has been measured. Result: There is significant correlation between underlying mental illness with drug indulgence and specific drug preference with type of mental illness have been elicited. The outcome measures along with the sensitivity and specificity of the questionnaire have been found significantly positive. Conclusion: It seems that the integrated treatment program is quite effective although resource consuming. Limitation: Small sample and limited duration which needs further replication.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".