Evaluation of a <scp>one‐hour</scp> asynchronous video training for eating disorder screening and referral in U.S. Pediatric Primary Care: A pilot study
Bibliographic record
Abstract
OBJECTIVE: Develop and pilot-test the efficacy of an online training in improving comfort, knowledge, and behaviors related to eating disorders (EDs) screening among U.S.-based pediatric primary care providers (PCPs). METHODS: PCPs (N = 84) completed a baseline survey assessing comfort, knowledge, and behaviors regarding ED screening and referral, then watched a 1-h training video followed by a post-video survey. Half of the participants were randomly assigned to complete spaced-education questions in the following 2 months. All participants completed a 2-month follow-up survey. We used McNemar's and McNemar-Bowker tests to assess differences from baseline to post-video and post-video to follow-up, and logistic models to assess differences by spaced-education condition. RESULTS: From baseline to post-video, there were significant improvements in PCPs' knowledge about and comfort in screening and making referrals for EDs (p < .05). There were no differences between spaced-education conditions in knowledge and behaviors from baseline or post-video to follow-up, but spaced-education participants reported significantly greater comfort in screening for BN (p < .01) and BED (p < .01) compared to non-spaced-education participants. DISCUSSION: Findings suggest that a 1-h asynchronous training can improve PCP comfort, knowledge, and behavior in screening for EDs; spaced-education may provide slight additional benefits in PCP comfort. PUBLIC SIGNIFICANCE: The delivery of an 1-h asynchronous online video training helped to improve PCPs' comfort, knowledge, and behavior in screening and referral for EDs among pediatric populations. This has implications for future evaluations of brief trainings among this provider population, which could ultimately help to improve early identification of EDs and referrals to appropriate treatment.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".