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Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: a systematic review and meta-analysis
Open accessAbstract
BACKGROUND: High levels of sedentary behaviour (SB) are associated with negative health consequences. Technology enhanced solutions such as mobile applications, activity monitors, prompting software, texts, emails and websites are being harnessed to reduce SB. The aim of this paper is to evaluate the effectiveness of such technology enhanced interventions aimed at reducing SB in healthy adults and to examine the behaviour change techniques (BCTs) used. METHODS: Five electronic databases were searched to identify randomised-controlled trials (RCTs), published up to June 2016. Interventions using computer, mobile or wearable technologies to facilitate a reduction in SB, using a measure of sedentary time as an outcome, were eligible for inclusion. Risk of bias was assessed using the Cochrane Collaboration's tool and interventions were coded using the BCT Taxonomy (v1). RESULTS: Meta-analysis of 15/17 RCTs suggested that computer, mobile and wearable technology tools resulted in a mean reduction of -41.28 min per day (min/day) of sitting time (95% CI -60.99, -21.58, I2 = 77%, n = 1402), in favour of the intervention group at end point follow-up. The pooled effects showed mean reductions at short (≤ 3 months), medium (>3 to 6 months), and long-term follow-up (>6 months) of -42.42 min/day, -37.23 min/day and -1.65 min/day, respectively. Overall, 16/17 studies were deemed as having a high or unclear risk of bias, and 1/17 was judged to be at a low risk of bias. A total of 46 BCTs (14 unique) were coded for the computer, mobile and wearable components of the interventions. The most frequently coded were "prompts and cues", "self-monitoring of behaviour", "social support (unspecified)" and "goal setting (behaviour)". CONCLUSION: Interventions using computer, mobile and wearable technologies can be effective in reducing SB. Effectiveness appeared most prominent in the short-term and lessened over time. A range of BCTs have been implemented in these interventions. Future studies need to improve reporting of BCTs within interventions and address the methodological flaws identified within the review through the use of more rigorously controlled study designs with longer-term follow-ups, objective measures of SB and the incorporation of strategies to reduce attrition. TRIAL REGISTRATION: The review protocol was registered with PROSPERO: CRD42016038187.
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“Mobile phones can deliver programs to support behavioral change [1,2], data management or surveillance [3,4], and other essential public health activities.”
From Assessing the Cross-Cultural Adaptation and Translation of a Text-Based Mobile Smoking Cessation Program in Samoa (TXTTaofiTapaa): Pilot Study (2018) · cites this paper as [2]
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“These have been successfully applied to improve diet/Physical Activity (PA) [11, 12], sexual health behaviours [13], weight management [14], alcohol reduction [12] and smoking cessation [15, 16].”
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Hardeman, W., Houghton, J., Lane, K., Jones, A., & Naughton, F. (2019) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-019-0792-7 · Cited by 396
“These interventions significantly reduced sitting time up to 6 months after the intervention, but only in studies with shorter follow-ups [4].”
Fitbit-based interventions for healthy lifestyle outcomes: systematic review and meta-analysis
Ringeval, M., Wagner, G., Denford, J., Paré, G., & Kitsiou, S. (2020) · Journal of Medical Internet Research · doi:10.2196/23954 · Cited by 225
“Furthermore, there is inconclusive evidence that wearable-based interventions are effective at achieving healthier lifestyles through decreases in sedentary behavior [16,34] or through weight loss [28,30,32,35].”
BackgroundBidargaddi, N., Almirall, D., Murphy, S., Nahum-Shani, I., Kovalcik, M., Pituch, T., Maaieh, H., & Strecher, V. (2018) · JMIR mHealth and uHealth · doi:10.2196/10123 · Cited by 189
Digital Interventions on Healthy Lifestyle Management: Systematic Review
Chatterjee, A., Prinz, A., Gerdes, M. W., & Martínez, S. (2021) · Journal of Medical Internet Research · doi:10.2196/26931 · Cited by 229
Müller, A. M., Maher, C. A., Vandelanotte, C., Hingle, M., Middelweerd, A., Lopez, M. L., DeSmet, A., Short, C. E., Nathan, N., Hutchesson, M. J., et al. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8954 · Cited by 180
Metadata
- Authors
- Stephenson, A., McDonough, S. M., Murphy, M. H., Nugent, C. D., & Mair, J. L.
- Affiliations
- University of Ulster (GB)
- Corresponding author
- Stephenson, Aoife
- Venue
- International Journal of Behavioral Nutrition and Physical Activity
- Published
- 2017-08-11
- Volume
- 14
- Issue
- 1
- Pages
- 105-105
- ISSN
- 1479-5868 (ISSN-L)
- PMC
- PMC5553917
- OpenAlex
- W2744204866
- Cited by
- 290
- References
- 59
- Citations by year
- 2026: 16 · 2025: 28 · 2024: 29 · 2023: 25 · 2022: 44 · 2021: 49 · 2020: 52 · 2019: 22 · 2018: 20 · 2017: 4
- FWCI
- 3.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- International Journal of Behavioral Nutrition and Physical Activity (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Ulster University Research Portal (Ulster University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Edinburgh Napier Research Repository (Edinburgh Napier University) (submittedVersion, cc-by)
- Funders
- Ulster University (PhD Scholarship)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- sedentary behavior, technology-based interventions, mobile application, wearable activity trackers, computer-based intervention, behaviour change techniques, sitting time reduction, self-monitoring, prompts and cues, social support, goal setting, healthy adults, intervention effectiveness, attrition, long-term follow-up, risk of bias
- MeSH terms
- Wearable Electronic Devices, Health Promotion, Humans, Health Behavior, Randomized Controlled Trials as Topic, Databases, Factual, Sedentary Behavior, Mobile Applications
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