Examining the feasibility of a parental <scp>self‐help</scp> intervention for families awaiting pediatric eating disorder services
Bibliographic record
Abstract
OBJECTIVE: Waitlists for eating disorder (ED) services grew immensely during the COVID-19 pandemic. To address this, we studied the feasibility of a novel parental self-help waitlist intervention. METHOD: Parents of a child/adolescent (7-17 years) awaiting pediatric ED services were provided with our intervention, adapted from the family-based treatment model, and consisting of videos and reading material with no therapist involvement. Parent-reported child/adolescent weight was collected weekly 6 weeks pre-intervention, 2 weeks during the intervention, and 6-week post-intervention. Recruitment and retention rates were calculated. Regression-based interrupted time series analyses were completed to measure changes in the rate of weight gain. RESULTS: Ninety-seven parents were approached, and 30 agreed to participate (31% recruitment rate). All but one completed end-of-study measures (97% retention rate). The average rate of weight gain was 0.24 lbs/week pre-intervention, which increased significantly to 0.78 lbs/week post-intervention (p < .034). DISCUSSION: Our findings provide preliminary evidence that this intervention is feasible. Future research is needed to confirm the efficacy of this intervention on a larger scale. PUBLIC SIGNIFICANCE: The COVID-19 pandemic has resulted in several challenges in providing care for children and adolescents with eating disorders, including long waiting lists and delays in treatment. This study suggests that providing parents on a waitlist with educational videos and reading material is acceptable to parents, and may even help in improving the child's symptoms of an eating disorder.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".