ArticlemHealth2018
Preconceptional health behavior change in women with overweight and obesity: prototype for SMART strong healthy women intervention.
Article in mHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04605406 (Daily Step Count and Achieving Goal Gestational Weight Gain), which is not on this map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Daily Step Count and Achieving Goal Gestational Weight Gain
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- eHealth Delivery of Educational Content Using Selected Visual Methods to Improve Health Literacy on Lifestyle-Related Diseases: Literature Review.JMIR mHealth and uHealth · 2020Pooled it
- Acceptability and feasibility of a planned preconception weight loss intervention in women with long-acting reversible contraception: the Plan-it mixed-methods study.Health technology assessment (Winchester, England) · 2023Trial
- Pregnant Adults' Interest in Physical and Mental Health Behavior Change Interventions Using Mobile Technology.Journal of technology in behavioral science · 2025Article
- Healthy Mom Zone Adaptive Intervention With a Novel Control System and Digital Platform to Manage Gestational Weight Gain in Pregnant Women With Overweight or Obesity: Study Design and Protocol for a Randomized Controlled Trial.JMIR research protocols · 2025Article
- Feasibility and acceptability of measuring prenatal stress in daily life using smartphone-based ecological momentary assessment and wearable physiological monitors.Journal of behavioral medicine · 2024Article
- Acceptability and concerns about innovative wearable health sensors in persons with and without chronic disease diagnosis.Internet interventions · 2024Article
- How Wearable Sensors Can Support the Research on Foetal and Pregnancy Outcomes: A Scoping Review.Journal of personalized medicine · 2023Article
- The acceptability of asking women to delay removal of a long-acting reversible contraceptive to take part in a preconception weight loss programme: a mixed methods study using qualitative and routine data (Plan-it).BMC pregnancy and childbirth · 2022Article
- App development in a sports science setting: A systematic review and lessons learned from an exemplary setting to generate recommendations for the app development process.Frontiers in sports and active living · 2022Article
- Article
- Acceptability of Intervention Design Factors in mHealth Intervention Research: Experimental Factorial Study.JMIR mHealth and uHealth · 2021Article
- Development and Field Evaluation of the INTER-ACT App, a Pregnancy and Interpregnancy Coaching App to Reduce Maternal Overweight and Obesity: Mixed Methods Design.JMIR formative research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundThe prevalence of maternal perinatal obesity is rising, and in turn, increases health risks and morbidity for both mother and child. Past evidence suggests the preconceptional Strong Healthy Women (SHW) intervention can reduce multiple biobehavioral risk factors for adverse perinatal health. The SHW intervention, however, was time- and resource-intensive to deliver. Mobile health (mHealth) technologies provide an opportunity to expand intervention reach while reducing implementation cost and burden. Previous research suggests that preconceptional women are broadly supportive of using smartphones for behavior change, yet few studies have elicited their specific preferences for a targeted mHealth intervention. The objective of this study was to evaluate women's preferences for receiving SHW content via smartphone to supplement the design of SMART SHW, a redeveloped version of the intervention that utilizes smartphones to enhance delivery.
methodsOverweight/obese (mean BMI =31.4) preconceptional community women (N=40) participated in semi-structured focus group interviews. SHW components across four content areas (physical activity, nutrition, stress, weight management) were presented to participants; women provided preferences for program elements viewed as acceptable to convert to smartphone. Thematic analysis was used to analyze interview data. After the interviews were completed, an iterative review of the data to determine which aspects of SHW were feasible to modify for mobile delivery was conducted.
resultsWomen preferred to receive SHW communications, surveys, and educational materials on their smartphones via texting, mobile websites, and a SMART SHW app; MyFitnessPal and a wearable pedometer were preferred methods for tracking nutrition and activity. Salient mHealth design themes included providing pop-ups as reminders, using web-based videos to supplement the curriculum, and presenting on-screen information in a concise format. In designing the final prototype, 87% of participant preferences were able to be incorporated.
conclusionsSmartphone devices can enhance the reach of face-to-face behavioral interventions by reducing implementation burden. Engaging end-users (in this case, preconceptional women with overweight/obesity) in the mHealth design process through semi-structured focus groups is a feasible and useful approach. Eliciting and leveraging user preferences guides the development of an intervention framework that is highly acceptable to the target participants.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.