Welcome to Psychiatryai.com: Latest Evidence - RAISR4D

Implementing Supported Digital Enhanced Cognitive Behavior Therapy for Binge Eating Disorder in Routine Care: Mixed Methods Service Evaluation

AI Summary
  • Supported digital programme-led CBT-E was implementable in a specialist NHS service, with 84% suitability and most patients engaging with sessions.
  • Participants completing the programme showed large, significant reductions in binge eating frequency and eating disorder psychopathology, with improved impairment and depressive symptoms.
  • Patients and staff reported positive acceptability and accessibility, though challenges existed for those with low motivation or co-occurring conditions; further controlled research is required.
Summarise with AI (MRCPsych/FRANZCP)

J Med Internet Res. 2026 Jul 17;28:e92069. doi: 10.2196/92069.

ABSTRACT

BACKGROUND: Binge eating disorder (BED) is highly prevalent and impairing; yet, the UK national guideline-recommended first-line treatment of guided self-help (ie, supported program-led interventions in which content is delivered by the program with brief support) remains underused in routine National Health Service (NHS) care. Digital delivery offers a scalable approach, but evidence from real-world NHS settings is limited.

OBJECTIVE: This real-world evaluation aimed to pilot a supported digital program-led version of enhanced cognitive behavior therapy (CBT-E) in a specialist adult eating disorder outpatient service within the UK NHS and assess its implementation in routine practice, acceptability, and preliminary clinical outcomes.

METHODS: An independent evaluation service conducted this service evaluation in a specialist NHS eating disorder service. Adults assessed by NHS clinicians as having features consistent with BED and for whom a supported program-led intervention was considered appropriate were offered a 12-session digital CBT-E program (delivered over 8-12 weeks), with brief remote support from trained nonspecialist practitioners. Patients completed an in-program suitability assessment to ensure that the intervention was appropriate (eg, excluding those with suicidal ideation). Self-report measures of binge eating frequency, eating disorder psychopathology, secondary impairment, and depressive symptoms were collected before and after the program. Outcomes were analyzed using paired t tests. All patients were offered an optional interview. Semistructured interviews with 8 patients, 2 supporters, and a survey completed by 6 staff members were analyzed thematically to explore experiences of the intervention within the care pathway.

RESULTS: Between January and October 2024, 43 patients registered, and the program was deemed suitable for 36 (84%), all of whom completed preprogram assessments. Among these, 6 were still using the program at the end of the evaluation period, and 30 had either completed or discontinued the program. These patients (n=30) completed a mean of 8 of 12 sessions; 16 completed the full program and postprogram assessments. Among these 16, significant reductions were observed in binge eating frequency (mean 18.91, SD 11.28 to 1.88, SD 1.82; P<.001) and eating disorder psychopathology (mean 3.94, SD 1.20 to 1.85, SD 1.14; P<.001), with similar improvements in secondary impairment and depressive symptoms (both P<.001). Qualitative feedback highlighted the program’s accessibility, its role in keeping patients on track, and its positive impact on staff development and satisfaction. Some patients initially expressed skepticism about the digital format, and staff noted challenges for individuals with low motivation or co-occurring conditions.

CONCLUSIONS: This evaluation suggests that the supported digital program-led version of CBT-E can be successfully implemented within a specialist NHS service and may lead to improvements in clinical outcomes. This approach may increase access to guideline-recommended first-line treatment for BED in routine care. Further research with larger samples and controlled designs is needed to confirm effectiveness and evaluate resource use and cost-effectiveness.

PMID:42470185 | DOI:10.2196/92069

Document this CPD

Share Evidence Blueprint

QR Code

Save to Google Notes

Search Google Scholar

Save as PDF

close chatgpt icon
ChatGPT

Enter your request.

Psychiatry AI: Real-Time AI Scoping Review