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Engagement with smartphone-delivered behavioural activation interventions: a study of the MoodMission smartphone application

Published online by Cambridge University Press:  28 December 2020

Abby Aizenstros
Affiliation:
Cognitive Behaviour Therapy Research Unit, Monash University, Australia
David Bakker*
Affiliation:
Cognitive Behaviour Therapy Research Unit, Monash University, Australia Cognitive Behaviour Therapy Research Unit, Institute for Social Neuroscience, Australia
Stefan G. Hofmann
Affiliation:
Department of Psychological and Brain Sciences, Boston University, USA
Joshua Curtiss
Affiliation:
Department of Psychological and Brain Sciences, Boston University, USA
Nikolaos Kazantzis
Affiliation:
Cognitive Behaviour Therapy Research Unit, Monash University, Australia Cognitive Behaviour Therapy Research Unit, Institute for Social Neuroscience, Australia
*
*Corresponding author. Email: [email protected]

Abstract

Background:

Despite increased research interest in smartphone mental health applications (MHapps), few studies have examined user engagement and its determinants. MoodMission is a MHapp that targets low mood and anxiety via evidence-based techniques including behavioural activation (BA).

Aims:

The present study aimed to investigate (i) whether BA interventions delivered with visual psychoeducation had greater engagement than BA interventions delivered with solely written psychoeducation, (ii) whether BA interventions targeting mastery would have greater engagement than those targeting pleasure, and (iii) the relationship between level of engagement and MHapp benefit.

Method:

Participants downloaded MoodMission and completed activities and within-app evaluations over a 30-day period. Data from 238 MoodMission users were analysed via multi-level modelling and linear regression.

Results:

The average number of app-based activities completed was 5.46 and the average self-reported engagement level was in the low to moderate range. As hypothesized, higher levels of engagement significantly predicted more positive activity appraisal.

Conclusions:

The results suggest that BA technique beliefs are involved in MHapp engagement and future research examining user appraisals of techniques is warranted.

Type
Main
Copyright
© British Association for Behavioural and Cognitive Psychotherapies 2020

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References

Bakker, D., & Kazantzis, N. (2020). Homework Rating Scale – Mobile Application Version [Measurement instrument]. In Kazantzis, N. (ed), Using Homework Assignments in Cognitive Behavior Therapy. Routledge.Google Scholar
Bakker, D., Kazantzis, N., Rickwood, D., & Rickard, N. (2018a). A randomized controlled trial of three smartphone apps for enhancing public mental health. Behaviour Research and Therapy, 109, 7583. https://doi.org/10.1016/j.brat.2018.08.003 CrossRefGoogle ScholarPubMed
Bakker, D., Kazantzis, N., Rickwood, D., & Rickard, N. (2018b). Development and pilot evaluation of smartphone-delivered cognitive behavior therapy strategies for mood- and anxiety-related problems: MoodMission. Cognitive and Behaviour Practice, 25, 496514. https://doi.org/10.1016/j.cbpra.2018.07.002 CrossRefGoogle Scholar
Bakker, D., & Rickard, N. (2018). Engagement in mobile phone app for self-monitoring of emotional wellbeing predicts changes in mental health: MoodPrism. Journal of Affective Disorders, 227, 432442. https://doi.org/10.1016/j.jad.2017.11.016 CrossRefGoogle ScholarPubMed
Bakker, D., & Rickard, N. (2019). Engagement with a cognitive behavioural therapy mobile phone app predicts changes in mental health and wellbeing: MoodMission. Australian Psychologist, 54, 245260. https://doi.org/10.1111/ap.12383 CrossRefGoogle Scholar
Bakker, M., & Wicherts, J. M. (2014). Outlier removal and the relation with reporting errors and quality of psychological research. PLoS One, 9, e103360. https://doi.org/10.1371/journal.pone.0103360 CrossRefGoogle ScholarPubMed
Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice-Hall.Google Scholar
Bauer, M., Glenn, T., Geddes, J., Gitlin, M., Grof, P., Kessing, L. V., Monteith, S., Faurholt-Jepsen, M., Severus, E., & Whybrow, P. C. (2020). Smartphones in mental health: a critical review of background issues, current status and future concerns. International Journal of Bipolar Disorders, 8. https://doi.org/10.1186/s40345-019-0164-x CrossRefGoogle Scholar
Deady, M., Johnston, D. A., Glozier, N., Milne, D., Choi, I., Mackinnon, A., Mykletun, A., Calvo, R. A., Gayed, A., Bryant, R., Christensen, H., & Harvey, S. B. (2018). Smartphone application for preventing depression: study protocol for a workplace randomised controlled trial. BMJ Open, 8, e020510. https://doi.org/10.1136/bmjopen-2017-020510 CrossRefGoogle ScholarPubMed
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39, 122. https://doi.org/10.1111/j.2517-6161.1977.tb01600.x Google Scholar
Dimidjian, S., Barrera, M., Martell, C., Munoz, R. F., & Lewinsohn, P. M. (2011). The origins and current status of behavioral activation treatments for depression. Annual Review of Clinician Psychology, 7, 138. https://doi.org/10.1146/annurev-clinpsy-032210-104535 CrossRefGoogle ScholarPubMed
Duncan, S. F., Childs, G. R., & Larson, J. H. (2010). Perceived helpfulness of four different types of marriage preparation interventions. Family Relations, 59, 623636. https://doi.org/10.1111/j.1741-3729.2010.00628.x CrossRefGoogle Scholar
Economides, M., Martman, J., Bell., M. J., & Sanderson, B. (2018). Improvements in stress, affect, and irritability following brief use of a mindfulness-based smartphone app: a randomized controlled trial. Mindfulness, 9, 15841593. https://doi.org/10.1007/s12671-018-0905-4 CrossRefGoogle ScholarPubMed
Finch, H. (2017). Multilevel modeling in the presence of outliers: a comparison of robust estimation methods. Psicologica, 38, 5792. https://www.uv.es/psicologica/articulos1.17/3FINCH.pdf Google Scholar
Firth, J., Torous, J., Nicholas, J., Carney, R., Rosenbaum, S., & Sarris, J. (2017). Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. Journal of Affective Disorders, 218, 1522. https://doi.org/10.1016/j.jad.2017.04.046 CrossRefGoogle ScholarPubMed
Fung, W. K., & Xu, X. C. (2010). Estimation and robustness of linear mixed models in credibility context. Variance: Advancing the Science of Risk, 2, 6680. http://www.variancejournal.org/issues/04-01/66.pdf Google Scholar
Giosan, C., Cobeanu, O., Mogoaşe, C., Szentagotai, A., Mureşan, V., & Boian, R. (2017). Reducing depressive symptomatology with a smartphone app: study protocol for a randomized, placebo-controlled trial. Trials, 18, e215. https://doi.org/10.1186/s13063-017-1960-1 CrossRefGoogle ScholarPubMed
Hara, K. M., Aviram, A., Constantino, M. J., Westra, H. A., & Antony, M. M. (2017). Therapist empathy, homework compliance, and outcome in cognitive behavioral therapy for generalised anxiety disorder: partitioning within- and between-therapist effects. Cognitive Behaviour Therapy, 46, 375390. https://doi.org/10.1080/16506073.2016.1253605 CrossRefGoogle Scholar
Hidalgo-Mazzei, D., Reinares, M., Mateu, A., Nikolova, V. L., Bonnin, C. D. M., Samalin, L., Garcia-Estela, A., Perez-Sola, V., Young, A. H., Strejilevich, S., Vieta, E., & Colom, F. (2018). OpenSIMPLe: a real-world implementation feasibility study of a smartphone-based psychoeducation programme for bipolar disorder. Journal of Affective Disorders, 241, 436445. https://doi.org/10.1016/j.jad.2018.08.048 CrossRefGoogle ScholarPubMed
Holdsworth, E., Bowen, E., Brown, S., & Howat, D. (2014). Client engagement in psychotherapeutic treatment and associations with client characteristics, therapist characteristics, and treatment factors. Clinical Psychology Review, 34, 428450. https://doi.org/10.1016/j.cpr.2014.06.004 CrossRefGoogle ScholarPubMed
Jacobs, N. W., Berduszek, R. J., Dijkstra, P. U., & van der Sluis, C. K. (2017). Validity and reliability of the Upper Extremity Work Demands Scale. Journal of Occupational Rehabilitation, 27, 520529. https://doi.org/10.1007/s10926-016-9683-9 CrossRefGoogle ScholarPubMed
Kazantzis, N., Brownfield, N., Mosely, L., Usatoff, A., & Flighty, A. (2017). Homework in cognitive behavioral therapy: a systematic review of adherence assessment in anxiety and depression treatment (2011–2016). Psychiatric Clinics of North America, 40, 625639. https://doi.org/10.1016/j.psc.2017.08.001 CrossRefGoogle Scholar
Kazantzis, N., Deane, F., Ronan, K. R., & L’Abate, L. (eds) (2005). Using Homework Assignments in Cognitive Behavior Therapy. Routledge.CrossRefGoogle Scholar
Kazantzis, N., & L’Abate, L. (2005). Theoretical foundations. In Kazantzis, N., Deane., F. P., Ronan., K. R., & L’Abate, L. (eds), Using Homework Assignments in Cognitive Behavior Therapy (pp. 933). Routledge.CrossRefGoogle Scholar
Kazantzis, N., Luong, H. K., Usatoff, A. S., Impala, T., Yew, R. Y., & Hofmann, S. G. (2018). The processes of cognitive behavioral therapy: a review of meta-analyses. Cognitive Therapy and Research, 42, 349357. https://doi.org/10.1007/s10608-018-9920-y CrossRefGoogle Scholar
Kazantzis, N., Whittington, C., & Dattilio, F. (2010). Meta-analysis of homework effects in cognitive and behavioral therapy: a replication and extension. Clinical Psychology: Science and Practice, 17, 144156. https://doi.org/10.1111/j.1468-2850.2010.01204.x Google Scholar
Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine, 16, 606613. https://doi.org/10.1046/j.1525-1497.2001.016009606.x CrossRefGoogle ScholarPubMed
Martell, C. R., Dimidjian, S., & Lewinsohn, P. M. (2010). Behavioral activation therapy. In Kazantzis, N., Reinecke, M. A., & Freeman, A. (eds), Cognitive and Behavioral Theories in Clinical Practice (pp. 193217). Guilford Press.Google Scholar
McDonald, B. R., & Morgan, R. D. (2013). Enhancing homework compliance in correctional psychotherapy. Criminal Justice and Behaviour, 40, 814828. https://doi.org/10.1177/0093854813480781 CrossRefGoogle Scholar
MoodMission Pty Ltd (2019). MoodMission (version 1.4.7) [Mobile application software]. https://apps.apple.com/au/app/moodmission/id1140332763 Google Scholar
Ng, M. M., Firth, J., Minen, M., & Torous, J. (2019). User engagement in mental health apps: a review of measurement, reporting, and validity. Psychiatric Services, 70, 538544. https://doi.org/10.1176/appi.ps.201800519 CrossRefGoogle ScholarPubMed
Ozonur, D., Akdur, H. T. K., & Bayrak, H. (2017). Comparisons of tests of distributional assumption in Poisson regression model. Communications in Statistics – Simulation and Computation, 46, 61976207. https://doi.org/10.1080/03610918.2016.1202267 CrossRefGoogle Scholar
Parrish, D. E., Oxhandler, H. K., Duron, J. F., Swank, P., & Bordnick, P. (2016). Feasibility of virtual reality environments for adolescent social anxiety disorder. Research on Social Work Practice, 26, 825835. https://doi.org/10.1177/1049731514568897 CrossRefGoogle Scholar
Pepinsky, T. (2018). A note on listwise deletion versus multiple imputation. Political Analysis, 26, 480488. https://doi.org/10.1017/pan.2018.18 CrossRefGoogle Scholar
Richardson, D., Hosemans, D., & Kazantzis, N. (2020). Engagement with Health-Promoting Activities: Psychometric Evaluation of the Homework Rating Scale in a Large Community Sample. Manuscript in preparation.Google Scholar
Sachsenweger, M. A., Fletcher, R. B., & Clarke, D. (2015). Pessimism and homework in CBT for depression. Journal of Clinical Psychology, 71, 11531172. https://doi.org/10.1002/jclp.22227 CrossRefGoogle ScholarPubMed
Sagar, R., & Pattanayak, R. D. (2015). Use of smartphone apps for mental health: can they translate to a smart and effective mental health care? Journal of Mental Health and Human Behaviour, 20, 13. https://doi.org/10.4103/0971-8990.164791 CrossRefGoogle Scholar
Skinner, B. F. (1938). The Behaviour of Organisms: An Experimental Analysis. Appleton-Century.Google Scholar
Snijders, T. A., & Berkhof, J. (2008). Diagnostic checks for multilevel models. In de Leeuw, J., Meijer, E., Goldstein, H., & de Deleeuw, J. (eds), Handbook of Multilevel Analysis (pp. 141175). Springer.CrossRefGoogle Scholar
Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Lowe, B. (2006). A brief measure for assessing generalised anxiety disorder. Archives of Internal Medicine, 166, 10921097. https://doi.org/10.1001/archinte.166.10.1092 CrossRefGoogle Scholar
Statista (2016, Sept 15). Worldwide mobile app retention rate during the first 90 days of ownership as of March 2016, by mobile platform. Available at: https://www.statista.com/statistics/243728/worldwide-mobile-app-user-retention-by-mobile-plaform/ Google Scholar
Tanner, B. A. (2012). Validity of global physical and emotional SUDS. Applied Psychophysiology and Biofeedback, 37, 3134. https://doi.org/10.1007/s10484-011-9174-x CrossRefGoogle ScholarPubMed
Tennant, R., Hiller, L., Fishwick, R., Platt, S., Joseph, S., Weich, S., Parkinson, J., Secker, J., & Stewart-Brown, S. (2007). The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): development and UK validation. Health and Quality of Life Outcomes, 5, 63. https://doi.org/10.1186/1477-7525-5-63 CrossRefGoogle ScholarPubMed
Torous, J., Nicholas, J., Larsen, M. E., Firth, J., & Christensen, H. (2018). Clinical review of user engagement with mental health smartphone apps: evidence, theory and improvements. Evidence Based Mental Health, 21, 116119. https://doi.org/10.1136/eb-2018-102891 CrossRefGoogle ScholarPubMed
Wolpe, J. (1969). The Practice of Behavior Therapy. Pergamon Press.Google Scholar
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