Ecological Momentary Assessment for Adolescents With Anorexia Nervosa and Their Parents/Caregivers in Family‐Based Treatment
Bibliographic record
Abstract
INTRODUCTION: Studies have shown that early weight gain in family-based treatment (FBT) predicts treatment response in adolescents with anorexia nervosa (AN); however, research examining factors associated with early weight gain in FBT is limited. This study tested the feasibility and acceptability of ecological momentary assessment (EMA) in early FBT, particularly to capture momentary data on family climate during mealtimes. METHODS: Using multiple methods, quantitative (EMA) and qualitative (interviews) data were collected in the first 4 weeks of FBT. Participants (11 families; 9 adolescents, 19 parents/caregivers) completed EMA assessments daily on the emotional climate during meals, parental strategies and confidence/agreement in renourishment. Qualitative interviews obtained technological and procedural data using EMA. Completion rates and markers of change were explored using repeated measures ANOVA. Interviews were analyzed using reflexive thematic analysis. RESULTS: The EMA completion rate for all family members was 78%: 84% for adolescents, 83% for mothers, 64% for fathers. Results demonstrated changes in caregivers' use of renourishment strategies and in the emotional climate (decreased anger) at mealtimes. No changes were observed in caregiver confidence/agreement in renourishment. Qualitative analyses revealed factors interfering with and facilitating the use of EMA. DISCUSSION: EMA is an acceptable and feasible tool for use with adolescents and their families in early FBT, particularly to capture momentary data on family climate during mealtimes. Future research is needed with larger sample sizes to examine the mechanisms of change in early FBT, and the utility of EMA as a clinical tool in FBT.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".