Bridging the gap: a mixed-methods real-world pilot of a digital intervention for adults with binge eating
Bibliographic record
Abstract
BACKGROUND: Many individuals who experience binge eating face significant challenges in accessing timely and adequate treatment, often due to limited healthcare resources. To address this, the digital, programme-led (self-help) version of Enhanced Cognitive Behaviour Therapy (CBT-E) has been developed. This service improvement project piloted the digital programme with adults on a specialist eating disorder service waiting list in the UK's National Health Service (NHS). Its aim was to assess the feasibility, acceptability, and preliminary clinical effects of a digital programme for adults on a waiting list for an eating disorder characterised by binge eating. METHODS: The digital programme was offered to patients with eating problems characterised by binge eating (binge eating disorder or bulimia nervosa or atypical or subclinical threshold cases), for whom a programme-led treatment was appropriate and who were on a waiting list for a specialist outpatient service. Patients used the programme independently, without any additional support. They completed self-report measures assessing eating disorder features, secondary impairment, and features of depression before and after the programme. Patients provided feedback through semi-structured interviews, and staff completed a survey. RESULTS: Fifty patients started the programme, and 19 completed all active programme sessions. Those who completed the full programme and the post-programme assessments (n = 14) reported significant reductions in binge eating frequency, eating disorder psychopathology, secondary impairment, and features of depression. Qualitative feedback from patients and staff highlighted the programme's value as a waiting list offer and its role in supporting patients' progress towards recovery. Some patients expressed a desire for human interaction to help them better engage with the programme. CONCLUSIONS: These findings suggest that the digital, programme-led version of CBT-E is feasible, acceptable, and shows promise in reducing binge eating and related impairments in adults on a waiting list for a specialist outpatient eating disorder services. Offering this evidence-informed programme could help address the challenge of long delays in accessing care. Future research should focus on strategies to enhance patient engagement and adherence, improve human interaction within the programme, and explore ways to scale the intervention to benefit broader populations, including its use as an early 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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".