Rong-Rong Han, Lei Zeng, Jia-Rui Lin, Qian Xu, Jia-Yuan Ma, Xin Chen, Yu Ding, Li Cheng, Ling-Ling Gao
{"title":"电子健康干预改善孕妇身体活动的有效性：一项系统回顾和荟萃分析。","authors":"Rong-Rong Han, Lei Zeng, Jia-Rui Lin, Qian Xu, Jia-Yuan Ma, Xin Chen, Yu Ding, Li Cheng, Ling-Ling Gao","doi":"10.1111/jocn.70112","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>This study aimed to (1) evaluate the effectiveness of e-health interventions in improving physical activity and associated health outcomes during pregnancy, (2) compare the e-health functions employed across interventions and (3) systematically identify the behaviour change techniques (BCTs) used and examine their interrelationships.</p><p><strong>Design: </strong>A systematic review and meta-analysis following the PRISMA 2020 guidelines.</p><p><strong>Methods: </strong>Randomised controlled trials were included. Meta-analyses and subgroup analyses were performed using RevMan 5.3. Social network analysis was conducted to determine the most central BCTs within the intervention landscape.</p><p><strong>Data sources: </strong>Ten databases were searched, including PubMed, Embase, Web of Science, Cochrane Library, ProQuest, Scopus, SinoMed, China National Knowledge Infrastructure, WanFang and the China Science and Technology Journal Database, from inception to April 22, 2024.</p><p><strong>Results: </strong>Thirty-five studies were included. Pooled analyses indicated that e-health interventions significantly improved both total (SMD: 0.19; 95% CI: 0.10 to 0.27; I<sup>2</sup> = 55%) and moderate-to-vigorous physical activity (SMD: 0.16, 95% CI: 0.06 to 0.26; I<sup>2</sup> = 53%) in pregnant women. Subgroup analyses revealed that interventions based on theoretical frameworks and those not specifically targeting overweight or obese women demonstrated greater effectiveness. Additionally, e-health interventions were associated with significant reductions in both total and weekly gestational weight gain. Six of the twelve e-health functions were utilised, with 'client education and behaviour change communication' being the most prevalent. Thirty unique BCTs were identified; among them, 'instruction on how to perform the behaviour', 'self-monitoring', 'problem solving', and 'goal setting' showed the highest degree of interconnectedness.</p><p><strong>Conclusion: </strong>E-health interventions are effective in enhancing physical activity and reducing gestational weight gain during pregnancy. Incorporating theoretical frameworks and well-integrated BCTs is recommended to optimise intervention outcomes.</p><p><strong>Relevant to the clinical practice: </strong>Integrating e-health interventions into existing perinatal care models holds promise for enhancing physical activity among pregnant women and improving maternal health outcomes.</p><p><strong>Reporting method: </strong>This study adhered to the PRISMA checklist.</p><p><strong>Patient or public contribution: </strong>No patient or public involvement.</p><p><strong>Trial registration: </strong>The study protocol was preregistered in the International Prospective Register of Systematic Reviews (CRD42024518740).</p>","PeriodicalId":50236,"journal":{"name":"Journal of Clinical Nursing","volume":" ","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effectiveness of E-Health Interventions on Improving Physical Activity in Pregnant Women: A Systematic Review and Meta-Analysis.\",\"authors\":\"Rong-Rong Han, Lei Zeng, Jia-Rui Lin, Qian Xu, Jia-Yuan Ma, Xin Chen, Yu Ding, Li Cheng, Ling-Ling Gao\",\"doi\":\"10.1111/jocn.70112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>This study aimed to (1) evaluate the effectiveness of e-health interventions in improving physical activity and associated health outcomes during pregnancy, (2) compare the e-health functions employed across interventions and (3) systematically identify the behaviour change techniques (BCTs) used and examine their interrelationships.</p><p><strong>Design: </strong>A systematic review and meta-analysis following the PRISMA 2020 guidelines.</p><p><strong>Methods: </strong>Randomised controlled trials were included. Meta-analyses and subgroup analyses were performed using RevMan 5.3. Social network analysis was conducted to determine the most central BCTs within the intervention landscape.</p><p><strong>Data sources: </strong>Ten databases were searched, including PubMed, Embase, Web of Science, Cochrane Library, ProQuest, Scopus, SinoMed, China National Knowledge Infrastructure, WanFang and the China Science and Technology Journal Database, from inception to April 22, 2024.</p><p><strong>Results: </strong>Thirty-five studies were included. Pooled analyses indicated that e-health interventions significantly improved both total (SMD: 0.19; 95% CI: 0.10 to 0.27; I<sup>2</sup> = 55%) and moderate-to-vigorous physical activity (SMD: 0.16, 95% CI: 0.06 to 0.26; I<sup>2</sup> = 53%) in pregnant women. Subgroup analyses revealed that interventions based on theoretical frameworks and those not specifically targeting overweight or obese women demonstrated greater effectiveness. Additionally, e-health interventions were associated with significant reductions in both total and weekly gestational weight gain. Six of the twelve e-health functions were utilised, with 'client education and behaviour change communication' being the most prevalent. Thirty unique BCTs were identified; among them, 'instruction on how to perform the behaviour', 'self-monitoring', 'problem solving', and 'goal setting' showed the highest degree of interconnectedness.</p><p><strong>Conclusion: </strong>E-health interventions are effective in enhancing physical activity and reducing gestational weight gain during pregnancy. 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Effectiveness of E-Health Interventions on Improving Physical Activity in Pregnant Women: A Systematic Review and Meta-Analysis.
Aims: This study aimed to (1) evaluate the effectiveness of e-health interventions in improving physical activity and associated health outcomes during pregnancy, (2) compare the e-health functions employed across interventions and (3) systematically identify the behaviour change techniques (BCTs) used and examine their interrelationships.
Design: A systematic review and meta-analysis following the PRISMA 2020 guidelines.
Methods: Randomised controlled trials were included. Meta-analyses and subgroup analyses were performed using RevMan 5.3. Social network analysis was conducted to determine the most central BCTs within the intervention landscape.
Data sources: Ten databases were searched, including PubMed, Embase, Web of Science, Cochrane Library, ProQuest, Scopus, SinoMed, China National Knowledge Infrastructure, WanFang and the China Science and Technology Journal Database, from inception to April 22, 2024.
Results: Thirty-five studies were included. Pooled analyses indicated that e-health interventions significantly improved both total (SMD: 0.19; 95% CI: 0.10 to 0.27; I2 = 55%) and moderate-to-vigorous physical activity (SMD: 0.16, 95% CI: 0.06 to 0.26; I2 = 53%) in pregnant women. Subgroup analyses revealed that interventions based on theoretical frameworks and those not specifically targeting overweight or obese women demonstrated greater effectiveness. Additionally, e-health interventions were associated with significant reductions in both total and weekly gestational weight gain. Six of the twelve e-health functions were utilised, with 'client education and behaviour change communication' being the most prevalent. Thirty unique BCTs were identified; among them, 'instruction on how to perform the behaviour', 'self-monitoring', 'problem solving', and 'goal setting' showed the highest degree of interconnectedness.
Conclusion: E-health interventions are effective in enhancing physical activity and reducing gestational weight gain during pregnancy. Incorporating theoretical frameworks and well-integrated BCTs is recommended to optimise intervention outcomes.
Relevant to the clinical practice: Integrating e-health interventions into existing perinatal care models holds promise for enhancing physical activity among pregnant women and improving maternal health outcomes.
Reporting method: This study adhered to the PRISMA checklist.
Patient or public contribution: No patient or public involvement.
Trial registration: The study protocol was preregistered in the International Prospective Register of Systematic Reviews (CRD42024518740).
期刊介绍：
The Journal of Clinical Nursing (JCN) is an international, peer reviewed, scientific journal that seeks to promote the development and exchange of knowledge that is directly relevant to all spheres of nursing practice. The primary aim is to promote a high standard of clinically related scholarship which advances and supports the practice and discipline of nursing. The Journal also aims to promote the international exchange of ideas and experience that draws from the different cultures in which practice takes place. Further, JCN seeks to enrich insight into clinical need and the implications for nursing intervention and models of service delivery. Emphasis is placed on promoting critical debate on the art and science of nursing practice.
JCN is essential reading for anyone involved in nursing practice, whether clinicians, researchers, educators, managers, policy makers, or students. The development of clinical practice and the changing patterns of inter-professional working are also central to JCN''s scope of interest. Contributions are welcomed from other health professionals on issues that have a direct impact on nursing practice.
We publish high quality papers from across the methodological spectrum that make an important and novel contribution to the field of clinical nursing (regardless of where care is provided), and which demonstrate clinical application and international relevance.
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