Cited by 689Behavioral Health and InterventionsMobile Health and mHealth ApplicationsDigital Mental Health Interventions

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A Meta-Analysis of Web-Delivered Tailored Health Behavior Change Interventions

Lustria, Mia Liza A., Noar, Seth M., Cortese, Juliann, Van Stee, Stephanie K., Glueckauf, Robert L., Lee, Junga·2013·Journal of Health Communication

DOI 10.1080/10810730.2013.768727

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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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Yaşlı Kadınlarda Üreme Sağlığı
Kokanalı, D., & Engin Üstün, Y. (n.d.) · DergiPark (Istanbul University) · Cited by 170,090
Content Analysis: An Introduction to its Methodology.
Shelley, M., & Krippendorff, K. (1984) · Journal of the American Statistical Association · doi:10.2307/2288384 · Cited by 24,351
Trim and Fill: A Simple Funnel‐Plot–Based Method of Testing and Adjusting for Publication Bias in Meta‐Analysis
Duval, S., & Tweedie, R. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.00455.x · Cited by 14,099
Book Reviews: Statistical Methods for Meta-Analysis Larry V. Hedges and Ingram Olkin New York: Academic Press, 1985. xxii + 369 pp
Wasserman, S. S., Hedges, L. V., & Olkin, I. (1988) · Journal of Educational Statistics · doi:10.2307/1164953 · Cited by 10,377
Statistical Methods for Meta-Analysis.
Freeman, P. R., Hedges, L. V., & Olkin, I. (1986) · Biometrics · doi:10.2307/2531069 · Cited by 4,840
Meta-Analytic Procedures for Social Research
Rosenthal, R. (1991) · doi:10.4135/9781412984997 · Cited by 4,635
Meta-Analytic Procedures for Social Research.
Metcalfe, A., & Rosenthal, R. (1994) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.2307/2348600 · Cited by 4,249
Answering the Call for a Standard Reliability Measure for Coding Data
Hayes, A. F., & Krippendorff, K. (2007) · Communication Methods and Measures · doi:10.1080/19312450709336664 · Cited by 4,225
Health promotion from the perspective of Social Cognitive Theory
Bandura, A. (1998) · Psychology & Health · doi:10.1080/08870449808407422 · Cited by 3,087
Using the Internet to Promote Health Behavior Change: A Systematic Review and Meta-analysis of the Impact of Theoretical Basis, Use of Behavior Change Techniques, and Mode of Delivery on Efficacy
Webb, T. L., Joseph, J., Yardley, L., & Michie, S. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1376 · Cited by 2,517

Show all 102 references

Research works printed but not linked: 14

Davis S., 2008, Interface on the Internet
10.1111/j.1460–2466.2006. 00280.x · DOI
Lipsey M. W., 2001, Practical meta-analysis: Applied social research methods
10.1001/archinte. 167.9.944 · DOI
Noar S. M., 2009, Communication Yearbook 33, 73
10.3102/10769986008002157 · DOI · Paper page
Shire N., 2002, Journal of Gender-Specific Medicine, 5, 48
10.2196/jmir.113 · DOI
10.1016/j.ypmed.2007. 06.009 · DOI
10.1093/her/cy1096 · DOI
10.1016/S0778–3991(98)00128–1 · DOI
10.1016/j. amepre.2007.12.024 · DOI
10.2307/4597943 · DOI
10.2307/20747900 · DOI

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Background
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Background
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BackgroundInfluential
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Self-citation
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“To date, only 13 (31, 32), suggesting that it might be sensible to offer video, text, or other channels specifically to those who prefer or can benefit from the respective channel.”
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Dance, S., Adams, S. H., Weyman, A. K., Herbert, A., Burke, C., Cassidy, N., Higson‐Sweeney, N., & Dack, C. (2025) · BMC Public Health · doi:10.1186/s12889-025-24508-z · Cited by 3
“Enhanced understanding of the psychosocial context of AU in lower SEP populations may increase the impact of tailored public health interventions, in line with Medical Research Council guidance on intervention design [7] and as demonstrated by tailored public health interventions [8, 9].”
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“…Burgoon & Newton, 1991; Goodwin, 1989), and additionally that audience characteristics such as involvement might determine health message effects (Lustria et al., 2013; Noar, Benac, & Harris, 2007), to date no studies have investigated involvement as an explanatory factor for health conversation…”
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Banna, J. C., Reicks, M. M., Gunther, C. W., Richards, R., Bruhn, C., Cluskey, M., Wong, S. S., Misner, S. L., Hongu, N. K., & Johnston, N. P. (2016) · Nutrition Research and Practice · doi:10.4162/nrp.2016.10.4.456 · Cited by 3
“Evidence suggests that participants in website programs respond to tailored messages with better outcome than information only [46].”
Background
The use of interactive technologies in health promotion and education
Kuang, K. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-816958-2.00001-0 · Cited by 3
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“When tested empirically, tailoring typically adds only small gains in outcomes relative to generic materials, although gains are typically maintained over time [37,38].”
Does personalized mean popular? A content analysis of suicide prevention smartphone applications
Kelly, L. M., Buuh, S., Schick, M. R., Peikes, C., & Zajac, K. (2024) · Current Psychology · doi:10.1007/s12144-024-06169-0 · Cited by 3
“…given its sensitive nature relative to information provided to other apps for which personalization and tailor - ing has been found to be associated with increased popularity and user-rated quality (e.g., Hoeppner et al., 2016, 2017; Krebs et al., 2010; Lustria et al., 2013; Tong et al., 2021).”
Evidence based and intensity specific services in the integrated care setting: Ethical considerations for a developing field.
Maragakis, A., Lindeman, S., & Nolan, J. (2018) · Behavior Analysis Research and Practice · doi:10.1037/bar0000127 · Cited by 3
“…mixed depression and anxiety, PTSD, smoking cessation, drinking, body image, exercise, and weight loss (Andersson, Nordgren, Buhrman, & Carlbring, 2014; Barak, Hen, BonielNissim, & Shapira, 2008; Lustria et al., 2013), and many have similar effect sizes to live therapy (Andersson et al., 2014).”
Background
The Maine Nutrition and Physical Activity Self Assessment for Childcare (NAP SACC) Experience
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“Many of the Center Directors found this to be true which resulted in enhanced environmental changes such as the purchasing of new playground equipment, related to increases in physical activity among children [17].”
Background
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Bakırcı-Taylor, A. L., Reed, D. B., & Colwell, M. J. (2016) · International Quarterly of Community Health Education · doi:10.1177/0272684x16685257 · Cited by 3
“Research has determined that tailored web-based interventions approaches are more effective across a variety of populations than nontailored interventions.(14) The objectives of this study were to determine the effectiveness of the Jump2Health Website on improving selected health practices of parents of International…”
Background
Anti-alcohol campaigns effects depending on target drinking levels and source perception
Stanojlović, M., Cancela, A., Cárdaba, M. Á. M., & Cambra, U. C. (2020) · African journal of rhetoric · doi:10.21134/haaj.v20i1.464 · Cited by 3
“Lustria et al., 2013; Noar, Benac, & Harris, 2007).”
Finding the 'Self' in Self-Regulation: The Identity-Value ModelPreprint
Berkman, E. T., Livingston, J., & Kahn, L. E. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2621251 · Cited by 3
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Garfield, S., & Judah, G. (2021) · BMJ Quality & Safety · doi:10.1136/bmjqs-2021-013381 · Cited by 3
Experiences of Using an Electronic Health Tool Among Health Care Professionals Involved in Chronic Obstructive Pulmonary Disease Management: Qualitative Analysis
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“Furthermore, similar to our findings, previous meta-analyses have demonstrated a positive relationship between an autonomy-supportive health care climate and the personalization of eHealth intervention contents, successful self-management, and behavior change [44,45].”
Fluctuations in mHealth engagement following receipt of goal-discrepant feedback messages
Hurley, L., Gottfredson, N. C., Nezami, B. T., Valle, C. G., & Tate, D. F. (2025) · Digital Health · doi:10.1177/20552076241312569 · Cited by 2
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Beuken, M. J., Kleynen, M., Braun, S. M., van Berkel, K., Kallen, C., Koster, A., Bosma, H., Berendschot, T. T. J. M., Houben, A. J. H. M., Dukers–Muijrers, N. H. T. M., et al. (2025) · JMIR Medical Informatics · doi:10.2196/64479 · Cited by 3
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“Web-based interventions that employ computer-tailoring may have greater effects on health outcomes than those that do not [64]; however, there are uncertainties about the optimal computer-tailoring strategies and it is important to avoid unnecessarily complex computer-tailoring due to the…”
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de Groot, E., Hermans, A.-M., de Jongh, M. A. C., Geuze, R. E., van Dongen, I. M., Hommes, S., Vromans, R., Krahmer, E., Houwen, T., Janssens, K. M. E., et al. (2025) · Journal of Occupational Rehabilitation · doi:10.1007/s10926-025-10309-z · Cited by 2
“Additionally, applications allow for information to be personalized, meaning that information can be provided that is applicable to an individual patient [44].”
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“12,13 For example, messages about care for chronic health conditions may have little appeal to individuals who are healthy and rarely engage the system.”
Background
Morality- and Norm-Based Subgroups of Disability-Sport Athletes Differ on Their Anticipated Guilt and Intentions Toward Doping
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“Developing a more sophisticated specification algorithm could improve content adjustment according to participant profiles [82], potentially incorporating a therapeutic chatbot and artificial intelligence technologies [83].”
Background
Playing a serious game to increase fertility awareness: perceptions of adolescents, parents and teachers
Martins, M. V., Pereira, L., Veleva, Z., Popova, I., Rautakallio-Hokkanen, S., & Galhardo, A. B. (2025) · Human Fertility · doi:10.1080/14647273.2025.2451334 · Cited by 2
“Serious games have been demonstrated to effectively promote informed health behaviours, including increased sexual health literacy and healthier habits among students (Haruna et al., 2019; Lustria et al., 2013; Marchetti et al., 2018).”
Changes in physical activity and sedentary behaviour following geriatric rehabilitation in older adults with stroke
Kraaijkamp, J. J. M., Geerars, M., Chavannes, N. H., Achterberg, W. P., van Isselt, E. F. V. D., & Punt, M. (2025) · BMC Geriatrics · doi:10.1186/s12877-025-06007-3 · Cited by 2
“Previously, researchers identified several barriers that may hamper improvements in sedentary behaviour such as fatigue, lack of knowledge, lack of motivation or fear of falling [27, 28].”
Predicting healthcare-seeking behavior based on stated readiness to act: development and validation of a prediction model
Green, E. P., Pradheep, S., Heinzelman, J., Nyanchoka, A., Achieng, D., Goyal, S., Cusson, L., Kurz, A. S., & Bellows, B. (2021) · Translational Behavioral Medicine · doi:10.1093/tbm/ibab096 · Cited by 2
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Krūmiņa, A. A., & Ļubenko, J. (2016) · Journal of Teacher Education for Sustainability · doi:10.1515/jtes-2016-0006 · Cited by 2
“The analysis of the selected scientific literature sources (Glanz, Rimer & Viswanath, 2008; Kerr, et al., 2006; Lustria et al., 2013; Ruwaard & Kok, 2015) allowed to identify different types of WBI that are useful for the improvement of an individualís health literacy and health behaviour, and most…”
BackgroundInfluential
mHealth literacy: characterizing people’s ability to use smartphone-based health-related applications
Ahmed, S. (2017) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 2
Receipt and Perceived Helpfulness of Mental Illness Information: Findings from the Australian National Survey of Mental Health and Wellbeing
Graham, A. L., Brooker, J., Hasking, P. A., Clarke, D. M., & Meadows, G. N. (2017) · Health Communication · doi:10.1080/10410236.2017.1384355 · Cited by 2
“The preparation of targeted messages (message tailoring) has been found to be an effective strategy in health communication (Lustria et al., 2013).”
Background
E-Health als zentrale Komponente des digitalen Betrieblichen Gesundheitsmanagements – psychologische Ansätze, Erkenntnisse und Evaluationsmethoden
Lippke, S. (2017) · Springer eBooks · doi:10.1007/978-3-658-14550-7_8 · Cited by 2
Tune your sun right
Hussain, M. S., Nicholson, B. D.-R., & Freyne, J. (2017) · Australian Conference on Computer-Human Interaction (OzCHI) · doi:10.1145/3152771.3156137 · Cited by 2
“in health-promoting behavior change and even likely to have a greater impact over generalized interventions [16, 19].”
Background

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.
ORCID: Lustria, Mia Liza A.
Noar, Seth M.
Glueckauf, Robert L.
Lee, Junga
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
DOI: 10.1080/10810730.2013.768727
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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A Meta-Analysis of Web-Delivered Tailored Health Behavior Change Interventions

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