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A Meta-Analysis of Web-Delivered Tailored Health Behavior Change Interventions
Abstract
Web-based tailored intervention programs show considerable promise in effecting health-promoting behaviors and improving health outcomes across a variety of medical conditions and patient populations. This meta-analysis compares the effects of tailored versus nontailored web-based interventions on health behaviors and explores the influence of key moderators on treatment outcomes. Forty experimental and quasi-experimental studies (N =20,180) met criteria for inclusion and were analyzed using meta-analytic procedures. The findings indicated that web-based tailored interventions effected significantly greater improvement in health outcomes as compared with control conditions both at posttesting, d =.139 (95% CI = .111, .166, p <.001, k =40) and at follow-up, d =.158 (95% CI = .124, .192, p <.001, k =21). The authors found no evidence of publication bias. These results provided further support for the differential benefits of tailored web-based interventions over nontailored approaches. Analysis of participant/descriptive, intervention, and methodological moderators shed some light on factors that may be important to the success of tailored interventions. Implications of these findings and directions for future research are discussed.
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“Tailoring can have a positive impact on intervention outcomes and engagement, but this varies between studies and contexts.31,52”
From Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions (2016) · cites this paper as [52]
In the citing paper
“Compared to more traditional knowledge transfer methods in digital health (eg, tailored modules), the conversational methods in virtual assistance may be perceived as more personally relevant and humanistic, which is critical given that perceived relevance and the inclusion of social support are associated with increased effect sizes in digital behavior change interventions [7,8].”
From A Physical Activity and Diet Program Delivered by Artificially Intelligent Virtual Health Coach: Proof-of-Concept Study (2020) · cites this paper as [8]
In the citing paper
“Clinically relevant results, such as adopting a healthy lifestyle or adhering to medication, and statistically significant effect sizes of tailored Web-based interventions have been recognized for health behavior change among diverse populations facing chronic disease [20,29,30].”
From Tailored web-based interventions for pain: Systematic review and meta-analysis (2017) · cites this paper as [30]
In the citing paper
“A meta-analysis on tailored Web-based interventions in general found that expert input does not necessarily mean more efficacy [30].”
From Tailored web-based interventions for pain: Systematic review and meta-analysis (2017) · cites this paper as [30]
In the citing paper
“Hence, it has been shown that Web-based tailored interventions that are preventive in nature and targeting a general population, not a specific condition, were more successful [30].”
From Tailored web-based interventions for pain: Systematic review and meta-analysis (2017) · cites this paper as [30]
In the citing paper
“It is generally accepted that user engagement with DBCI is a precursor to improved health outcomes.”
From Understanding Health Behavior Technology Engagement: Pathway to Measuring Digital Behavior Change Interventions (2019) · cites this paper as [5]
In the citing paper
“Growing evidence supports that interaction with DBCI and adherence to intervention features improve the likelihood of reaching desired health outcomes [5].”
From Understanding Health Behavior Technology Engagement: Pathway to Measuring Digital Behavior Change Interventions (2019) · cites this paper as [5]
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Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions
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“Tailoring can have a positive impact on intervention outcomes and engagement, but this varies between studies and contexts.(31,52) Selfdetermination theory,(53) a prominent theory of motivation, argues that autonomy is a fundamental human need that facilitates learning.”
BackgroundApps to promote physical activity among adults: a review and content analysis
Middelweerd, A., Mollee, J. S., van der Wal, C. N., Brug, J., & te Velde, S. J. (2014) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-014-0097-9 · Cited by 546
“, feedback based on the user’s own characteristics [10]) and advice is more likely to be effective than generic information about physical activity [9,11,12].”
BackgroundThe promise of machine learning in predicting treatment outcomes in psychiatry
Chekroud, A. M., Bondar, J., Delgadillo, J., Doherty, G., Wasil, A., Fokkema, M., Cohen, Z., Belgrave, D., DeRubeis, R., Iniesta, R., et al. (2021) · World Psychiatry · doi:10.1002/wps.20882 · Cited by 531
Galiano‐Castillo, N., Cantarero‐Villanueva, I., Fernández‐Lao, C., Ariza‐García, A., Díaz‐Rodríguez, L., del Moral-Ávila, R., & Arroyo‐Morales, M. (2016) · Cancer · doi:10.1002/cncr.30172 · Cited by 349
The impact of self-affirmation on health-behavior change: A meta-analysis
Epton, T., Harris, P. R., Kane, R., van Koningsbruggen, G. M., & Sheeran, P. (2015) · Health Psychology · doi:10.1037/hea0000116 · Cited by 277
Metadata
- Authors
- Lustria, M. L. A., Noar, S. M., Cortese, J., Van Stee, S. K., Glueckauf, R. L., & Lee, J.
- Affiliations
- Florida State University (US)
- University of North Carolina at Chapel Hill (US)
- Yonsei University (KR)
- Corresponding author
- Lustria, Mia Liza A.
- Venue
- Journal of Health Communication
- Publisher
- Informa UK Limited
- Published
- 2013-09
- Volume
- 18
- Issue
- 9
- Pages
- 1039-1069
- ISSN
- 1081-0730 (ISSN-L)
- 1087-0415
- OpenAlex
- W2057902960
- Cited by
- 689
- References
- 102
- Citations by year
- 2026: 25 · 2025: 63 · 2024: 45 · 2023: 62 · 2022: 68 · 2021: 69 · 2020: 61 · 2019: 68 · 2018: 52 · 2017: 57 · 2016: 41 · 2015: 49 · 2014: 25 · 2013: 3
- FWCI
- 4.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Health Communication (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- personalized interventions, online intervention, health behavior change, health-promoting behaviors, health outcomes, treatment moderators, online health interventions
- MeSH terms
- Adolescent, Adult, Behavior Therapy, Child, Female, Follow-Up Studies, Health Promotion, Humans, Male, Middle Aged, Program Evaluation, Health Behavior, Randomized Controlled Trials as Topic, Treatment Outcome, Internet, Young Adult
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