Original Article
Preconceptional health behavior change in women with overweight and obesity: prototype for SMART strong healthy women intervention
Abstract
Background: The 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.
Methods: Overweight/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.
Results: Women 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.
Conclusions: Smartphone 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.
Methods: Overweight/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.
Results: Women 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.
Conclusions: Smartphone 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.
