Abstract
Behavioral Activation (BA)therapy has shown to be effective in treating depression. Recommending healthy activities is a core principle in Behavioral Activation (BA), which is typically done by the therapist. However, most BA smartphone applications do not recommend specific activities. This article reports quantitative results from an 8-week feasibility study of a previously presented smartphone-based BA recommender system. The system supports the planning and enacting of pleasurable activities and promotes activation of diverse activity types. Enrollment included 43 clinically depressed patients who installed the system on their phone and initiated activity scheduling. Twenty-nine patients used the system daily for more than a week.These patients presented a significant reduction in depressive symptoms during the study period. They displayed a more personalized usage approach and created recurring health goals comprising of their own customized activities. Furthermore, they took inspiration within various types of activities, thereby displaying more activity diversity. This study suggests that enacting a diverse mixture of activities that promote good sleep, personal hygiene, exercise, social contact, and leisure time can be essential in managing depressive symptoms. A smartphone-based activity recommender system can help patients achieve this.
- Saeed Abdullah, Elizabeth L. Murnane, Mark Matthews, and Tanzeem Choudhury. 2017. Circadian Computing: Sensing, Modeling, and Maintaining Biological Rhythms. Springer International Publishing, Cham, 35–58. https://doi.org/10.1007/978-3-319-51394-2_3Google Scholar
- American Psychiatric Association et al. 2013. Diagnostic and Statistical Manual of Mental Disorders (DSM-5). American Psychiatric Publishing, Washington, DC. https://doi.org/10.1176/appi.books.9780890425596.dsm04Google Scholar
- Sepideh Bakht, Tahereh Mahdavi Haji, Ensiyeh Ghasemian Shirvan, and Hamed Ekhtiari. 2015. The persian checklist of pleasant events (PCPE): Development, validity and reliability. Iran. J. Psychiatr. 10, 4 (2015), 246–264.Google Scholar
- Jakob E. Bardram, Mads Frost, Károly Szántó, Maria Faurholt-Jepsen, Maj Vinberg, and Lars Vedel Kessing. 2013. Designing mobile health technology for bipolar disorder: A field trial of the monarca system. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’13). Association for Computing Machinery, New York, NY, 2627–2636. https://doi.org/10.1145/2470654.2481364 Google Scholar
Digital Library
- Aaron T. Beck. 1979. Cognitive Therapy of Depression. Guilford Press.Google Scholar
- Michelle Nicole Burns, Mark Begale, Jennifer Duffecy, Darren Gergle, Chris J. Karr, Emily Giangrande, and David C. Mohr. 2011. Harnessing context sensing to develop a mobile intervention for depression. J. Med. Internet Res. 13, 3 (12 Aug 2011), e55. https://doi.org/10.2196/jmir.1838Google Scholar
Cross Ref
- Christopher Burton, Brian McKinstry, Aurora Szentagotai Tǎtar, Antoni Serrano-Blanco, Claudia Pagliari, and Maria Wolters. 2013. Activity monitoring in patients with depression: A systematic review. J. Affect. Disord. 145, 1 (2013), 21–28. https://doi.org/10.1016/j.jad.2012.07.001Google Scholar
Cross Ref
- Peter A. Creed and Sean R. Macintyre. 2001. The relative effects of deprivation of the latent and manifest benefits of employment on the well-being of unemployed people.J. Occupat. Health Psychol. 6, 4 (2001), 324. https://doi.org/10.1037/1076-8998.6.4.324Google Scholar
- Pim Cuijpers, Annemieke van Straten, and Lisanne Warmerdam. 2007. Behavioral activation treatments of depression: A meta-analysis. Clin. Psychol. Rev. 27, 3 (2007), 318–326. https://doi.org/10.1016/j.cpr.2006.11.001Google Scholar
Cross Ref
- Jennifer Dahne, Anahi Collado, C. W. Lejuez, Cristina M. Risco, Vanessa A. Diaz, Lisa Coles, Jacob Kustanowitz, Michael J. Zvolensky, and Matthew J. Carpenter. 2019. Pilot randomized controlled trial of a spanish-language behavioral activation mobile app Aptivate for the treatment of depressive symptoms among united states Latinx adults with limited English proficiency. J. Affect. Disord. 250, (Feb. 2019), 210–217. https://doi.org/10.1016/j.jad.2019.03.009Google Scholar
- Jennifer Dahne, C. W. Lejuez, Vanessa A. Diaz, Marty S. Player, Jacob Kustanowitz, Julia W. Felton, and Matthew J. Carpenter. 2019. Pilot randomized trial of a self-help behavioral activation mobile app for utilization in primary care. Behav. Ther. 50, 4 (2019), 817–827. http://doi.org/10.1016/j.beth.2018.12.003Google Scholar
Cross Ref
- Mark Deady, David Johnston, David Milne, Nick Glozier, Dorian Peters, Rafael Calvo, and Samuel Harvey. 2018. Preliminary effectiveness of a smartphone app to reduce depressive symptoms in the workplace: Feasibility and acceptability study. JMIR Mhealth Uhealth 6, 12 (04 Dec. 2018), e11661. https://doi.org/10.2196/11661Google Scholar
- Anind K. Dey, Katarzyna Wac, Denzil Ferreira, Kevin Tassini, Jin-Hyuk Hong, and Julian Ramos. 2011. Getting closer: An empirical investigation of the proximity of user to their smart phones. In Proceedings of the 13th International Conference on Ubiquitous Computing (UbiComp’11). Association for Computing Machinery, New York, NY, 163–172. https://doi.org/10.1145/2030112.2030135 Google Scholar
Digital Library
- Amandeep Dhir, Yossiri Yossatorn, Puneet Kaur, and Sufen Chen. 2018. Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression. Int. J. Inf. Manage. 40 (2018), 141–152. http://doi.org/10.1016/j.ijinfomgt.2018.01.012 Google Scholar
Digital Library
- Sona Dimidjian, Manuel Barrera, Christopher Martell, Ricardo F. Muñoz, and Peter M. Lewinsohn. 2011. The origins and current status of behavioral activation treatments for depression. Annu. Rev. Clin. Psychol. 7, 1 (2011), 1–38. https://doi.org/10.1146/annurev-clinpsy-032210-104535Google Scholar
Cross Ref
- Michael H. Ebert, Peter T. Loosen, Barry Nurcombe, and J. F. Leckman. 2000. Current Diagnosis & Treatment in Psychiatry. Lange Medical Books/McGraw–Hill.Google Scholar
- Amanda Edwards-Stewart. 2012. Using technology to enhance empirically supported psychological treatments: Positive activity jackpot. Arch. Med. Psychol. 3, 2 (2012), 60–66.Google Scholar
- Joseph Firth, John Torous, Jennifer Nicholas, Rebekah Carney, Abhishek Pratap, Simon Rosenbaum, and Jerome Sarris. 2017. The efficacy of smartphone-based mental health interventions for depressive symptoms: A meta-analysis of randomized controlled trials. World Psychiatr. 16, 3 (2017), 287–298. http://doi.org/10.1002/wps.20472Google Scholar
Cross Ref
- Theresa Fleming, Lynda Bavin, Mathijs Lucassen, Karolina Stasiak, Sarah Hopkins, and Sally Merry. 2018. Beyond the trial: Systematic review of real-world uptake and engagement with digital self-help interventions for depression, low mood, or anxiety. J Med. Internet Res. 20, 6 (06 Jun. 2018), e199. https://doi.org/10.2196/jmir.9275Google Scholar
Cross Ref
- Matthew Fuller-Tyszkiewicz, Ben Richardson, Britt Klein, Helen Skouteris, Helen Christensen, David Austin, David Castle, Cathrine Mihalopoulos, Renee O’Donnell, Lilani Arulkadacham, Adrian Shatte, and Anna Ware. 2018. A mobile app-based intervention for depression: End-user and expert usability testing study. J. Med. Internet Res. 20, 8 (2018), 1–12. https://doi.org/10.2196/mental.9445Google Scholar
- Toshi A. Furukawa, Masaru Horikoshi, Hirokazu Fujita, Naohisa Tsujino, Ran Jinnin, Yuki Kako, Sei Ogawa, Hirotoshi Sato, Nobuki Kitagawa, Yoshihiro Shinagawa, Yoshio Ikeda, Hissei Imai, Aran Tajika, Yusuke Ogawa, Tatsuo Akechi, Mitsuhiko Yamada, Shinji Shimodera, Norio Watanabe, Masatoshi Inagaki, and Akio Hasegawa. 2018. Cognitive and behavioral skills exercises completed by patients with major depression during smartphone cognitive behavioral therapy: Secondary analysis of a randomized controlled trial. JMIR Ment. Health 5, 1 (11 Jan. 2018), e4. https://doi.org/10.2196/mental.9092Google Scholar
- Toshi A. Furukawa, Hissei Imai, Masaru Horikoshi, Shinji Shimodera, Takahiro Hiroe, Tadashi Funayama, and Tatsuo Akechi. 2018. Behavioral activation: Is it the expectation or achievement, of mastery or pleasure that contributes to improvement in depression?J. Affect. Disord. 238, (May 2018), 336–341. https://doi.org/10.1016/j.jad.2018.05.067Google Scholar
- Franz Gravenhorst, Amir Muaremi, Jakob Bardram, Agnes Grünerbl, Oscar Mayora, Gabriel Wurzer, Mads Frost, Venet Osmani, Bert Arnrich, Paul Lukowicz, and Others. 2015. Mobile phones as medical devices in mental disorder treatment: An overview. Pers. Ubiq. Comput. 19, 2 (2015), 335–353. https://doi.org/10.1007/s00779-014-0829-5 Google Scholar
Digital Library
- Allison G. Harvey. 2008. Sleep and circadian rhythms in bipolar disorder: Seeking synchrony, harmony, and regulation. Am. J. Psychiatr. 165, 7 (2008), 820–829. https://doi.org/10.1176/appi.ajp.2008.08010098Google Scholar
Cross Ref
- Ainslie Hatch, Julia E. Hoffman, Ruth Ross, and John P. Docherty. 2018. Expert consensus survey on digital health tools for patients with serious mental illness: Optimizing for user characteristics and user support. J. Med. Internet Res. 20, 6 (2018), e46. https://doi.org/10.2196/mental.9777Google Scholar
- Keith Hawton and Kees van Heeringen. 2009. Suicide.Lancet (Lond. Engl.) 373, 9672 (Apr. 2009), 1372–81. https://doi.org/10.1016/S0140-6736(09)60372-XGoogle Scholar
- Anna Huguet, Sanjay Rao, Patrick J. McGrath, Lori Wozney, Mike Wheaton, Jill Conrod, and Sharlene Rozario. 2016. A systematic review of cognitive behavioral therapy and behavioral activation apps for depression. PLoS ONE 11, 5 (2016), 1–19. https://doi.org/10.1371/journal.pone.0154248Google Scholar
Cross Ref
- Neil S. Jacobson, Keith S. Dobson, Paula A. Truax, Michael E. Addis, Kelly Koerner, Jackie K. Gollan, Eric Gortner, and Stacey E. Prince. 1996. A component analysis of cognitive-behavioral treatment for depression.J. Consult. Clin. Psychol. 64, 2 (1996), 295. http://doi.org/10.1037//0022-006x.64.2.295Google Scholar
Cross Ref
- Jonathan W. Kanter, Rachel C. Manos, William M. Bowe, David E. Baruch, Andrew M. Busch, and Laura C. Rusch. 2010. What is behavioral activation?: A review of the empirical literature. Clin. Psychol. Rev. 30, 6 (2010), 608–620. http://doi.org/10.1016/j.cpr.2010.04.001Google Scholar
- Patricia P. Katz and Edward H. Yelin. 2001. Activity loss and the onset of depressive symptoms: Do some activities matter more than others?Arthrit. Rheumat. 44, 5 (2001), 1194–1202. https://doi.org/10.1002/1529-0131(200105)44:5<1194::AID-ANR203>3.0.CO;2-6Google Scholar
- Predrag Klasnja, Sunny Consolvo, and Wanda Pratt. 2011. How to evaluate technologies for health behavior change in HCI research. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’11). ACM, New York, NY, 3063–3072. https://doi.org/10.1145/1978942.1979396 Google Scholar
Digital Library
- Leon Kreitzman and Russell Foster. 2011. The Rhythms of Life: The Biological Clocks that Control the Daily Lives of Every Living Thing. Profile Books.Google Scholar
- Soomi Lee, Rachel E. Koffer, Briana N. Sprague, Susan T. Charles, Nilam Ram, and David M. Almeida. 2018. Activity diversity and its associations with psychological well-being across adulthood. J. Gerontol. Ser. B, Psychol. Sci. Soc. Sci. 73, 6 (2018), 985–995. http://doi.org/10.1093/geronb/gbw118Google Scholar
- C. W. Lejuez, Derek R. Hopko, James P. LePage, Sandra D. Hopko, and Daniel W. McNeil. 2001. A brief behavioral activation treatment for depression. Cogn. Behav. Pract. 8, 2 (Mar. 2001), 164–175. https://doi.org/10.1016/S1077-7229(01)80022-5Google Scholar
- Peter M. Lewinsohn. 1974. A Behavioral Approach to Depression. New York University Press, New York, NY. 150–172 pages.Google Scholar
- Peter M. Lewinsohn and Michael Graf. 1973. Pleasant activities and depression.J. Consult. Clin. Psychol. 41, 2 (1973), 261. https://doi.org/10.1037/h0035142Google Scholar
- Kien Hoa Ly, Elsa Janni, Richard Wrede, Mina Sedem, Tara Donker, Per Carlbring, and Gerhard Andersson. 2015. Experiences of a guided smartphone-based behavioral activation therapy for depression: A qualitative study. Internet Intervent. 2, 1 (2015), 60–68. https://doi.org/10.1016/j.invent.2014.12.002Google Scholar
Cross Ref
- Kien Hoa Ly, Naira Topooco, Hanna Cederlund, Anna Wallin, Jan Bergstrom, Olof Molander, Per Carlbring, and Gerhard Andersson. 2015. Smartphone-supported versus full behavioural activation for depression: A randomised controlled trial. PLoS ONE 10, 5 (2015), 1–16. https://doi.org/10.1371/journal.pone.0126559Google Scholar
- Kien Hoa Ly, Anna Trüschel, Linnea Jarl, Susanna Magnusson, Tove Windahl, Robert Johansson, and Per Carlbring. 2014. Behavioural activation versus mindfulness-based guided self-help treatment administered through a smartphone application: A randomised controlled trial.Br. Med. J. 4 (2014), e003440. https://doi.org/10.1136/bmjopen-2013-003440Google Scholar
- D. J. MacPhillamy and P. M. Lewinsohn. 1972. The measurement of reinforcing events. In Proceedings of the 80th Annual Convention of the American Psychological Association, Vol. 7. American Psychological Association, Washington, DC, 399–400.Google Scholar
- Douglas J. MacPhillamy and Peter M. Lewinsohn. 1982. The pleasant events schedule: Studies on reliability, validity, and scale intercorrelation. J. Consult. Clin. Psychol. 50, 3 (1982), 363–380. https://doi.org/10.1037/0022-006X.50.3.363Google Scholar
Cross Ref
- Akio Mantani, Tadashi Kato, Toshi A. Furukawa, Masaru Horikoshi, Hissei Imai, Takahiro Hiroe, Bun Chino, Tadashi Funayama, Naohiro Yonemoto, Qi Zhou, and Nao Kawanishi. 2017. Smartphone cognitive behavioral therapy as an adjunct to pharmacotherapy for refractory depression: Randomized controlled trial. J. Med. Internet Res. 19, 11 (3 Nov 2017), e373. https://doi.org/10.2196/jmir.8602Google Scholar
- Gabriela Marcu, Jakob E. Bardram, and Silvia Gabrielli. 2011. A framework for overcoming challenges in designing persuasive monitoring and feedback systems for mental illness. In Proceedings of the 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth’11). IEEE, 1–8. http://doi.org/10.4108/icst.pervasivehealth.2011.246097Google Scholar
- Christopher R. Martell, Sona Dimidjian, and Ruth Herman-Dunn. 2013. Behavioral Activation for Depression: A Clinician’s Guide. Guilford Press.Google Scholar
- Charlotte M. McKercher, Michael D. Schmidt, Kristy A. Sanderson, George C. Patton, Terence Dwyer, and Alison J. Venn. 2009. Physical activity and depression in young adults. Am. J. Prevent. Med. 36, 2 (2009), 161–164. https://doi.org/10.1016/j.amepre.2008.09.036Google Scholar
- Merete M. Mørch and Nicole K. Rosenberg. 2005. Kognitiv Terapi: Modeller og Metoder. Gyldendal A/S.Google Scholar
- Ehimwenma Nosakhare and Rosalind Picard. 2020. Toward assessing and recommending combinations of behaviors for improving health and well-being. ACM Trans. Comput. Healthcare 1, 1, Article 4 (Mar. 2020), 29 pages. https://doi.org/10.1145/3368958 Google Scholar
Digital Library
- Francisco Nunes. 2019. From medicalized to mundane self-care technologies. Interactions 26, 3 (Apr. 2019), 67–69. https://doi.org/10.1145/3319374 Google Scholar
Digital Library
- Mashfiqui Rabbi, Min S. H. Aung, Geri Gay, M. Cary Reid, and Tanzeem Choudhury. 2018. Feasibility and acceptability of mobile phone–based auto-personalized physical activity recommendations for chronic pain self-management: Pilot study on adults. J. Med. Internet Res. 20, 10 (26 Oct. 2018), e10147. https://doi.org/10.2196/10147Google Scholar
- David A. Richards, David Ekers, Dean McMillan, Rod S. Taylor, Sarah Byford, Fiona C. Warren, Barbara Barrett, Paul A. Farrand, Simon Gilbody, Willem Kuyken, Heather O’Mahen, Ed R. Watkins, Kim A. Wright, Steven D. Hollon, Nigel Reed, Shelley Rhodes, Emily Fletcher, and Katie Finning. 2016. Cost and outcome of behavioural activation versus cognitive behavioural therapy for depression (COBRA): A randomised, controlled, non-inferiority trial. The Lancet 388, 10047 (Aug. 2016), 871–880. https://doi.org/10.1016/S0140-6736(16)31140-0Google Scholar
- Kenneth L. Rider, Larry W. Thompson, and Dolores Gallagher-Thompson. 2016. California older persons pleasant events scale: A tool to help older adults increase positive experiences. Clin. Gerontol. 39, 1 (2016), 64–83. https://doi.org/10.1080/07317115.2015.1101635Google Scholar
- Darius A. Rohani, Maria Faurholt-Jepsen, Lars Vedel Kessing, and Jakob E. Bardram. 2018. Correlations between objective behavioral features collected from mobile and wearable devices and depressive mood symptoms in patients with affective disorders: Systematic review. JMIR Mhealth Uhealth 6, 8 (13 Aug. 2018), e165. https://doi.org/10.2196/mhealth.9691Google Scholar
- Darius A. Rohani, Andrea Quemada Lopategui, Nanna Tuxen, Maria Faurholt-Jepsen, Lars V. Kessing, and Jakob E. Bardram. 2020. MUBS: A personalized recommender system for behavioral activation in mental health. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI’20). Association for Computing Machinery, New York, NY, 1–13. https://doi.org/10.1145/3313831.3376879 Google Scholar
Digital Library
- D. A. Rohani, A. Springer, V. Hollis, J. E. Bardram, and S. Whittaker. 2020. Recommending activities for mental health and well-being: Insights from two user studies. IEEE Trans. Emerg. Top. Comput. (2020), https://doi.org/10.1109/tetc.2020.2972007Google Scholar
- Darius A. Rohani, Nanna Tuxen, Andrea Quemada Lopategui, Maria Faurholt-Jepsen, Lars V. Kessing, and Jakob E. Bardram. 2019. Personalizing mental health: A feasibility study of a mobile behavioral activation tool for depressed patients. In Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth’19). ACM, New York, NY, 282–291. https://doi.org/10.1145/3329189.3329214 Google Scholar
Digital Library
- Darius Adam Rohani, Nanna Tuxen, Andrea Quemada Lopategui, Lars Vedel Kessing, and Jakob Eyvind Bardram. 2018. Data-driven learning in high-resolution activity sampling from patients with bipolar depression: Mixed-methods study. JMIR Ment. Health 5, 2 (2018), e10122. https://doi.org/10.2196/10122Google Scholar
Cross Ref
- John Rooksby, Alistair Morrison, and Dave Murray-Rust. 2019. Student perspectives on digital phenotyping: The acceptability of using smartphone data to assess mental health. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI’19). Association for Computing Machinery, New York, NY, 1–14. https://doi.org/10.1145/3290605.3300655 Google Scholar
Digital Library
- Mattias Rost, John Rooksby, Alexandra Weilenmann, Thomas Hillman, Pål Dobrin, and Juan Ye. 2016. Mobile wellbeing. In Proceedings of the 9th Nordic Conference on Human-Computer Interaction (NordiCHI’16). Association for Computing Machinery, New York, NY, Article 137, 3 pages. https://doi.org/10.1145/2971485.2987676 Google Scholar
Digital Library
- Sohrab Saeb, Mi Zhang, Christopher J. Karr, Stephen M. Schueller, Marya E. Corden, Konrad P. Kording, and David C. Mohr. 2015. Mobile phone sensor correlates of depressive symptom severity in daily-life behavior: An exploratory study. J. Med. Internet Res. 17, 7 (2015), 1–11. https://doi.org/10.2196/jmir.4273Google Scholar
Cross Ref
- Pedro Sanches, Axel Janson, Pavel Karpashevich, Camille Nadal, Chengcheng Qu, Claudia Daudén Roquet, Muhammad Umair, Charles Windlin, Gavin Doherty, Kristina Höök, and Corina Sas. 2019. HCI and affective health: Taking stock of a decade of studies and charting future research directions. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI’19). ACM, New York, NY, Article 245, 17 pages. https://doi.org/10.1145/3290605.3300475 Google Scholar
Digital Library
- Ziggi Ivan Santini, Ai Koyanagi, Stefanos Tyrovolas, Catherine Mason, and Josep Maria Haro. 2015. The association between social relationships and depression: A systematic review. J. Affect. Disord. 175 (2015), 53–65. http://doi.org/10.1016/j.jad.2014.12.049Google Scholar
- Tobias Sonne, Jörg Müller, Paul Marshall, Carsten Obel, and Kaj Grønbæk. 2016. Changing family practices with assistive technology: MOBERO improves morning and bedtime routines for children with ADHD. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI’16). Association for Computing Machinery, New York, NY, 152–164. https://doi.org/10.1145/2858036.2858157 Google Scholar
Digital Library
- Aaron Springer, Victoria Hollis, and Steve Whittaker. 2018. Mood modeling: Accuracy depends on active logging and reflection. Pers. Ubiq. Comput. 22, 4 (2018), 723–737. https://doi.org/10.1007/s00779-018-1123-8 Google Scholar
Digital Library
- Linda Teri and Rebecca G. Logsdon. 1991. Identifying pleasant activities for alzheimer’s disease patients: The pleasant events schedule-AD. The Gerontol. 31, 1 (1991), 124–127. http://doi.org/10.1093/geront/31.1.124Google Scholar
- Megan Teychenne, Kylie Ball, and Jo Salmon. 2010. Sedentary behavior and depression among adults: A review. Int. J. Behav. Med. 17, 4 (2010), 246–254. https://doi.org/10.1007/s12529-010-9075-zGoogle Scholar
Cross Ref
- John Torous, Rohn Friedman, and Matcheri Keshavan. 2014. Smartphone ownership and interest in mobile applications to monitor symptoms of mental health conditions. JMIR mHealth uHealth 2, 1 (21 Jan. 2014), e2. https://doi.org/10.2196/mhealth.2994Google Scholar
- John Torous and Laura Weiss Roberts. 2017. Needed innovation in digital health and smartphone applications for mental health: Transparency and trust. JAMA Psychiatr. 74, 5 (2017), 437–438. http://doi.org/10.1001/jamapsychiatry.2017.0262Google Scholar
- John Torous, Jessica Woodyatt, Matcheri Keshavan, and Laura M. Tully. 2019. A new hope for early psychosis care: The evolving landscape of digital care tools. Br. J. Psychiatr. 214, 5 (2019), 269–272. https://doi.org/10.1192/bjp.2019.8Google Scholar
- Yonatan Vaizman, Katherine Ellis, Gert Lanckriet, and Nadir Weibel. 2018. ExtraSensory app: Data collection in-the-wild with rich user interface to self-report behavior. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI’18). Association for Computing Machinery, New York, NY, 1–12. https://doi.org/10.1145/3173574.3174128 Google Scholar
Digital Library
- Fabian Wahle, Tobias Kowatsch, Elgar Fleisch, Michael Rufer, and Steffi Weidt. 2016. Mobile sensing and support for people with depression: A pilot trial in the wild. JMIR mHealth uHealth 4, 3 (2016), e111. https://doi.org/10.2196/mhealth.5960Google Scholar
Index Terms
Benefits of Using Activity Recommender Technology for Self-management of Depressive Symptoms
Recommendations
Personalizing Mental Health: A Feasibility Study of a Mobile Behavioral Activation Tool for Depressed Patients
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