Medicated Anxious Children: Characteristics and Cognitive-Behavioural Treatment Response
Bibliographic record
Abstract
OBJECTIVE: To determine whether individual and family characteristics of children with anxiety disorders who take psychotropic medications differ from those that are unmedicated and whether there is a differential response to cognitive-behavioural therapy (CBT). METHOD: Children ages 8 to 12 years (n = 102: 18 medicated, 84 unmedicated) were recruited in a specialized outpatient clinic over a 3-year period. All had a primary diagnosis of an anxiety disorder. Comparisons were done using t-tests for continuous measures and chi-square tests for discrete measures. Treatment-related changes were assessed using repeated measures analyses of variance. RESULTS: Medicated and unmedicated groups did not differ by age, sex, socioeconomic status, or diagnostic profile. Initial ratings of anxiety symptoms, depressive symptoms, and global functioning were comparable. Greater family dysfunction and family frustration were reported in medicated children. With treatment, both groups improved symptomatically and showed improved family functioning. Families of medicated children showed a greater reduction in frustration than families of unmedicated children, whereas unmedicated children showed greater gains in global functioning. CONCLUSIONS: Initial family functioning of medicated children seems to show more disturbances. Both medicated and unmedicated children can benefit from CBT. Further studies of differential treatment effects for medicated and unmedicated children are indicated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".