Psychotherapy for child and adolescent with psychiatric disorder attending in National Institute of Mental Health, Dhaka
Bibliographic record
Abstract
Psychotherapy for child and adolescent with psychiatric disorder is relatively a newer concept in Bangladesh. This cross sectional study was done to determine the pattern of psychotherapy provided by the psychotherapy department for children and adolescents with psychiatric disorder in National Institute of Mental Health (NIMH) from June 2010 to November 2014. Total 121 samples were taken purposefully from the records of psychotherapy department where data were collected retrospectively using check list. Results showed that among respondents more were boys than girls (64.5% vs. 35.5%) whereas their mean (±SD) age was 12.1 (±3.2) years. Majority (47.9%) of them were within class six to class ten. Most of the respondents (89%) were referred from the outpatient department and 11% were referred by inpatient department. Conduct disorder (27.3%), conversion disorder (13.2%), attention deficit hyperactivity disorder (12.4%) and intellectual developmental disorder (9.1%) were common diagnoses of the respondents. It was found that 74.4% respondents attended up to one to five psychotherapy sessions and cognitive behavior therapy (38%) and behavior therapy (25.6%) were most commonly used psychotherapy. Though 60.3% of the respondents improved to certain extent in psychotherapy sessions, patients dropout rate was found as 55.4%.Bang J Psychiatry Dec 2014; 28(2): 53-57
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".