Proof-of-concept testing of a brief virtual ACT workshop for emotional eating
Bibliographic record
Abstract
BACKGROUND: Emotional eating, or eating in response to negative emotions, is a commonly reported short-term emotion regulation strategy but has been shown to be ineffective in the long term. Most emotional eating interventions based on Acceptance and Commitment Therapy (ACT) have been delivered in the context of weight loss trials, highlighting a need for ACT-based emotional eating interventions in weight-neutral contexts. AIMS: This proof-of-concept study aimed to test the acceptability and efficacy potential of a brief virtual ACT workshop for emotional eating in a small sample of adults identifying as emotional eaters. METHODS: Twenty-six adult emotional eaters completed an ACT workshop delivered in two 1.5-h sessions over two weeks. The workshop targeted awareness and acceptance of emotions and eating urges, and valued actions around eating. RESULTS: The acceptability of the workshop was demonstrated by high participant satisfaction. Significant improvements on all outcome measures were found and maintained up to 3 months follow-up. CONCLUSIONS: These proof-of-concept findings suggest that a brief virtual ACT workshop may improve emotional eating and associated ACT processes. Results from this study can inform a future randomized controlled trial to test the efficacy of the workshop and the role of theoretical processes of change. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04457804. LEVEL OF EVIDENCE: Level IV, evidence obtained from multiple time series with the intervention.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".