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 improve intervention outcomes and engagement, but the size of this effect differs across studies and settings.
“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]
Perceived relevance and the inclusion of social support are associated with increased effect sizes in digital behavior change interventions.
“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]
Tailored Web-based interventions have been recognized for statistically significant effect sizes for health behavior change among diverse populations facing chronic disease.
“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]
A meta-analysis on tailored Web-based interventions in general found that expert input does not necessarily mean more efficacy.
“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]
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.
“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]
User engagement with DBCI is a precursor to improved health outcomes.
“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]
Interaction with DBCI and adherence to intervention features improve the likelihood of reaching desired health outcomes.
“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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Effects of race, ethnicity, gender, culture, literacy, and social marketing on public health.
Shire, N. J. (2002) · PubMed · Cited by 24 · see citing works
Noël, L. T. (2010) · The Science of Diabetes Self-Management and Care · doi:10.1177/0145721710380145 · Cited by 15 · see citing works
Davis, S. (2008) · CommonKnowledge Research Repository (Pacific University Oregon) · Cited by 7 · see citing works
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Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions
Yardley, L., Spring, B. J., Riper, H., Morrison, L. G., Crane, D. H., Curtis, K., Merchant, G. C., Naughton, F., & Blandford, A. (2016) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2016.06.015 · Cited by 1,118 · see citing works
“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 · see citing works
“, 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 · see citing works
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 · see citing works
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 · see citing works
Just-in-the-Moment Adaptive Interventions (JITAI): A Meta-Analytical Review
Wang, L., & Miller, L. C. (2020) · Health Communication · doi:10.1080/10410236.2019.1652388 · Cited by 264 · see citing works
Rogers, M. A., Lemmen, K., Kramer, R., Mann, J., & Chopra, V. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7111 · Cited by 259 · see citing works
“There were 71 meta-analyses of Internet-based interventions that met eligibility criteria and were included in this study [7-76].”
A Review and Conceptual Framework for Understanding Personalized Matching Effects in Persuasion
Teeny, J. D., Siev, J. J., Briñol, P., & Petty, R. E. (2020) · Journal of Consumer Psychology · doi:10.1002/jcpy.1198 · Cited by 252 · see citing works
“Nonetheless, the present work does not restrict itself to a specific consumer characteristic (e.g., matching the functional basis of an attitude; Carpenter, 2012) nor to a specific content domain (e.g., matching in health domains; Rothman et al., 2020; Lustria et al., 2013).”
BackgroundFischer, B., Robinson, T., Bullen, C., Curran, V., Jutras-Aswad, D., Medina-Mora, M. E., Pacula, R. L., Rehm, J., Room, R., Brink, W. V. D., et al. (2022) · International Journal of Drug Policy · doi:10.1016/j.drugpo.2021.103381 · Cited by 236 · see citing works
Western, M. J., Armstrong, M. E. G., Islam, I., Morgan, K., Jones, U., & Kelson, M. J. (2021) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-021-01218-4 · Cited by 218 · see citing works
“As the importance of personalisation of digital behaviour change tools is increasingly recognised and tailored interventions are being implemented [76, 84, 85], ensuring that contextual factors related to SES that may influence behaviour are catered for would be a useful direction for further intervention research.”
BackgroundLunde, P., Nilsson, B. B., Bergland, A., Kværner, K. J., & Bye, A. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9751 · Cited by 214 · see citing works
“Another meta-analyses (n=20,000) supports this and concludes that tailored Web-based interventions was significantly more effective in improving health outcomes compared with nontailored Web-based interventions [14].”
BackgroundArcia, A., Suero-Tejeda, N. M., Bales, M. E., Merrill, J. A., Yoon, S., Woollen, J., & Henry, S. B. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv079 · Cited by 193 · see citing works
The history and future of digital health in the field of behavioral medicine
Arigo, D., Jake‐Schoffman, D. E., Wolin, K. Y., Beckjord, E. B., Hekler, E. B., & Pagoto, S. (2019) · Journal of Behavioral Medicine · doi:10.1007/s10865-018-9966-z · Cited by 189 · see citing works
Sorgente, A., Pietrabissa, G., Manzoni, G. M., Re, F., Simpson, S., Perona, S., Rossi, A., Cattivelli, R., Innamorati, M., Jackson, J. B., et al. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6972 · Cited by 165 · see citing works
“In terms of gender, nine systematic reviews reported no gender-specific data [32-36]; the majority of reviews that included information on participant gender had samples with more female participants than male participants.”
BackgroundPublic Health Messaging during the COVID-19 Pandemic and Beyond: Lessons from Communication Science
Nan, X., Iles, I. A., Yang, B. K., & Ma, Z. (2021) · Health Communication · doi:10.1080/10410236.2021.1994910 · Cited by 183 · see citing works
“The use of internet and computer-mediated communication drastically increased the efficiency and precision of health message tailoring (Lustria et al., 2009, 2013).”
BackgroundHsu, M. S. H., Rouf, A. S., & Allman-Farinelli, M. A. (2018) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2018.06.009 · Cited by 178 · see citing works
Morrison, L. G., Hargood, C., Pejovic, V., Geraghty, A. W. A., Lloyd, S., Goodman, N., Michaelides, D. T., Weston, A., Musolesi, M., Weal, M. J., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169162 · Cited by 162 · see citing works
Finding The “Self” in Self-Regulation: The Identity-Value Model
Berkman, E. T., Livingston, J., & Kahn, L. E. (2017) · Psychological Inquiry · doi:10.1080/1047840x.2017.1323463 · Cited by 172 · see citing works
“As expected, tailored messages are generally more effective than generic ones at promoting health behavior change (Krebs, Prochaska, & Rossi, 2010; Lustria et al., 2013).”
The Science of Using Science: Researching the Use of Research Evidence in Decision-Making
Langer, L., Tripney, J., & Gough, D. (2016) · UCL Discovery (University College London) · Cited by 166 · see citing works
Maher, C. A., Davis, C. R., Curtis, R. G., Short, C. E., & Murphy, K. J. (2020) · JMIR mHealth and uHealth · doi:10.2196/17558 · Cited by 165 · see citing works
“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 increa…”
BackgroundBatterham, P. J., & Calear, A. L. (2017) · JMIR Mental Health · doi:10.2196/mental.7722 · Cited by 161 · see citing works
“The desire for briefer programs may be met by the tailoring of content to individual needs [32], a greater focus on the core components of cognitive and behavioral therapies with an emphasis on overlearning [33], and delivery of activities to practice therapeutic strategies delivered offline through stand-alone worksh…”
BackgroundMedication nonadherence: health impact, prevalence, correlates and interventions
Stewart, S.-J., Moon, Z., & Horne, R. (2022) · Psychology and Health · doi:10.1080/08870446.2022.2144923 · Cited by 180 · see citing works
“…is supported by research that consistently demonstrates that tailored interventions are likely to be more effective than non-tailored interventions (gatwood et al., 2016; Horne et al., 2019; Kassavou & Sutton, 2017, 2018; lustria et al., 2013; Noar et al., 2007, 2011; Sainsbury et al., 2020).”
BackgroundCole-Lewis, H., Ezeanochie, N., & Turgiss, J. (2019) · JMIR Formative Research · doi:10.2196/14052 · Cited by 155 · see citing works
The Impact of the COVID-19 Pandemic on US College Students’ Physical Activity and Mental Health
Wilson, O. W. A., Holland, K. E., Elliott, L. D., Duffey, M., & Bopp, M. (2021) · Journal of Physical Activity and Health · doi:10.1123/jpah.2020-0325 · Cited by 161 · see citing works
Schippers, M., Adam, P. C. G., Smolenski, D. J., Wong, H. T. H., & de Wit, J. B. F. (2017) · Obesity Reviews · doi:10.1111/obr.12492 · Cited by 150 · see citing works
“Internet-based behaviour change interventions have been found effective in improving various health behaviours (19 – 21), and systematic reviews suggest there is evidence that Internet-based health behaviour interventions can be effective in promoting weight loss (22,23).”
Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges
Pejović, V., & Musolesi, M. (2013) · Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) · doi:10.48550/arxiv.1306.2356 · Cited by 150 · see citing works
“We base this assumption on the recent evidence of the importance of personally tailored messages for inducing behaviour change [Lustria et al. 2013], and of the highly personalised patterns in human-mobile interaction [Pejovic and Musolesi 2014b].”
Health and Fitness App Use in College Students: A Qualitative Study
Gowin, M., Cheney, M., Gwin, S., & Franklin Wann, T. (2015) · American Journal of Health Education · doi:10.1080/19325037.2015.1044140 · Cited by 148 · see citing works
A systematic review of tailored eHealth interventions for weight loss
Ryan, K., Dockray, S., & Linehan, C. (2019) · DIGITAL HEALTH · doi:10.1177/2055207619826685 · Cited by 183 · see citing works
“Previous work on tailoring has met with difficulty in differentiating the range of approaches to tailoring, differences in modality, intervention features and components.(10) In addition, Harrington and Noar(16) have called for improved reporting standards in tailored research.”
BackgroundMethodResultInfluentialTowards Health (Aware) Recommender Systems
Schäfer, H., Hors-Fraile, S., Karumur, R. P., Valdez, A. S. C., Said, A., Torkamaan, H., Ulmer, T., & Trattner, C. (2017) · International Conference on Digital Health · doi:10.1145/3079452.3079499 · Cited by 139 · see citing works
“[26]indicatesthatphysical activities(42%),nutrition(25%),smoking(18%),anddrinking(9”
Muench, F. J., & Baumel, A. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7463 · Cited by 138 · see citing works
“…intervention itself is typically tailored according to components of behavior change theories, with readiness or importance of change being the most frequently used [5,12,22], nearly every component of a digital trigger (ie, content, frequency, interactivity) can be tailored to increase engagement.”
Tong, H. L., Quiroz, J. C., Kocaballi, A. B., Fat, S. C. M., Dao, K. P., Gehringer, H., Chow, C. K., & Laranjo, L. (2021) · Preventive Medicine · doi:10.1016/j.ypmed.2021.106532 · Cited by 136 · see citing works
Antypas, K., & Wangberg, S. C. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3132 · Cited by 137 · see citing works
“Tailored health information is generally perceived as more interesting and personally relevant, better liked, more thoroughly read and discussed, and better remembered than nontailored educational material [16,20,24-27].”
InfluentialSchulz, D. N., Kremers, S., Vandelanotte, C., van Adrichem, M. J., Schneider, F., Candel, M. J. J. M., & de Vries, H. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3094 · Cited by 134 · see citing works
“The effect sizes were small which is common for computer-tailored interventions, but they can still result in a large public health impact when widely implemented [14,59].”
BackgroundConceptualising Mobility as a Service
Giesecke, R., Surakka, T., & Hakonen, M. (2016) · International Conference on Ecological Vehicles and Renewable Energies · doi:10.1109/ever.2016.7476443 · Cited by 96 · see citing works
Morrison, L. G. (2015) · DIGITAL HEALTH · doi:10.1177/2055207615595335 · Cited by 116 · see citing works
“1,2 However, low reported effect sizes and lack of sustained usage of DIs highlights the need to further understand how engagement with, and effectiveness of, DIs can be optimised.”
BackgroundSahin, C., Courtney, K. L., Naylor, P., & E Rhodes, R. (2019) · DIGITAL HEALTH · doi:10.1177/2055207619845279 · Cited by 133 · see citing works
“Computer-tailored interventions were effective on health behavior change,(24,25) but there is a lack of knowledge in tailoring message design and delivery mode and other intervention components in these interventions.(24) Previously, tailoring was considered as a “unitary construct” as opposed to either personalized a…”
BackgroundHornstein, S., Zantvoort, K., Lueken, U., Funk, B., & Hilbert, K. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1170002 · Cited by 134 · see citing works
“In line with that idea, a meta-analysis from 2013 showed that algorithm-based tailoring of DMHIs is associated with better outcomes (23).”
BackgroundResultDuan, Y. P., Wienert, J., Hu, C., Si, G. Y., & Lippke, S. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7152 · Cited by 131 · see citing works
“A meta-analysis by Lustria et al [12] concluded that tailored Web-based interventions could lead to significant improvement in health outcomes at posttesting ( d =.14) and follow-up ( d =. 16).”
Dao, K. P., Cocker, K. A. D., Tong, H. L., Kocaballi, A. B., Chow, C. K., & Laranjo, L. (2021) · JMIR mhealth and uhealth · doi:10.2196/22890 · Cited by 133 · see citing works
“Personalization has been commonly suggested as a way to make interventions more engaging, effective, and better received by users [57-60].”
BackgroundWeb-based health interventions for family caregivers of elderly individuals: A Scoping Review
Wasilewski, M. B., Stinson, J., & Cameron, J. I. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.04.009 · Cited by 127 · see citing works
Golsteijn, R. H. J., Bolman, C. A. W., Volders, E., Peels, D. A., de Vries, H., & Lechner, L. (2018) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-018-0734-9 · Cited by 119 · see citing works
Pouls, B. P. H., Vriezekolk, J. E., Bekker, C. L., Linn, A. J., van Onzenoort, H. A. W., Vervloet, M., van Dulmen, S., & van den Bemt, B. J. F. (2021) · Journal of Medical Internet Research · doi:10.2196/18901 · Cited by 123 · see citing works
Gamification as a tool for engaging student learning: A field experiment with a gamified app
Welbers, K., Konijn, E. A., Burgers, C. F., de Vaate, N. A. J. D. B., Eden, A., & Brugman, B. C. (2019) · E-Learning and Digital Media · doi:10.1177/2042753018818342 · Cited by 137 · see citing works
Cigarette Smoking in South Korea: A Narrative Review
Gunter, R., Szeto, E. H., Jeong, S., Suh, S. A., & Waters, A. J. (2019) · Korean Journal of Family Medicine · doi:10.4082/kjfm.18.0015 · Cited by 114 · see citing works
Videoconferencing in psychiatry, a meta-analysis of assessment and treatment
Drago, A., Winding, T. N., & Antypa, N. (2016) · European Psychiatry · doi:10.1016/j.eurpsy.2016.03.007 · Cited by 106 · see citing works
Twomey, C., O’Reilly, G., & Meyer, B. (2017) · Psychiatry Research · doi:10.1016/j.psychres.2017.06.081 · Cited by 103 · see citing works
Using New Technologies to Improve the Prevention and Management of Chronic Conditions in Populations
Oldenburg, B. F., Taylor, C. B., O'Neil, A. E., Cocker, F., & Cameron, L. D. (2015) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-031914-122848 · Cited by 104 · see citing works
Voorheis, P., Zhao, A., Kuluski, K., Pham, Q., Scott, T., Sztur, P., Khanna, N., Ibrahim, M., & Petch, J. (2022) · JMIR mHealth and uHealth · doi:10.2196/35799 · Cited by 94 · see citing works
“Tailoring mHealth content to users’ unique behavioral, clinical, and personal needs can help facilitate the delivery of features to support effective engagement [33].”
BackgroundCommunicating With Vaccine-Hesitant Parents: A Narrative Review
Limaye, R. J., Opel, D. J., Dempsey, A. F., Ellingson, M. K., Spina, C. I., Omer, S. B., Dudley, M. Z., Salmon, D. A., & O’Leary, S. T. (2021) · Academic Pediatrics · doi:10.1016/j.acap.2021.01.018 · Cited by 99 · see citing works
Dennison, L., Morrison, L., Lloyd, S., Phillips, D., Stuart, B., Williams, S., Bradbury, K., Roderick, P., Murray, E., Michie, S., et al. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3199 · Cited by 98 · see citing works
Nurmi, J., Knittle, K. P., Ginchev, T., Khattak, F., Helf, C., Zwickl, P., Castellano‐Tejedor, C., Lusilla, P., Costa‐Requena, J., Ravaja, N., et al. (2019) · JMIR mhealth and uhealth · doi:10.2196/12884 · Cited by 93 · see citing works
“In line with the self-determination theory, participants valued the autonomy supportive features, such as the tailoring of goals, behaviors, and activities, instead of an externally set behavioral target, as seen in previous Web-based interventions [92,96].”
Pope, J. P., Pelletier, L. G., & Guertin, C. (2017) · Health Communication · doi:10.1080/10410236.2017.1331305 · Cited by 96 · see citing works
“Although message tailoring has received less empirical attention compared to message framing, there is some agreement amongst scholars that tailored messages are much more effective than non-tailored or generic messages (e.g., Lustria et al., 2013; Noar, Benac, & Harris, 2007; Sohl & Moyer, 2007).”
BackgroundInfluentialFeatures of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses
Syrowatka, A., Krömker, D., Meguerditchian, A. N., & Tamblyn, R. M. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.4982 · Cited by 96 · see citing works
“The negative effects of tailoring and patient narratives on quality of decision making in decision aids were unexpected, considering the positive impact of tailoring and patient narratives when employed in behavior change interventions [111-113].”
Al-Dhahir, I., Reijnders, T., Faber, J. S., van den Berg-Emons, R. J. G., Janssen, V. R., Kraaijenhagen, R. A., Visch, V., Chavannes, N. H., & Evers, A. W. M. (2022) · Journal of Medical Internet Research · doi:10.2196/34229 · Cited by 91 · see citing works
“The use of the latest information and communication technologies, such as websites, smartphones, email, text messaging, tablets, and smartwatches [16], offers health professionals and researchers more options to tailor intervention content to the specific needs and characteristics of the user [17].”
Tailored web-based interventions for pain: Systematic review and meta-analysis
Martorella, G., Boitor, M., Berube, M., Fredericks, S., Le May, S., & Gélinas, C. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.8826 · Cited by 88 · see citing works
“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].”
BackgroundInfluentialNelson, L. A., Coston, T. D., Cherrington, A., & Osborn, C. Y. (2016) · Current Diabetes Reports · doi:10.1007/s11892-016-0755-1 · Cited by 83 · see citing works
Tailored health communication: Opportunities and challenges in the digital era
Bol, N., Smit, E. S., & Lustria, M. L. A. (2020) · Digital Health · doi:10.1177/2055207620958913 · Cited by 86 · see citing works
Self-citationWeymann, N., Dirmaier, J., von Wolff, A., Kriston, L., & Härter, M. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3904 · Cited by 73 · see citing works
“Computer tailoring strategies such as the individualization and personalization of information, as well as an interactive presentation, have been found to effectively increase the exposure to [42] and effectiveness of Web-delivered interventions [43,44].”
Wyatt, J. C. (2018) · BMC Medicine · doi:10.1186/s12916-018-1211-7 · Cited by 61 · see citing works
Joyal‐Desmarais, K., Scharmer, A., Madzelan, M. K., See, J. V., Rothman, A. J., & Snyder, M. (2022) · Psychological Bulletin · doi:10.1037/bul0000377 · Cited by 88 · see citing works
Morrison, L. G., Hargood, C., Lin, S. X., Dennison, L., Joseph, J., Hughes, S., Michaelides, D. T., Johnston, D., Johnston, M., Michie, S., et al. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3579 · Cited by 79 · see citing works
Ariza‐García, A., Lozano‐Lozano, M., Galiano‐Castillo, N., Postigo-Martín, P., Arroyo‐Morales, M., & Cantarero‐Villanueva, I. (2019) · Journal of Medical Internet Research · doi:10.2196/14418 · Cited by 80 · see citing works
“However, the participants did not receive an adequate tailored intervention [21], or audiovisual material was used [22].”
mHealth Pilot Study: Text Messaging Intervention to Promote HPV Vaccination
Lee, H. Y., Koopmeiners, J. S., McHugh, J., Raveis, V. H., & Ahluwalia, J. S. (2015) · American Journal of Health Behavior · doi:10.5993/ajhb.40.1.8 · Cited by 80 · see citing works
Friederichs, S. A. H., Oenema, A., Bolman, C. A. W., & Lechner, L. (2015) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-015-0262-9 · Cited by 74 · see citing works
“Delivery via the internet makes it possible to reach large numbers of people for relatively low costs [10, 11, 13, 14].”
BackgroundJander, A., Crutzen, R., Mercken, L. A. G., Candel, M. J. J. M., & de Vries, H. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.4708 · Cited by 75 · see citing works
“Computer-tailored interventions have been shown repeatedly to effectively change various health behaviors and their determinants [16-18], although their effect sizes are generally small to medium.”
Using personas to tailor educational messages to the preferences of coronary heart disease patients
Vosbergen, S., Mulder-Wiggers, J. M. R., Lacroix, J. P. W., Kemps, H., Kraaijenhagen, R. A., Jaspers, M., & Peek, N. B. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.09.004 · Cited by 72 · see citing works
Physical activity and nutrition interventions for older adults with cancer: a systematic review
Forbes, C. C., Swan, F., Greenley, S. L., Lind, M., & Johnson, M. J. (2020) · Journal of Cancer Survivorship · doi:10.1007/s11764-020-00883-x · Cited by 71 · see citing works
Liu, Y., Yan, W., Hu, B., Li, Z., & Lai, Y. L. (2022) · Digital Health · doi:10.1177/20552076221129718 · Cited by 73 · see citing works
Pot, M., Paulussen, T. G., Ruiter, R. A., Eekhout, I., de Melker, H. E., Spoelstra, M. E., & van Keulen, H. M. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7449 · Cited by 62 · see citing works
“Meta-analyses have shown computer-tailored interventions to be more effective than universal interventions in achieving behavioral change outcomes (eg, [20,21]).”
Personalised nutrition: the role of new dietary assessment methods
Forster, H., Walsh, M. C., Gibney, M. J., Brennan, L., & Gibney, E. R. (2015) · Proceedings of The Nutrition Society · doi:10.1017/s0029665115002086 · Cited by 70 · see citing works
Beevers, C. G., Pearson, R., Hoffman, J. S., Foulser, A. A., Shumake, J., & Meyer, B. (2017) · Journal of Consulting and Clinical Psychology · doi:10.1037/ccp0000171 · Cited by 69 · see citing works
“There are a number of successful interventions for other health conditions that have taken such a tailored approach which tend to outperform their nontailored counterparts (Krebs, Prochaska, & Rossi, 2010; Lustria et al., 2013).”
BackgroundAcceptability and feasibility of a self-management intervention for women prescribed tamoxifen
Moon, Z., Moss-Morris, R. E., Hunter, M. S., Goodliffe, S., & Hughes, L. D. (2019) · Health Education Journal · doi:10.1177/0017896919853856 · Cited by 66 · see citing works
“While further testing in an RCT is necessary, the results from this study are promising, showing small improvements to adherence and the potential for further improvements by modifying several key variables such as medication beliefs and side-effects.”
BackgroundInfluentialElbert, S., Dijkstra, A., & Oenema, A. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5056 · Cited by 69 · see citing works
“Furthermore, tailoring can have beneficial effects in health interventions over providing nontailored information, for example, by increasing the relevance of the information [17-20].”
Simons, D., Bourdeaudhuij, I. D., Clarys, P., Cocker, K. A. D., Vandelanotte, C., & Deforche, B. I. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.8287 · Cited by 65 · see citing works
“Previously, it has been shown that individually tailored feedback and advice (ie, based on the user’s own characteristics [93]) is more likely to be effective than generic information about PA [94-96].”
BackgroundPhillips, W. J. (2019) · Current Psychology · doi:10.1007/s12144-019-00452-1 · Cited by 67 · see citing works
Bol, N., Høie, N. M., Nguyen, M. H., & Smit, E. S. (2019) · Digital Health · doi:10.1177/2055207619888074 · Cited by 62 · see citing works
“Such tailored information is expected to benefit a variety of (health-related) outcomes because it provides personally relevant feedback.(20,21,50) Based on the findings of our study, future mobile health apps may benefit from adding customization features to ensure that – especially for those with a greater need for…”
BackgroundShort, C. E., Rebar, A. L., James, E. L., Duncan, M. J., Courneya, K. S., Plotnikoff, R. C., Crutzen, R., & Vandelanotte, C. (2016) · Journal of Cancer Survivorship · doi:10.1007/s11764-016-0565-0 · Cited by 63 · see citing works
Schayck, T. S.-V., Tuithof, M., Otten, R., Engels, R. C. M. E., & Kleinjan, M. (2019) · European Addiction Research · doi:10.1159/000498988 · Cited by 63 · see citing works
Reinwand, D. A., Schulz, D. N., Crutzen, R., Kremers, S. P., & de Vries, H. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3932 · Cited by 62 · see citing works
“Consequently, computer-tailored interventions provide feedback that is more relevant to the individual, contains less redundant information, and is more likely to be processed and remembered than generic information [7-10].”
Xu, X., Ge, Z., Chow, E. P. F., Yu, Z. T., Lee, D. M., Wu, J., Ong, J. J., Fairley, C. K., & Zhang, L. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11071818 · Cited by 62 · see citing works
“Our web-based HIV/STI risk-prediction tool may offer a useful method for potential sexual behavioural interventions to reduce future HIV/STI risk in addition to just promoting testing [53].”
MethodLustria, M. L. A., Cortese, J., Gerend, M. A., Schmitt, K., Kung, Y. M., & McLaughlin, C. (2016) · Health Psychology · doi:10.1037/hea0000399 · Cited by 62 · see citing works
Self-citationPalacios, J. E., Lee, G., Duaso, M. J., Clifton, A., Norman, I. J., Richards, D., & Barley, E. A. (2017) · The Journal of Cardiovascular Nursing · doi:10.1097/jcn.0000000000000392 · Cited by 62 · see citing works
Gold, N., Yau, A., Rigby, B., Dyke, C., Remfry, E. A., & Chadborn, T. (2021) · Journal of Medical Internet Research · doi:10.2196/19688 · Cited by 56 · see citing works
Web-Based Multidomain Lifestyle Programs for Brain Health: Comprehensive Overview and Meta-Analysis
Wesselman, L. M. P., Hooghiemstra, A. M., Schoonmade, L. J., de Wit, M. C., van der Flier, W. M., & Sikkes, S. A. M. (2019) · JMIR Mental Health · doi:10.2196/12104 · Cited by 60 · see citing works
“The adherence rates of the described studies were moderate to good and might be related to the tailoring of content [19,20].”
BackgroundResultFood structure, function and artificial intelligence
Mengucci, C., Ferranti, P., Romano, A., Masi, P., Picone, G., & Capozzi, F. (2022) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2022.03.015 · Cited by 60 · see citing works
Levin, M. E., Haeger, J., & Cruz, R. A. (2019) · Mindfulness · doi:10.1007/s12671-018-1004-2 · Cited by 59 · see citing works
Chaplais, E., Naughton, G. A., Thivel, D., Courteix, D., & Greene, D. (2015) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2014.0197 · Cited by 58 · see citing works
“22 This systematic review provides a comparative evaluation of the effectiveness of smartphones in multidisciplinary treatment of childhood obesity in the last 5 years, with a specific interest in behavior change.”
Meng, X., Fang, S., Zhang, S., Li, H., Ma, D., Ye, Y., Su, J.-P., & Sun, J. (2022) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2022.104236 · Cited by 58 · see citing works
Conceptual tensions and practical trade-offs in tailoring implementation interventions
McHugh, S., Riordan, F., Curran, G. M., Lewis, C. C., Wolfenden, L., Presseau, J., Lengnick‐Hall, R., & Powell, B. J. (2022) · Frontiers in Health Services · doi:10.3389/frhs.2022.974095 · Cited by 56 · see citing works
“The behavioral science field also grapples with clarifying the distinction between interventions customized at the individual level (24, 25), and targeted interventions which are modified in advance based on selected characteristics of population subgroups (26).”
BackgroundSimons, D., De Bourdeaudhuij, I., Clarys, P., De Cocker, K., Vandelanotte, C., & Deforche, B. (2018) · JMIR mHealth and uHealth · doi:10.2196/10003 · Cited by 56 · see citing works
“Providing individually tailored feedback and advice (ie, based on users’ own characteristics [79]) has shown to be important for the engagement with and effectiveness of health behavioral change interventions [80-82].”
Storm, V., Dörenkämper, J., Reinwand, D. A., Wienert, J., de Vries, H., & Lippke, S. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5147 · Cited by 56 · see citing works
“Previous studies on computer-tailored Web-based health behavior change interventions provided positive results for a variety of health behaviors, including physical activity [44-48], fruit and vegetable consumption [49,50], and multiple health behaviors [51-53] among the general adult population as well as people with…”
Bott, N. T., Hall, A., Madero, E. N., Glenn, J. M., Fuseya, N., Gills, J. L., & Gray, M. (2019) · Nutrients · doi:10.3390/nu11092258 · Cited by 54 · see citing works
“Adherence to digitally delivered programs is an important area of current research [91,92], with evidence supporting the role of content and intervention tailoring to specific populations and individuals to improve adherence [93,94].”
BackgroundFunctional Mechanisms of Health Behavior Change Techniques: A Conceptual Review
Michaelsen, M. M., & Esch, T. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.725644 · Cited by 55 · see citing works
“Meta-analyses have shown that interventions that have participant-relevant content and trigger participant engagement tend to be more effective (Noar et al., 2007; Lustria et al., 2013).”
BackgroundFriederichs, S. A. H., Oenema, A., Bolman, C. A. W., Guyaux, J., van Keulen, H. M., & Lechner, L. (2014) · BMC Public Health · doi:10.1186/1471-2458-14-212 · Cited by 54 · see citing works
“In the last decade, more and more computer tailored interventions are web-based, instead of print-delivered, which allows for more interactivity, higher accessibility and lower costs [11,14,15].”
BackgroundInterventions to Improve Adolescent Vaccination
Dempsey, A. F., & Zimet, G. D. (2015) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2015.04.013 · Cited by 54 · see citing works
Forster, H., Walsh, M. C., O’Donovan, C. B., Woolhead, C., McGirr, C., Daly, E. J., O'Riordan, R., Celis-Morales, C. A., Fallaize, R., Macready, A. L., et al. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5620 · Cited by 54 · see citing works
Kresovich, A., & Noar, S. M. (2020) · Journal of Health Communication · doi:10.1080/10810730.2020.1818148 · Cited by 54 · see citing works
Self-citationAraujo, T., & Bol, N. (2023) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2023.100030 · Cited by 56 · see citing works
Huang, L., Huhulea, E. N., Abraham, E., Bienenstock, R., Aifuwa, E., Hirani, R., Schulhof, A., Tiwari, R. K., & Etienne, M. (2025) · Medicina · doi:10.3390/medicina61020358 · Cited by 58 · see citing works
“In contrast, NLP-powered assistants offer dynamic, conversational interactions that feel more personalized and supportive, leading to better outcomes in digital behavior change interventions [57,58].”
Inter-individual differences in attitude content: Cognition, affect, and attitudes
Haddock, G., & Maio, G. R. (2018) · Advances in experimental social psychology · doi:10.1016/bs.aesp.2018.10.002 · Cited by 52 · see citing works
- 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 · 2012: 1
- 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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