# A pilot feasibility study of digitally delivered modules focused on preventing the development of obesity during the first year of life within an existing statewide home visitation program

> **NIH NIH R34** · UNIVERSITY OF FLORIDA · 2023 · $271,150

## Abstract

PROJECT SUMMARY/ABSTRACT
 The first 1,000 days (conception to age 2) have been deemed a critical period for obesity prevention yet,
effective, sustainable efforts are lacking. Current home visitation programs (HVP) targeting at-risk families for
other child development related issues are a potential innovative opportunity for early childhood obesity
prevention. The overall goal of the project is to reduce the prevalence of overweight and obesity in children
under the age of 1 year thereby reducing obesity rates of older children and adults in the long term. Prior pilot
work by members of the research team demonstrated feasibility of embedding an early childhood obesity
prevention (ECHO) program in an existing home visitation program (HVP+) during an infant’s first year of life.
Five obesity-associated behaviors (i.e., breastfeeding, introduction to solids, limiting juice, sleep routines,
screen time) were emphasized through brief interactive lessons utilizing behavior change strategies and an
ecological approach by providing linkages to community resources that support healthy behaviors. The pilot
program was well received by families, mothers breastfed longer, infants had fewer nocturnal awakenings,
were less likely to receive juice, and had a lower weight-for-length (WFL) z-score at 12 months. However, there
is a critical need for alternative and innovative, consistent, and sustainable digital delivery methods especially
during times when face-to-face home visits are not feasible. Qualitative interviews were conducted with home
visitors (n=27) from Florida’s (FL) Maternal, Infant Early Childhood Home Visitation (MIECHV) Program and
revealed that they were highly receptive to using digital learning with at-risk families.
 The specific aims of the proposed research are to a) Develop, refine, and conduct usability testing of early
childhood obesity prevention digital learning modules with mothers (n=30) participating in FL MIECHV; and b)
Conduct a pilot RCT of a 12 month digitally-enhanced early childhood obesity prevention intervention
(HVP+E), with 50 mother-infant pairs (25 HVP+E/25 standard HVP) participating in FL MIECHV to determine
feasibility and acceptability of the HVP+E intervention and study recruitment, implementation and evaluation
protocols; and obtain data on preliminary efficacy of the intervention on children’s WFL z-scores (primary
outcome), maternal feeding practices, child sleep and screen time (secondary outcomes).
 Mother-infant dyads (n=50) enrolled in the Maternal, Infant Early Childhood Home Visitation (MIECHV)
Program parentally or within one month of giving birth will be randomized to receive either the standard home
visitation program (HVP) or the digitally delivered obesity prevention-enhanced home visitation program
(HVP+E) for 1 year. HVP+E content will also be expanded to support mothers in engaging fathers and other
family members in target behaviors. Mother-infant dyads will be assessed at study entry and at 6 an...

## Key facts

- **NIH application ID:** 10667696
- **Project number:** 1R34HL163373-01A1
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** Amy R Mobley
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $271,150
- **Award type:** 1
- **Project period:** 2023-08-07 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10667696

## Citation

> US National Institutes of Health, RePORTER application 10667696, A pilot feasibility study of digitally delivered modules focused on preventing the development of obesity during the first year of life within an existing statewide home visitation program (1R34HL163373-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10667696. Licensed CC0.

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