Feasibility of acceptance and commitment therapy for post-bariatric surgery patients: the FAB study protocol
Bibliographic record
Abstract
<p class="abstract"><strong>Background:</strong> Bariatric surgery is an effective treatment for obesity. However, around one in five people experience significant weight regain. In the months following surgery, loss of food as a hedonic reward, increased sensitivity to food-related cues, alcohol use and depression may translate into new obesogenic behaviours which can be targeted in therapy. Acceptance and Commitment Therapy (ACT) teaches acceptance of and defusion from thoughts and feelings which influence behaviour, and commitment to act in line with personal values. We will test whether people who have had bariatric surgery over one year ago find 10 weeks of ACT group therapy an acceptable treatment and whether a larger trial to test whether ACT can improve long-term post-operative outcomes would be feasible.</p><p class="abstract"><strong>Methods:</strong> This will be a feasibility randomised controlled trial (RCT) with participants randomised to either ACT or a Usual Care Support Group control. Participants will be recruited at 15-18 months post-surgery and compared at baseline, 3, 6 and 12 months. The trial will provide information about recruitment and characteristics of the proposed outcome measures to inform a definitive RCT.</p><p class="abstract"><strong>Conclusions: </strong>Trials big enough to determine whether a treatment approach works are costly, so this small study will help determine whether the methods used, such as how people are recruited, allocated to groups, and how data are collected, are likely to work on a bigger scale. This project is the first step in testing whether ACT can help people who have had bariatric surgery.</p><p><strong>Trial Registration: </strong>Researchregistry.com, UIN: 3959 (date registered: 10 April 2018); ISRCTN registry ID: ISRCTN52074801.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".