Effectiveness of Computer-Based Psychoeducational Self-Help Platforms for Eating Disorders (With or Without an Associated App): Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Access to psychological health care is extremely difficult, especially for individuals with severely stigmatized disorders such as eating disorders (EDs). There has been an increase in children, adolescents, and adults with ED symptoms and ED, especially following the COVID-19 pandemic. Computer-based self-help platforms (± associated apps) allow people to bridge the treatment gap and receive support when in-person treatment is unavailable or not preferred. OBJECTIVE: The aim of this systematic review is to evaluate the effectiveness of computer-based self-help platforms for EDs, some of which may have associated apps. METHODS: The proposed systematic review will follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. This review will report and evaluate the literature concerning the efficacy of self-help platforms for EDs. Articles were obtained from the Ovid MEDLINE, Embase, Global Health, and APA PsycInfo. The inclusion criteria included research with original data and gray literature; research evaluating the efficacy of web-based psychoeducational self-help platforms for EDs; people with an ED diagnosis, ED symptoms, at risk of developing EDs, or from the general population without ED-related behaviors; pre- and post-computer-based ± associated apps intervention clinical outcome of ED symptoms; pre- and post-computer-based ± associated apps intervention associated mental health difficulties; and literature in English. The exclusion criteria were solely guided self-help platforms, only in-person interventions with no computer-based ± associated apps comparison group, only in-person-delivered CBT, self-help platforms for conditions other than eating disorders, systematic reviews, meta-analyses, posters, leaflets, books, reviews, and research that only reported physical outcomes. Two independent authors used the search terms to conduct the initial search. The collated articles then were screened by their titles and abstracts, and finally, full-text screenings were conducted. The Cochrane Risk of Bias 2 tool will be used to assess the risks of bias in the included studies. Data extraction will be conducted, included studies will undergo narrative synthesis, and results will be presented in tables. The systematic review will be submitted to a peer-reviewed journal. RESULTS: The authors conducted a database search for articles published by May 31, 2024. In total, 14 studies were included in the systematic review. Data charting, synthesis, and analysis were completed in Microsoft Excel by the end of July 2024. Results will be grouped based on the intervention stages. The results are expected to be published by the end of 2024. Overall, the systematic review found that computer-based self-help platforms are effective in reducing global ED psychopathology and ED-related behaviors. CONCLUSIONS: Self-help platforms are helpful first-stage resource in a tiered health care system. TRIAL REGISTRATION: PROSPERO CRD42024520866; https://tinyurl.com/5ys2unsw. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/60165.
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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 | 0.066 | 0.066 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.021 | 0.026 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.081 | 0.010 |
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".