--- title: "Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Sy" url: "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/" type: "study" language: de-DE description: "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. 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. 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. 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. 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." --- # Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Sy > Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Systematic Review and Meta-Analysis of Randomized Controlled Trials.: 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. 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. 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. 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. 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. Evidenzgrad A, Risk of Bias unclear. ## Quelle Autor:innen: Sijia Li, You Zhou, Ying Tang, Haoming Ma, Yuying Zhang, Aoqi Wang Jahr: 2025 Journal/Quelle: JMIR mHealth and uHealth DOI: 10.1161/01.hyp.0000165680.59733.d4 APA: Li, S., Zhou, Y., Tang, Y., Ma, H., Zhang, Y., Wang, A., Tang, X., Pei, R., & Piao, M. (2025). Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Systematic Review and Meta-Analysis of Randomized Controlled Trials. JMIR mHealth and uHealth. https://doi.org/10.1161/01.hyp.0000165680.59733.d4 ## Forschungsfrage / Summary 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. 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. 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. 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. 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. ## Methode und Evidenzqualität [Studien](/studien/)typ: Studie Risk of Bias: unclear Evidenzgrad: A ## Key Findings Evidence-Fill Queue: Findings werden aus Volltext, Abstract und Review-Notizen konsolidiert. ## Effektgrößen / Outcomes Evidence-Fill Queue: Effektgrößen und Outcomes werden aus Volltext-Extraktionen priorisiert. ## Conversion-Implikationen Evidence-Fill Queue: Conversion-Implikationen werden nur ausgespielt, wenn Mechanismus, Kontext und Messgröße ableitbar sind. ## Limitationen Evidence-Fill Queue: Limitationen werden aus Risk-of-Bias-, Sample- und Methodikfeldern ergänzt. ## Verknüpfte Konzepte - [Default Effect](/konzepte/default-effect/) ## Unterstützte Claims - [Der untersuchte Consumer-Psychology-Effekt ist potenziell relevant für Conversion-Optimierung, benötigt aber noch genauere Claim-Extraktion.](/claims/consumer-psychology-effect-relevant-to-conversion/) ## FAQ ### Worum geht es in dieser Studie? Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Systematic Review and Meta-Analysis of Randomized Controlled Trials.: 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. 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. 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. 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. 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. Evidenzgrad A, Risk of Bias unclear. ### Welche Evidenz wird genutzt? Die Seite nutzt Claims, Studien, Use Cases und Quellen aus dem SurrealDB Knowledge Graph der Conversion-Psychologie-Wissensbasis. ### Ist die Ausgabe auf Deutsch verfügbar? Ja. Alle menschenlesbaren Inhalte und Agent-Ausgaben sind standardmäßig deutsch. ## Quellen - Li, S., Zhou, Y., Tang, Y., Ma, H., Zhang, Y., Wang, A., Tang, X., Pei, R., & Piao, M. (2025). Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Systematic Review and Meta-Analysis of Randomized Controlled Trials. JMIR mHealth and uHealth. https://doi.org/10.1161/01.hyp.0000165680.59733.d4 [Quelle öffnen](https://doi.org/10.1161/01.hyp.0000165680.59733.d4) ## JSON-LD ```json { "@context": "https://schema.org", "@graph": [ { "@type": "WebSite", "@id": "https://conversion.stevebaka.de/#website", "url": "https://conversion.stevebaka.de", "name": "conversion.stevebaka.de", "description": "Deutschsprachige Wissensbasis und Audit-Plattform für evidenzbasierte Conversion-Psychologie.", "publisher": { "@id": "https://conversion.stevebaka.de/#organization" } }, { "@type": "Organization", "@id": "https://conversion.stevebaka.de/#organization", "name": "conversion.stevebaka.de", "url": "https://conversion.stevebaka.de", "parentOrganization": { "@id": "https://stevebaka.de/#organization" }, "sameAs": [ "https://stevebaka.de" ] }, { "@type": "Person", "@id": "https://conversion.stevebaka.de/autoren/steve-baka/#person", "name": "Steve Baka", "url": "https://conversion.stevebaka.de/autoren/steve-baka/", "sameAs": [ "https://stevebaka.de" ], "jobTitle": "Conversion- und AI-Infrastructure-Berater", "knowsAbout": [ "Conversion-Psychologie", "Verkaufspsychologie", "Behavioral Science", "GraphRAG", "SurrealDB", "D-A-CH Conversion Optimierung" ] }, { "@type": "WebPage", "@id": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/#webpage", "url": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/", "name": "Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Sy", "description": "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. 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. 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. 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. 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.", "inLanguage": "de-DE", "isPartOf": { "@id": "https://conversion.stevebaka.de/#website" }, "breadcrumb": { "@id": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/#breadcrumb" }, "datePublished": "2026-07-01", "dateModified": "2026-07-04", "mainEntity": { "@id": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/#article" } }, { "@type": "ScholarlyArticle", "@id": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/#article", "headline": "Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Sy", "name": "Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Sy", "description": "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. 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. 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. 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. 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.", "inLanguage": "de-DE", "author": { "@id": "https://conversion.stevebaka.de/autoren/steve-baka/#person" }, "publisher": { "@id": "https://conversion.stevebaka.de/#organization" }, "mainEntityOfPage": { "@id": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/#webpage" }, "datePublished": "2026-07-01", "dateModified": "2026-07-04", "citation": [ "https://doi.org/10.1161/01.hyp.0000165680.59733.d4" ], "mentions": [], "text": "Behavior Change Resources Used in Mobile App Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Systematic Review and Meta Analysis of Randomized Controlled Trials.: 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. 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. 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. 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. 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. Evidenzgrad A, Risk of Bias unclear. Quelle. Autor:innen: Sijia Li, You Zhou, Ying Tang, Haoming Ma, Yuying Zhang, Aoqi Wang Jahr: 2025 Journal/Quelle: JMIR mHealth and uHealth DOI: 10.1161/01.hyp.0000165680.59733.d4 APA: Li, S., Zhou, Y., Tang, Y., Ma, H., Zhang, Y., Wang, A., Tang, X., Pei, R., & Piao, M. (2025). Behavior Change Resources Used in Mobile App Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Systematic Review and Meta Analysis of Randomized Controlled Trials. JMIR mHealth and uHealth. https://doi.org/10.1161/01.hyp.0000165680.59733.d4 Forschungsfrage / Summary. 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. 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 e", "learningResourceType": "Evidence source", "isBasedOn": [ "https://doi.org/10.1161/01.hyp.0000165680.59733.d4" ], "about": [] }, { "@type": "BreadcrumbList", "@id": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/#breadcrumb", "itemListElement": [ { "@type": "ListItem", "position": 1, "name": "Startseite", "item": "https://conversion.stevebaka.de/" }, { "@type": "ListItem", "position": 2, "name": "Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Sy", "item": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/" } ] }, { "@type": "FAQPage", "@id": "https://conversion.stevebaka.de/studien/10-1161-01-hyp-0000165680-59733-d4/#faq", "inLanguage": "de-DE", "mainEntity": [ { "@type": "Question", "name": "Worum geht es in dieser Studie?", "acceptedAnswer": { "@type": "Answer", "text": "Behavior Change Resources Used in Mobile App-Based Interventions Addressing Weight, Behavioral, and Metabolic Outcomes in Adults With Overweight and Obesity: Systematic Review and Meta-Analysis of Randomized Controlled Trials.: 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. 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. 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. 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. 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. Evidenzgrad A, Risk of Bias unclear." } }, { "@type": "Question", "name": "Welche Evidenz wird genutzt?", "acceptedAnswer": { "@type": "Answer", "text": "Die Seite nutzt Claims, Studien, Use Cases und Quellen aus dem SurrealDB Knowledge Graph der Conversion-Psychologie-Wissensbasis." } }, { "@type": "Question", "name": "Ist die Ausgabe auf Deutsch verfügbar?", "acceptedAnswer": { "@type": "Answer", "text": "Ja. Alle menschenlesbaren Inhalte und Agent-Ausgaben sind standardmäßig deutsch." } } ] } ] } ```