Impact of Antidepressant Side Effects on Adolescent Quality of Life
Bibliographic record
Abstract
OBJECTIVE: This study examines the relative impact of antidepressant side effects on adolescents with a history of major depression. METHODS: We used Q-sort methodology to capture the opinions of adolescents with a history of depression (n = 22), adults with a history of depression (n = 20), healthy adolescents (n = 20), and clinicians (n = 18) on the impact of 40 common antidepressant side effects. We asked subjects to force rank the side effects, judging each side effect on its relative impact on their daily lives. We also examined the impact of these side effects on health status and medication compliance. Primary analyses compared adolescents with depression with the other groups on their mean rankings for each of the 40 side effects. Secondary analyses included paired comparisons for ratings on health status and compliance. RESULTS: Although all groups ranked syncope and vomiting among the worst 5 side effects, significant differences were found between the groups on other side effects, such as anxiety, sleepiness, and hair loss. Based on the side effect with the most negative impact, adolescents with depression judged their own compliance (mean = 22%) to be higher than predicted by clinicians (mean = 11%). There were no significant differences between the groups on the mean rating of health status. CONCLUSIONS: Adolescents with depression, adults with depression, healthy adolescents, and clinicians agreed on the negative impact of 2 side effects: vomiting and syncope. Q-sort methodology provides valuable insight into the similarities and differences in opinion regarding the potential impact of side effects in patient groups.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".