Patient satisfaction with psychotropic drugs: sensitivity to change and relationship to clinical status, quality-of-life, compliance and effectiveness of treatment. Results from a nation-wide 6-month prospective study
Bibliographic record
Abstract
OBJECTIVE: To see if patient satisfaction with psychotropics (PSP) could be used as a patient-oriented outcome variable in the evaluation of PSP drugs in clinical epidemiological studies, relationships between PSP, clinical status, QoL, compliance and the type of antipsychotic were analyzed. Elements of validation of PSP were also assessed. METHOD: In a 6-month prospective study, 933 schizophrenic outpatients with initiation or change to their antipsychotic treatment were enrolled. Psychiatrists completed five CGI-SCH scales (positive, negative, cognitive, depressive and global), hospitalization, compliance, and prescription variables. Patients completed PSP, EuroQoL scales, sexual function and compliance variables. RESULTS: A satisfactory structural equation model was obtained showing significant relationships PSP/compliance (coef.=0.16), QoL/PSP (coef.=0.37), clinical status/QoL (coef.=0.61), clinical status/compliance (coef.=0.09). Patients receiving olanzapine were more satisfied than patients receiving other atypicals (coef.=012) and had better clinical status than patients treated with typicals (coef.=0.08). Evolution of PSP was related to clinical status, QoL, and continuation of treatment (all P<001). Sensitivity to change of PSP was moderate (effect size=0.2). CONCLUSION: PSP produced consistent results in relation to validated outcome variables. However, a single-item measure was not sufficiently sensitive to change. Multi-item questionnaires evaluating different dimensions are needed.
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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 | 0.004 | 0.009 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".