The DOI matches its Crossref record; 31 of the 32 references it cites were found in a registry or an index.
Predicting user adherence to behavioral eHealth interventions in the real world: examining which aspects of intervention design matter most
Abstract
Existing frameworks have identified a range of intervention design features that may facilitate adherence to eHealth interventions; however, empirical data are lacking on whether intervention design features can predict user adherence in the real world-where the public access available tools-and whether some design aspects of behavioral eHealth interventions are more important than others in predicting adherence. This study examined whether intervention design qualities predict user adherence to behavioral eHealth interventions in real-world use and which qualities matter the most. We correlated the online activities of users of 30 web-based behavioral interventions-collected from a proprietary data set of anonymized logs from consenting users of Microsoft Internet Explorer add-on-with interventions' quality ratings obtained by trained raters prior to empirical examination. The quality ratings included: Usability, Visual Design, User Engagement, Content, Therapeutic Persuasiveness (i.e., persuasive design and incorporation of behavior change techniques), and Therapeutic Alliance. We found Therapeutic Persuasiveness (i.e., the incorporation of persuasive design/behavior change principles) to be the most robust predictor of adherence (i.e., duration of use, number of unique sessions; 40 ≤ rs ≤ .58, ps ≤ .005), explaining 42% of the variance in user adherence in our regression model. Results indicated up to six times difference in the percentage of users utilizing the interventions for more than a minimum amount of time and sessions based on Therapeutic Persuasiveness. Findings suggest the importance of persuasive design and behavior change techniques incorporation during the design and evaluation of digital behavioral interventions.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“However, the scope of IMIs seems to be limited by a low uptake and intervention adherence of individuals (Baumel and Yom-Tov, 2018; Baumel et al., 2017).”
From Feasibility of a Software agent providing a brief Intervention for Self-help to Uplift psychological wellbeing (“SISU”). A single-group pretest-posttest trial investigating the potential of SISU to act as therapeutic agent (2021) · cites this paper as Baumel and Yom-Tov, 2018
Citations
Cites
Eysenbach, G. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.1.e11 · Cited by 2,524
Webb, T. L., Joseph, J., Yardley, L., & Michie, S. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1376 · Cited by 2,517
What is user engagement? A conceptual framework for defining user engagement with technology
O'Brien, H. L., & Toms, E. G. (2008) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20801 · Cited by 1,397
Persuasive System Design Does Matter: a Systematic Review of Adherence to Web-based Interventions
Kelders, S. M., Kok, R. N., Ossebaard, H. C., & Van Gemert-Pijnen, J. E. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.2104 · Cited by 1,308
Adherence in Internet Interventions for Anxiety and Depression
Christensen, H., Griffiths, K. M., & Farrer, L. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1194 · Cited by 1,133
Health behavior models in the age of mobile interventions: are our theories up to the task?
Riley, W. T., Rivera, D. E., Atienza, A. A., Nilsen, W., Allison, S. M., & Mermelstein, R. (2011) · Translational Behavioral Medicine · doi:10.1007/s13142-011-0021-7 · Cited by 978
Healthcare via Cell Phones: A Systematic Review
Krishna, S., Boren, S. A., & Balas, E. A. (2009) · Telemedicine and e-Health · doi:10.1089/tmj.2008.0099 · Cited by 882
A Review of eHealth Interventions for Physical Activity and Dietary Behavior Change
Norman, G. J., Zabinski, M. F., Adams, M. A., Rosenberg, D. E., Yaroch, A. L., & Atienza, A. A. (2007) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2007.05.007 · Cited by 605
A Behavior Change Model for Internet Interventions
Ritterband, L. M., Thorndike, F. P., Cox, D. J., Kovatchev, B. P., & Gonder-Frederick, L. A. (2009) · Annals of Behavioral Medicine · doi:10.1007/s12160-009-9133-4 · Cited by 591
van Ballegooijen, W., Cuijpers, P., van Straten, A., Karyotaki, E., Andersson, G., Smit, J. H., & Riper, H. (2014) · PLoS ONE · doi:10.1371/journal.pone.0100674 · Cited by 409
Research works printed but not linked: 1
- Aitken, 2013, Patient apps for improved healthcare from novelty to mainstream
Cited by
Sorted by citations
Items 101–127 of 127
Tael‐Öeren, M., Jordan, I., Coughlin, D., & Turnbull, S. (2022) · JMIR Formative Research · doi:10.2196/25715 · Cited by 2
Kwok, I., Freedman, M. E., Kamsickas, L., Lattie, E. G., Yang, D., & Moskowitz, J. T. (2024) · Journal of Medical Internet Research · doi:10.2196/49714 · Cited by 2
Ha, J., Kim, J. N., Hidalgo, J. E., Noble, N. C., & Price, M. (2024) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-024-00468-w · Cited by 2
Behavior Change in Community Contexts
Trickett, E. J., & Paterson, S. E. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.028 · Cited by 2
Fleming, T. M., Bavin, L. M., Lucassen, M., Stasiak, K., Hopkins, S., & Merry, S. (2020) · doi:10.26686/wgtn.12331259.v4 · Cited by 2
Cost-Effectiveness Evaluations of Behavior Change Interventions
Wang, T., Downes, M., Byrnes, J., & Scuffham, P. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.026 · Cited by 1
Smits, M., Back, N., & Ebbers, W. E. (2023) · Public Health · doi:10.1016/j.puhe.2023.06.027 · Cited by 1
Motivational Factors for Experienced Users of Mobile Health Applications in Heart Failure Management
Flaucher, M., Pruemer, F., Jaeger, K. M., Rolny, J., Trißler, P., Eckl, S., Eskofier, B. M., & Leutheuser, H. (2024) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3677045.3685447 · Cited by 1
Dondanville, K. A., Calloway, A. L., Stade, E. C., Hull, T. D., Jo, B., Huang, S., Hall‐Clark, B. N., LoSavio, S. T., Schuhmann, B. B., Elhusseini, S. A., et al. (2025) · Contemporary Clinical Trials · doi:10.1016/j.cct.2025.108149 · Cited by 2
Saar, C. R., Brandes, O., & Baumel, A. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1586668 · Cited by 1
Self-citationBaumel, A., Brandes, O., & Saar, C. R. (2025) · JMIR Pediatrics and Parenting · doi:10.2196/80420 · Cited by 1
Self-citationMeßner, E.-M., Kraft, R., Baumel, A., Pryss, R. C., & Baumeister, H. (2023) · Springer eBooks · doi:10.1007/978-3-662-65816-1_26 · Cited by 1
Self-citationDelivery of Nurse Psychotherapy: Digital Technologies and Psychotherapy
Kalia, K., & Narikuzhy, S. (2024) · Springer eBooks · doi:10.1007/978-981-97-4738-2_8 · Cited by 1
Pereira, H. V., Teixeira, P. J., Marques, M. M., Carraça, E. V., Silva, M. N., Encantado, J., Santos, I., & Palmeira, A. L. (2021) · Health Psychology and Behavioral Medicine · doi:10.1080/21642850.2021.1885410 · Cited by 1
Shaw, J. (2021) · Open Access Victoria University of Wellington | Te Herenga Waka (Figshare) · doi:10.26686/wgtn.14471310.v1
Fleming, T. M., Bavin, L. M., Lucassen, M., Stasiak, K., Hopkins, S., & Merry, S. (2020) · doi:10.26686/wgtn.12331259.v3
Hagger, M. S., Cameron, L. D., Hamilton, K., Hankonen, N. E., & Lintunen, T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.047
Saar, C. R., Brandes, O., Aderka, I. M., & Baumel, A. (2025) · Journal of Child and Family Studies · doi:10.1007/s10826-025-03094-z
Self-citationFrom prediction to explanation: Using screen text to understand smartphone use and user behaviour
Teng, S., Jia, H. G., D’Alfonso, S., & Kostakos, V. (2026) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2026.103878
Ashur, O., Saar, C. R., Brandes, O., & Baumel, A. (2025) · Internet Interventions · doi:10.1016/j.invent.2025.100895
Self-citationKhan, K., Hall, C. L., Babbage, C. M., Dodzo, S., Greenhalgh, C., Lucassen, M., Merry, S., Sayal, K. S., Sprange, K., Stasiak, K., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26697908
Design, Implement, Sustain: Advancing Program‐Led Interventions for Binge Eating, a Narrative Review
Melisse, B., van Doornik, S. F. W., & Elburg, A. A. V. (2026) · European Eating Disorders Review · doi:10.1002/erv.70118
AlBurno, H., Mercken, L. A. G., de Vries, H., Mohannadi, D. A., & Schneider, F. (2026) · Health Systems · doi:10.1080/20476965.2026.2678819
Claes, S., Vandepitte, S., Clays, E., & Annemans, L. (2026) · BMC Psychology · doi:10.1186/s40359-026-05013-3
Behavioural intervention to improve sleep in childhood epilepsy: the CASTLE RCT programme
Pal, D. K., Gringras, P., Anilkumar, A., Bray, L., Carter, B., Cook, G., Crudgington, H., Currier, J., Hardy, W. A. S., Hughes, D. A., et al. (2025) · Programme Grants for Applied Research · doi:10.3310/gjdp1929
Mohapatra, A., Bhattacharya, S., & Misra, S. (2026) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2026.124849
Drivers of and barriers to adoption of digital therapeutics in five European countries
Fassbender, A., Silva, M., Costa, E., Winders, T. A., Tranchier, D., van Galen, P., Verhoeye, W., Cornet, A., Olisa, N., Schuster, F., et al. (2026) · Digital Health · doi:10.1177/20552076261492350
Metadata
- Authors
- Baumel, A., & Yom-Tov, E.
- Affiliations
- Northwell Health (US)
- Microsoft Research, Herzeliya, Israel
- Corresponding author
- Baumel, Amit
- ORCID
- Baumel, Amit
- Venue
- Translational Behavioral Medicine
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-02-17
- Volume
- 8
- Issue
- 5
- Pages
- 793-798
- ISSN
- 1613-9860 (ISSN-L)
- 1869-6716
- OpenAlex
- W2790152727
- Cited by
- 128
- References
- 32
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 14 · 2023: 8 · 2022: 6 · 2021: 14 · 2020: 59 · 2019: 10 · 2018: 3
- FWCI
- 27.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Translational Behavioral Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- user adherence, intervention design, persuasive design, behaviour change techniques, therapeutic relationship, usability, user engagement, online intervention, real-world applications
- MeSH terms
- Therapeutic Alliance, Adult, Behavior Therapy, Mental Disorders, Humans, Outcome and Process Assessment, Health Care, Patient Compliance, Persuasive Communication, Telemedicine, Internet
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
