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The influence of social networking sites on health behavior change: a systematic review and meta-analysis
Open accessAbstract
Objective Our aim was to evaluate the use and effectiveness of interventions using social networking sites (SNSs) to change health behaviors. Materials and methods Five databases were scanned using a predefined search strategy. Studies were included if they focused on patients/consumers, involved an SNS intervention, had an outcome related to health behavior change, and were prospective. Studies were screened by independent investigators, and assessed using Cochrane's ‘risk of bias’ tool. Randomized controlled trials were pooled in a meta-analysis. Results The database search retrieved 4656 citations; 12 studies (7411 participants) met the inclusion criteria. Facebook was the most utilized SNS, followed by health-specific SNSs, and Twitter. Eight randomized controlled trials were combined in a meta-analysis. A positive effect of SNS interventions on health behavior outcomes was found (Hedges’ g 0.24; 95% CI 0.04 to 0.43). There was considerable heterogeneity (I2 = 84.0%; T2 = 0.058) and no evidence of publication bias. Discussion To the best of our knowledge, this is the first meta-analysis evaluating the effectiveness of SNS interventions in changing health-related behaviors. Most studies evaluated multi-component interventions, posing problems in isolating the specific effect of the SNS. Health behavior change theories were seldom mentioned in the included articles, but two particularly innovative studies used ‘network alteration’, showing a positive effect. Overall, SNS interventions appeared to be effective in promoting changes in health-related behaviors, and further research regarding the application of these promising tools is warranted. Conclusions Our study showed a positive effect of SNS interventions on health behavior-related outcomes, but there was considerable heterogeneity. Protocol registration The protocol for this systematic review is registered at http://www.crd.york.ac.uk/PROSPERO with the number CRD42013004140.
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“Several systematic reviews and meta-analyses [15–19] have shown that these digital technology-based programs resulted in increased PA and reduced body weight, at least for a short duration.”
From A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss (2021) · cites this paper as [18]
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Metadata
- Authors
- Laranjo, L., Arguel, A., Neves, A. L., Gallagher, A. M., Kaplan, R., Mortimer, N., Mendes, G. A., & Lau, A. Y. S.
- Affiliations
- Universidade Nova de Lisboa (PT)
- UNSW Sydney (AU)
- Universidade do Porto (PT)
- Royal Hospital for Women (AU)
- ACES Estuário do Tejo, Lisbon, Portugal
- Corresponding author
- Laranjo, Liliana
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-07-08
- Volume
- 22
- Issue
- 1
- Pages
- 243-256
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC4433372
- OpenAlex
- W2128000797
- Cited by
- 661
- References
- 74
- Citations by year
- 2026: 24 · 2025: 55 · 2024: 51 · 2023: 49 · 2022: 60 · 2021: 66 · 2020: 75 · 2019: 58 · 2018: 78 · 2017: 65 · 2016: 48 · 2015: 30 · 2014: 2
- FWCI
- 7.00
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Funders
- Medical Research Council
- National Health and Medical Research Council (1032664)
- Topics
- Social Sciences › Health › Social Media in Health Education
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Keywords
- social networking sites, health behavior change, Facebook, Twitter, health interventions, multicomponent intervention, health behavior theory, online health promotion
- MeSH terms
- Health Promotion, Humans, Health Behavior, Consumer Health Information, Social Networking, Social Media
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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