An Online Family Literacy and Wellness Program for Latino Dual Language Learners: Pilot Randomized Waitlist Controlled Trial
Bibliographic record
Abstract
Background: Early childhood interventions can simultaneously promote positive health and early language experiences, but implementation and health equity often receive insufficient attention during the development process. Objective: We apply a health equity lens to refine and pilot-test a family literacy and wellness program designed for Latino dual language learners (DLLs) entering kindergarten and their caregivers. Methods: In collaboration with a parent and community advisory board, we refined an 8-week family literacy and wellness program and conducted a pilot randomized controlled trial (RCT) with a waitlist control. The program, specifically designed by our interprofessional team for Latino DLLs, uses health topics (ie, nutrition, physical activity, sleep, and social-emotional development) to (1) introduce foundational language and literacy skills to children; (2) empower families to engage in health and home literacy activities using a strengths-based approach; and (3) encourage maintenance of families' home language. We assessed reach by collecting sociodemographic information; attendance and acceptability using a parent survey; and preliminary effects on home literacy activities through a validated parent-report instrument (StimQ2 quantity, quality, content, and concepts subdomains) and on child literacy skills using investigator-developed assessments. We analyzed quantitative data using descriptive statistics and regression analyses. Results: Parents and community advisors informed the program content. A total of 32 parent-child dyads were enrolled in the pilot RCT. All parents identified as Latino, and half had not completed high school, indicating that we reached the intended audience. Parents rated the program as highly acceptable, and 23 (72%) participants attended at least half of the sessions. After participation, group 1 had higher StimQ2 quality scores (effect size 0.99, P=.02) and higher quantity scores (effect size 1.01, P=.04) compared with group 2. Conclusions: Similar interprofessional collaborations may be a promising strategy to promote equity in early language experiences for Latino DLLs and their families.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".