<p>Comparison of Different Adherence Measures in Adolescent Outpatients with Depressive Disorder</p>
Bibliographic record
Abstract
PURPOSE: Adolescent depression can have a chronic course; hence, the importance of adherence to antidepressant medication for successful treatment outcomes is emphasized. This study aimed to examine different adherence measures and identify clinical factors that influence adherence in adolescent depression. PATIENTS AND METHODS: A prospective study was conducted for patients diagnosed with depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition from outpatient psychiatric settings at Korea University Medical Center, Guro Hospital. Patient demographics were obtained from a questionnaire, interview, and review of chart records. Adherence was assessed by four methods (Medication Event Monitoring System [MEMS], pill count, clinical rating scale, and patient's self-report). The Toronto Side Effect Scale was used to evaluate side effects, and specific depressive symptoms were assessed using the Hamilton Rating Scale for Depression and Childhood Depression Inventory-Korean version. The Multidimensional Scale of Perceived Social Support was administered to analyze social support, and the Parenting Stress Index-Short Form was used to evaluate parental stress levels. We used concordance correlation analysis to evaluate the relationship among the four adherence measures and the relationship between adherence level and clinical factors. RESULTS: Overall, the study enrolled 48 outpatients (mean age 16.33±1.93 years). The mean duration of illness was 1.27±2.17 years. Adherence rates for MEMS, clinician rating scale, pill count, and self-report after conversion to dichotomous measures were 67.5%, 48.9%, 60.0%, and 56.3%, respectively. Only the duration of illness remained significantly correlated with MEMS (r = 0.510, p =0.001). CONCLUSION: Pill count exhibited a higher degree of agreement with MEMS adherence than the other two adherence measures, possibly indicating that pill count may be a considerably reliable measure of adherence. Furthermore, MEMS adherence was positively correlated with disease duration, suggesting that the longer the duration of illness, the higher the adherence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".