New Antipsychotics, Compliance, Quality of Life, and Subjective Tolerability—Are Patients Better Off?
Bibliographic record
Abstract
OBJECTIVES: This overview reviews the impact of second-generation antipsychotics on less frequently researched outcomes such as medication-adherence behaviour, quality of life, and subjective tolerability in patients with schizophrenia. METHODS: We selectively reviewed recent literature and considered our own research and experiences in the field. RESULTS: Most published studies about second-generation antipsychotics have dealt with issues related to efficacy and safety. So far, not many studies have focused on effectiveness in terms of such important outcomes as medication-adherence behaviour, quality of life, subjective tolerability, and overall satisfaction with treatment. Although most studies are inconclusive and their results are inconsistent--which has to do with several design and methodological limitations--there seems, on balance, to be a trend indicating superiority of second-generation, compared with first-generation, antipsychotics in improving medication-adherence behaviour and quality of life. The trend toward more favourable subjective tolerability and less frequent neuroleptic dysphoria seems to be relatively stronger. CONCLUSIONS: At present, the state of the art can only indicate a more favourable trend for second-generation antipsychotics in regard to improving medication adherence behaviour, quality of life, and subjective tolerability. It is surprising that such important outcomes, which are likely the defining factors in the superiority of second-generation antipsychotics, have not received adequate research attention. Well-designed, controlled, and adequately powered studies are urgently needed before any firm conclusions can be reached.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".