Kaylee Payne Kruzan
ABSTRACT
Mental health symptoms are commonly discovered in primary care. Yet, these settings are not set up to provide psychological treatment. Digital interventions can play a crucial role in stepped care management of patients’ symptoms where patients are offered a low intensity intervention, and treatment evolves to incorporate providers if needed. Though digital interventions often use smartphone and wearable sensor data, little is known about patients’ desires to use these data to manage mental health symptoms. In 10 interviews with patients with symptoms of depression and anxiety, we explored their: symptom self-management, current and desired use of sensor data, and comfort sharing such data with providers. Findings support the use digital interventions to manage mental health, yet they also highlight a misalignment in patient needs and current efforts to use sensors. We outline considerations for future research, including extending design thinking to wraparound services that may be necessary to truly reduce healthcare burden.
Supplemental Material
- ELENA AGAPIE, PATRICIA A AREÁN, GARY HSIEH, and SEAN A MUNSON. 2022. A Longitudinal Goal Setting Model for Addressing Complex Personal Problems in Mental Health. (2022).Google Scholar
- Elena Agapie, Lucas Colusso, Sean A Munson, and Gary Hsieh. 2016. Plansourcing: Generating behavior change plans with friends and crowds. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. 119–133.Google ScholarDigital Library
- Jessica S Ancker, Holly O Witteman, Baria Hafeez, Thierry Provencher, Mary Van de Graaf, and Esther Wei. 2015. “You get reminded you’re a sick person”: personal data tracking and patients with multiple chronic conditions. Journal of medical Internet research 17, 8 (2015), e4209.Google ScholarCross Ref
- Gerhard Andersson, Jan Bergström, Monica Buhrman, Per Carlbring, Fredrik Holländare, Viktor Kaldo, Elisabeth Nilsson-Ihrfelt, Björn Paxling, Lars Ström, and Johan Waara. 2008. Development of a new approach to guided self-help via the Internet: The Swedish experience. Journal of Technology in Human Services 26, 2-4 (2008), 161–181.Google ScholarCross Ref
- Janine Archer, Peter Bower, Simon Gilbody, Karina Lovell, David Richards, Linda Gask, Chris Dickens, and Peter Coventry. 2012. Collaborative care for depression and anxiety problems. Cochrane Database of Systematic Reviews10 (2012).Google Scholar
- Min Hane Aung, Mark Matthews, and Tanzeem Choudhury. 2017. Sensing behavioral symptoms of mental health and delivering personalized interventions using mobile technologies. Depression and anxiety 34, 7 (2017), 603–609.Google Scholar
- Dror Ben-Zeev, Emily A Scherer, Rui Wang, Haiyi Xie, and Andrew T Campbell. 2015. Next-generation psychiatric assessment: Using smartphone sensors to monitor behavior and mental health.Psychiatric rehabilitation journal 38, 3 (2015), 218.Google Scholar
- Natalie Berry, Sandra Bucci, Fiona Lobban, 2017. Use of the internet and mobile phones for self-management of severe mental health problems: qualitative study of staff views. JMIR mental health 4, 4 (2017), e8311.Google Scholar
- Eric J Bruns and Janet S Walker. 2010. Defining practice: Flexibility, legitimacy, and the nature of systems of care and wraparound. Evaluation and Program Planning 33, 1 (2010), 45–48.Google ScholarCross Ref
- Eleanor R Burgess, Madhu C Reddy, and David C Mohr. 2022. " I Just Can’t Help But Smile Sometimes": Collaborative Self-Management of Depression. Proceedings of the ACM on Human-Computer Interaction 6, CSCW1(2022), 1–32.Google ScholarDigital Library
- Eleanor R Burgess, Kathryn E Ringland, Jennifer Nicholas, Ashley A Knapp, Jordan Eschler, David C Mohr, and Madhu C Reddy. 2019. " I think people are powerful" The Sociality of Individuals Managing Depression. Proceedings of the ACM on Human-Computer Interaction 3, CSCW(2019), 1–29.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. Journal of medical Internet research 13, 3 (2011), e1838.Google ScholarCross Ref
- Clara Caldeira, Yu Chen, Lesley Chan, Vivian Pham, Yunan Chen, and Kai Zheng. 2017. Mobile apps for mood tracking: an analysis of features and user reviews. In AMIA Annual Symposium Proceedings, Vol. 2017. American Medical Informatics Association, 495.Google Scholar
- Luca Canzian and Mirco Musolesi. 2015. Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis. In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. 1293–1304.Google ScholarDigital Library
- Eun Kyoung Choe, Saeed Abdullah, Mashfiqui Rabbi, Edison Thomaz, Daniel A Epstein, Felicia Cordeiro, Matthew Kay, Gregory D Abowd, Tanzeem Choudhury, James Fogarty, 2017. Semi-automated tracking: a balanced approach for self-monitoring applications. IEEE Pervasive Computing 16, 1 (2017), 74–84.Google ScholarDigital Library
- Taskina Chowdhury and Jane Dimmitt Champion. 2020. Outcomes of depression screening for adolescents accessing pediatric primary care-based services. Journal of Pediatric Nursing 52 (2020), 25–29.Google ScholarCross Ref
- Karen Church, Eve Hoggan, and Nuria Oliver. 2010. A study of mobile mood awareness and communication through MobiMood. In Proceedings of the 6th Nordic conference on human-computer interaction: extending boundaries. 128–137.Google ScholarDigital Library
- Richard Churchill, Mandip Khaira, Virginia Gretton, Clair Chilvers, Michael Dewey, Conor Duggan, Alan Lee, Antidepressants in Primary Care (CAPC) Study Group, 2000. Treating depression in general practice: factors affecting patients’ treatment preferences.British Journal of General Practice 50, 460 (2000), 905–906.Google Scholar
- William E Copeland, Dieter Wolke, Lilly Shanahan, and E Jane Costello. 2015. Adult functional outcomes of common childhood psychiatric problems: a prospective, longitudinal study. JAMA psychiatry 72, 9 (2015), 892–899.Google ScholarCross Ref
- Victor P Cornet and Richard J Holden. 2018. Systematic review of smartphone-based passive sensing for health and wellbeing. Journal of biomedical informatics 77 (2018), 120–132.Google ScholarCross Ref
- Pim Cuijpers, Matthias Berking, Gerhard Andersson, Leanne Quigley, Annet Kleiboer, and Keith S Dobson. 2013. A meta-analysis of cognitive-behavioural therapy for adult depression, alone and in comparison with other treatments. The Canadian Journal of Psychiatry 58, 7 (2013), 376–385.Google ScholarCross Ref
- Pim Cuijpers, Annemieke Van Straten, and Lisanne Warmerdam. 2007. Behavioral activation treatments of depression: A meta-analysis. Clinical psychology review 27, 3 (2007), 318–326.Google Scholar
- Gerald C Davison. 2000. Stepped care: doing more with less?Journal of consulting and clinical psychology 68, 4(2000), 580.Google Scholar
- Paul L de Zwart, Bertus F Jeronimus, and Peter de Jonge. 2019. Empirical evidence for definitions of episode, remission, recovery, relapse and recurrence in depression: a systematic review. Epidemiology and psychiatric sciences 28, 5 (2019), 544–562.Google ScholarCross Ref
- Danae Dinkel, Jennifer Harsh Caspari, Louis Fok, Maxine Notice, David J Johnson, Shinobu Watanabe-Galloway, and Margaret Emerson. 2021. A qualitative exploration of the feasibility of incorporating depression apps into integrated primary care clinics. Translational behavioral medicine 11, 9 (2021), 1708–1716.Google Scholar
- Megan Dwight-Johnson, Cathy D Sherbourne, Diana Liao, and Kenneth B Wells. 2000. Treatment preferences among depressed primary care patients. Journal of general internal medicine 15, 8 (2000), 527–534.Google ScholarCross Ref
- Daniel A Epstein, Clara Caldeira, Mayara Costa Figueiredo, Xi Lu, Lucas M Silva, Lucretia Williams, Jong Ho Lee, Qingyang Li, Simran Ahuja, Qiuer Chen, 2020. Mapping and taking stock of the personal informatics literature. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 4 (2020), 1–38.Google ScholarDigital Library
- Daniel A Epstein, Monica Caraway, Chuck Johnston, An Ping, James Fogarty, and Sean A Munson. 2016. Beyond abandonment to next steps: understanding and designing for life after personal informatics tool use. In Proceedings of the 2016 CHI conference on human factors in computing systems. 1109–1113.Google ScholarDigital Library
- Daniel A Epstein, An Ping, James Fogarty, and Sean A Munson. 2015. A lived informatics model of personal informatics. In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. 731–742.Google ScholarDigital Library
- Shan Feng, Matti Mäntymäki, Amandeep Dhir, Hannu Salmela, 2021. How self-tracking and the quantified self promote health and well-being: systematic review. Journal of Medical Internet Research 23, 9 (2021), e25171.Google ScholarCross Ref
- David M Fergusson, Lianne J Woodward, and L John Horwood. 2000. Risk factors and life processes associated with the onset of suicidal behaviour during adolescence and early adulthood. Psychological medicine 30, 1 (2000), 23–39.Google Scholar
- Joseph Firth, Jack Cotter, Rebecca Elliott, Paul French, and Alison R Yung. 2015. A systematic review and meta-analysis of exercise interventions in schizophrenia patients. Psychological medicine 45, 7 (2015), 1343–1361.Google Scholar
- Joseph Firth, John Torous, Jennifer Nicholas, Rebekah Carney, Simon Rosenbaum, and Jerome Sarris. 2017. Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. Journal of affective disorders 218 (2017), 15–22.Google ScholarCross Ref
- Richard G Frank, Haiden A Huskamp, and Harold Alan Pincus. 2003. Aligning incentives in the treatment of depression in primary care with evidence-based practice. Psychiatric Services 54, 5 (2003), 682–687.Google ScholarCross Ref
- Adrian Furnham and Viren Swami. 2018. Mental health literacy: A review of what it is and why it matters.International Perspectives in Psychology: Research, Practice, Consultation 7, 4(2018), 240.Google Scholar
- Simon B Goldberg, Sin U Lam, Otto Simonsson, John Torous, and Shufang Sun. 2022. Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials. PLOS digital health 1, 1 (2022), e0000002.Google Scholar
- Andrea K Graham, Carolyn J Greene, Mary J Kwasny, Susan M Kaiser, Paul Lieponis, Thomas Powell, and David C Mohr. 2020. Coached mobile app platform for the treatment of depression and anxiety among primary care patients: a randomized clinical trial. JAMA psychiatry 77, 9 (2020), 906–914.Google ScholarCross Ref
- Amelia Gulliver, Kathleen M Griffiths, and Helen Christensen. 2010. Perceived barriers and facilitators to mental health help-seeking in young people: a systematic review. BMC psychiatry 10, 1 (2010), 1–9.Google Scholar
- Clara E Hill, Sarah Knox, Barbara J Thompson, Elizabeth Nutt Williams, Shirley A Hess, and Nicholas Ladany. 2005. Consensual qualitative research: An update.Journal of counseling psychology 52, 2 (2005), 196.Google Scholar
- Adam S Hoffberg, Kelly A Stearns-Yoder, and Lisa A Brenner. 2020. The effectiveness of crisis line services: a systematic review. Frontiers in public health 7 (2020), 399.Google Scholar
- Stefan G Hofmann and Jasper AJ Smits. 2008. Cognitive-behavioral therapy for adult anxiety disorders: a meta-analysis of randomized placebo-controlled trials. Journal of clinical psychiatry 69, 4 (2008), 621.Google ScholarCross Ref
- Hsiu-Fang Hsieh and Sarah E Shannon. 2005. Three approaches to qualitative content analysis. Qualitative health research 15, 9 (2005), 1277–1288.Google Scholar
- Daoyan Jin, Hallgeir Halvari, Natalia Maehle, and Anja H Olafsen. 2022. Self-tracking behaviour in physical activity: a systematic review of drivers and outcomes of fitness tracking. Behaviour & Information Technology 41, 2 (2022), 242–261.Google ScholarCross Ref
- Eirini Karyotaki, Orestis Efthimiou, Clara Miguel, Frederic Maas genannt Bermpohl, Toshi A Furukawa, Pim Cuijpers, Heleen Riper, Vikram Patel, Adriana Mira, Alan W Gemmil, 2021. Internet-based cognitive behavioral therapy for depression: a systematic review and individual patient data network meta-analysis. JAMA psychiatry 78, 4 (2021), 361–371.Google Scholar
- Alan E Kazdin. 2017. Addressing the treatment gap: A key challenge for extending evidence-based psychosocial interventions. Behaviour research and therapy 88 (2017), 7–18.Google Scholar
- Christina Kelley, Bongshin Lee, and Lauren Wilcox. 2017. Self-tracking for mental wellness: understanding expert perspectives and student experiences. In Proceedings of the 2017 CHI conference on human factors in computing systems. 629–641.Google ScholarDigital Library
- Ronald C Kessler, Patricia Berglund, Olga Demler, Robert Jin, Kathleen R Merikangas, and Ellen E Walters. 2005. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of general psychiatry 62, 6 (2005), 593–602.Google Scholar
- Taewan Kim, Haesoo Kim, Ha Yeon Lee, Hwarang Goh, Shakhboz Abdigapporov, Mingon Jeong, Hyunsung Cho, Kyungsik Han, Youngtae Noh, Sung-Ju Lee, 2022. Prediction for Retrospection: Integrating Algorithmic Stress Prediction into Personal Informatics Systems for College Students’ Mental Health. In CHI Conference on Human Factors in Computing Systems. 1–20.Google ScholarDigital Library
- Tine Kolenik. 2022. Methods in digital mental health: smartphone-based assessment and intervention for stress, anxiety, and depression. In Integrating Artificial Intelligence and IoT for Advanced Health Informatics. Springer, 105–128.Google Scholar
- Rachel Kornfield, Renwen Zhang, Jennifer Nicholas, Stephen M Schueller, Scott A Cambo, David C Mohr, and Madhu Reddy. 2020. " Energy is a Finite Resource": Designing Technology to Support Individuals across Fluctuating Symptoms of Depression. In Proceedings of the 2020 CHI Conference on Human factors in Computing systems. 1–17.Google ScholarDigital Library
- Jennifer Krafft, Clarissa W Ong, Carter H Davis, Julie M Petersen, Michael E Levin, and Michael P Twohig. 2022. An open trial of group acceptance and commitment therapy with an adjunctive mobile app for generalized anxiety disorder. Cognitive and Behavioral Practice 29, 4 (2022), 846–859.Google ScholarCross Ref
- Brittney S Lange-Maia, Fernando De Maio, Elizabeth F Avery, Elizabeth B Lynch, Emily M Laflamme, David A Ansell, and Raj C Shah. 2018. Association of community-level inequities and premature mortality: Chicago, 2011–2015. J Epidemiol Community Health 72, 12 (2018), 1099–1103.Google ScholarCross Ref
- Emily G Lattie, Andrea K Graham, Heather D Hadjistavropoulos, Blake F Dear, Nickolai Titov, and David C Mohr. 2019. Guidance on defining the scope and development of text-based coaching protocols for digital mental health interventions. Digital Health 5(2019), 2055207619896145.Google ScholarCross Ref
- Emily G Lattie, Colleen Stiles-Shields, and Andrea K Graham. 2022. An overview of and recommendations for more accessible digital mental health services. Nature Reviews Psychology 1, 2 (2022), 87–100.Google ScholarCross Ref
- Jong Ho Lee, Jessica Schroeder, and Daniel A Epstein. 2021. Understanding and Supporting Self-Tracking App Selection. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, 4 (2021), 1–25.Google ScholarDigital Library
- Kwangyoung Lee and Hwajung Hong. 2018. MindNavigator: Exploring the stress and self-interventions for mental wellness. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 1–14.Google ScholarDigital Library
- Jake Linardon, Pim Cuijpers, Per Carlbring, Mariel Messer, and Matthew Fuller-Tyszkiewicz. 2019. The efficacy of app-supported smartphone interventions for mental health problems: A meta-analysis of randomized controlled trials. World Psychiatry 18, 3 (2019), 325–336.Google ScholarCross Ref
- Tony Liu, Jonah Meyerhoff, Johannes C Eichstaedt, Chris J Karr, Susan M Kaiser, Konrad P Kording, David C Mohr, and Lyle H Ungar. 2022. The relationship between text message sentiment and self-reported depression. Journal of affective disorders 302 (2022), 7–14.Google ScholarCross Ref
- Shaun Liverpool, Catarina Pinheiro Mota, Célia MD Sales, Anja Čuš, Sara Carletto, Camellia Hancheva, Sónia Sousa, Sonia Conejo Cerón, Patricia Moreno-Peral, Giada Pietrabissa, 2020. Engaging children and young people in digital mental health interventions: systematic review of modes of delivery, facilitators, and barriers. Journal of medical Internet research 22, 6 (2020), e16317.Google ScholarCross Ref
- Haley MacLeod, Anthony Tang, and Sheelagh Carpendale. 2013. Personal informatics in chronic illness management. In Proceedings of Graphics Interface 2013. Citeseer, 149–156.Google ScholarDigital Library
- Lena Mamykina, Elizabeth Mynatt, Patricia Davidson, and Daniel Greenblatt. 2008. MAHI: investigation of social scaffolding for reflective thinking in diabetes management. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 477–486.Google ScholarDigital Library
- Mark Matthews, Gavin Doherty, John Sharry, and Carol Fitzpatrick. 2008. Mobile phone mood charting for adolescents. British Journal of Guidance & Counselling 36, 2 (2008), 113–129.Google ScholarCross Ref
- Mark Matthews, Elizabeth Murnane, and Jaime Snyder. 2017. Quantifying the Changeable Self: The role of self-tracking in coming to terms with and managing bipolar disorder. Human–Computer Interaction 32, 5-6 (2017), 413–446.Google ScholarDigital Library
- Tesfa Mekonen, Gary CK Chan, Jason P Connor, Leanne Hides, and Janni Leung. 2021. Estimating the global treatment rates for depression: a systematic review and meta-analysis. Journal of Affective Disorders 295 (2021), 1234–1242.Google ScholarCross Ref
- Jingbo Meng, Syed Ali Hussain, David C Mohr, Mary Czerwinski, Mi Zhang, 2018. Exploring user needs for a mobile behavioral-sensing technology for depression management: qualitative study. Journal of medical Internet research 20, 7 (2018), e10139.Google ScholarCross Ref
- Jonah Meyerhoff, Tony Liu, Konrad P Kording, Lyle H Ungar, Susan M Kaiser, Chris J Karr, David C Mohr, 2021. Evaluation of changes in depression, anxiety, and social anxiety using smartphone sensor features: longitudinal cohort study. Journal of medical Internet research 23, 9 (2021), e22844.Google ScholarCross Ref
- David Mohr, Pim Cuijpers, Kenneth Lehman, 2011. Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions. Journal of medical Internet research 13, 1 (2011), e1602.Google ScholarCross Ref
- David C Mohr, Francisca Azocar, Andrew Bertagnolli, Tanzeem Choudhury, Paul Chrisp, Richard Frank, Henry Harbin, Trina Histon, Debra Kaysen, Camille Nebeker, 2021. Banbury forum consensus statement on the path forward for digital mental health treatment. Psychiatric Services 72, 6 (2021), 677–683.Google ScholarCross Ref
- David C Mohr, Stacey L Hart, Isa Howard, Laura Julian, Lea Vella, Claudine Catledge, and Mitchell D Feldman. 2006. Barriers to psychotherapy among depressed and nondepressed primary care patients. Annals of Behavioral Medicine 32, 3 (2006), 254–258.Google ScholarCross Ref
- David C Mohr, Joyce Ho, Jenna Duffecy, Kelly G Baron, Kenneth A Lehman, Ling Jin, and Douglas Reifler. 2010. Perceived barriers to psychological treatments and their relationship to depression. Journal of clinical psychology 66, 4 (2010), 394–409.Google ScholarCross Ref
- David C Mohr, Aaron R Lyon, Emily G Lattie, Madhu Reddy, and Stephen M Schueller. 2017. Accelerating digital mental health research from early design and creation to successful implementation and sustainment. Journal of medical Internet research 19, 5 (2017), e7725.Google ScholarCross Ref
- David C Mohr, Stephen M Schueller, Kathryn Noth Tomasino, Susan M Kaiser, Nameyeh Alam, Chris Karr, Jessica L Vergara, Elizabeth L Gray, Mary J Kwasny, and Emily G Lattie. 2019. Comparison of the effects of coaching and receipt of app recommendations on depression, anxiety, and engagement in the IntelliCare platform: factorial randomized controlled trial. Journal of medical Internet research 21, 8 (2019), e13609.Google ScholarCross Ref
- David C Mohr, Kathryn Noth Tomasino, Emily G Lattie, Hannah L Palac, Mary J Kwasny, Kenneth Weingardt, Chris J Karr, Susan M Kaiser, Rebecca C Rossom, Leland R Bardsley, 2017. IntelliCare: an eclectic, skills-based app suite for the treatment of depression and anxiety. Journal of medical Internet research 19, 1 (2017), e6645.Google ScholarCross Ref
- David C Mohr, Ken R Weingardt, Madhu Reddy, and Stephen M Schueller. 2017. Three problems with current digital mental health research... and three things we can do about them. Psychiatric services 68, 5 (2017), 427–429.Google Scholar
- Ramin Mojtabai, Mark Olfson, Nancy A Sampson, Robert Jin, Benjamin Druss, Philip S Wang, Kenneth B Wells, Harold A Pincus, and Ronald C Kessler. 2011. Barriers to mental health treatment: results from the National Comorbidity Survey Replication. Psychological medicine 41, 8 (2011), 1751–1761.Google Scholar
- Francesca Mongelli, Penelope Georgakopoulos, and Michele T Pato. 2020. Challenges and opportunities to meet the mental health needs of underserved and disenfranchised populations in the United States. Focus 18, 1 (2020), 16–24.Google ScholarCross Ref
- Faraz Mughal, Muhammad Z Hossain, Angela Brady, Judy Samuel, and Carolyn A Chew-Graham. 2021. Mental health support through primary care during and after covid-19.Google Scholar
- Kiyuri Naicker, Nancy L Galambos, Yiye Zeng, Ambikaipakan Senthilselvan, and Ian Colman. 2013. Social, demographic, and health outcomes in the 10 years following adolescent depression. Journal of Adolescent Health 52, 5 (2013), 533–538.Google ScholarCross Ref
- Mark Olfson, Carlos Blanco, and Steven C Marcus. 2016. Treatment of adult depression in the United States. JAMA internal medicine 176, 10 (2016), 1482–1491.Google Scholar
- S Place, DL Blanch-Hartigan, C Rubin, C Gorrostieta, C Mead, J Kane, BP Marx, J Feast, and T Deckersbach. 2017. Survey Instrument (appears in: Behavioral Indicators on a Mobile Sensing Platform Predict Clinically Validated Psychiatric Symptoms of Mood and Anxiety Disorders). Copyright: Creative Commons License.(2017).Google Scholar
- Adam C Powell, Zongyang Yue, Chenglei Shan, and John B Torous. 2019. The monetization strategies of apps for anxiety management: an international comparison. Journal of Technology in Behavioral Science 4, 2 (2019), 67–72.Google ScholarCross Ref
- Robert G Priest, Christine Vize, Ann Roberts, Megan Roberts, and Andre Tylee. 1996. Lay people’s attitudes to treatment of depression: results of opinion poll for Defeat Depression Campaign just before its launch. Bmj 313, 7061 (1996), 858–859.Google ScholarCross Ref
- Mashfiqui Rabbi, Shahid Ali, Tanzeem Choudhury, and Ethan Berke. 2011. Passive and in-situ assessment of mental and physical well-being using mobile sensors. In Proceedings of the 13th international conference on Ubiquitous computing. 385–394.Google ScholarDigital Library
- Jerica Radez, Tessa Reardon, Cathy Creswell, Peter J Lawrence, Georgina Evdoka-Burton, and Polly Waite. 2021. Why do children and adolescents (not) seek and access professional help for their mental health problems? A systematic review of quantitative and qualitative studies. European child & adolescent psychiatry 30, 2 (2021), 183–211.Google Scholar
- Brenna N Renn, Abhishek Pratap, David C Atkins, Sean D Mooney, and Patricia A Areán. 2018. Smartphone-based passive assessment of mobility in depression: Challenges and opportunities. Mental health and physical activity 14 (2018), 136–139.Google Scholar
- Kira E Riehm, Emily Brignone, Elizabeth A Stuart, Joseph J Gallo, and Ramin Mojtabai. 2022. Diagnoses and Treatment After Depression Screening in Primary Care Among Youth. American journal of preventive medicine 62, 4 (2022), 511–518.Google Scholar
- Sohrab Saeb, Mi Zhang, Christopher J Karr, Stephen M Schueller, Marya E Corden, Konrad P Kording, David C Mohr, 2015. Mobile phone sensor correlates of depressive symptom severity in daily-life behavior: an exploratory study. Journal of medical Internet research 17, 7 (2015), e4273.Google ScholarCross Ref
- Jessica Schroeder, Ravi Karkar, Natalia Murinova, James Fogarty, and Sean A Munson. 2019. Examining opportunities for goal-directed self-tracking to support chronic condition management. Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies 3, 4 (2019), 1–26.Google ScholarDigital Library
- Stephen M Schueller, Kathryn Noth Tomasino, and David C Mohr. 2017. Integrating human support into behavioral intervention technologies: The efficiency model of support.Clinical Psychology: Science and Practice 24, 1 (2017), 27.Google Scholar
- Albert Siu. 2016. Follow-up After Screening Response.Google Scholar
- Albert L Siu, Kirsten Bibbins-Domingo, David C Grossman, Linda Ciofu Baumann, Karina W Davidson, Mark Ebell, Francisco AR García, Matthew Gillman, Jessica Herzstein, Alex R Kemper, 2016. Screening for depression in adults: US Preventive Services Task Force recommendation statement. Jama 315, 4 (2016), 380–387.Google ScholarCross Ref
- John Torous, Steven Richard Chan, Shih Yee-Marie Tan, Jacob Behrens, Ian Mathew, Erich J Conrad, Ladson Hinton, Peter Yellowlees, Matcheri Keshavan, 2014. Patient smartphone ownership and interest in mobile apps to monitor symptoms of mental health conditions: a survey in four geographically distinct psychiatric clinics. JMIR mental health 1, 1 (2014), e4004.Google Scholar
- John Torous, Erin E Michalak, and Heather L O’Brien. 2020. Digital health and engagement—looking behind the measures and methods. JAMA Network Open 3, 7 (2020), e2010918–e2010918.Google ScholarCross Ref
- Alina Trifan, Maryse Oliveira, José Luís Oliveira, 2019. Passive sensing of health outcomes through smartphones: systematic review of current solutions and possible limitations. JMIR mHealth and uHealth 7, 8 (2019), e12649.Google Scholar
- Annemieke Van Straten, Wike Seekles, Nelleke J Van ‘t Veer-Tazelaar, Aartjan TF Beekman, and Pim Cuijpers. 2010. Stepped care for depression in primary care: what should be offered and how?Medical Journal of Australia 192 (2010), S36–S39.Google Scholar
- John E VanDenBerg and E Mary Grealish. 1996. Individualized services and supports through the wraparound process: Philosophy and procedures. Journal of Child and Family Studies 5, 1 (1996), 7–21.Google ScholarCross Ref
- Elizabeth Reisinger Walker, Janet R Cummings, Jason M Hockenberry, and Benjamin G Druss. 2015. Insurance status, use of mental health services, and unmet need for mental health care in the United States. Psychiatric Services 66, 6 (2015), 578–584.Google ScholarCross Ref
- Philip S Wang, Michael Lane, Mark Olfson, Harold A Pincus, Kenneth B Wells, and Ronald C Kessler. 2005. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Archives of general psychiatry 62, 6 (2005), 629–640.Google ScholarCross Ref
- Rui Wang, Weichen Wang, Alex DaSilva, Jeremy F Huckins, William M Kelley, Todd F Heatherton, and Andrew T Campbell. 2018. Tracking depression dynamics in college students using mobile phone and wearable sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 1 (2018), 1–26.Google ScholarDigital Library
- Haining Zhu, Joanna Colgan, Madhu Reddy, and Eun Kyoung Choe. 2016. Sharing patient-generated data in clinical practices: an interview study. In AMIA Annual Symposium Proceedings, Vol. 2016. American Medical Informatics Association, 1303.Google Scholar
Index Terms
- The Perceived Utility of Smartphone and Wearable Sensor Data in Digital Self-tracking Technologies for Mental Health
Recommendations
4th Symposium on Computing and Mental Health: Designing Ethical eMental Health Services
CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing SystemsWith psychiatric conditions like depression now the leading global causing of disability, the need for innovative solutions is apparent. The promise of mental health care delivered through technology (eMentalHealth) to provide personalized care offers a ...
Mental Health for Medical Students, what do we know today?
AbstractMental health illnesses are rampant among university students. Symptoms of depression, anxiety, stress, and burnout are experienced in undergraduate and graduate levels especially among medical students. This systematic review explores the ...
Self-Care Technologies in HCI: Trends, Tensions, and Opportunities
Many studies show that self-care technologies can support patients with chronic conditions and their carers in understanding the ill body and increasing control of their condition. However, many of these studies have largely privileged a medical ...
Comments