The relationship between patient satisfaction and treatment outcomes in schizophrenia
Bibliographic record
Abstract
In recent years, the goals of treatment in schizophrenia have evolved from objective improvements in psychotic symptoms to encompass patient-related factors such as subjective response and quality of life. In order to examine factors that influence patient satisfaction with treatment, subjective quality of life and subjective response to treatment, two literature searches were performed using PubMed. The first searched for articles of any kind with no time limits using the search parameters 'schizophrenia AND satisfaction', 'antipsychotic AND satisfaction', 'schizophrenia AND subjective response', 'schizophrenia AND therapeutic alliance', 'schizophrenia AND psychosocial OR psychoeducation'. Secondly, PubMed was searched between January 1990 and December 2005 using the key words 'satisfaction', 'subjective response' and 'quality of life' in combination with an array of atypical agents. Results demonstrated that patient satisfaction with antipsychotic therapy is influenced by multiple factors. The most frequently reported reasons for dissatisfaction include drug side effects, lack of involvement in treatment planning or decision-making and lack of involvement of family members in the care plan. The majority of studies have demonstrated that the atypical antipsychotics are associated with significant improvements in quality of life, functional status and patient satisfaction compared with conventional agents. The therapeutic alliance is key to achieving optimal outcomes, by providing information and education to meet patients' needs, while facilitating compliance with drug therapy to ensure better clinical outcomes. A long-acting atypical antipsychotic that can ensure medication delivery will provide a platform for psychosocial interventions, and thus may further increase patient satisfaction and, ultimately, improve long-term outcomes in schizophrenia.
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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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".