A Systematic Review of Psychological Therapies for Nonulcer Dyspepsia
Bibliographic record
Abstract
OBJECTIVES: We conducted a systematic review to determine the effectiveness of psychological interventions including psychodrama, cognitive behavioral therapy, relaxation therapy, guided imagery, or hypnosis in the improvement of dyspepsia symptoms in patients with nonulcer dyspepsia (NUD). DESIGN: Trials were identified through electronic searches of the Cochrane Controlled Trials Register (CCTR), MEDLINE, EMBASE, CINAHL, and PsycLIT, using appropriate subject headings and text words and searching bibliographies of retrieved articles. All randomized controlled trials (RCTs) or quasi-randomized studies were eligible. RESULTS: The four eligible trials all used different psychological interventions including applied relaxation therapy, psychodynamic psychotherapy, cognitive therapy, and hypnotherapy. Trials did not present data in a form that could be synthesized. All reported an improvement in the dyspepsia symptom scores at the end of treatment and at 1 yr in the intervention arm compared with controls. All studies only achieved statistically significant results through adjusting for baseline differences between groups. This reflects the small sample sizes of the trials. There were also problems with assumptions made in the statistical analyses used to achieve statistical significance. The studies highlighted problems with recruitment and compliance. CONCLUSIONS: There was insufficient evidence on the efficacy of psychological therapies in NUD. This emphasizes the need for appropriately powered well-designed trials in this area.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".