The influence of therapeutic alliance on adult obesity interventions in primary care: A systematic review protocol
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Obesity is a common chronic condition, and general practitioners are seeking more effective strategies for assisting their patients. The therapeutic relationship between patients and practitioners is increasingly recognised as a fundamental part of intervention effectiveness. The influence of therapeutic relationships in obesity interventions in primary care has not been systematically studied. We plan to undertake a systematic review and meta-analysis to identify the influence of the therapeutic alliance on the effectiveness of obesity interventions in primary healthcare. The aim of this article is to outline the study protocol. METHOD: A systematic review of primary care interventions for patients with obesity will be undertaken. Using Bordin's framework for the therapeutic alliance, interventions will be categorised as to whether they incorporate the alliance or not. A meta‑analysis will be performed if studies of sufficiently homogenous primary outcome data are found. DISCUSSION: Understanding the role of the therapeutic alliance on interventions for obesity management will have implications for both future intervention development and the translation of current interventions from trial settings to the real world.
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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 | 0.070 | 0.072 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.018 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.054 | 0.006 |
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".