Optimising maternal health from preconception to pregnancy: a randomised type III hybrid implementation feasibility trial - the OptimalMe program

Abstract Background The continuum of preconception to pregnancy presents a critical window to optimise maternal health. We aimed to evaluate the reach, engagement, acceptability, and health-related behaviours associated with the pregnancy phase of the OptimalMe program, a digital health intervention with health coaching support delivered across preconception and pregnancy. Methods Using a randomised type III hybrid implementation feasibility design, women aged 18–44 planning a pregnancy within 12 months were recruited. Participants received access to a digital health platform, ongoing text messaging and health coaching with randomisation to different delivery modalities (telephone or videoconferencing). Quantitative program fidelity measures, questionnaires and implementation data were used to inform a collective program evaluation. Results Overall n=298 women were recruited preconception, of which n=197 (66.1%) reported a pregnancy (n=101 phone vs n=96 videoconferencing), with an average time to conception of 7.1±6.1 months and a cumulative conception rate of 77.1% (n=148) by 12 months. Of those that remained engaged with the program during pregnancy (n=119), n=117 (98.3%) engaged with the OptimalMe platform, n=97 (82.9%) attended at least one health coaching session and n=74 (63.2%) attended two coaching sessions. Total gestational weight gain was 10.69 ± 5.44 kg (phone: 10.66±5.98kg vs videoconferencing: 10.71±5.02kg, p=0.928) with 27.4% exceeding GWG based on their BMI category (phone: n=6 [25.0%] vs videoconferencing: n=8 [29.6%] p=0.712). On evaluation, preconception program engagement (i.e. health coaching attendance and digital platform use) and health behaviour change were associated with sustained engagement during pregnancy. Personalised health coaching was associated with increased engagement and program satisfaction compared with other intervention components. Conclusions The OptimalMe study demonstrates a model for effectiveness-implementation programs targeting continuity of preconception and pregnancy healthcare. Findings support feasibility and value of early, sustained intervention with embedded health coaching, by both phone or videoconferencing delivery methods, alongside innovative digital health technologies in fostering strong engagement in lifestyle change. Trial registration The Australian and New Zealand Clinical Trial Registry (ACTRN12620001053910); retrospectively registered.

Authors

Institutions

Publication Details

Journal
International Journal of Behavioral Nutrition and Physical Activity
Published
2026-10-26
DOI
https://doi.org/10.1186/s12966-026-01998-7
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimising maternal health from preconception to pregnancy: a randomised type III hybrid implementation feasibility trial - the OptimalMe program

Saeede Saadati, Bonnie R Brammall, Courtney K. Brown, Helena Jane Teede et al.
International Journal of Behavioral Nutrition and Physical Activity
Mobile Health and mHealth Applications
article

Optimising maternal health from preconception to pregnancy: a randomised type III hybrid implementation feasibility trial - the OptimalMe program

Saeede Saadati, Bonnie R Brammall, Courtney K. Brown, Helena Jane Teede, Cheryce L. Harrison, Catherine Keating
article en

Abstract

Abstract Background The continuum of preconception to pregnancy presents a critical window to optimise maternal health. We aimed to evaluate the reach, engagement, acceptability, and health-related behaviours associated with the pregnancy phase of the OptimalMe program, a digital health intervention with health coaching support delivered across preconception and pregnancy. Methods Using a randomised type III hybrid implementation feasibility design, women aged 18–44 planning a pregnancy within 12 months were recruited. Participants received access to a digital health platform, ongoing text messaging and health coaching with randomisation to different delivery modalities (telephone or videoconferencing). Quantitative program fidelity measures, questionnaires and implementation data were used to inform a collective program evaluation. Results Overall n=298 women were recruited preconception, of which n=197 (66.1%) reported a pregnancy (n=101 phone vs n=96 videoconferencing), with an average time to conception of 7.1±6.1 months and a cumulative conception rate of 77.1% (n=148) by 12 months. Of those that remained engaged with the program during pregnancy (n=119), n=117 (98.3%) engaged with the OptimalMe platform, n=97 (82.9%) attended at least one health coaching session and n=74 (63.2%) attended two coaching sessions. Total gestational weight gain was 10.69 ± 5.44 kg (phone: 10.66±5.98kg vs videoconferencing: 10.71±5.02kg, p=0.928) with 27.4% exceeding GWG based on their BMI category (phone: n=6 [25.0%] vs videoconferencing: n=8 [29.6%] p=0.712). On evaluation, preconception program engagement (i.e. health coaching attendance and digital platform use) and health behaviour change were associated with sustained engagement during pregnancy. Personalised health coaching was associated with increased engagement and program satisfaction compared with other intervention components. Conclusions The OptimalMe study demonstrates a model for effectiveness-implementation programs targeting continuity of preconception and pregnancy healthcare. Findings support feasibility and value of early, sustained intervention with embedded health coaching, by both phone or videoconferencing delivery methods, alongside innovative digital health technologies in fostering strong engagement in lifestyle change. Trial registration The Australian and New Zealand Clinical Trial Registry (ACTRN12620001053910); retrospectively registered.

International Journal of Behavioral Nutrition and Physical Activity
The University of Melbourne (AU), Monash Health (AU), Monash University (AU)
Medical Research Future Fund
Openalex Percentile: Top 8%
Mobile Health and mHealth Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon