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Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic
Sijia Li1, You Zhou1, Ying Tang2
1Chinese Academy of Medical Sciences, Peking Union Medical College School of Nursing, No 33 Ba Da Chu Road, Shijingshan District, Beijing, 100144, China, 86 13522112889.
Background:
Overweight and obesity have become a public health issue. Lifestyle modifications delivered through mobile devices, especially mobile phones, present an opportunity to support weight loss efforts. However, evidence regarding the effects of mobile apps on other outcomes, such as blood pressure and physical activity (PA), remains limited. Recent studies on this topic require a systematic review and updating, and the active elements that promote behavior change remain unclear.
Objective:
The meta-analysis aimed to explore the effects of mobile phone apps on weight-related outcomes (weight, BMI, waist circumference [WC], fat mass, fat mass percentage), behavioral outcomes (moderate-to-vigorous physical activity [MVPA], energy intake), and metabolic outcomes (systolic blood pressure [SBP], diastolic blood pressure [DBP], triglycerides, hemoglobin A1c [HbA1c]) among adults with overweight and obesity. Behavior change techniques (BCTs), the smallest replicable intervention elements, were also identified to clarify the components used in current studies, along with associated resources, including facilitating, boosting, and nudging. In addition, factors influencing the effectiveness of these interventions were explored.
Methods:
Six databases (PubMed, Embase, CENTRAL, Web of Science, PsycINFO, and CINAHL) were searched for relevant randomized controlled trials (RCTs) published in English from inception to May 20, 2024. Two independent authors conducted study selection, data extraction, and quality assessment. The effect size of interventions was calculated using the mean difference (MD), and a random-effects model was applied for data analysis. Subgroup and sensitivity analyses were conducted to explore potential influencing factors and identify possible sources of heterogeneity.
Results:
A total of 29 studies were included. The results indicated that mobile phone app interventions significantly reduced weight (MD=-1.45 kg, 95% CI -2.01 to -0.89; P<.001), BMI (MD=-0.35 kg/m2, 95% CI -0.57 to -0.13; P=.002), WC (MD=-1.98 cm, 95% CI -3.42 to -0.55; P=.007), fat mass (MD=-1.32 kg, 95% CI -1.94 to -0.69; P<.001), DBP (MD=-1.76 mm Hg, 95% CI -3.47 to -0.04; P=.04), and HbA1c (MD=-0.13%, 95% CI -0.22 to -0.04; P=.005). However, nonsignificant effects were observed for other outcomes. The most frequently used BCTs included 2.3 "self-monitoring of behavior" (n=25), 4.1 "instruction on how to perform the behavior" (n=24), 2.2 "feedback on behavior" (n=20), 1.1 "goal setting (behavior)" (n=19), and 1.4 "action planning" (n=15). Fifty-nine percent of included studies used 3 resource types (ie, facilitating, boosting, and nudging). Subgroup analyses identified combined diet and PA interventions, medium-term intervention duration, and the use of ≥8 BCTs as potential reference interventions for improving outcomes.
Conclusions:
This meta-analysis demonstrates that mobile phone app interventions significantly reduce weight, BMI, WC, fat mass, DBP, and HbA1c in adults with overweight and obesity. However, future studies should explore ways to optimize app interventions by incorporating behavior change strategies and resources to further enhance their overall effectiveness.
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