<scp>S</scp>ocial support satisfaction in adults with eating disorders: <scp>D</scp>oes stance matter?
Bibliographic record
Abstract
Although the role of social support is clearly established in the recovery of youth with eating disorders, little is known about factors that contribute to support satisfaction and improved treatment outcome in adults. This study examined the contribution of patient factors and perceived support stance used by family and friends in determining social support satisfaction. Individuals meeting DSM-IV criteria for an eating disorder (n = 182) completed measures of eating disorder and psychiatric severity, interpersonal functioning, perceived support stance used by family and friends, and social support satisfaction. Correlations indicated that both patient factors (lower psychiatric distress and fewer interpersonal difficulties) and perceived support stance (higher concerned and lower directive support) were associated with patient support satisfaction. Multiple regression analyses indicated that perceived support stance accounted for greater variance in social support satisfaction than did patient factors. Patient age was associated with differences in preferred support stance: expressions of caring were most critical for younger patients, whereas not being criticized or told what to do was most significant for older patients. This research suggests that the stance used when offering support is vital to the care of individuals with eating disorders.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".