Measuring Adherence Within a Self-Guided Online Intervention for Depression and Anxiety: Secondary Analyses of a Randomized Controlled Trial
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Abstract
Background: Self-guided online interventions offer users the ability to participate in an intervention at their own pace and address some traditional service barriers (eg, attending in-person appointments, cost). However, these interventions suffer from high dropout rates, and current literature provides little guidance for defining and measuring online intervention adherence as it relates to clinical outcomes. Objective: This study aims to develop and test multiple measures of adherence to a specific self-guided online intervention, as guided by best practices from the literature. Methods: We conducted secondary analyses on data from a randomized controlled trial of an 8-week online cognitive behavioral program that targets depression and anxiety in college students. We defined multiple behavioral and attitudinal adherence measures at varying levels of effort (ie, low, moderate, and high). Linear regressions were run with adherence terms predicting improvement in the primary outcome measure, the 21-item Depression, Anxiety, and Stress Scale (DASS-21). Results: Of the 947 participants, 747 initiated any activity and 449 provided posttest data. Results from the intent-to-treat sample indicated that high level of effort for behavioral adherence significantly predicted symptom change (F4,746=17.18, P<.001; and β=–.26, P=.04). Moderate level of effort for attitudinal adherence also significantly predicted symptom change (F4,746=17.25, P<.001; and β=–.36, P=.03). Results differed in the initiators-only sample, such that none of the adherence measures significantly predicted symptom change (P=.09-.27). Conclusions: Our findings highlight the differential results of dose-response models testing adherence measures in predicting clinical outcomes. We summarize recommendations that might provide helpful guidance to future researchers and intervention developers aiming to investigate online intervention adherence. Trial Registration: ClinicalTrials.gov NCT04361045; https://clinicaltrials.gov/ct2/show/NCT04361045
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The study by Hanano et al evaluated clinical outcomes in anxiety and depression in terms of treatment adherence.
“The foregoing is consistent with the evidence identified in the study by Hanano et al [86] conducted to evaluate clinical outcomes in anxiety and depression in terms of treatment adherence.”
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
(2010) · Cited by 7,034 · see citing works
Adherence to Long-Term Therapies: Evidence for Action
Geest, S. D., & Sabate, E. J. (2003) · European Journal of Cardiovascular Nursing · doi:10.1016/s1474-5151(03)00091-4 · Cited by 6,274 · see citing works
A Measure of Subjective Happiness: Preliminary Reliability and Construct Validation
Lyubomirsky, S., & Lepper, H. S. (1999) · Social Indicators Research · doi:10.1023/a:1006824100041 · Cited by 4,071 · see citing works
Development and validation of the short grit scale (grit-s)
Duckworth, A. L., & Quinn, P. D. (2009) · Journal of Personality Assessment · doi:10.1080/00223890802634290 · Cited by 3,376 · see citing works
Eysenbach, G. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.1.e11 · Cited by 2,524 · see citing works
Computer-based psychological treatments for depression: A systematic review and meta-analysis
Richards, D., & Richardson, T. (2012) · Clinical Psychology Review · doi:10.1016/j.cpr.2012.02.004 · Cited by 1,442 · see citing works
Internet-Based and Other Computerized Psychological Treatments for Adult Depression: A Meta-Analysis
Andersson, G., & Cuijpers, P. (2009) · Cognitive Behaviour Therapy · doi:10.1080/16506070903318960 · Cited by 1,368 · see citing works
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 · see citing works
Peugh, J., & Enders, C. K. (2004) · Review of Educational Research · doi:10.3102/00346543074004525 · Cited by 1,107 · see citing works
A Systematic Review of the Impact of Adherence on the Effectiveness of e-Therapies
Donkin, L., Christensen, H., Naismith, S. L., Neal, B., Hickie, I. B., & Glozier, N. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1772 · Cited by 876 · see citing works
Hollis, C., Falconer, C. J., Martin, J. L., Whittington, C., Stockton, S., Glazebrook, C., & Davies, E. B. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12663 · Cited by 846 · cited 2× · see citing works
“Recent meta-analyses have shown that both guided and self-guided online interventions can be effective for treating a range of problems such as depression and anxiety [1,3,6].”
BackgroundRyan, R. M., Plant, R., & O'Malley, S. (1995) · Addictive Behaviours · doi:10.1016/0306-4603(94)00072-7 · Cited by 709 · see citing works
Depression Anxiety and Stress Scales (DASS-21): Psychometric analysis across four racial groups
Norton, P. J. (2007) · Anxiety, Stress, & Coping · doi:10.1080/10615800701309279 · Cited by 708 · see citing works
Validation of the PHQ-9 in a psychiatric sample
Beard, C., Hsu, K. J., Rifkin, L. S., Busch, A. B., & Björgvinsson, T. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.12.075 · Cited by 467 · see citing works
Harrer, M., Adam, S. H., Baumeister, H., Cuijpers, P., Karyotaki, E., Auerbach, R. P., Kessler, R. C., Bruffaerts, R., Berking, M., & Ebert, D. D. (2019) · International Journal of Methods in Psychiatric Research · doi:10.1002/mpr.1759 · Cited by 445 · see citing works
Computer‐Aided Psychotherapy for Anxiety Disorders: A Meta‐Analytic Review
Cuijpers, P., Marks, I. M., van Straten, A., Cavanagh, K., Gega, L., & Andersson, G. (2009) · Cognitive Behaviour Therapy · doi:10.1080/16506070802694776 · Cited by 429 · see citing works
Karyotaki, E., Kleiboer, A., Smit, F., Turner, D. T., Pastor, A. M., Andersson, G., Berger, T., Botella, C., Breton, J. M., Carlbring, P., et al. (2015) · Psychological Medicine · doi:10.1017/s0033291715000665 · Cited by 408 · see citing works
Waller, R., & Gilbody, S. (2009) · Psychological Medicine · doi:10.1017/s0033291708004224 · Cited by 393 · cited 1× · see citing works
“Despite the promising nature of self-guided online interventions, multiple reviews report high dropout and poor adherence rates [1,7].”
BackgroundTreatment Engagement with Caregivers of At-risk Children: Gaps in Research and Conceptualization
Staudt, M. M. (2007) · Journal of Child and Family Studies · doi:10.1007/s10826-006-9077-2 · Cited by 349 · see citing works
Beatty, L., & Binnion, C. (2016) · International Journal of Behavioral Medicine · doi:10.1007/s12529-016-9556-9 · Cited by 347 · see citing works
Sieverink, F., Kelders, S. M., & van Gemert-Pijnen, J. E. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.8578 · Cited by 331 · see citing works
Christensen, H., Griffiths, K. M., Korten, A. E., Brittliffe, K., & Groves, C. (2004) · Journal of Medical Internet Research · doi:10.2196/jmir.6.4.e46 · Cited by 240 · see citing works
Maximizing the Impact of e-Therapy and Serious Gaming: Time for a Paradigm Shift
Fleming, T. M., de Beurs, D., Khazaal, Y., Gaggioli, A., Riva, G., Botella, C., Baños, R. M., Aschieri, F., Bavin, L. M., Kleiboer, A., et al. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00065 · Cited by 212 · see citing works
Donkin, L., Hickie, I. B., Christensen, H., Naismith, S. L., Neal, B., Cockayne, N. L., & Glozier, N. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2771 · Cited by 193 · see citing works
Stepwise Multiple Regression Method to Forecast Fish Landing
Ghani, I. M. M., & Ahmad, S. (2010) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2010.12.076 · Cited by 147 · see citing works
Beintner, I., Vollert, B., Zarski, A.-C., Bolinski, F., Musiat, P., Görlich, D., Ebert, D. D., & Jacobi, C. (2019) · Journal of Medical Internet Research · doi:10.2196/14181 · Cited by 89 · see citing works
Web-based depression treatment: Associations of clients׳ word use with adherence and outcome
van der Zanden, R. A., Curie, K., van Londen, M., Kramer, J., Steen, G. J., & Cuijpers, P. J. (2014) · Journal of Affective Disorders · doi:10.1016/j.jad.2014.01.005 · Cited by 60 · see citing works
Mazza, G. L., & Enders, C. K. (2014) · Cambridge University Press eBooks · doi:10.1017/cbo9780511996481.029 · Cited by 34 · see citing works
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- [16]Rith-Najarian L A dissemination and implementation approach to preventing anxiety and depression in young people Doctoral dissertation, University of California Los Angeles 2019 2022-01-26 https://escholarship.org/content/qt6786366q/qt6786366q.pdf
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Potts, C., Kealy, C., McNulty, J. M., Madrid‐Cagigal, A., Wilson, T., Mulvenna, M. D., O’Neill, S. M., Donohoe, G. J., & Barry, M. M. (2025) · Journal of Medical Internet Research · doi:10.2196/72892 · Cited by 57 · see citing works
D'Adamo, L., Paraboschi, L., Claire Grammer, A., Fennig, M., Graham, A. K., Yaeger, L. H., Newman, M. G., Wilfley, D. E., Barr Taylor, C., Eisenberg, D., et al. (2023) · Journal of Behavioral and Cognitive Therapy · doi:10.1016/j.jbct.2023.05.002 · Cited by 37 · see citing works
Jackson, H. M., Calear, A. L., Batterham, P. J., Ohan, J. L., Farmer, G. M., & Farrer, L. M. (2023) · Journal of Medical Internet Research · doi:10.2196/44673 · Cited by 25 · see citing works
Digital Intervention Barriers Scale–7 (DIBS-7): Development, Evaluation, and Preliminary Validation
Ramos, G., Montoya, A. K., Hammons, H. R., Smith, D. A., Chavira, D. A., & Rith‐Najarian, L. (2023) · JMIR Formative Research · doi:10.2196/40509 · Cited by 7 · see citing works
Self-citationHanano, M., Rith‐Najarian, L., Gong-Guy, E., & Chavira, D. A. (2024) · JMIR Formative Research · doi:10.2196/56118 · Cited by 6 · see citing works
Self-citationRohde, J. S., Goldy, S. P., Graziosi, M., Ferguson, M. A., Thrul, J., & Yaden, D. B. (2024) · BMC Psychology · doi:10.1186/s40359-024-01836-0 · Cited by 4 · see citing works
Li, S. H., Achilles, M. R., Subotic-Kerry, M., Werner‐Seidler, A., Newby, J. M., Batterham, P. J., Christensen, H. M., Mackinnon, A. J., & O’Dea, B. (2022) · BMC Psychiatry · doi:10.1186/s12888-022-04383-3 · Cited by 4 · see citing works
Steyn, S., & Slabbert, M. (2024) · JMIR Formative Research · doi:10.2196/54216 · Cited by 4 · see citing works
Leung, D. K. Y., Wong, D. H. S., Wong, F. H. C., Wong, S. M. Y., Chan, O. L. H., Wong, G. H. Y., Chan, W. C., & Lum, T. Y. S. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119756 · Cited by 2 · see citing works
Zhang, N., Lin, H., Wu, X., Zheng, Y., Yin, J., Ding, C., Pan, Q., Yang, S., Luo, H., Zou, X., et al. (2025) · Journal of Medical Internet Research · doi:10.2196/71668 · Cited by 2 · see citing works
Lansing, A. H., Cohen, L. B., Glaser, N. S., & Loomba, L. A. (2024) · JMIR Formative Research · doi:10.2196/59246 · Cited by 2 · see citing works
Conversational Agent Utilization Patterns of Individuals with Autism Spectrum Disorder
Aghakhani, S., Rousseau, A., Mizrahi, S., Tan, X., Dosovitsky, G., Mlodzianowski, L., Marshall, Z., & Bunge, E. L. (2024) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-024-00451-5 · Cited by 2 · see citing works
Bartha, S., Schmidt, S., & Tomczyk, S. (2025) · Internet Interventions · doi:10.1016/j.invent.2025.100827 · Cited by 2 · see citing works
Eylem, Ö., Poulter, S., Ashcroft, K., Robinson, T., Mane, P., Islam, M., Condell, J. V., & Leavey, G. (2024) · BMJ Open · doi:10.1136/bmjopen-2023-083554 · Cited by 2 · see citing works
Dominguez-Rodriguez, A., Sanz-Gomez, S., González Ramírez, L. P., Herdoiza-Arroyo, P. E., Trevino Garcia, L. E., de la Rosa-Gómez, A., González-Cantero, J. O., Macias-Aguinaga, V., Arenas Landgrave, P., & Chávez-Valdez, S. M. (2024) · JMIR Formative Research · doi:10.2196/53767 · Cited by 1 · see citing works
“The foregoing is consistent with the evidence identified in the study by Hanano et al [86] conducted to evaluate clinical outcomes in anxiety and depression in terms of treatment adherence.”
ResultEylem-van Bergeijk, O., Robinson, T., Manktelow, M., Olympios, M., Poulter, S., Mane, P., Panagioti, M., Condell, J., & Leavey, G. (2025) · JMIR mHealth and uHealth · doi:10.2196/70691 · Cited by 2 · see citing works
Duddeck, L., Stolz, T., Zottl, C., Berger, T., & Boettcher, J. (2025) · JMIR Formative Research · doi:10.2196/62781 · Cited by 1 · see citing works
Zhang, T., Feng, W., Sun, Y., Li, Y., Hu, J., Du, X., Lai, L., Ke, Y., Hui, B. P. H., & Ren, Z. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100859 · Cited by 1 · see citing works
Neubert, M., Sünkel, E. T., Planert, J., Hildebrand, A. S., & Klucken, T. (2026) · Internet Interventions · doi:10.1016/j.invent.2026.100915 · Cited by 1 · see citing works
Evia, Á. F. V. D. L. G., Eberle, J. W., Baee, S., Wolfe, E. C., Boukhechba, M., Funk, D., Teachman, B. A., & Barnes, L. E. (2024) · doi:10.31234/osf.io/yucqf · Cited by 1 · see citing works
Evia, Á. F. V. D. L. G., Eberle, J. W., Baee, S., Wolfe, E. C., Boukhechba, M., Funk, D. H., Teachman, B. A., & Barnes, L. E. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000945
Rohde, J. S., Goldy, S. P., Graziosi, M., Ferguson, M. A., Thrul, J., & Yaden, D. B. (2024) · Figshare · doi:10.6084/m9.figshare.26741585
Rohde, J. S., Goldy, S. P., Graziosi, M., Ferguson, M. A., Thrul, J., & Yaden, D. B. (2024) · Figshare · doi:10.6084/m9.figshare.26741582
Kim, J., Lee, S.-H., Shin, C., Han, K.-M., Jeon, S.-W., & Han, C.-S. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.122143
Ribeiro, A. J., & Padovan‐Neto, F. E. (2026) · Current Psychology · doi:10.1007/s12144-026-09830-y
Corthorne, S., Wakelin, K., & Jones, C. J. (2026) · Veterinary Record · doi:10.1002/vetr.71214
- Authors
- Hanano, M., Rith-Najarian, L., Boyd, M., & Chavira, D.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Hanano, Maria
- Venue
- JMIR Mental Health
- Publisher
- JMIR Publications Inc.
- Published
- 2022-03-28
- Volume
- 9
- Issue
- 3
- Pages
- e30754
- ISSN
- 2368-7959 (ISSN-L)
- PMC
- PMC9002610
- OpenAlex
- W3199029986
- Cited by
- 26
- References
- 29
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 10 · 2023: 3 · 2022: 1
- FWCI
- 3.14
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Mental Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
- Keywords
- depression, anxiety, university students, cognitive behavioral therapy, behavioral adherence, dropout, dose-response relationship, DASS-21, mental health interventions
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