A brief eHealth tool delivered in primary care to help parents prevent childhood obesity: a randomized controlled trial
Bibliographic record
Abstract
OBJECTIVES: To determine the feasibility and preliminary impact of an electronic health (eHealth) screening, brief intervention and referral to treatment (SBIRT) delivered in primary care to help parents prevent childhood obesity. METHODS: Parents of children (5-17 years) were recruited from a primary care clinic. Children's measured height and weight were entered into the SBIRT on a study-designated tablet. The SBIRT screened for children's weight status, block randomized parents to one of four brief interventions or an eHealth control and provided parents with a menu of optional obesity prevention resources. Feasibility was determined by parents' interest in, and uptake of, the SBIRT. Preliminary impact was based on parents' concern about children's weight status and intention to change lifestyle behaviours post-SBIRT. RESULTS: Parents (n = 226) of children (9.9 ± 3.4 years) were primarily biological mothers (87.6%) and Caucasian (70.4%). The proportion of participants recruited (84.3%) along with parents who selected optional resources within the SBIRT (85.8%) supported feasibility. Secondary outcomes did not vary across groups, but non-Caucasian parents classified as inaccurate estimators of children's weight status reported higher levels of concern and intention to change post-SBIRT. CONCLUSIONS: Our innovative, eHealth SBIRT was feasible in primary care and has the potential to encourage parents of unhealthy weight children towards preventative action.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".