The Role of Psychological Variables on Medication Adherence in Patients with Obsessive-Compulsive Disorder
Bibliographic record
Abstract
Background: The aim of this study was to investigate the role of psychological variables in medication adherence in OCD. Methods: This descriptive and correlational study was carried out at Tehran Institute of Psychiatry in Tehran. The statistical population of the present study includes all OCD patients referred to the Tehran Institute of Psychiatry. The participants were selected by available sampling method. The patients completed the demographic questionnaire, Yale Brown Obsessive-Compulsive Disorder Scale-Second Edition (Y-BOCS-II), Vancouver Obsessional Compulsive Inventory (VOCI), Medication Adherence Rating Scale (MARS), Drug Attitude Questionnaire (DAI-10), Multidimensional Scale of Perceived Special Support (MSPSS), Coping strategies scale of Lazarus and Folkman (WOCQ), and Temperament and Character Inventory (TCI). Multiple Linear Regression (MLR) was used to analyze the data. Results: The variable of education status (r=0.18) had a positive relationship and the variable of hospitalization history (r=-0.26) had a negative relationship with medication adherence. Medication adherence is only negatively associated with obsessive thoughts (r=- 0.18, r=-0.20). Duration of drug use (r=0.27), attitude to treatment (r=0.25) and social support (r=0.54) had a positive relationship with medication adherence. Among the various dimensions of temperament and character, four dimensions of harm avoidance (r=-0.29), reward dependence (r=-0.44), persistence (r=-0.20) and self-transcendence (r=0.32) had a significant correlation with medication adherence. Variables of social support, reward dependence, persistence, harm avoidance and education status had the highest regression effect on medication adherence. Conclusion: Medication adherence is one of the behaviors that predicts successful treatment and reduces the negative side effects and severity of the OCD.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".