Short-term psychodynamic psychotherapies for common mental disorders
Bibliographic record
Abstract
BACKGROUND: Over the past 40 years, short-term psychodynamic psychotherapies (STPP) for a broad range of psychological and somatic disorders have been developed and studied. Four published meta-analyses of STPP, using different methods and samples, have found conflicting results. OBJECTIVES: This review evaluated the efficacy of STPP relative to minimal treatment and non-treatment controls for adults with common mental disorders. SEARCH STRATEGY: We searched CCDANCTR-Studies and CCDANCTR-References on 25/4/2005, CENTRAL, MEDLINE, CINAHL, EMBASE, PsycINFO, DARE and Biological Abstracts were also searched. We contacted triallists and checked references from papers retrieved. SELECTION CRITERIA: All randomised controlled trials (RCT) of adults with common mental disorders, in which a brief psychodynamic therapy lasting less than 40 hours in total, and provided in individual format, were included. DATA COLLECTION AND ANALYSIS: Three reviewers working in pairs evaluated studies. Studies were selected only if pairs of reviewers agreed they met inclusion criteria. A third reviewer was consulted if two reviewers could not reach consensus. Data were collected and entered into Review Manager. Study quality was assessed and scored by pairs of raters. Publication bias was assessed using a funnel plot. Sensitivity analyses were also conducted. MAIN RESULTS: 23 studies of 1431 randomised patients with common mental disorders were included. These studies evaluated STPP for general, somatic, anxiety, and depressive symptom reduction, as well as social adjustment. Outcomes for most categories of disorder suggested significantly greater improvement in the treatment versus the control groups, which were generally maintained in medium and long term follow-up. However, only a small number of studies contributed data for each category of disorder, there was significant heterogeneity between studies, and results were not always maintained in sensitivity analyses. AUTHORS' CONCLUSIONS: STPP shows promise, with modest to moderate, often sustained gains for a variety of patients. However, given the limited data and heterogeneity between studies, these findings should be interpreted with caution. Furthermore, variability in treatment delivery and treatment quality may limit the reliability of estimates of effect for STPP. Larger studies of higher quality and with specific diagnoses are warranted.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".