Improving body image in female Chinese social media users with eating disorder symptoms: a randomized controlled trial of two online self-guided single-session interventions
Bibliographic record
Abstract
Social media use is a risk factor for eating and body image disturbances. The overlap between social media and eating and body image disturbances is particularly concerning in the Chinese context given an estimated billion active social media users in China, especially among females. This highlights the need for scalable, culturally adapted prevention and intervention strategies. This study developed and evaluated two online, self-guided, single-session interventions (SSIs), including a Media Literacy Intervention (MLI) and a Body Functionality-focused expressive writing Intervention (BFI), alongside waitlist controls, and examined their ability to improve body image among adult female Chinese social media users with eating disorder (ED) symptoms. A total of 204 female social media users with ED symptoms were recruited via Xiaohongshu (Little Red Note) and randomized to the MLI (n = 68), BFI (n = 68), or waitlist control group (n = 68). Primary outcomes included measures of negative and positive body image. Secondary outcomes included a range of measures including ED psychopathology and psychological distress. Assessments were conducted at baseline, 1-week post-intervention, and 4 weeks after baseline. Both MLI and BFI interventions significantly outperformed the waitlist control on primary and secondary outcomes. The two interventions demonstrated comparable efficacy across most domains, except for eating flexibility, where BFI yielded greater improvements. Intervention uptake was high (93%), and most participants (95%) reported they would recommend the intervention to others. SSIs show promise as accessible, acceptable, and effective tools for improving body image and reducing ED symptoms among Chinese female social media users with ED symptoms. Future research should conduct larger-scale studies to examine their effectiveness and long-term impact. Social media use is associated with body image concerns and increased risk of eating disorders. We developed two culturally adapted, self-guided online programs delivered via WeChat: a Media Literacy Intervention (MLI) and a Body Functionality Intervention (BFI). In a randomized controlled trial with 204 female social media users experiencing eating disorder symptoms, both interventions significantly improved body image and reduced eating disorder symptoms and psychological distress at follow-ups, compared to a control group. The interventions were highly acceptable, with 95% of participants indicating they would recommend them to others. These results suggest that brief, accessible online programs may be effective in improving body image, eating behaviors, and general mental health among female social media users with eating disorder symptoms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".