Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression

• Autor(a) principal: Laranjo, Liliana
• Data de Publicação: 2021
• Outros Autores: Ding, Ding, Heleno, Bruno, Kocaballi, Baki, Quiroz, Juan C., Tong, Huong Ly, Chahwan, Bahia, Neves, Ana Luisa, Gabarron, Elia, Dao, Kim Phuong, Rodrigues, David, Neves, Gisela Costa, Antunes, Maria L., Coiera, Enrico, Bates, David W.
• Tipo de documento: Outros
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/147424
• topic: accelerometer; app; behaviour; effectiveness; physical activity; Orthopedics and Sports Medicine; Physical Therapy, Sports Therapy and Rehabilitation

Objective: To determine the effectiveness of physical activity interventions involving mobile applications (apps) or trackers with automated and continuous self-monitoring and feedback. Design: Systematic review and meta-analysis. Data sources: PubMed and seven additional databases, from 2007 to 2020. Study selection: Randomised controlled trials in adults (18-65 years old) without chronic illness, testing a mobile app or an activity tracker, with any comparison, where the main outcome was a physical activity measure. Independent screening was conducted. Data extraction and synthesis: We conducted random effects meta-analysis and all effect sizes were transformed into standardised difference in means (SDM). We conducted exploratory metaregression with continuous and discrete moderators identified as statistically significant in subgroup analyses. Main outcome measures: Physical activity: daily step counts, min/week of moderate-to-vigorous physical activity, weekly days exercised, min/week of total physical activity, metabolic equivalents. Results: Thirty-five studies met inclusion criteria and 28 were included in the meta-analysis (n=7454 participants, 28% women). The meta-analysis showed a small-to-moderate positive effect on physical activity measures (SDM 0.350, 95% CI 0.236 to 0.465, I2=69%, T2=0.051) corresponding to 1850 steps per day (95% CI 1247 to 2457). Interventions including text-messaging and personalisation features were significantly more effective in subgroup analyses and metaregression. Conclusion: Interventions using apps or trackers seem to be effective in promoting physical activity. Longer studies are needed to assess the impact of different intervention components on long-term engagement and effectiveness.