Bibliographic record
Abstract
One common feature of psychotherapies and professional interventions for people with schizophrenia is to provide support. For example, in a consultation, there will often be time allocated to listening to patients' concerns, giving encouragement, or arranging help with day-to-day living. There is, however, no universally accepted definition of supportive therapy. We used a wide definition to include any intervention from a single person with the aim of maintaining current functioning or to assist with a person's preexisting abilities. This includes interventions that require a trained therapist, such as supportive psychotherapy, as well as other interventions that require no training, such as “befriending.” We did not include interventions that sought to educate, train, or change a person's way of coping. To assess the effects of supportive therapy for people with schizophrenia, primarily on the outcomes of relapse, hospitalization, important change in mental state, global functioning, engagement with services, and satisfaction with care. We searched the Cochrane Schizophrenia Group's Register of trials (January 2004), supplemented by manual reference searching and contact with authors of relevant reviews or studies. All randomized trials involving people with schizophrenia comparing supportive therapy with any other treatment or standard care. We independently selected articles to be read fully from the abstracts, and, again working independently, selected articles for inclusion in the review, and extracted data for analysis. We resolved all disagreement by discussion. We could include 22 studies but data were limited. We found no significant differences in the primary outcomes when supportive therapy was compared with standard care. When, however, supportive therapy was the control intervention and was being compared with other psychological therapies, some differences were apparent—all favoring the other therapies (see table 1). More detailed findings are reported in the full version of this review.1 Comparison of Supportive Therapy With Other Therapies Note: CI, confidence interval. RR, relative risk. NNT, number needed to treat. CBT, cognitive behavioral therapy. Weighted mean difference. Standardized mean difference. Comparison of Supportive Therapy With Other Therapies Note: CI, confidence interval. RR, relative risk. NNT, number needed to treat. CBT, cognitive behavioral therapy. Weighted mean difference. Standardized mean difference. There is insufficient data to identify a difference in outcome between supportive therapy and standard care (4 randomized controlled trial [RCT], n = 354). For a variety of outcomes, including hospitalization, general mental state, and satisfaction with care, there is some indication of an advantage of other psychological therapies over supportive therapy. However, there were always few data, a lack of consistency on reporting of outcomes, and the potential of inclusion bias favoring the group not receiving supportive therapy. From this review, data do not support the conclusion that supportive therapy offers anything different to other forms of psychological intervention. In addition, there is currently no evidence that supportive therapy adds to standard care in terms of the outcomes we sought. It seems intuitive that support be given to people with schizophrenia. Whether this should be formalized into a therapy package remains in doubt. Further trials are indicated for this common approach. Researchers should consider using supportive therapy as the main treatment arm rather than a comparator and should ensure therapists have been specifically trained in a well-defined supportive therapy. Outcome measures could also address areas that have been relatively neglected to date, including adverse effects, social functioning, occupational status, quality of life, and economic outcomes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".