Reminders make people adhere better to a self-help sleep intervention
Open accessAbstract
The experiment presented in this paper investigated the effects of different kinds of reminders on adherence to automated parts of a cognitive behavioural therapy for insomnia (CBT-I) delivered via a mobile device. Previous studies report that computerized health interventions can be effective. However, treatment adherence is still an issue. Reminders are a simple technique that could improve adherence. A minimal intervention prototype in the realm of sleep treatment was developed to test the effects of reminders on adherence. Two prominent ways to determine the reminder-time are: a) ask users when they want to be reminded, and b) let an algorithm decide when to remind users. The prototype consisted of a sleep diary, a relaxation exercise and reminders. A within subject design was used in which the effect of reminders and two underlying principles were tested by 45 participants that all received the following three different conditions (in random order): a) event-based reminders b) time-based reminders c) no reminders. Both types of reminders improved adherence compared to no reminders. No differences were found between the two types of reminders. Opportunity and self-empowerment could partly mediate adherence to filling out the sleep diary, but not to the number of relaxation exercises conducted. Although the study focussed on CBT-I, we expect that designers of other computerized health interventions benefit from the tested opportunity and self-empowerment principles for reminders to improve adherence, as well.
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Email reminders have shown to be effective for increasing adherence to interventions.
“In order to increase the adherence to the intervention the platform will send email reminders, a tool that has shown to be effective for this purpose (Horsch et al., 2017).”
From A Self-Applied Multi-Component Psychological Online Intervention Based on UX, for the Prevention of Complicated Grief Disorder in the Mexican Population During the COVID-19 Outbreak: Protocol of a Randomized Clinical Trial (2021) · cites this paper as Horsch et al., 2017
The Discussion and conclusion reports that reminders increased adherence to sleep-diary and relaxation activities in a mobile sleep intervention. The Method describes smartphone-generated reminders; although participants received procedural emails, the paper does not show that email reminders increased adherence. (LLM, conf=0.88)
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Cites
Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414 · see citing works
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035 · see citing works
Ryan, R. M., & Deci, E. L. (2000) · American Psychologist · doi:10.1037//0003-066x.55.1.68 · Cited by 27,815 · see citing works
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241 · see citing works
A Theory of Cognitive Dissonance
Morvan, C., & O’Connor, A. (2017) · Macat Library eBooks · doi:10.4324/9781912282432 · Cited by 18,284 · see citing works
Michie, S., van Stralen, M. M., & West, R. (2011) · Implementation Science · doi:10.1186/1748-5908-6-42 · Cited by 13,697 · see citing works
Reconsidering Baron and Kenny: myths and truths about mediation analysis
Zhao, X., Lynch, J. G., & Chen, Q. (2010) · Journal of Consumer Research · doi:10.1086/651257 · Cited by 12,583 · see citing works
Trust and TAM in Online Shopping: An Integrated Model1
Gefen, D., Karahanna, E., & Straub, D. W. (2003) · MIS Quarterly · doi:10.2307/30036519 · Cited by 8,635 · see citing works
Validation of the Insomnia Severity Index as an outcome measure for insomnia research
Bastien, C. (2001) · Sleep Medicine · doi:10.1016/s1389-9457(00)00065-4 · Cited by 8,067 · see citing works
Human behavior and the principle of least effort
Zipf, G. K. (1949) · Max Planck Digital Library · Cited by 6,598 · see citing works
Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control
Ajzen, I., & Madden, T. J. (1986) · Journal of Experimental Social Psychology · doi:10.1016/0022-1031(86)90045-4 · Cited by 5,718 · see citing works
Moral Identity and Developmental Theory
Lapsley, D. K. (2015) · Human Development · doi:10.1159/000435926 · Cited by 3,836 · see citing works
Epidemiology of insomnia: what we know and what we still need to learn
Ohayon, M. M. (2002) · Sleep Medicine Reviews · doi:10.1053/smrv.2002.0186 · Cited by 3,743 · cited 1× · see citing works
“Studies estimate that about 10% of the adults suffer from insomnia [34].”
BackgroundEysenbach, G. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.1.e11 · Cited by 2,524 · see citing works
A behavior model for persuasive design
Fogg, B. (2009) · Proceedings of the 4th International Conference on Persuasive Technology · doi:10.1145/1541948.1541999 · Cited by 2,328 · see citing works
(1993) · Medical Entomology and Zoology · Cited by 2,324 · see citing works
Guay, F., Vallerand, R. J., & Blanchard, C. (2000) · Motivation and Emotion · doi:10.1023/a:1005614228250 · Cited by 1,579 · see citing works
Patient Adherence and Medical Treatment Outcomes: A Meta-Analysis
Robin DiMatteo, M., Giordani, P. J., Lepper, H. S., & Croghan, T. W. (2002) · Medical Care · doi:10.1097/00005650-200209000-00009 · Cited by 1,490 · see citing works
Calculating correlation coefficients with repeated observations: Part 2—correlation between subjects
Bland, J. M., & Altman, D. G. (1995) · BMJ · doi:10.1136/bmj.310.6980.633 · Cited by 1,083 · see citing works
Wantland, D. J., Portillo, C. J., Holzemer, W. L., Slaughter, R., & McGhee, E. M. (2004) · Journal of Medical Internet Research · doi:10.2196/jmir.6.4.e40 · Cited by 966 · see citing works
Rothschild, J. M., Landrigan, C. P., CRONIN, J. W., Kaushal, R., Lockley, S. W., Burdick, E., Stone, P. H., Lilly, C. M., Katz, J. T., Czeisler, C. A., et al. (2005) · Critical Care Medicine · doi:10.1097/01.ccm.0000171609.91035.bd · Cited by 925 · see citing works
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 · 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
Estimating and testing mediation and moderation in within-subject designs.
Judd, C. M., Kenny, D. A., & McClelland, G. H. (2001) · Psychological Methods · doi:10.1037/1082-989x.6.2.115 · Cited by 846 · see citing works
Prospective Memory: An Overview and Synthesis of an Emerging Field
McDaniel, M. A., & Einstein, G. O. (2007) · Sage eBooks · doi:10.4135/9781452225913 · Cited by 715 · see citing works
A Review of Methods for Missing Data
Pigott, T. (2001) · Educational Research and Evaluation · doi:10.1076/edre.7.4.353.8937 · Cited by 654 · see citing works
Using context-aware computing to reduce the perceived burden of interruptions from mobile devices
Ho, J., & Intille, S. S. (2005) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1054972.1055100 · Cited by 367 · see citing works
Cognitive-behavioral therapy for primary insomnia
Edinger, J. D., & Means, M. K. (2005) · Clinical Psychology Review · doi:10.1016/j.cpr.2005.04.003 · Cited by 344 · cited 1× · see citing works
“Since, the efficacy of treatment is partly determined by adherence [20–23] it is crucial to optimize adherence [24].”
BackgroundA meta-analysis of self-help treatment approaches
Gould, R. A., & Clum, G. A. (1993) · Clinical Psychology Review · doi:10.1016/0272-7358(93)90039-o · Cited by 337 · see citing works
Contraceptive Use among U.S. Women Having Abortions in 2000-2001
Jones, R. K., Darroch, J. E., & Henshaw, S. K. (2002) · Perspectives on Sexual and Reproductive Health · doi:10.2307/3097748 · Cited by 335 · see citing works
Yang, M. S., Morin, C. M., Schaefer, K., & Wallenstein, G. V. (2009) · Current Medical Research and Opinion · doi:10.1185/03007990903167415 · Cited by 317 · see citing works
Espie, C. A., Macmahon, K., Kelly, H.-L., Broomfield, N. M., Douglas, N. J., Engleman, H. M., McKinstry, B., Morin, C. M., Walker, A., & Wilson, P. (2007) · SLEEP · doi:10.1093/sleep/30.5.574 · Cited by 297 · see citing works
Predicting human interruptibility with sensors: a Wizard of Oz feasibility study
Hudson, S., Fogarty, J., Atkeson, C., Avrahami, D., Forlizzi, J., Kiesler, S., Lee, J., & Yang, J. (2003) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/642611.642657 · Cited by 295 · see citing works
Armstrong, A. W., Watson, A. J., Makredes, M., Frangos, J. E., Kimball, A. B., & Kvedar, J. C. (2009) · Archives of Dermatology · doi:10.1001/archdermatol.2009.269 · Cited by 235 · see citing works
Donkin, L., & Glozier, N. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.2100 · Cited by 212 · see citing works
The effect of reminder systems on patients' adherence to treatment
West, C. E., Fenerty, Feldman, S. R., Kaplan, & Davis (2012) · Patient Preference and Adherence · doi:10.2147/ppa.s26314 · Cited by 194 · see citing works
Fischer, J. E., Greenhalgh, C., & Benford, S. (2011) · International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) · doi:10.1145/2037373.2037402 · Cited by 189 · see citing works
Pielot, M., de Oliveira, R., Kwak, H., & Oliver, N. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2556973 · Cited by 176 · see citing works
Prospective memory research: Why is it relevant?
Kliegel, M., & Martin, M. G. (2003) · International Journal of Psychology · doi:10.1080/00207590344000114 · Cited by 173 · see citing works
Motivational interpretations of hindsight bias: An individual difference analysis
Campbell, J. D., & Tesser, A. (1983) · Journal of Personality · doi:10.1111/j.1467-6494.1983.tb00868.x · Cited by 153 · see citing works
Cheung, C. M. K., & Lee, M. (2002) · Advances in global information management (AGIM) book series · doi:10.4018/978-1-930708-43-3.ch003 · Cited by 143 · see citing works
Insomnia risks and costs: health, safety, and quality of life.
Rosekind, M. R., & Gregory, K. B. (2010) · PubMed · Cited by 138 · see citing works
Prospective Memory in Workplace and Everyday Situations
Dismukes, R. K. (2012) · Current Directions in Psychological Science · doi:10.1177/0963721412447621 · Cited by 132 · see citing works
Krueger, K. P., Felkey, B. G., & Berger, B. A. (2003) · Journal of the American Pharmacists Association · doi:10.1331/154434503322642598 · Cited by 120 · see citing works
Unintentional non-adherence and belief in medicines in older adults
Unni, E., & Farris, K. B. (2010) · Patient Education and Counseling · doi:10.1016/j.pec.2010.05.006 · Cited by 116 · see citing works
The promise and pitfalls of the internet for cognitive behavioral therapy
Andersson, G. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-82 · Cited by 114 · cited 1× · see citing works
“There is substantial evidence that computerized health interventions can be effective [16 – 18].”
BackgroundThe power of mobile notifications to increase wellbeing logging behavior
Bentley, F. R., & Tollmar, K. (2013) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2470654.2466140 · Cited by 100 · see citing works
An online lifestyle diary with a persuasive computer assistant providing feedback on self-management
Blanson Henkemans, O. A., van der Boog, P. J. M., Lindenberg, J., van der Mast, C. A. P. G., Neerincx, M. A., & Zwetsloot-Schonk, B. J. H. M. (2009) · Technology and Health Care · doi:10.3233/thc-2009-0545 · Cited by 96 · see citing works
Adherence to Technology-Mediated Insomnia Treatment: A Meta-Analysis, Interviews, and Focus Groups
Horsch, C. H. G., Lancee, J., Beun, R. J., Neerincx, M. A., & Brinkman, W. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4115 · Cited by 81 · see citing works
Interruptibility prediction for ubiquitous systems
Turner, L. D., Allen, S. M., & Whitaker, R. M. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2807514 · Cited by 75 · see citing works
Persuasion, Task Interruption and Health Regimen Adherence
Bickmore, T., Mauer, D., Crespo, F., & Brown, T. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-77006-0_1 · Cited by 68 · see citing works
Trust in Internet Shopping: A Proposed Model and Measurement Instrument
Cheung, C., & Lee, M. K. O. (2000) · Journal of the Association for Information Systems · Cited by 58 · see citing works
Smith, J. D., & Oakley, D. (2005) · Journal of Midwifery & Women s Health · doi:10.1016/j.jmwh.2005.01.011 · Cited by 53 · see citing works
Vidal, C., García, M., Benito‐Aracil, L., Milà, N., Binefa, G., & Moreno, V. R. (2014) · Journal of Medical Systems · doi:10.1007/s10916-014-0118-x · Cited by 52 · see citing works
Investigating The Role of Task Engagement in Mobile Interruptibility
Pejović, V., Musolesi, M., & Mehrotra, A. (2015) · International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (MobileHCI Adjunct) · doi:10.1145/2786567.2794336 · Cited by 42 · see citing works
Deng, X., Wang, Y., Zhu, T., Zhang, W., Yin, Y., & Ye, L. (2014) · Journal of Medical Systems · doi:10.1007/s10916-014-0169-z · Cited by 35 · see citing works
Computerised cognitive behavioural therapy and its uses
Kaltenthaler, E., & Cavanagh, K. (2010) · Progress in Neurology and Psychiatry · doi:10.1002/pnp.163 · Cited by 29 · see citing works
Learning to recognise disruptive smartphone notifications
Smith, J., Lavygina, A., Ma, J., Russo, A., & Naranker Dulay, A. (2014) · International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) · doi:10.1145/2628363.2628404 · Cited by 16 · see citing works
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Jakob, R., Harperink, S., Rudolf, A. M., Fleisch, E., Haug, S., Mair, J. L., Salamanca-Sanabria, A., & Kowatsch, T. (2022) · Journal of Medical Internet Research · doi:10.2196/35371 · Cited by 446 · see citing works
“The following information was extracted for each included study: general study characteristics, study population characteristics, intervention characteristics, factors influencing adherence relative to intended use, and information on app use (Multimedia Appendix 3 [20,26-123]).”
BackgroundMethodInfluentialLee, S., Oh, J. W., Park, K., Lee, E. M., & Lee, E. M. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00800-3 · Cited by 94 · see citing works
Digital Delivery of Cognitive Behavioral Therapy for Insomnia
Luik, A. I., van der Zweerde, T., van Straten, A., & Lancee, J. (2019) · Current Psychiatry Reports · doi:10.1007/s11920-019-1041-0 · Cited by 69 · see citing works
Ho, F. Y.-Y., Chan, C. S., Lo, W.-Y., & Leung, J. C.-Y. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.01.062 · Cited by 58 · see citing works
de Vries, R. A. J., Truong, K. P., Zaga, C., Li, J. J., & Evers, V. (2017) · Personal and Ubiquitous Computing · doi:10.1007/s00779-017-1025-1 · Cited by 56 · see citing works
“For example, in [21], they found that the implemented reminder strategy, in the context of sleep behavior, did not work for people who had a negative attitude towards their intended activity.”
The Implementation of Behavior Change Techniques in mHealth Apps for Sleep: Systematic Review
Arroyo, A. C., & Zawadzki, M. J. (2022) · JMIR mhealth and uhealth · doi:10.2196/33527 · Cited by 52 · see citing works
“Multimedia Appendix 3 [24,45-55] details the subjective and objective measures used for sleep outcomes across studies.”
BackgroundAdherence to Cognitive Behavior Therapy for Insomnia
Agnew, S., Vallières, A., Hamilton, A., McCrory, S., Nikolič, M., Kyle, S. D., Fleming, L., & Crawford, M. (2020) · Sleep Medicine Clinics · doi:10.1016/j.jsmc.2020.11.002 · Cited by 40 · see citing works
Mallawaarachchi, S. R., Tieppo, A., Hooley, M., & Horwood, S. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107492 · Cited by 36 · see citing works
A self-guided internet-delivered intervention for adults with ADHD: a feasibility study
Nordby, E. S., Kenter, R. M. F., Lundervold, A. J., & Nordgreen, T. (2021) · Internet Interventions · doi:10.1016/j.invent.2021.100416 · Cited by 22 · see citing works
“This may be obtained by improving the usability of the platform (Eysenbach, 2005), including more event-based or frequent reminders (Horsch et al., 2017), by providing rewards or motivators (Christensen et al., 2009), or by giving the participants more time to complete the intervention modules…”
BackgroundChen, Y.-P., Woodward, J., Bista, D., Zhang, X., Singh, I., Obajemu, O., Shankar, M. N., Ross, K. M., Ruiz, J., & Anthony, L. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3641993 · Cited by 21 · see citing works
“For example, Horsch et al. [40] found no efect of notifcation type (context-based vs. time-based reminders) on user engagement of a sleep diary app over a one-week study.”
BackgroundResultInfluentialDominguez-Rodriguez, A., Martínez-Luna, S. C., Hernández Jiménez, M. J., De La Rosa-Gómez, A., Arenas-Landgrave, P., Esquivel Santoveña, E. E., Arzola-Sánchez, C., Alvarez Silva, J., Solis Nicolas, A. M., Colmenero Guadián, A. M., et al. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.644782 · Cited by 18 · see citing works
“In order to increase the adherence to the intervention the platform will send email reminders, a tool that has shown to be effective for this purpose (Horsch et al., 2017).”
The influence of concurrent mobile notifications on individual responses
Turner, L. D., Allen, S. M., & Whitaker, R. M. (2019) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2019.07.011 · Cited by 19 · see citing works
A Survey of Notification Designs in Commercial mHealth Apps
Woodward, J., Chen, Y.-P., Jurczyk, K., Ross, K. M., Anthony, L., & Ruiz, J. (2021) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3411763.3451639 · Cited by 19 · see citing works
“While prior work has shown that mHealth notifications help users with behavioral change through increasing user engagement and commitment [2, 16, 19], notifications may also create dependencies on technology instead of supporting habit formation [29].”
BackgroundInfluentialNordby, E. S., Gjestad, R., Kenter, R. M. F., Guribye, F., Mukhiya, S. K., Lundervold, A. J., & Nordgreen, T. (2022) · Frontiers in Digital Health · doi:10.3389/fdgth.2022.821031 · Cited by 14 · see citing works
“In previous studies, digital reminders have been found to increase adherence rates in interventions for anxiety, depression, and sleep (20, 28).”
BackgroundTimlin, D., McCormack, J. M., Kerr, M. A., Keaver, L., & Simpson, E. E. A. (2025) · BMC Nutrition · doi:10.1186/s40795-025-01020-6 · Cited by 11 · see citing works
“Similar Cronbach’s Alpha for COM-B components were seen in previous research [42].”
Theory-Based and Tailor-Made : motivational messages for behavior change technology
de Vries, R. (2018) · doi:10.3990/1.9789036546492 · Cited by 12 · see citing works
Im, E., Chee, W., Paul, S., Choi, M., Kim, S. Y., Deatrick, J. A., Inouye, J., Grace, X., Meghani, S. H., Nguyen, G. T., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42132-6 · Cited by 11 · see citing works
“The reminders encouraged both groups to use TICAA and/or the ACS website; reminders are an elementary approach to boost adherence in behavioral intervention studies 25 .”
Cognitive Behavioral Therapy for Insomnia in the Digital Age
Kang, S., & Kim, Y. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-981-32-9721-0_30 · Cited by 11 · see citing works
Albers, N., Neerincx, M. A., Penfornis, K. M., & Brinkman, W. (2022) · PeerJ · doi:10.7717/peerj.13824 · Cited by 11 · see citing works
“One could address this by making suggestions at convenient times ( e.g ., Horsch et al. (2017) ) or helping people create action plans ( Hagger & Luszczynska, 2014 ).”
InfluentialMoumane, K., Idri, A., Aouni, F. E., Laghnimi, J., Benabdellah, N. C., & Hamal, O. (2024) · Clinical and Experimental Obstetrics & Gynecology · doi:10.31083/j.ceog5104088 · Cited by 23 · see citing works
Høeg, B. L., Løppenthin, K. B., Savard, J., Johansen, C., Christensen, J. F., Svendsen, M. N., Holländer, N. H., & Bidstrup, P. E. (2025) · Acta Oncologica · doi:10.2340/1651-226x.2025.42246 · Cited by 9 · see citing works
Chandler, C. R. A., Catanzaro, M., & Siette, J. (2024) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2024.105440 · Cited by 6 · see citing works
Wang, W., van Lint, C. L., Brinkman, W., Rövekamp, T., van Dijk, S., van der Boog, P., & Neerincx, M. A. (2019) · Health and Technology · doi:10.1007/s12553-019-00295-7 · Cited by 6 · see citing works
Jakob, R., Narauskas, J., Fleisch, E., König, L. M., & Kowatsch, T. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100445 · Cited by 7 · see citing works
Kang, J., & Wei, L. (2020) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.1145/3421937.3422014 · Cited by 6 · see citing works
“[11] examined the effectiveness of user-set reminders and system-set reminders in the context of logging sleep information (e.”
BackgroundResultHentati, A., Isacsson, N. H., Rosén, A., Jernelöv, S., Kaldo, V., Ljótsson, B., Forsell, E., Lindefors, N., & Kraepelien, M. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01839-0 · Cited by 5 · see citing works
“Reminders represent another strategy suggested to boost engagement with digital interventions 13,14 .”
Chan, N. Y., Chen, S., Ngan, C. L., Li, S. X., Zhang, J., Lam, S. P., Chan, J. W. Y., Yu, M. W. M., Chan, K. C. C., Li, A. M., et al. (2025) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.14115 · Cited by 4 · see citing works
Pretolesi, D., Motnikar, L., Bieg, T., Gafert, M., & Uhl, J. C. (2024) · Behaviour and Information Technology · doi:10.1080/0144929x.2024.2434892 · Cited by 3 · see citing works
“In the context of applications for health and well-being, several works have illustrated how notifications can positively impact users’ adherence and commitment to the intervention programs (Bell et al. 2023; Bentley and Tollmar 2013; Gravenhorst et al. 2015; Haggag et al. 2022; Horsch et al. 2017).”
Notifying Users: Customisation Preferences for Notifications in Health and Well-being Applications
Pretolesi, D., Motnikar, L., Bieg, T., & Uhl, J. C. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-30933-5_26 · Cited by 3 · see citing works
Tarp, K., Christiansen, R., Bilberg, R., Borkner, S., Dalsgaard, C., Folker, M. P., & Nielsen, A. S. (2024) · Journal of Medical Internet Research · doi:10.2196/47083 · Cited by 5 · see citing works
“This finding aligns with previous studies that concluded check-ins serve as motivating factors, helping patients hold themselves accountable [30].”
Moumane, K., Idri, A., & Aouni, F. E. (2023) · Research Square · doi:10.21203/rs.3.rs-2720323/v1 · Cited by 3 · see citing works
Naderi, M., Alipour, Z., Khalajinia, Z., & Momenimovahed, Z. (2025) · Reproductive Health · doi:10.1186/s12978-025-02238-0 · Cited by 2 · see citing works
“The underlying framework for improving sleep quality in pregnant women likely stems from the interactive components of the intervention, such as reminders and question-and-answer sessions, which enhance adherence and self-efficacy, as suggested in other digital health engagement models [30, 43].”
Katapally, T. R., Elsahli, N., Ibrahim, S. T., & Bhawra, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4819875 · Cited by 2 · see citing works
Barley, B. K., & Scullin, M. K. (2025) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.11780 · Cited by 1 · see citing works
Katapally, T. R., Elsahli, N., Ibrahim, S. T., & Bhawra, J. (2026) · PeerJ · doi:10.7717/peerj.20772 · Cited by 3 · see citing works
“Instead, more frequent nudges, like daily reminders, are needed to see signi fi cant changes ( Chen et al., 2017 ; Horsch et al., 2017 ; Balato et al., 2013 ; Belton et al., 2013 ; Strandbygaard, Thomsen & Backer, 2010 ; Armstrong et al., 2009 ).”
Boult, L., Douglass, T., Tremblett, M., & Joyce, J. B. (2026) · Vox Sanguinis · doi:10.1111/vox.70263 · Cited by 1 · see citing works
“General reminders have been shown previously to be helpful in the context of sleep interventions [68] and are cited in blood donation reviews as a retention tool [69, 70].”
Telemedizin in der Therapie von Ein- und Durchschlafstörungen
Frase, L., & Spiegelhalder, K. (2018) · Schlaf · doi:10.1055/s-0038-1677341
The Differences in Sleep Skills between Insomnia Patients with and without Need of Hypnotics
Kong, B., Ko, M.-A., Chang, J. G., Hong, M., Kim, W. J., Lee, S. Y., Kim, H.-S., & Song, H. R. (2020) · Sleep Medicine Research · doi:10.17241/smr.2020.00640
“Reminding people to do their relaxation exercises improves adherence to target behaviors and provides an opportunity to test the effect [31].”
BackgroundKanady, J. C., Luik, A. I., & Espie, C. A. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822963-7.00027-x
La promoción del sueño a través de las ciencias del comportamiento como una política pública
Coldeira, M. F., Charreau, L. V. L., Casas, A. E., Casiraghi, L. P., Spiousas, I., Morán, T. M. D. C., Iparraguirre, G., & Golombek, D. A. (2024) · Revista Argentina de Ciencias del Comportamiento ( RACC ) · doi:10.32348/1852.4206.v16.n1.44609
de Groot, E. C. S., de Vries, L. P., Gadiraju, U., Kudina, O., Keijsers, L., Hillegers, M. H. J., & Brinkman, W. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101109
- Authors
- Horsch, C., Spruit, S., Lancee, J., van Eijk, R., Beun, R. J., Neerincx, M., & Brinkman, W.-P.
- Affiliations
- Delft University of Technology (NL)
- Utrecht University (NL)
- University of Amsterdam (NL)
- Corresponding author
- Horsch, Corine
- Venue
- Health and Technology
- Published
- 2016-12-23
- Volume
- 7
- Issue
- 2-3
- Pages
- 173-188
- ISSN
- 2190-7188 (ISSN-L)
- 2190-7196
- PMC
- PMC5686282
- OpenAlex
- W2563838322
- Cited by
- 44
- References
- 58
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 8 · 2023: 4 · 2022: 8 · 2021: 4 · 2020: 4 · 2019: 4 · 2018: 2 · 2017: 1
- FWCI
- 3.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Health and Technology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Research Repository (Delft University of Technology) (submittedVersion, cc-by)
- Funders
- Stichting voor de Technische Wetenschappen
- Philips
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Keywords
- reminders, medication adherence, cognitive behavioral therapy for insomnia, mobile health intervention, sleep diary, relaxation techniques, self-empowerment, opportunity
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