Pilot Randomized Trial of a Self-Help Behavioral Activation Mobile App for Utilization in Primary Care
Open accessAbstract
Mobile technologies can be leveraged to meet the need for evidence-based psychological depression treatment via primary care. The purpose of the present study was to preliminarily examine the feasibility and efficacy of a self-help brief behavioral activation mobile application (app; "Moodivate") for depressive symptoms among adults treated via primary care. Participants (N = 52) were recruited from primary care practices between January and December 2017 and were randomized 2:2:1 to receive (a) Moodivate, (b) an active control cognitive-behavioral therapy-based mobile app ("MoodKit"), or (c) treatment as usual (TAU; no app). Participants completed assessments of depressive symptoms weekly for 8 weeks. App analytics data were captured to examine Moodivate feasibility (analytics unavailable for control app). Moodivate participants on average had 46.76 (SD = 30.10) app sessions throughout the trial duration, spent 3.50 (2.76) minutes using the app per session, and spent 120.76 (101.02) minutes using the app in total throughout the trial. Nearly 70% of Moodivate participants continued to use the app 1 month after trial enrollment and 50% at the end of the 8-week follow-up period. A generalized estimating equation model examining change in depressive symptoms over time by treatment condition indicated a significant interaction between time and treatment condition (χ 2 = 42.21, df = 14, p < .001). As compared to TAU, participants in both app conditions evidenced significant decreases in depressive symptoms over time, and these treatment gains were sustained across the trial period. These results preliminarily indicate feasibility of Moodivate as well as efficacy of both Moodivate and MoodKit for the treatment of depression among adults recruited via primary care. Future studies should focus on larger-scale examinations of treatment efficacy and effectiveness across primary care settings.
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Our included studies covered several publications that were published after 2019 to reflect updated evidence.
“First, our included studies covered several publications that were published after 2019 [32-34,38,44] to reflect updated evidence, which can support future development and use of app-based mHealth interventions for anxiety and depression.”
From Effectiveness and Minimum Effective Dose of App-Based Mobile Health Interventions for Anxiety and Depression Symptom Reduction: Systematic Review and Meta-Analysis (2022) · cites this paper as [38]
The Methods (Procedures; page unavailable) describe this paper’s own mobile-app trial, not the citing authors’ included studies. Neither that passage nor the Discussion and References passages establish which publications the citing authors included or whether several were published after 2019 (searched: publication year and post-2019 studies). (LLM, conf=0.77)
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Cites
Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2008.08.010 · Cited by 51,384 · see citing works
The PHQ-8 as a measure of current depression in the general population
Kroenke, K., Strine, T. W., Spitzer, R. L., Williams, J. B. W., Berry, J. T., & Mokdad, A. H. (2009) · Journal of Affective Disorders · doi:10.1016/j.jad.2008.06.026 · Cited by 5,121 · see citing works
Generalized Estimating Equations
Hardin, J. W., & Hilbe, J. M. (2002) · doi:10.1201/9781420035285 · Cited by 1,766 · see citing works
Screening for Depression in Adults: US Preventive Services Task Force Recommendation Statement
Siu, A. L., and the US Preventive Services Task Force (USPSTF), Bibbins-Domingo, K., Grossman, D. C., Baumann, L. C., Davidson, K. W., Ebell, M., García, F. A. R., Gillman, M., Herzstein, J., et al. (2016) · JAMA · doi:10.1001/jama.2015.18392 · Cited by 1,407 · see citing works
Collins, L. M., Murphy, S. A., & Strecher, V. (2007) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2007.01.022 · Cited by 1,082 · see citing works
An experimental design for the development of adaptive treatment strategies
Murphy, S. A. (2005) · Statistics in Medicine · doi:10.1002/sim.2022 · Cited by 595 · see citing works
County-level estimates of mental health professional shortage in the United States.
Thomas, K., Ellis, A. R., Konrad, T., Holzer, C., & Morrissey, J. (2009) · Psychiatric Services · doi:10.1176/ps.2009.60.10.1323 · Cited by 589 · see citing works
Lejuez, C. W., Hopko, D. R., Acierno, R. E., Daughters, S. B., & Pagoto, S. (2011) · Behavior Modification · doi:10.1177/0145445510390929 · Cited by 574 · see citing works
Self-citationCan Mobile Health Technologies Transform Health Care?
Steinhubl, S. R., Muse, E. D., & Topol, E. J. (2013) · JAMA · doi:10.1001/jama.2013.281078 · Cited by 496 · see citing works
Beck Depression Inventory-II (BDI-II)
Bortnick, K. (2024) · Routledge eBooks · doi:10.4324/9781003525288-77 · Cited by 496 · see citing works
mHealth: A Mechanism to Deliver More Accessible, More Effective Mental Health Care
Price, M., Yuen, E. K., Goetter, E. M., Herbert, J. D., Forman, E. M., Acierno, R., & Ruggiero, K. J. (2014) · Clinical Psychology & Psychotherapy · doi:10.1002/cpp.1855 · Cited by 488 · see citing works
Treatment preferences among depressed primary care patients
Dwight-Johnson, M., Sherbourne, C. D., Liao, D., & Wells, K. B. (2000) · Journal of General Internal Medicine · doi:10.1046/j.1525-1497.2000.08035.x · Cited by 478 · see citing works
Patients' preferences in the treatment of depressive disorder in primary care
van Schaik, D. J. F., Klijn, A. F. J., van Hout, H. P. J., van Marwijk, H. W. J., Beekman, A. T. F., de Haan, M., & van Dyck, R. (2004) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2003.12.001 · Cited by 428 · see citing works
Cunningham, P. J. (2009) · Health Affairs · doi:10.1377/hlthaff.28.3.w490 · Cited by 420 · see citing works
The Use and Effectiveness of Mobile Apps for Depression: Results From a Fully Remote Clinical Trial
Arean, P. A., Hallgren, K. A., Jordan, J. T., Gazzaley, A., Atkins, D. C., Heagerty, P. J., & Anguera, J. A. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6482 · Cited by 376 · see citing works
Cuijpers, P. J. (2002) · Journal of Affective Disorders · doi:10.1016/s0165-0327(02)00348-8 · Cited by 369 · see citing works
Treatment of Adult Depression in the United States
Olfson, M., Blanco, C., & Marcus, S. C. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2016.5057 · Cited by 352 · see citing works
The prevalence, clinical relevance, and public health significance of subthreshold depressions
Judd, L. L., Schettler, P. J., & Akiskal, H. S. (2002) · Psychiatric Clinics of North America · doi:10.1016/s0193-953x(02)00026-6 · Cited by 307 · see citing works
MacPherson, L., Tull, M. T., Matusiewicz, A. K., Rodman, S., Strong, D. R., Kahler, C. W., Hopko, D. R., Zvolensky, M. J., Brown, R. A., & Lejuez, C. W. (2010) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0017939 · Cited by 293 · see citing works
Self-citationShim, R. S., Baltrus, P., Ye, J., & Rust, G. (2011) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2011.01.100121 · Cited by 267 · see citing works
State of the Field of Mental Health Apps
Neary, M., & Schueller, S. M. (2018) · Cognitive and Behavioral Practice · doi:10.1016/j.cbpra.2018.01.002 · Cited by 247 · see citing works
Hopko, D. R., Lejuez, C. W., Lepage, J. P., Hopko, S. D., & McNeil, D. W. (2003) · Behavior Modification · doi:10.1177/0145445503255489 · Cited by 238 · see citing works
Self-citationHopko, D. R., Armento, M. E. A., Robertson, S. M. C., Ryba, M. M., Carvalho, J. P., Colman, L. K., Mullane, C., Gawrysiak, M., Bell, J. L., McNulty, J. K., et al. (2011) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0025450 · Cited by 193 · see citing works
Self-citationBehavioral activation for moderately depressed university students: randomized controlled trial
Gawrysiak, M., Nicholas, C., & Hopko, D. R. (2009) · Journal of Counseling Psychology · doi:10.1037/a0016383 · Cited by 169 · see citing works
Continuous Evaluation of Evolving Behavioral Intervention Technologies
Mohr, D. C., Cheung, K., Schueller, S. M., Brown, C. H., & Duan, N. (2013) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2013.06.006 · Cited by 169 · see citing works
Strategies for mHealth Research: Lessons from 3 Mobile Intervention Studies
Ben‐Zeev, D., Schueller, S. M., Begale, M. J., Duffecy, J. L., Kane, J. M., & Mohr, D. C. (2014) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-014-0556-2 · Cited by 167 · see citing works
Behavioral Activation Is an Evidence-Based Treatment for Depression
Sturmey, P. (2009) · Behavior Modification · doi:10.1177/0145445509350094 · Cited by 164 · see citing works
Towards a Framework for Evaluating Mobile Mental Health Apps
Chan, S., Torous, J., Hinton, L., & Yellowlees, P. (2015) · Telemedicine and e-Health · doi:10.1089/tmj.2015.0002 · Cited by 163 · see citing works
Daughters, S. B., Braun, A., Sargeant, M. N., Reynolds, E. K., Hopko, D. R., Blanco, C., & Lejuez, C. W. (2008) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v69n0116 · Cited by 160 · see citing works
Self-citationUsing e-technologies in clinical trials
Rosa, C., Campbell, A. N. C., Miele, G. M., Brunner, M., & Winstanley, E. L. (2015) · Contemporary Clinical Trials · doi:10.1016/j.cct.2015.07.007 · Cited by 147 · see citing works
App-based psychological interventions: friend or foe?
Leigh, S., & Flatt, S. (2015) · Evidence Based Mental Health · doi:10.1136/eb-2015-102203 · Cited by 140 · see citing works
Jakupcak, M., Wagner, A. W., Paulson, A., Varra, A. A., & McFall, M. (2010) · Journal of Traumatic Stress · doi:10.1002/jts.20543 · Cited by 114 · see citing works
Behavioral Activation as an Intervention for Coexistent Depressive and Anxiety Symptoms
Hopko, D. R., Lejuez, C. W., & Hopko, S. D. (2004) · Clinical Case Studies · doi:10.1177/1534650103258969 · Cited by 113 · see citing works
Self-citationBry, L. J., Chou, T., Miguel, E. M., & Comer, J. S. (2017) · Behavior Therapy · doi:10.1016/j.beth.2017.07.008 · Cited by 103 · see citing works
Grös, D. F., Price, M., Strachan, M., Yuen, E. K., Milanak, M. E., & Acierno, R. E. (2012) · Behavior Modification · doi:10.1177/0145445512448097 · Cited by 89 · see citing works
Reynolds, E. K., MacPherson, L., Tull, M. T., Baruch, D. E., & Lejuez, C. W. (2011) · Journal of Counseling Psychology · doi:10.1037/a0024634 · Cited by 77 · see citing works
Self-citationBehavioral Activation and Problem-Solving Therapy for Depressed Breast Cancer Patients
Hopko, D. R., Funderburk, J. S., Shorey, R. C., McIndoo, C. C., Ryba, M. M., File, A. A., Benson, K., & Vitulano, M. L. (2013) · Behavior Modification · doi:10.1177/0145445513501512 · Cited by 58 · see citing works
National Patterns of Depression Treatment in Primary Care
Stafford, R. S., Ausiello, J. C., Misra, B., & Saglam, D. (2000) · The Primary Care Companion For CNS Disorders · doi:10.4088/pcc.v02n0603 · Cited by 49 · see citing works
Generalized Estimating Equations
Pickles, A. R. (2001) · Encyclopedia of Environmetrics · doi:10.1002/9780470057339.vag007m · Cited by 49 · see citing works
Dahne, J., Lejuez, C. W., Kustanowitz, J., Felton, J. W., Díaz, V. A., Player, M. S., & Carpenter, M. J. (2017) · The International Journal of Psychiatry in Medicine · doi:10.1177/0091217417720899 · Cited by 31 · see citing works
Self-citationPredictors of Poor Response to Depression Treatment in Primary Care
Rossom, R. C., Solberg, L. I., Vazquez‐Benitez, G., Whitebird, R. R., Crain, A. L., Beck, A. L., & Unützer, J. (2016) · Psychiatric Services · doi:10.1176/appi.ps.201400285 · Cited by 23 · see citing works
Collado, A., Long, K., MacPherson, L., & Lejuez, C. W. (2014) · Trials · doi:10.1186/1745-6215-15-231 · Cited by 14 · see citing works
Self-citationSovereignty of the Apps: There's more to Relevance than DownloadsPreprint
Sigg, S., Lagerspetz, E., Peltonen, E., Nurmi, P., & Tarkoma, S. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1611.10161 · Cited by 7 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Erhardt D, & Dorian E (2013). Going Mobile: A Case Vignette Illustrating the Integration of Mobile Technology in Psychotherapy. Independent Practitioner, 33(1), 15– 21.
Cited by
Sorted by citations
Challenges in Participant Engagement and Retention Using Mobile Health Apps: Literature Review
Amagai, S., Pila, S., Kaat, A. J., Nowinski, C. J., & Gershon, R. C. (2022) · Journal of Medical Internet Research · doi:10.2196/35120 · Cited by 343 · see citing works
“Refer to Figure 1 for the study selection flowchart and Multimedia Appendix 1 [4-8,17-73] for characteristics of the studies.”
BackgroundEngagement and retention in digital mental health interventions: a narrative review
Boucher, E. M., & Raiker, J. S. (2024) · BMC Digital Health · doi:10.1186/s44247-024-00105-9 · Cited by 200 · see citing works
“Similarly, Dahne et al. found that although there was a drop of nearly 20% in active users between the second and third week of their trial, the rate of active users remained flat between the third and sixth weeks (with smaller drops in active users occurring at the seventh and eighth weeks) [9].”
BackgroundResultInfluentialWu, A., Scult, M. A., Barnes, E. D., Betancourt, J. A., Falk, A. E., & Gunning, F. M. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00386-8 · Cited by 164 · see citing works
Hornstein, 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
Digital Mental Health Interventions for Depression: Scoping Review of User Engagement
Lipschitz, J. M., Van Boxtel, R., Torous, J., Firth, J., Lebovitz, J. G., Burdick, K. E., & Hogan, T. P. (2022) · Journal of Medical Internet Research · doi:10.2196/39204 · Cited by 105 · see citing works
Digital Health Interventions to Enhance Prevention in Primary Care: Scoping Review
Willis, V. C., Craig, K. J. T., Jabbarpour, Y., Scheufele, E. L., Arriaga, Y. E., Ajinkya, M., Rhee, K. B. L., & Bazemore, A. (2021) · JMIR Medical Informatics · doi:10.2196/33518 · Cited by 129 · see citing works
“These applied limits resulted in 310 articles for full-text review, of which 241 articles [17-257] were included for the subgroup analysis (Figure 1).”
BackgroundInfluentialSix, S. G., Byrne, K. A., Tibbett, T. P., & Pericot-Valverde, I. (2021) · JMIR Mental Health · doi:10.2196/32199 · Cited by 95 · see citing works
“The following data were extracted from each article: first author, year of publication, participants’ characteristics (ie, gender and age), population, and study length (Multimedia Appendix 3), as well as app name, app classification (ie, mobile or internet), presence of gamification elements, type of gamification ele…”
MethodResultSerrano-Ripoll, M. J., Zamanillo-Campos, R., Fiol-DeRoque, M. A., Castro, A., & Ricci-Cabello, I. (2022) · JMIR mHealth and uHealth · doi:10.2196/29621 · Cited by 96 · see citing works
“Our assessment of the risk of bias in individual studies is shown in Multimedia Appendix 3 [33-44].”
BackgroundMethodResultInfluentialEaton, C. K., Vallejo, N., McDonald, X., Wu, J., Rodríguez, R., Muthusamy, N., Mathioudakis, N. N., & Riekert, K. A. (2024) · Journal of Medical Internet Research · doi:10.2196/50508 · Cited by 108 · see citing works
Ford, D. W., Harvey, J., McElligott, J. T., King, K. L., Simpson, K. N., Valenta, S., Warr, E. H., Walsh, T., Debenham, E., Teasdale, C., et al. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa157 · Cited by 69 · see citing works
Bally, E., & Cesuroğlu, T. (2020) · Frontiers in Public Health · doi:10.3389/fpubh.2019.00407 · Cited by 68 · see citing works
“FIGURE 2 | Analytical approach to assessment of the health system for the integration of mHealth (18, 19).”
MethodEngagement with mobile health interventions for depression: A systematic review
Molloy, A. G., & Anderson, P. L. (2021) · Internet Interventions · doi:10.1016/j.invent.2021.100454 · Cited by 58 · see citing works
Teepe, G. W., Fonseca, A. D., Kleim, B., Jacobson, N. C., Salamanca-Sanabria, A., Car, L. T., Fleisch, E., & Kowatsch, T. (2021) · Journal of Medical Internet Research · doi:10.2196/29412 · Cited by 60 · see citing works
Martinengo, L., Stona, A., Griva, K., Dazzan, P., Pariante, C. M., von Wangenheim, F., & Car, J. (2021) · Journal of Medical Internet Research · doi:10.2196/27619 · Cited by 57 · see citing works
“A total of 33% (6/18) of papers included randomized controlled trials [67-72] reporting that apps or some specific app functions were effective in improving mood, anxiety, stress, or general well-being compared with active or waitlist controls.”
BackgroundApp-Based Interventions for Moderate to Severe Depression
Bae, H., Shin, H., Ji, H.-G., Kwon, J. S., Kim, H., & Hur, J. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.44120 · Cited by 47 · see citing works
Lu, S.-C., Xu, M., Wang, M., Hardi, A., Cheng, A. L., Chang, S.-H., & Yen, P.-Y. (2022) · JMIR Mental Health · doi:10.2196/39454 · Cited by 45 · see citing works
“We included a total of 15 randomized controlled trials (RCTs), with many studies [32-34, 38, 44] published after previous reviews on a With regard to depression, we found that participants receiving interventions for depression experienced little symptom reduction that was not statistically…”
InfluentialAlmuqrin, A., Hammoud, R., Terbagou, I., Tognin, S., & Mechelli, A. (2025) · BMJ Open · doi:10.1136/bmjopen-2024-093932 · Cited by 51 · see citing works
Systematic review and meta-analysis of adverse events in clinical trials of mental health apps
Linardon, J., Fuller-Tyszkiewicz, M., Firth, J., Goldberg, S. B., Anderson, C., McClure, Z., & Torous, J. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01388-y · Cited by 44 · see citing works
McCall, H. C., Hadjistavropoulos, H. D., & Sundström, C. (2021) · Journal of Medical Internet Research · doi:10.2196/26939 · Cited by 39 · see citing works
“Low Unclear Unclear Unclear Unclear Dahne et al, 2019 [50]”
BackgroundInfluentialSix, S. G., Byrne, K., Aly, H., & Harris, M. W. (2022) · JMIR Mental Health · doi:10.2196/39516 · Cited by 31 · see citing works
“The finding that depressive symptoms declined from baseline after the 14-day app intervention period is consistent with randomized controlled trials evaluating cCBT mental health app efficacy [20,23,56-59].”
ResultInternet-Based Behavioral Activation for Depression: Systematic Review and Meta-Analysis
Alber, C. S., Krämer, L. V., Rosar, S. M., & Mueller-Weinitschke, C. (2023) · Journal of Medical Internet Research · doi:10.2196/41643 · Cited by 35 · see citing works
“…concerns were further raised, if studies could not rule out nonadherence or unequal therapist support (deviations from the intended intervention) [20,29,30,32,35], did not present a preregistration or protocol (selection of the reported result) [19,31,33-35], or could not verify that dropout was…”
InfluentialHrynyschyn, R., & Dockweiler, C. (2021) · JMIR mHealth and uHealth · doi:10.2196/24703 · Cited by 35 · see citing works
“Arean et al [16], Dahne et al [33], Stiles-Shields et al [34], and Lüdtke et al [36] reported no results for anxiety.”
BackgroundMethodInfluentialMezzi, R., Yahyaoui, A., Krir, M. W., Boulila, W., & Koubâa, A. (2022) · Sensors · doi:10.3390/s22030846 · Cited by 29 · see citing works
“It is applied for checking thought, tracking the mood, and the schedule of activities, on a set of instructions while using text-based information to interact with the person [24].”
BackgroundDiano, F., Sica, L. S., & Ponticorvo, M. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20021431 · Cited by 26 · see citing works
“(2019) [19] Depression Randomized controlled trial: comparison between behavioral activation program, BA + App and TAU.”
BackgroundHan, A., & Kim, T. H. (2022) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2022.05.031 · Cited by 26 · see citing works
Plant Robot for At-Home Behavioral Activation Therapy Reminders to Young Adults with Depression
Bhat, A. S., Boersma, C., Meijer, M. J., Dokter, M., Bohlmeijer, E. T., & Li, J. J. (2021) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3442680 · Cited by 24 · see citing works
“A randomized trial [17] with 52 adults (averaging 44 years old) found that 70% were using the app 1 month after deployment and had significantly lower depression at the end of the trial.”
Efficacy, Safety, and Evaluation Criteria of mHealth Interventions for Depression: Systematic Review
Duarte‐Díaz, A., Perestelo‐Pérez, L., Gelabert, E., Robles, N., Pérez-Navarro, A., Vidal‐Alaball, J., Solà-Morales, O., Sales-Masnou, A., & Carrión, C. (2023) · JMIR Mental Health · doi:10.2196/46877 · Cited by 25 · see citing works
“The specific characteristics and elements included in each mHealth intervention are presented in Multimedia Appendix 2 [31-58].”
BackgroundInfluentialJesús-Romero, R. D., Holder-Dixon, A. R., Buss, J. F., & Lorenzo-Luaces, L. (2023) · Journal of Medical Internet Research · doi:10.2196/50780 · Cited by 36 · see citing works
Morello, K., Schäfer, S. K., Kunzler, A. M., Priesterroth, L., Tüscher, O., & Kubiak, T. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1253390 · Cited by 19 · see citing works
Planas, R., & Yuguero, O. (2021) · Informatics for Health and Social Care · doi:10.1080/17538157.2021.1887196 · Cited by 17 · see citing works
“In the article by Dahne, Lejuez et al. 30 , which compared the use of a mobile application based on behavioral activation (Moodivate) in a population with depressive symptoms to the use of another app (MoodKit) or the routine treatment, a statistically significant difference was only obtained…”
BackgroundMethodNa, H., Jo, M., Lee, C., & Kim, D. (2022) · Healthcare · doi:10.3390/healthcare10101880 · Cited by 16 · see citing works
“[26] in the US, a self-help mobile app (Moodivate) based on the BA approach was provided to adults who were being treated for depressive symptoms in a primary care setting.”
MethodKiosses, D. N., Monkovic, J., Stern, A., Czaja, S. J., Alexopoulos, G. S., Arslanoglou, E., Ebo, T., Pantelides, J., Yu, H., Dunefsky, J., et al. (2021) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2021.08.015 · Cited by 15 · see citing works
Parker, A. M., Nelliot, A., Chessare, C. M., Malik, A. M., Koneru, M., Hosey, M. M., Ozok, A. A., Lyons, K. D., & Needham, D. M. (2020) · Australian Critical Care · doi:10.1016/j.aucc.2020.02.010 · Cited by 15 · see citing works
Kulakli, A., & Shubina, I. (2020) · JMIR mhealth and uhealth · doi:10.2196/19391 · Cited by 15 · see citing works
“Another study showed the efficiency of the Moodivate app in managing limitations associated with evidence-based psychotherapy by decreasing the symptoms of PTSD and depression among adults [22,23].”
BackgroundA Bibliometric Study on Mobile Applications for PTSD Treatment : The Period of 2010-2019
Kulakli, A., & Shubina, I. (2020) · International Conference on Information Management · doi:10.1109/icim49319.2020.244717 · Cited by 13 · see citing works
“The use of Moodivate app was considered as promising for managing limitations related to evidence-based psychotherapy and are significantly effective for the treatment of depression among adults [24], [25].”
MethodFuster‐Casanovas, A., Melero, S. M., Cabutto, D., Carrión, C., Vidal‐Alaball, J., Herrera‐Ramos, E., Barcons, C., & Duarte‐Díaz, A. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.03.187 · Cited by 12 · see citing works
Heffner, J. L., Watson, N. L., Serfozo, E., Mull, K. E., MacPherson, L., Gasser, M., & Bricker, J. B. (2019) · JMIR Formative Research · doi:10.2196/13728 · Cited by 10 · see citing works
“With the most advanced evaluation of a BAT-D app to date being pilot RCTs not adequately powered to test efficacy [18,22,23] and the remainder of the published work limited to intervention descriptions or single-arm feasibility studies [19-21], there remains much to be learned about how to effectively translate BAT-D…”
BackgroundRajeshkumar, L., Mishkind, M., Coleman, J. J., Pahwa, M., LaPreze, D., Solenske, S., & Wright, J. H. (2024) · Journal of Psychiatric Practice · doi:10.1097/pra.0000000000000815 · Cited by 7 · see citing works
Three Questions to Consider Before Applying Ecological Momentary Interventions (EMI) in Psychiatry
Gründahl, M., Deckert, J., & Hein, G. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00333 · Cited by 11 · see citing works
“Regarding EMI applications, most RCT studies compared experimental groups that receive EMI treatment [usually combined with “therapy as usual [TAU]” or at least weekly face-to-face feedback (14)] and control groups that only receive TAU (15, 16).”
BackgroundLi, V. W., Sahota, J., Dev, D. K., Gill, D. D., Evans, V. C., Axler, A., Chakrabarty, T., Do, A., Keramatian, K., Nunez, J.-J., et al. (2024) · The Canadian Journal of Psychiatry · doi:10.1177/07067437241245331 · Cited by 8 · see citing works
“22 Compared to other symptom tracking apps, 23 – 26 MoodFX has more questions and takes longer to complete.”
BackgroundVitorino, C., Canavarro, M. C., & Carona, C. (2023) · BJPsych Advances · doi:10.1192/bja.2023.12 · Cited by 8 · see citing works
“‘ Moodivate ’ , for example, has been suggested as an effective brief behavioural activation app for depression that helps individuals identify, schedule and re-engage in positive activities (Dahne 2019).”
BackgroundMurphy, K. M., Glock, R., Victorson, D. E., Reddy, M. C., Birken, S. A., & Salsman, J. M. (2025) · JMIR Formative Research · doi:10.2196/67175 · Cited by 7 · see citing works
A Digital Depression Treatment Program for Adults Treated in Primary Care
Dahne, J., Wahlquist, A. E., Carpenter, M. J., Graboyes, E. M., Lejuez, C. W., Kustanowitz, J., Natale, N., Levins, O., Player, M. S., & Díaz, V. A. (2025) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2025.0494 · Cited by 7 · see citing works
Self-citationO’Toole, M. S., Ramsdal, N. B., Nørskov, C. S., Roepstorff, I. G., Buskbjerg, C. R., Mads, B., Christiansen, & Elkjær, E. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119791 · Cited by 7 · see citing works
Testing a Behavioral Activation Gaming App for Depression During Pregnancy: Multimethod Pilot Study
Vanderkruik, R. C., Ferguson, C., Kobylski, L. A., Locascio, J. J., Hamlett, G. E., Killenberg, P. C., Lewis, R., Jones, N. C., Rossa, E. T., Dineen, H., et al. (2024) · JMIR Formative Research · doi:10.2196/44029 · Cited by 7 · see citing works
“A preliminary randomized controlled trial (RCT) recruited adults with elevated depression from primary care practices (N=52) and randomized them to receive (1) Moodivate, (2) an active control cognitive behavioral therapy–based mobile app (MoodKit), or (3) treatment as usual (no app) [21].”
MethodSegovia, F. A. R., & Benuto, L. T. (2022) · Behavior Therapy · doi:10.1016/j.beth.2022.03.003 · Cited by 7 · see citing works
Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder
Daus, H., Blocher, T., Egeler, R., Klerk, R. D., Stork, W., & Backenstraß, M. (2020) · JMIR Mental Health · doi:10.2196/14267 · Cited by 7 · see citing works
“Beyond that, several studies indicate that mobile-based approaches can reduce the symptom severity in bipolar or other mood disorders [13,14,33-36].”
BackgroundRosenfeld, E. A., Lyman, C., & Roberts, J. E. (2022) · JMIR Formative Research · doi:10.2196/40045 · Cited by 6 · see citing works
“A pilot trial found initial evidence of its feasibility and efficacy [21], and a large-scale randomized clinical trial is underway [22].”
BackgroundStrauss, J., Zhang, J., Jarrett, M. L., Patterson, B. A., & Ameringen, M. V. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822201-0.00006-x · Cited by 8 · see citing works
Efficiency of mobile apps for monitoring and management of mental health - review article
Jędrzejewska, B., Borycka, A., Kotulska, M., Laskus, P., Lichman, M., Lubczyńska, Z., Potocka, Z., Przeradzki, J., & Rząd, K. (2023) · Journal of Education Health and Sport · doi:10.12775/jehs.2023.35.01.006 · Cited by 6 · see citing works
Vitorino, C., Canavarro, M. C., Caçador, M. I., & Carona, C. (2023) · Adversity and Resilience Science · doi:10.1007/s42844-023-00106-z · Cited by 4 · see citing works
“To fill this treatment gap, evidence-based mobile apps (e.g., Moodivate, a self-help behavioral activation mobile app to manage depression) have been developed to allow patients to access treatment materials when and where it is convenient, at low cost (Dahne, 2019).”
González‐Roz, A., Secades‐Villa, R., García–Fernández, G., Loredo, V. M., & Pérez, F. A. (2021) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2021.108808 · Cited by 4 · see citing works
Kato, S., Tanoue, H., Fukuzoe, J., & Ishida, Y. (2024) · SAGE Open Nursing · doi:10.1177/23779608241290717 · Cited by 3 · see citing works
“Behavioral Activation Treatment for Depression is characterized by its fl exible format, and in recent years, it has been developed using mobile technology (Dahne et al., 2019; Moffett et al., 2022).”
MethodMartínez‐García, L., Mendizabal, J. B., Santos-Goñi, M. A., Miralles, I., & Osma, J. (2025) · Digital Health · doi:10.1177/20552076251334442 · Cited by 3 · see citing works
“Finally, alongside these are also available Behavioral Apptivation, 40 MoodKit, 41 and Ascend, 42 which focus on behavioral activation and cognitive restructuring to improve emotional regulation.”
Benefits of Using Activity Recommender Technology for Self-management of Depressive Symptoms
Rohani, D. A., Faurholt‐Jepsen, M., Kessing, L. V., & Bardram, J. E. (2021) · ACM Transactions on Computing for Healthcare · doi:10.1145/3462212 · Cited by 3 · see citing works
“The systems were designed to be used in combination with therapy [38] or as a stand-alone tool [11, 12, 70].”
MethodNegative emotionality, stress, and depressive symptoms in the transition through of college
Samek, D. R., & Dawson, M. R. (2023) · Personality and Individual Differences · doi:10.1016/j.paid.2023.112403 · Cited by 3 · see citing works
Steyn, S., & Slabbert, M. (2024) · JMIR Formative Research · doi:10.2196/54216 · Cited by 4 · see citing works
The Promise and Peril of Mental Health Apps
Kushlev, K., Moon, K., Harris, M., & Falgoust, G. (2025) · Policy Insights from the Behavioral and Brain Sciences · doi:10.1177/23727322251405255 · Cited by 3 · see citing works
“…United States with 52 participants, who were primarily Black (55.8%), found that both a self-guided app based on Behavioral Activation and a self-guided app based on CBT were ef fi cacious in reducing symptoms of depression compared to primary care with small to medium effects (Dahne et al., 2019).”
InfluentialGonzález-Robles, A., Romero-Ferreiro, V., Roca, P., Rodríguez‐Jiménez, T., & Díaz‐García, A. (2026) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2026.03.008 · Cited by 2 · see citing works
Graboyes, E. M., Levins, O., DeMass, R., Baskar, N., Natale, N., Sterba, K. R., Obeid, J. S., Sharma, S., Hill, E. G., & Dahne, J. (2025) · Psycho-Oncology · doi:10.1002/pon.70309 · Cited by 1 · see citing works
Self-citationBrief behavioural activation for treating depressive symptoms in children and adolescents
Felton, J. W., Anvari, M. S., Magidson, J. F., & Lejuez, C. W. (2022) · doi:10.1093/med-psych/9780198867791.003.0011 · Cited by 1 · see citing works
Self-citationFahey, M. C., Wahlquist, A. E., Díaz, V. A., Player, M. S., Natale, N., Sterba, K. R., Chen, B., Hermes, E. D. A., Carpenter, M. J., & Dahne, J. (2023) · BMC Family Practice · doi:10.1186/s12875-023-02205-3 · Cited by 1 · see citing works
“We estimate this at 0.013 for providers, based on previous site-randomized primary care studies [49, 50].”
MethodInfluentialSelf-citationStroian, P., David, D. O., Hora, A., Erenler, B., Tuominen, E. W., Vlachantonis, K., & Žagar, T. (2024) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2024.100839 · Cited by 1 · see citing works
How I lost my mother : care, death, and the politics of invisibility
Swartz, L. M. (2020) · SUNScholar (Stellenbosch University)
Castelnuovo, G., & Manzoni, G. M. (2021) · Comprehensive Clinical Psychology · doi:10.1016/b978-0-12-818697-8.00004-2
Rewards in Mental Health Applications for Aiding with Depression: A Meta-analysis
Six, S., Harris, M. W., Winterlind, E. L., & Byrne, K. A. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-90179-0_26
Arshad, R., Hamid, A., & Shahid, S. (2021) · Behaviour and Information Technology · doi:10.1080/0144929x.2021.2006787
“A study conducted to examine the feasibility and e ffi cacy of a behavioural activation mobile application showed a signi fi cant decrease in users ’ depressive symptoms over time (Dahne et al. 2019).”
MethodLipschitz, J. M., Boxtel, R. V., Torous, J. B., Firth, J., Lebovitz, J. G., Burdick, K. E., & Hogan, T. P. (2022) · doi:10.2196/preprints.39204
Rosenfeld, E. A., Lyman, C., & Roberts, J. E. (2022) · doi:10.2196/preprints.40045
Shubina, I. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4184290
Using apps in clinical practice: 8 studies
Khanchandani, A. T. (2023) · Current Psychiatry · doi:10.12788/cp.0377
Liu, L., Song, J., Wang, J., Liu, C., & Liu, X. (2023) · doi:10.2196/preprints.52863
Li, S., Gao, S., Shi, X., Guo, Y., & Xu, T. (2023) · Research Square · doi:10.21203/rs.3.rs-3479766/v1
Fuster‐Casanovas, A., Melero, S. M., Cabutto, D., Carrión, C., Vidal‐Alaball, J., Herrera‐Ramos, E., Barcons, C., & Duarte‐Díaz, A. (2024) · doi:10.2196/preprints.68851
Ribanszki, R., Oziel, R., Fonseca, J. A. S., & POTTS, H. W. W. (2025) · doi:10.2196/preprints.73500
Severe, J., Lapidos, A., Taubman, D. S., Sochowicz, A., Wolk, S., López, D., Biehl, A., & Parikh, S. V. (2025) · Journal of Participatory Medicine · doi:10.2196/55349
“Such a decline in frequency of use is expected and has been observed in numerous digital mental health studies [10,11,14,15,19,23-26], including those involving moodgym [[[[[[[[[[14,15]]]]]]]]]] and Moodkit [25].”
Fahey, M. C., Wahlquist, A. E., Díaz, V. A., Player, M. S., Natale, N., Sterba, K. R., Chen, B. K., Hermes, E. D. A., Carpenter, M. J., & Dahne, J. (2023) · Figshare · doi:10.6084/m9.figshare.24670001
Self-citation
- Authors
- Dahne, J., Lejuez, C. W., Diaz, V. A., Player, M. S., Kustanowitz, J., Felton, J. W., & Carpenter, M. J.
- Affiliations
- Medical University of South Carolina (US)
- University of Kansas (US)
- Michigan State University (US)
- Corresponding author
- Dahne, Jennifer
- ORCID
- Venue
- Behavior Therapy
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 50
- Issue
- 4
- Pages
- 817-827
- ISSN
- 0005-7894 (ISSN-L)
- PMC
- PMC6582985
- OpenAlex
- W2904008552
- Cited by
- 78
- References
- 42
- Citations by year
- 2026: 1 · 2025: 10 · 2024: 10 · 2023: 16 · 2022: 13 · 2021: 18 · 2020: 9 · 2019: 1
- FWCI
- 8.83
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Behavior Therapy (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health
- National Institute on Drug Abuse
- 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 › Mental Health Research Topics
- Keywords
- behavioral activation, depression, mobile health apps, self-help intervention, primary care, depressive symptoms, cognitive behavioral therapy, app usage, medication adherence
- MeSH terms
- Adult, Depression, Female, Humans, Male, Pilot Projects, Primary Health Care, Health Behavior, Cognitive Behavioral Therapy, Mobile Applications
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