Related Experiment Video
Updated: Jun 7, 2025
Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
Published on: February 3, 2023
Effects of using wearable devices on reducing sedentary time and prolonged sitting in healthy adults: a network
Zihao He1,2, Guanggao Zhao3, Chao Li4
1School of Physical Education, Nanchang University, Nanchang, China.
Objectives:
This study aimed to compare the effectiveness of different wearable intervention strategies in reducing sedentary time (ST) and prolonged sitting (PS) on healthy adults.
Design:
A network meta-analysis (NMA).
Data Sources:
PubMed, Web of Science, SPORTDiscus, ProQuest, Opengrey, Medline and Cochrane Central Register of Controlled Trials were searched up to 1 June 2024.
Eligibility Criteria For Selecting Studies:
Randomised controlled trials (RCTs) that examined the effect of wearable device interventions on ST and PS among healthy adults were included.
Data Extraction And Synthesis:
Two independent reviewers used standardised methods to search, screen and code included studies. Bias risks were assessed using Cochrane tools (Risk of Bias 2.0). Data were analysed using a frequentist framework NMA to directly and indirectly compare the effects of the five different intervention strategies (comparators). The results were reported as standardised mean differences (SMDs) with 95% CI and surface under cumulative ranking curve (SUCRA) was used to rank the best interventions. The five comparators were as follows: (1) wearable-only intervention (only using wearable devices for self-monitoring); (2) wearable combined with online intervention (ie, online coaching and social media support); (3) wearable combined with offline intervention (ie, face-to-face seminars and courses); (4) comparison group (ie, traditional, non-wearable interventions); (5) control group (ie, maintaining daily routine, waitlist).
Results:
12 RCTs with a total of 2957 participants were included. Results of NMA showed that the 'wearable+online' has significantly better effects in reducing ST compared with control group, comparison group and 'wearable only', with moderate to large effect sizes (SMD=0.96, 95% CI 0.65 to 1.27; SMD=0.87, 95% CI 0.21 to 1.53; SMD=0.78, 95% CI 0.14 to 1.42, respectively). However, no significant differences were identified between the groups in reducing PS. The SUCRA values were ranked as wearable+online (98.1%), wearable+offline (64.4%,), 'wearable only' (40.5%), comparison group (25.9%) and control group (21.1%) for ST reduction. Similar rankings were observed for PS reduction, with probabilities of 69.9%, 61.1%, 59.7%, 37.1% and 22.1%, respectively.
Conclusions:
Wearable+online is the best intervention strategy for reducing ST in healthy adults. Additionally, none of the wearable-based interventions effectively reduced PS in healthy adults, but as there is little research on PS, it should receive more attention in the future. PROSPERO registration number: CRD42021290017.
