Virtual prevention of eating disorders in children, adolescents, and emerging adults: a scoping review
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, there was a necessity for eating disorder (ED) outpatient treatment to be delivered virtually. Given this transition, and the surge in new ED cases, there was an urgent need to investigate virtually delivered ED prevention programs. This review aimed to identify the available evidence on virtual ED prevention programs for children, adolescents, and emerging adults. METHOD: Using scoping review methodology, seven databases were searched for studies published from January 2000 to April 2021 reporting on virtually delivered ED prevention interventions for children and adolescents (< 18 years) and emerging adults (18-25 years). Studies were excluded if they contained adults (> 25 years) and individuals with clinical ED diagnoses. Abstracts and full-text papers were reviewed independently by two reviewers. Data was extracted on study type, methodology, age, sample size, virtual intervention, outcomes, and results. In April 2022, we used a forward citation chaining process to identify any relevant articles from April 2021 to April 2022. RESULTS: Of 5129 unique studies identified, 67 met eligibility criteria, which included asynchronous (n = 35) and synchronous (n = 18) internet-based programs, other e-technology including mobile apps (n = 3) and text messaging interventions (n = 1), computer-based programs (n = 6), and online caregiver interventions focused on child outcomes (n = 4). Few studies mainly included children and adolescents (n = 18), whereas the vast majority included emerging adults (n = 49). For children and adolescents, the most widely researched programs were Student Bodies and its adapted versions (n = 4), eBody Project (n = 2), and Parents Act Now (n = 2). For emerging adults, the most widely researched programs were Student Bodies and its adapted versions (n = 16), eBody Project (n = 6) and Expand Your Horizon (n = 4). These interventions were effective at reducing various symptoms and ED risk. Some studies demonstrated that virtual prevention intervention efficacy resembled in-person delivery. CONCLUSION: Virtual prevention interventions for EDs can be effective, however more research is needed studying their impact on children and adolescents and on improving access for vulnerable groups. Additional efficacy studies are required, such as for text messaging and mobile app ED prevention interventions. Evidence-based recommendations for virtual ED prevention for children, adolescents, and emerging adults at-risk for EDs should be prioritized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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 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".