Eating disorders treatment experiences and social support: Perspectives from service seekers in mainland China
Bibliographic record
Abstract
OBJECTIVE: This study explored treatment experiences and social support among individuals with eating disorders (EDs) in mainland China. METHOD: Subscribers of a Chinese online social media platform (WeChat) focused on EDs were invited to complete a screening questionnaire that included the Eating Disorder Diagnostic Scale for the DSM-5. Of the 116 questionnaire responses, 31 met inclusion criteria for follow-up interviews. Individuals who never sought treatment were not eligible for follow-up interviews, but provided brief explanations about why they did not seek treatment. All eligible participants (n = 31) completed a semi-structured interview about their experiences with ED treatment and social support. Qualitative data from the interviews and survey responses regarding not seeking treatment were subjected to inductive data-driven thematic analysis with deductive coding to illuminate treatment and social support experiences or reasons for not seeking treatment. RESULTS: Themes emerged from interviews revealed positive inpatient treatment experiences for anorexia nervosa, but negative outpatient treatment experiences, unaffordable care, and ineffective psychopharmacological treatments. Parents, friends, and partners were sources of social support, but participants largely felt misunderstood or blamed by these same entities. Shame, not recognizing ED as an illness, and financial constraints were listed as the primary reasons for not seeking treatment. DISCUSSION: The importance of hearing patients' perspectives, improving ED literacy in China, increasing knowledge of culturally specific manifestations of EDs, and developing culturally responsive services and dissemination of treatment resources are emphasized.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".