Effect of Technology-Supported Interventions on Prenatal Gestational Weight Gain, Physical Activity, and Healthy Eating Behaviors: a Systematic Review and Meta-analysis Krista S. Leonard 1 & M. Blair Evans 2 & Zita Oravecz 3 & Joshua M. Smyth 4 & Danielle Symons Downs 1,5 Received: 14 February 2020 /Accepted: 10 August 2020 # Springer Nature Switzerland AG 2020 Abstract This review characterizes the effect of technology-supported interventions on prenatal gestational weight gain (GWG), physical activity, and healthy eating behaviors and describes intervention characteristics that may influence intervention effectiveness. A systematic search was conducted using PubMed, Web of Science, and CINHAL and identified prenatal technology-supported randomized controlled trials (RCT) targeting GWG, physical activity, and/or healthy eating behaviors (N = 21). Authors aggre- gated effect sizes to estimate overall effectiveness and calculated means of effect sizes as a function of intervention characteristics (i.e., delivery mode, type of technology, frequency of technology, correspondence between technology tool and targeted behav- ior). Random effects models revealed technology-supported RCTs had small effects on GWG (d= 0.23), physical activity (d= 0.38), energy intake (d= 0.38), and eating behaviors (d= 0.16). RCTs using technology with face-to-face sessions, tracking tools, and incorporating devices daily were associated with slightly larger effects, particularly for physical activity and healthy eating behaviors. Although there are small effects of technology-supported interventions on lowering GWG and improving physical activity and healthy eating behaviors, these effects may be improved by particular intervention characteristics such as delivery mode (e.g., technology plus face-to-face), type of technology (e.g., tracking tools), and frequency of technology prescribed (e.g., daily). Given the challenges and barriers of promoting prenatal GWG regulation, physical activity, and healthy eating behaviors, leveraging the use of technology to implement interventions may be a useful strategy to optimize maternal and infant well-being. Keywords Technology . Pregnancy . Gestational weight gain . Physical activity . Healthy eating Excessive gestational weight gain (GWG; i.e., > 35 pounds for women with normal weight, > 25 pounds for women with overweight, > 20 pounds for women with obesity; IOM 2009) is a predictor of adverse perinatal outcomes such as preeclampsia, gestational diabetes, and macrosomia (McDowell et al. 2019). Furthermore, many pregnant women fall short of attaining recommendations for health behaviors such as physical activity and healthy eating which exacerbate the effects of excessive GWG (American College of Obstetrics & Gynecology [ACOG] 2015; Hesketh and Evenson 2016; Kaiser et al. 2014). More specifically, approx- imately 62–87% of pregnant women do not meet national physical activity guidelines (i.e., > 150 min activity/week; ACOG 2015; Hesketh and Evenson 2016; U.S. Department of Health and Human Services [USDHHS] 2018). Pregnant women also have difficulty adhering to healthy eating behav- iors such as regulating their energy intake to align with federal recommendations (i.e., recommended an additional 300–450 calories per day in the second and third pregnancy trimesters) and maintaining a healthy intake of fruits and vegetables (i.e., 1.5–2 and 2.5–3 cups, respectively; ACOG 2016; Kaiser et al. 2014). Because the majority of pregnant women exceed GWG recommendations and do not meet physical activity/healthy * Danielle Symons Downs dsd11@psu.edu 1 Exercise Psychology Laboratory, Department of Kinesiology, The Pennsylvania State University, 266 Recreation Building, University Park, PA 16802-5701, USA 2 Department of Kinesiology, The Pennsylvania State University, University Park, PA, USA 3 Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, USA 4 Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA 5 Department of Obstetrics and Gynecology, Penn State College of Medicine, Hershey, PA, USA Journal of Technology in Behavioral Science https://doi.org/10.1007/s41347-020-00155-6