This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (2939) Ecological Momentary Assessment (EMA) (309)

Published on in Vol 13, No 3 (2011): Jul-Sep

Harnessing Context Sensing to Develop a Mobile Intervention for Depression

Harnessing Context Sensing to Develop a Mobile Intervention for Depression

Harnessing Context Sensing to Develop a Mobile Intervention for Depression

Authors of this article:

Michelle Nicole Burns1 Author Orcid Image ;   Mark Begale1 ;   Jennifer Duffecy1 ;   Darren Gergle2 ;   Chris J Karr3 Author Orcid Image ;   Emily Giangrande1 ;   David C Mohr1 Author Orcid Image
Article Authors Cited by (455) Tweetations (33) Metrics

Journals

  1. Braz V, Lopes M. Evaluation of mobile applications related to nutrition. Public Health Nutrition 2018:1 View
  2. Castro L, Favela J, Quintana E, Perez M. Behavioral data gathering for assessing functional status and health in older adults using mobile phones. Personal and Ubiquitous Computing 2015;19(2):379 View
  3. Schueller S, Aguilera A, Mohr D. Ecological momentary interventions for depression and anxiety. Depression and Anxiety 2017;34(6):540 View
  4. Dallery J, Kurti A, Erb P. A New Frontier: Integrating Behavioral and Digital Technology to Promote Health Behavior. The Behavior Analyst 2015;38(1):19 View
  5. Doryab A, Frost M, Faurholt-Jepsen M, Kessing L, Bardram J. Impact factor analysis: combining prediction with parameter ranking to reveal the impact of behavior on health outcome. Personal and Ubiquitous Computing 2015;19(2):355 View
  6. Faurholt-Jepsen M, Busk J, Þórarinsdóttir H, Frost M, Bardram J, Vinberg M, Kessing L. Objective smartphone data as a potential diagnostic marker of bipolar disorder. Australian & New Zealand Journal of Psychiatry 2019;53(2):119 View
  7. Ebenfeld L, Kleine Stegemann S, Lehr D, Ebert D, Funk B, Riper H, Berking M. A mobile application for panic disorder and agoraphobia: Insights from a multi-methods feasibility study. Internet Interventions 2020;19:100296 View
  8. Kanjo E, Al-Husain L, Chamberlain A. Emotions in context: examining pervasive affective sensing systems, applications, and analyses. Personal and Ubiquitous Computing 2015;19(7):1197 View
  9. Wenze S, Armey M, Miller I. Feasibility and Acceptability of a Mobile Intervention to Improve Treatment Adherence in Bipolar Disorder. Behavior Modification 2014;38(4):497 View
  10. Aafjes-van Doorn K, Kamsteeg C, Bate J, Aafjes M. A scoping review of machine learning in psychotherapy research. Psychotherapy Research 2021;31(1):92 View
  11. Faherty L, Hantsoo L, Appleby D, Sammel M, Bennett I, Wiebe D. Movement patterns in women at risk for perinatal depression: use of a mood-monitoring mobile application in pregnancy. Journal of the American Medical Informatics Association 2017;24(4):746 View
  12. Jacobson N, Chung Y. Passive Sensing of Prediction of Moment-To-Moment Depressed Mood among Undergraduates with Clinical Levels of Depression Sample Using Smartphones. Sensors 2020;20(12):3572 View
  13. Reger G, Skopp N, Edwards-Stewart A, Lemus E. Comparison of Prolonged Exposure (PE) Coach to Treatment as Usual: A Case Series With Two Active Duty Soldiers. Military Psychology 2015;27(5):287 View
  14. Yin K, Laranjo L, Tong H, Lau A, Kocaballi A, Martin P, Vagholkar S, Coiera E. Context-Aware Systems for Chronic Disease Patients: Scoping Review. Journal of Medical Internet Research 2019;21(6):e10896 View
  15. Granholm E, Holden J, Dwyer K, Link P. Mobile-assisted cognitive-behavioral social skills training in older adults with schizophrenia. Journal of Behavioral and Cognitive Therapy 2020;30(1):13 View
  16. Jashinsky J, Burton S, Hanson C, West J, Giraud-Carrier C, Barnes M, Argyle T. Tracking Suicide Risk Factors Through Twitter in the US. Crisis 2014;35(1):51 View
  17. Giosan C, Cobeanu O, Mogoaşe C, Szentágotai Tătar A, Mureşan V, Boian R. Using a smartphone app to reduce cognitive vulnerability and mild depressive symptoms: Study protocol of an exploratory randomized controlled trial. Trials 2016;17(1) View
  18. Payne H, Lister C, West J, Bernhardt J. Behavioral Functionality of Mobile Apps in Health Interventions: A Systematic Review of the Literature. JMIR mHealth and uHealth 2015;3(1):e20 View
  19. Briffault X, Morgiève M, Courtet P. From e-Health to i-Health: Prospective Reflexions on the Use of Intelligent Systems in Mental Health Care. Brain Sciences 2018;8(6):98 View
  20. Triantafyllidis A, Tsanas A. Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature. Journal of Medical Internet Research 2019;21(4):e12286 View
  21. Webb C, Rosso I, Rauch S. Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions. Harvard Review of Psychiatry 2017;25(3):114 View
  22. Saeb S, Zhang M, Karr C, Schueller S, Corden M, Kording K, Mohr D. Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study. Journal of Medical Internet Research 2015;17(7):e175 View
  23. Pinder C, Vermeulen J, Cowan B, Beale R. Digital Behaviour Change Interventions to Break and Form Habits. ACM Transactions on Computer-Human Interaction 2018;25(3):1 View
  24. Kennedy C, Powell J, Payne T, Ainsworth J, Boyd A, Buchan I. Active Assistance Technology for Health-Related Behavior Change: An Interdisciplinary Review. Journal of Medical Internet Research 2012;14(3):e80 View
  25. Hoff K, Bashir M. Trust in Automation. Human Factors: The Journal of the Human Factors and Ergonomics Society 2015;57(3):407 View
  26. López-Montoyo A, Modrego-Alarcón M, Morillo H, García-Campayo J, Quero S. Programas de ordenador basados en mindfulness . Una revisión de la literatura médica. Mindfulness & Compassion 2016;1(1):23 View
  27. Msetfi R, O'Sullivan D, Walsh A, Nelson J, Van de Ven P. Using Mobile Phones to Examine and Enhance Perceptions of Control in Mildly Depressed and Nondepressed Volunteers: Intervention Study. JMIR mHealth and uHealth 2018;6(11):e10114 View
  28. Donker T, Petrie K, Proudfoot J, Clarke J, Birch M, Christensen H. Smartphones for Smarter Delivery of Mental Health Programs: A Systematic Review. Journal of Medical Internet Research 2013;15(11):e247 View
  29. Schueller S, Adkins E. Mobile Health Technologies to Deliver and Support Cognitive-Behavioral Therapy. Psychiatric Annals 2019;49(8):348 View
  30. Torous J, Friedman R, Keshavan M. Smartphone Ownership and Interest in Mobile Applications to Monitor Symptoms of Mental Health Conditions. JMIR mHealth and uHealth 2014;2(1):e2 View
  31. Callan J, Wright J, Siegle G, Howland R, Kepler B. Use of Computer and Mobile Technologies in the Treatment of Depression. Archives of Psychiatric Nursing 2017;31(3):311 View
  32. Pratap A, Atkins D, Renn B, Tanana M, Mooney S, Anguera J, Areán P. The accuracy of passive phone sensors in predicting daily mood. Depression and Anxiety 2019;36(1):72 View
  33. Boonstra T, Nicholas J, Wong Q, Shaw F, Townsend S, Christensen H. Using Mobile Phone Sensor Technology for Mental Health Research: Integrated Analysis to Identify Hidden Challenges and Potential Solutions. Journal of Medical Internet Research 2018;20(7):e10131 View
  34. Castro A, García-Palacios A, García-Campayo J, Mayoral F, Botella C, García-Herrera J, Pérez-Yus M, Vives M, Baños R, Roca M, Gili M. Efficacy of low-intensity psychological intervention applied by ICTs for the treatment of depression in primary care: a controlled trial. BMC Psychiatry 2015;15(1) View
  35. Vilardaga R, B. Bricker J, G. McDonell M. The promise of mobile technologies and single case designs for the study of individuals in their natural environment. Journal of Contextual Behavioral Science 2014;3(2):148 View
  36. McClernon F, Roy Choudhury R. I Am Your Smartphone, and I Know You Are About to Smoke: The Application of Mobile Sensing and Computing Approaches to Smoking Research and Treatment. Nicotine & Tobacco Research 2013;15(10):1651 View
  37. Torous J, Staples P, Shanahan M, Lin C, Peck P, Keshavan M, Onnela J. Utilizing a Personal Smartphone Custom App to Assess the Patient Health Questionnaire-9 (PHQ-9) Depressive Symptoms in Patients With Major Depressive Disorder. JMIR Mental Health 2015;2(1):e8 View
  38. Fox E, Beevers C. Differential sensitivity to the environment: contribution of cognitive biases and genes to psychological wellbeing. Molecular Psychiatry 2016;21(12):1657 View
  39. Narziev N, Goh H, Toshnazarov K, Lee S, Chung K, Noh Y. STDD: Short-Term Depression Detection with Passive Sensing. Sensors 2020;20(5):1396 View
  40. DURDU AKGÜN B, AKTAÇ A, YORULMAZ O. Ruh Sağlığında Mobil Uygulamalar: Etkinliğe Yönelik Sistematik Bir Gözden Geçirme. Psikiyatride Güncel Yaklaşımlar 2019;11(4):519 View
  41. Colombo D, Fernández-Álvarez J, Patané A, Semonella M, Kwiatkowska M, García-Palacios A, Cipresso P, Riva G, Botella C. Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic Review. Journal of Clinical Medicine 2019;8(4):465 View
  42. Gravenhorst F, Muaremi A, Bardram J, Grünerbl A, Mayora O, Wurzer G, Frost M, Osmani V, Arnrich B, Lukowicz P, Tröster G. Mobile phones as medical devices in mental disorder treatment: an overview. Personal and Ubiquitous Computing 2015;19(2):335 View
  43. Myin‐Germeys I, Kasanova Z, Vaessen T, Vachon H, Kirtley O, Viechtbauer W, Reininghaus U. Experience sampling methodology in mental health research: new insights and technical developments. World Psychiatry 2018;17(2):123 View
  44. Torous J, Powell A. Current research and trends in the use of smartphone applications for mood disorders. Internet Interventions 2015;2(2):169 View
  45. Mohr D, Zhang M, Schueller S. Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning. Annual Review of Clinical Psychology 2017;13(1):23 View
  46. . Grant Report on SCH: Personalized Depression Treatment Supported by Mobile Sensor Analytics. Journal of Psychiatry and Brain Science 2020 View
  47. DuPaul G, Kern L, Belk G, Custer B, Daffner M, Hatfield A, Peek D. Face-to-Face Versus Online Behavioral Parent Training for Young Children at Risk for ADHD: Treatment Engagement and Outcomes. Journal of Clinical Child & Adolescent Psychology 2018;47(sup1):S369 View
  48. Epstein D, Tyburski M, Kowalczyk W, Burgess-Hull A, Phillips K, Curtis B, Preston K. Prediction of stress and drug craving ninety minutes in the future with passively collected GPS data. npj Digital Medicine 2020;3(1) View
  49. Darcy A, Adler S, Miner A, Lock J. How smartphone applications may be implemented in the treatment of eating disorders: case reports and case series data. Advances in Eating Disorders 2014;2(3):217 View
  50. Choi D, Shah C, Singh V. Which team benefits from collaboration?: Investigating collaborative information seeking using personal and social contextual signals. Proceedings of the Association for Information Science and Technology 2016;53(1):1 View
  51. Brian R, Ben-Zeev D. Mobile health (mHealth) for mental health in Asia: Objectives, strategies, and limitations. Asian Journal of Psychiatry 2014;10:96 View
  52. Farrington C, Aristidou A, Ruggeri K. mHealth and global mental health: still waiting for the mH2 wedding?. Globalization and Health 2014;10(1):17 View
  53. Bamberger K. The Application of Intensive Longitudinal Methods to Investigate Change: Stimulating the Field of Applied Family Research. Clinical Child and Family Psychology Review 2016;19(1):21 View
  54. Depp C, Ceglowski J, Wang V, Yaghouti F, Mausbach B, Thompson W, Granholm E. Augmenting psychoeducation with a mobile intervention for bipolar disorder: A randomized controlled trial. Journal of Affective Disorders 2015;174:23 View
  55. Torous J, Staples P, Onnela J. Realizing the Potential of Mobile Mental Health: New Methods for New Data in Psychiatry. Current Psychiatry Reports 2015;17(8) View
  56. Bardram J, Frost M. The Personal Health Technology Design Space. IEEE Pervasive Computing 2016;15(2):70 View
  57. Zakaria C, Balan R, Lee Y. StressMon. Proceedings of the ACM on Human-Computer Interaction 2019;3(CSCW):1 View
  58. Ashford R, Lynch K, Curtis B. Technology and Social Media Use Among Patients Enrolled in Outpatient Addiction Treatment Programs: Cross-Sectional Survey Study. Journal of Medical Internet Research 2018;20(3):e84 View
  59. Huckins J, daSilva A, Wang R, Wang W, Hedlund E, Murphy E, Lopez R, Rogers C, Holtzheimer P, Kelley W, Heatherton T, Wagner D, Haxby J, Campbell A. Fusing Mobile Phone Sensing and Brain Imaging to Assess Depression in College Students. Frontiers in Neuroscience 2019;13 View
  60. W. Adams Z, McClure E, Gray K, Danielson C, Treiber F, Ruggiero K. Mobile devices for the remote acquisition of physiological and behavioral biomarkers in psychiatric clinical research. Journal of Psychiatric Research 2017;85:1 View
  61. Rausch J, Hametz P, Zuckerbrot R, Rausch W, Soren K. Screening for Depression in Urban Latino Adolescents. Clinical Pediatrics 2012;51(10):964 View
  62. Mak W, Chio F, Chan A, Lui W, Wu E. The Efficacy of Internet-Based Mindfulness Training and Cognitive-Behavioral Training With Telephone Support in the Enhancement of Mental Health Among College Students and Young Working Adults: Randomized Controlled Trial. Journal of Medical Internet Research 2017;19(3):e84 View
  63. Pennou A, Lecomte T, Potvin S, Khazaal Y. Mobile Intervention for Individuals With Psychosis, Dual Disorders, and Their Common Comorbidities: A Literature Review. Frontiers in Psychiatry 2019;10 View
  64. Lee J, Dallery J, Laracuente A, Ibe I, Joseph S, Huo J, Salloum R. A content analysis of free smoking cessation mobile applications in the USA. Journal of Smoking Cessation 2019;14(4):195 View
  65. Cai L, Boukhechba M, Gerber M, Barnes L, Showalter S, Cohn W, Chow P. An integrated framework for using mobile sensing to understand response to mobile interventions among breast cancer patients. Smart Health 2020;15:100086 View
  66. Peng Z, Hu Q, Dang J. Multi-kernel SVM based depression recognition using social media data. International Journal of Machine Learning and Cybernetics 2019;10(1):43 View
  67. Solvoll T, Scholl J, Hartvigsen G. Physicians Interrupted by Mobile Devices in Hospitals: Understanding the Interaction Between Devices, Roles, and Duties. Journal of Medical Internet Research 2013;15(3):e56 View
  68. Faurholt-Jepsen M, Frost M, Martiny K, Tuxen N, Rosenberg N, Busk J, Winther O, Bardram J, Kessing L. Reducing the rate and duration of Re-ADMISsions among patients with unipolar disorder and bipolar disorder using smartphone-based monitoring and treatment – the RADMIS trials: study protocol for two randomized controlled trials. Trials 2017;18(1) View
  69. Shatte A, Hutchinson D, Teague S. Machine learning in mental health: a scoping review of methods and applications. Psychological Medicine 2019;49(09):1426 View
  70. Reinertsen E, Nemati S, Vest A, Vaccarino V, Lampert R, Shah A, Clifford G. Heart rate-based window segmentation improves accuracy of classifying posttraumatic stress disorder using heart rate variability measures. Physiological Measurement 2017;38(6):1061 View
  71. van de Ven P, O’Brien H, Henriques R, Klein M, Msetfi R, Nelson J, Rocha A, Ruwaard J, O’Sullivan D, Riper H. ULTEMAT: A mobile framework for smart ecological momentary assessments and interventions. Internet Interventions 2017;9:74 View
  72. Ragsdale A, Rotheram-Borus M. Re-shaping HIV Interventions with Technology. AIDS and Behavior 2015;19(S2):77 View
  73. Dogan E, Sander C, Wagner X, Hegerl U, Kohls E. Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review. Journal of Medical Internet Research 2017;19(7):e262 View
  74. Berrocal A, Concepcion W, De Dominicis S, Wac K. Complementing Human Behavior Assessment by Leveraging Personal Ubiquitous Devices and Social Links: An Evaluation of the Peer-Ceived Momentary Assessment Method. JMIR mHealth and uHealth 2020;8(8):e15947 View
  75. Gandy M, Fogliati V, Terides M, Johnston L, Nicholson Perry K, Newall C, Titov N, Dear B. Short message service prompts for skills practice in Internet‐delivered cognitive behaviour therapy for chronic pain – are they feasible and effective?. European Journal of Pain 2016;20(8):1288 View
  76. Wahle F, Kowatsch T, Fleisch E, Rufer M, Weidt S. Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild. JMIR mHealth and uHealth 2016;4(3):e111 View
  77. Bardram J, Matic A. A Decade of Ubiquitous Computing Research in Mental Health. IEEE Pervasive Computing 2020;19(1):62 View
  78. Shen Y, Luo C, Yin D, Wen H, Daniela R, Hu W. Privacy-preserving sparse representation classification in cloud-enabled mobile applications. Computer Networks 2018;133:59 View
  79. Hilliard M, Hahn A, Ridge A, Eakin M, Riekert K. User Preferences and Design Recommendations for an mHealth App to Promote Cystic Fibrosis Self-Management. JMIR mHealth and uHealth 2014;2(4):e44 View
  80. Di Matteo D, Fotinos K, Lokuge S, Yu J, Sternat T, Katzman M, Rose J. The Relationship Between Smartphone-Recorded Environmental Audio and Symptomatology of Anxiety and Depression: Exploratory Study. JMIR Formative Research 2020;4(8):e18751 View
  81. Hung G, Yang P, Chang C, Chiang J, Chen Y. Predicting Negative Emotions Based on Mobile Phone Usage Patterns: An Exploratory Study. JMIR Research Protocols 2016;5(3):e160 View
  82. McKay J, Gustafson D, Ivey M, McTavish F, Pe-Romashko K, Curtis B, Oslin D, Polsky D, Quanbeck A, Lynch K. Effects of automated smartphone mobile recovery support and telephone continuing care in the treatment of alcohol use disorder: study protocol for a randomized controlled trial. Trials 2018;19(1) View
  83. Xu X, Chikersal P, Doryab A, Villalba D, Dutcher J, Tumminia M, Althoff T, Cohen S, Creswell K, Creswell J, Mankoff J, Dey A. Leveraging Routine Behavior and Contextually-Filtered Features for Depression Detection among College Students. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019;3(3):1 View
  84. Lokman S, Leone S, Sommers-Spijkerman M, van der Poel A, Smit F, Boon B. Complaint-Directed Mini-Interventions for Depressive Complaints: A Randomized Controlled Trial of Unguided Web-Based Self-Help Interventions. Journal of Medical Internet Research 2017;19(1):e4 View
  85. Yim S, Lui L, Lee Y, Rosenblat J, Ragguett R, Park C, Subramaniapillai M, Cao B, Zhou A, Rong C, Lin K, Ho R, Coles A, Majeed A, Wong E, Phan L, Nasri F, McIntyre R. The utility of smartphone-based, ecological momentary assessment for depressive symptoms. Journal of Affective Disorders 2020;274:602 View
  86. Hirano M, Ogura K, Kitahara M, Sakamoto D, Shimoyama H. Designing behavioral self-regulation application for preventive personal mental healthcare. Health Psychology Open 2017;4(1) View
  87. Stiles-Shields C, Montague E, Lattie E, Kwasny M, Mohr D. What might get in the way: Barriers to the use of apps for depression. DIGITAL HEALTH 2017;3 View
  88. Fulford H, McSwiggan L, Kroll T, MacGillivray S. Exploring the Use of Information and Communication Technology by People With Mood Disorder: A Systematic Review and Metasynthesis. JMIR Mental Health 2016;3(3):e30 View
  89. Wicaksono A, Hendley R, Beale R. Investigating the Impact of Adding Plan Reminders on Implementation Intentions to Support Behaviour Change. Interacting with Computers 2019;31(2):177 View
  90. Depp C, Kim D, Vergel de Dios L, Wang V, Ceglowski J. A Pilot Study of Mood Ratings Captured by Mobile Phone Versus Paper-and-Pencil Mood Charts in Bipolar Disorder. Journal of Dual Diagnosis 2012;8(4):326 View
  91. Dicianno B, Parmanto B, Fairman A, Crytzer T, Yu D, Pramana G, Coughenour D, Petrazzi A. Perspectives on the Evolution of Mobile (mHealth) Technologies and Application to Rehabilitation. Physical Therapy 2015;95(3):397 View
  92. Pouliakis A. Third Age and Mobile Health. International Journal of Reliable and Quality E-Healthcare 2019;8(4):67 View
  93. Dick S, O’Connor Y, Heavin C. Approaches to Mobile Health Evaluation: A Comparative Study. Information Systems Management 2020;37(1):75 View
  94. Ly K, Janni E, Wrede R, Sedem M, Donker T, Carlbring P, Andersson G. Experiences of a guided smartphone-based behavioral activation therapy for depression: A qualitative study. Internet Interventions 2015;2(1):60 View
  95. Juarascio A, Manasse S, Goldstein S, Forman E, Butryn M. Review of Smartphone Applications for the Treatment of Eating Disorders. European Eating Disorders Review 2015;23(1):1 View
  96. Castro A, López-del-Hoyo Y, Peake C, Mayoral F, Botella C, García-Campayo J, Baños R, Nogueira-Arjona R, Roca M, Gili M. Adherence predictors in an Internet-based Intervention program for depression. Cognitive Behaviour Therapy 2018;47(3):246 View
  97. Qu C, Sas C, Daudén Roquet C, Doherty G. Functionality of Top-Rated Mobile Apps for Depression: Systematic Search and Evaluation. JMIR Mental Health 2020;7(1):e15321 View
  98. Ahtinen A, Mattila E, Välkkynen P, Kaipainen K, Vanhala T, Ermes M, Sairanen E, Myllymäki T, Lappalainen R. Mobile Mental Wellness Training for Stress Management: Feasibility and Design Implications Based on a One-Month Field Study. JMIR mhealth and uhealth 2013;1(2):e11 View
  99. Boukhechba M, Daros A, Fua K, Chow P, Teachman B, Barnes L. DemonicSalmon: Monitoring mental health and social interactions of college students using smartphones. Smart Health 2018;9-10:192 View
  100. Burford S, Park S, Dawda P. Small Data and Its Visualization for Diabetes Self-Management: Qualitative Study. JMIR Diabetes 2019;4(3):e10324 View
  101. Ramanathan N, Swendeman D, Comulada W, Estrin D, Rotheram-Borus M. Identifying preferences for mobile health applications for self-monitoring and self-management: Focus group findings from HIV-positive persons and young mothers. International Journal of Medical Informatics 2013;82(4):e38 View
  102. Enam A, Torres-Bonilla J, Eriksson H. Evidence-Based Evaluation of eHealth Interventions: Systematic Literature Review. Journal of Medical Internet Research 2018;20(11):e10971 View
  103. Oliver N, Matic A, Frias-Martinez E. Mobile Network Data for Public Health: Opportunities and Challenges. Frontiers in Public Health 2015;3 View
  104. Angdembe M, Kohrt B, Jordans M, Rimal D, Luitel N. Situational analysis to inform development of primary care and community-based mental health services for severe mental disorders in Nepal. International Journal of Mental Health Systems 2017;11(1) View
  105. Kirchner T, Shiffman S. Spatio-temporal determinants of mental health and well-being: advances in geographically-explicit ecological momentary assessment (GEMA). Social Psychiatry and Psychiatric Epidemiology 2016;51(9):1211 View
  106. Otte C, Gold S, Penninx B, Pariante C, Etkin A, Fava M, Mohr D, Schatzberg A. Major depressive disorder. Nature Reviews Disease Primers 2016;2(1) View
  107. Giota K, Kleftaras G. Mental Health Apps: Innovations, Risks and Ethical Considerations. E-Health Telecommunication Systems and Networks 2014;03(03):19 View
  108. Reinertsen E, Clifford G. A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses. Physiological Measurement 2018;39(5):05TR01 View
  109. Grunerbl A, Muaremi A, Osmani V, Bahle G, Ohler S, Troster G, Mayora O, Haring C, Lukowicz P. Smartphone-Based Recognition of States and State Changes in Bipolar Disorder Patients. IEEE Journal of Biomedical and Health Informatics 2015;19(1):140 View
  110. Simões de Almeida R, Sousa T, Marques A, Queirós C. Patients’ perspectives about the design of a mobile application for psychotic disorders. Psychology, Community & Health 2018;7(1):16 View
  111. Cheng X, Fang L, Hong X, Yang L. Exploiting Mobile Big Data: Sources, Features, and Applications. IEEE Network 2017;31(1):72 View
  112. Becker D, van Breda W, Funk B, Hoogendoorn M, Ruwaard J, Riper H. Predictive modeling in e-mental health: A common language framework. Internet Interventions 2018;12:57 View
  113. Rohani D, Faurholt-Jepsen M, Kessing L, Bardram J. Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review. JMIR mHealth and uHealth 2018;6(8):e165 View
  114. Ghandeharioun A, Azaria A, Taylor S, Picard R. “Kind and Grateful”: A Context-Sensitive Smartphone App Utilizing Inspirational Content to Promote Gratitude. Psychology of Well-Being 2016;6(1) View
  115. Bastiaansen J, Kunkels Y, Blaauw F, Boker S, Ceulemans E, Chen M, Chow S, de Jonge P, Emerencia A, Epskamp S, Fisher A, Hamaker E, Kuppens P, Lutz W, Meyer M, Moulder R, Oravecz Z, Riese H, Rubel J, Ryan O, Servaas M, Sjobeck G, Snippe E, Trull T, Tschacher W, van der Veen D, Wichers M, Wood P, Woods W, Wright A, Albers C, Bringmann L. Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology. Journal of Psychosomatic Research 2020;137:110211 View
  116. Politou E, Alepis E, Patsakis C. A survey on mobile affective computing. Computer Science Review 2017;25:79 View
  117. Bailon C, Damas M, Pomares H, Sanabria D, Perakakis P, Goicoechea C, Banos O. Smartphone-Based Platform for Affect Monitoring through Flexibly Managed Experience Sampling Methods. Sensors 2019;19(15):3430 View
  118. Cornet V, Holden R. Systematic review of smartphone-based passive sensing for health and wellbeing. Journal of Biomedical Informatics 2018;77:120 View
  119. Mendez D, Sanders S, Karimi H, Gharani P, Rathbun S, Gary-Webb T, Wallace M, Gianakas J, Burke L, Davis E. Understanding Pregnancy and Postpartum Health Using Ecological Momentary Assessment and Mobile Technology: Protocol for the Postpartum Mothers Mobile Study. JMIR Research Protocols 2019;8(6):e13569 View
  120. Hebden L, Cook A, van der Ploeg H, Allman-Farinelli M. Development of Smartphone Applications for Nutrition and Physical Activity Behavior Change. JMIR Research Protocols 2012;1(2):e9 View
  121. Crookston B, West J, Hall P, Dahle K, Heaton T, Beck R, Muralidharan C. Mental and Emotional Self-Help Technology Apps: Cross-Sectional Study of Theory, Technology, and Mental Health Behaviors. JMIR Mental Health 2017;4(4):e45 View
  122. Fiordelli M, Diviani N, Schulz P. Mapping mHealth Research: A Decade of Evolution. Journal of Medical Internet Research 2013;15(5):e95 View
  123. Karcher N, Presser N. Ethical and Legal Issues Addressing the Use of Mobile Health (mHealth) as an Adjunct to Psychotherapy. Ethics & Behavior 2018;28(1):1 View
  124. Majumder S, Deen M. Smartphone Sensors for Health Monitoring and Diagnosis. Sensors 2019;19(9):2164 View
  125. Jim H, Hoogland A, Brownstein N, Barata A, Dicker A, Knoop H, Gonzalez B, Perkins R, Rollison D, Gilbert S, Nanda R, Berglund A, Mitchell R, Johnstone P. Innovations in research and clinical care using patient‐generated health data. CA: A Cancer Journal for Clinicians 2020;70(3):182 View
  126. Bachman DeSilva M, Gifford A, Keyi X, Li Z, Feng C, Brooks M, Harrold M, Yueying H, Gill C, Wubin X, Vian T, Haberer J, Bangsberg D, Sabin L. Feasibility and Acceptability of a Real-Time Adherence Device among HIV-Positive IDU Patients in China. AIDS Research and Treatment 2013;2013:1 View
  127. Pung A, Fletcher S, Gunn J. Mobile App Use by Primary Care Patients to Manage Their Depressive Symptoms: Qualitative Study. Journal of Medical Internet Research 2018;20(9):e10035 View
  128. Versluis A, Verkuil B, Spinhoven P, van der Ploeg M, Brosschot J. Changing Mental Health and Positive Psychological Well-Being Using Ecological Momentary Interventions: A Systematic Review and Meta-analysis. Journal of Medical Internet Research 2016;18(6):e152 View
  129. Fitzpatrick K, Darcy A, Vierhile M. Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial. JMIR Mental Health 2017;4(2):e19 View
  130. NeCamp T, Sen S, Frank E, Walton M, Ionides E, Fang Y, Tewari A, Wu Z. Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns: Micro-Randomized Trial. Journal of Medical Internet Research 2020;22(3):e15033 View
  131. Rana R, Hume M, Reilly J, Jurdak R, Soar J. Opportunistic and Context-Aware Affect Sensing on Smartphones. IEEE Pervasive Computing 2016;15(2):60 View
  132. East M, Havard B, Hastings N. Mental Health Mobile Apps’ Instruction: Technology Adoption Theories Applied in a Mixed Methods Study of Counseling Faculty. Journal of Technology in Human Services 2016;34(4):301 View
  133. Asselbergs J, Ruwaard J, Ejdys M, Schrader N, Sijbrandij M, Riper H. Mobile Phone-Based Unobtrusive Ecological Momentary Assessment of Day-to-Day Mood: An Explorative Study. Journal of Medical Internet Research 2016;18(3):e72 View
  134. Charbonneau K, Lalande M, Briand C. L’assistant personnel numérique : outil de soutien à la réadaptation en santé mentale. Canadian Journal of Occupational Therapy 2015;82(4):254 View
  135. Bauer M, Glenn T, Monteith S, Bauer R, Whybrow P, Geddes J. Ethical perspectives on recommending digital technology for patients with mental illness. International Journal of Bipolar Disorders 2017;5(1) View
  136. Proudfoot J. The future is in our hands: The role of mobile phones in the prevention and management of mental disorders. Australian & New Zealand Journal of Psychiatry 2013;47(2):111 View
  137. Roggeveen S, van Os J, Bemelmans K, van Poll M, Lousberg R. Investigating Associations Between Changes in Mobile Phone Use and Emotions Using the Experience Sampling Method: Pilot Study. JMIR Formative Research 2018;2(1):e12 View
  138. Rost T, Stein J, Löbner M, Kersting A, Luck-Sikorski C, Riedel-Heller S. User Acceptance of Computerized Cognitive Behavioral Therapy for Depression: Systematic Review. Journal of Medical Internet Research 2017;19(9):e309 View
  139. Marsch L, Campbell A, Campbell C, Chen C, Ertin E, Ghitza U, Lambert-Harris C, Hassanpour S, Holtyn A, Hser Y, Jacobs P, Klausner J, Lemley S, Kotz D, Meier A, McLeman B, McNeely J, Mishra V, Mooney L, Nunes E, Stafylis C, Stanger C, Saunders E, Subramaniam G, Young S. The application of digital health to the assessment and treatment of substance use disorders: The past, current, and future role of the National Drug Abuse Treatment Clinical Trials Network. Journal of Substance Abuse Treatment 2020;112:4 View
  140. Burgess E, Ringland K, Nicholas J, Knapp A, Eschler J, Mohr D, Reddy M. "I think people are powerful". Proceedings of the ACM on Human-Computer Interaction 2019;3(CSCW):1 View
  141. Myin-Germeys I, Klippel A, Steinhart H, Reininghaus U. Ecological momentary interventions in psychiatry. Current Opinion in Psychiatry 2016;29(4):258 View
  142. Wang W. Smartphones as Social Actors? Social dispositional factors in assessing anthropomorphism. Computers in Human Behavior 2017;68:334 View
  143. Dennison L, Morrison L, Conway G, Yardley L. Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior change: Qualitative Study. Journal of Medical Internet Research 2013;15(4):e86 View
  144. Razavi R, Gharipour A, Gharipour M. Depression screening using mobile phone usage metadata: a machine learning approach. Journal of the American Medical Informatics Association 2020;27(4):522 View
  145. Haberer J, Trabin T, Klinkman M. Furthering the reliable and valid measurement of mental health screening, diagnoses, treatment and outcomes through health information technology. General Hospital Psychiatry 2013;35(4):349 View
  146. Price M, Yuen E, Goetter E, Herbert J, Forman E, Acierno R, Ruggiero K. mHealth: A Mechanism to Deliver More Accessible, More Effective Mental Health Care. Clinical Psychology & Psychotherapy 2014;21(5):427 View
  147. Kumar S, Nilsen W, Abernethy A, Atienza A, Patrick K, Pavel M, Riley W, Shar A, Spring B, Spruijt-Metz D, Hedeker D, Honavar V, Kravitz R, Craig Lefebvre R, Mohr D, Murphy S, Quinn C, Shusterman V, Swendeman D. Mobile Health Technology Evaluation. American Journal of Preventive Medicine 2013;45(2):228 View
  148. Runyan J, Steinke E. Virtues, ecological momentary assessment/intervention and smartphone technology. Frontiers in Psychology 2015;6 View
  149. Brown C, Mohr D, Gallo C, Mader C, Palinkas L, Wingood G, Prado G, Kellam S, Pantin H, Poduska J, Gibbons R, McManus J, Ogihara M, Valente T, Wulczyn F, Czaja S, Sutcliffe G, Villamar J, Jacobs C. A Computational Future for Preventing HIV in Minority Communities. JAIDS Journal of Acquired Immune Deficiency Syndromes 2013;63(Supplement 1):S72 View
  150. McInnes D, Fix G, Solomon J, Petrakis B, Sawh L, Smelson D. Preliminary needs assessment of mobile technology use for healthcare among homeless veterans. PeerJ 2015;3:e1096 View
  151. Birney A, Gunn R, Russell J, Ary D. MoodHacker Mobile Web App With Email for Adults to Self-Manage Mild-to-Moderate Depression: Randomized Controlled Trial. JMIR mHealth and uHealth 2016;4(1):e8 View
  152. Wan N, Qu W, Whittington J, Witbrodt B, Henderson M, Goulding E, Schenk A, Bonasera S, Lin G. Assessing Smart Phones for Generating Life-Space Indicators. Environment and Planning B: Planning and Design 2013;40(2):350 View
  153. Blázquez Martín D, De La Torre I, Garcia-Zapirain B, Lopez-Coronado M, Rodrigues J. Managing and Controlling Stress Using mHealth: Systematic Search in App Stores. JMIR mHealth and uHealth 2018;6(5):e111 View
  154. Grossman J, Frumkin M, Rodebaugh T, Lenze E. mHealth Assessment and Intervention of Depression and Anxiety in Older Adults. Harvard Review of Psychiatry 2020;28(3):203 View
  155. Naughton F, Hopewell S, Lathia N, Schalbroeck R, Brown C, Mascolo C, McEwen A, Sutton S. A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study. JMIR mHealth and uHealth 2016;4(3):e106 View
  156. van der Meulen H, McCashin D, O'Reilly G, Coyle D. Using Computer Games to Support Mental Health Interventions: Naturalistic Deployment Study. JMIR Mental Health 2019;6(5):e12430 View
  157. Consolvo S, Bentley F, Hekler E, Phatak S. Mobile User Research: A Practical Guide. Synthesis Lectures on Mobile and Pervasive Computing 2017;9(1):i View
  158. Rootes-Murdy K, Glazer K, Van Wert M, Mondimore F, Zandi P. Mobile technology for medication adherence in people with mood disorders: A systematic review. Journal of Affective Disorders 2018;227:613 View
  159. Silva Almodovar A, Surve S, Axon D, Cooper D, Nahata M. Self-Directed Engagement with a Mobile App (Sinasprite) and Its Effects on Confidence in Coping Skills, Depression, and Anxiety: Retrospective Longitudinal Study. JMIR mHealth and uHealth 2018;6(3):e64 View
  160. Aggarwal N. Applying mobile technologies to mental health service delivery in South Asia. Asian Journal of Psychiatry 2012;5(3):225 View
  161. Marzano L, Bardill A, Fields B, Herd K, Veale D, Grey N, Moran P. The application of mHealth to mental health: opportunities and challenges. The Lancet Psychiatry 2015;2(10):942 View
  162. Chapman J, Roberts J, Nguyen V, Breakspear M. Quantification of free-living activity patterns using accelerometry in adults with mental illness. Scientific Reports 2017;7(1) View
  163. Shen N, Levitan M, Johnson A, Bender J, Hamilton-Page M, Jadad A, Wiljer D. Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace. JMIR mHealth and uHealth 2015;3(1):e16 View
  164. Jahnel T, Schüz B. Partizipative Entwicklung von Digital-Public-Health-Anwendungen: Spannungsfeld zwischen Nutzer*innenperspektive und Evidenzbasierung. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 2020;63(2):153 View
  165. Frank E, Pong J, Asher Y, Soares C. Smart phone technologies and ecological momentary data. Current Opinion in Psychiatry 2018;31(1):3 View
  166. Pryss R, Schlee W, Hoppenstedt B, Reichert M, Spiliopoulou M, Langguth B, Breitmayer M, Probst T. Applying Machine Learning to Daily-Life Data From the TrackYourTinnitus Mobile Health Crowdsensing Platform to Predict the Mobile Operating System Used With High Accuracy: Longitudinal Observational Study. Journal of Medical Internet Research 2020;22(6):e15547 View
  167. Bourla A, Ferreri F, Ogorzelec L, Guinchard C, Mouchabac S. Évaluation des troubles thymiques par l’étude des données passives : le concept de phénotype digital à l’épreuve de la culture de métier de psychiatre. L'Encéphale 2018;44(2):168 View
  168. Soares Teles A, Rocha A, José da Silva e Silva F, Correia Lopes J, O’Sullivan D, Van de Ven P, Endler M. Enriching Mental Health Mobile Assessment and Intervention with Situation Awareness. Sensors 2017;17(1):127 View
  169. Giosan C, Cobeanu O, Mogoaşe C, Szentagotai A, Mureşan V, Boian R. Reducing depressive symptomatology with a smartphone app: study protocol for a randomized, placebo-controlled trial. Trials 2017;18(1) View
  170. Robillard J, Feng T, Sporn A, Lai J, Lo C, Ta M, Nadler R. Availability, readability, and content of privacy policies and terms of agreements of mental health apps. Internet Interventions 2019;17:100243 View
  171. Goldberg S, Buck B, Raphaely S, Fortney J. Measuring Psychiatric Symptoms Remotely: a Systematic Review of Remote Measurement-Based Care. Current Psychiatry Reports 2018;20(10) View
  172. Huguet A, Rao S, McGrath P, Wozney L, Wheaton M, Conrod J, Rozario S, Choo K. A Systematic Review of Cognitive Behavioral Therapy and Behavioral Activation Apps for Depression. PLOS ONE 2016;11(5):e0154248 View
  173. Luhmann M. Using Big Data to study subjective well-being. Current Opinion in Behavioral Sciences 2017;18:28 View
  174. Rabbi M, Pfammatter A, Zhang M, Spring B, Choudhury T. Automated Personalized Feedback for Physical Activity and Dietary Behavior Change With Mobile Phones: A Randomized Controlled Trial on Adults. JMIR mHealth and uHealth 2015;3(2):e42 View
  175. Chatterjee S, Moreno A, Lizotte S, Akther S, Ertin E, Fagundes C, Lam C, Rehg J, Wan N, Wetter D, Kumar S. SmokingOpp. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(1):1 View
  176. Naghizade E, Kulik L, Tanin E, Bailey J. Privacy- and Context-aware Release of Trajectory Data. ACM Transactions on Spatial Algorithms and Systems 2020;6(1):1 View
  177. Ben-Zeev D. Technology-based interventions for psychiatric illnesses: improving care, one patient at a time. Epidemiology and Psychiatric Sciences 2014;23(4):317 View
  178. Fulmer R, Joerin A, Gentile B, Lakerink L, Rauws M. Using Psychological Artificial Intelligence (Tess) to Relieve Symptoms of Depression and Anxiety: Randomized Controlled Trial. JMIR Mental Health 2018;5(4):e64 View
  179. McDaniel B. Passive sensing of mobile media use in children and families: a brief commentary on the promises and pitfalls. Pediatric Research 2019;86(4):425 View
  180. Spates C, Padalino R, Hale A, Germain C, Nimmo K, Kohler R. A review of web‐based technology in behavioural activation. Clinical Psychologist 2016;20(1):27 View
  181. Parks A, Williams A, Kackloudis G, Stafford J, Boucher E, Honomichl R. The Effects of a Digital Well-Being Intervention on Patients With Chronic Conditions: Observational Study. Journal of Medical Internet Research 2020;22(1):e16211 View
  182. Aryana B, Brewster L, Nocera J. Design for mobile mental health: an exploratory review. Health and Technology 2019;9(4):401 View
  183. Jacobson N, Summers B, Wilhelm S. Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors. Journal of Medical Internet Research 2020;22(5):e16875 View
  184. Rashid H, Mendu S, Daniel K, Beltzer M, Teachman B, Boukhechba M, Barnes L. Predicting Subjective Measures of Social Anxiety from Sparsely Collected Mobile Sensor Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(3):1 View
  185. Brietzke E, Hawken E, Idzikowski M, Pong J, Kennedy S, Soares C. Integrating digital phenotyping in clinical characterization of individuals with mood disorders. Neuroscience & Biobehavioral Reviews 2019;104:223 View
  186. Rabbi M, Aung M, Gay G, Reid M, Choudhury T. Feasibility and Acceptability of Mobile Phone–Based Auto-Personalized Physical Activity Recommendations for Chronic Pain Self-Management: Pilot Study on Adults. Journal of Medical Internet Research 2018;20(10):e10147 View
  187. Alharthi R, Alharthi R, Guthier B, El Saddik A. CASP: context-aware stress prediction system. Multimedia Tools and Applications 2019;78(7):9011 View
  188. Morrison L, Hargood C, Lin S, Dennison L, Joseph J, Hughes S, Michaelides D, Johnston D, Johnston M, Michie S, Little P, Smith P, Weal M, Yardley L. Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study. Journal of Medical Internet Research 2014;16(10):e201 View
  189. Dallery J, Jarvis B, Marsch L, Xie H. Mechanisms of change associated with technology-based interventions for substance use. Drug and Alcohol Dependence 2015;150:14 View
  190. Faurholt-Jepsen M, Bauer M, Kessing L. Smartphone-based objective monitoring in bipolar disorder: status and considerations. International Journal of Bipolar Disorders 2018;6(1) View
  191. Theilig M, Korbel J, Mayer G, Hoffmann C, Zarnekow R. Employing Environmental Data and Machine Learning to Improve Mobile Health Receptivity. IEEE Access 2019;7:179823 View
  192. Wang J, Wang Y, Wei C, Yao N, Yuan A, Shan Y, Yuan C. Smartphone Interventions for Long-Term Health Management of Chronic Diseases: An Integrative Review. Telemedicine and e-Health 2014;20(6):570 View
  193. Schueller S, Begale M, Penedo F, Mohr D. Purple: A Modular System for Developing and Deploying Behavioral Intervention Technologies. Journal of Medical Internet Research 2014;16(7):e181 View
  194. Ng M, Firth J, Minen M, Torous J. User Engagement in Mental Health Apps: A Review of Measurement, Reporting, and Validity. Psychiatric Services 2019;70(7):538 View
  195. Burger F, Neerincx M, Brinkman W. Technological State of the Art of Electronic Mental Health Interventions for Major Depressive Disorder: Systematic Literature Review. Journal of Medical Internet Research 2020;22(1):e12599 View
  196. Juarascio A, Goldstein S, Manasse S, Forman E, Butryn M. Perceptions of the feasibility and acceptability of a smartphone application for the treatment of binge eating disorders: Qualitative feedback from a user population and clinicians. International Journal of Medical Informatics 2015;84(10):808 View
  197. Schueller S, Muñoz R, Mohr D. Realizing the Potential of Behavioral Intervention Technologies. Current Directions in Psychological Science 2013;22(6):478 View
  198. Chan S, Torous J, Hinton L, Yellowlees P. Mobile Tele-Mental Health: Increasing Applications and a Move to Hybrid Models of Care. Healthcare 2014;2(2):220 View
  199. Terhorst Y, Rathner E, Baumeister H, Sander L. «Hilfe aus dem App-Store?»: Eine systematische Übersichtsarbeit und Evaluation von Apps zur Anwendung bei Depressionen. Verhaltenstherapie 2018;28(2):101 View
  200. Wang L, Miller L. Just-in-the-Moment Adaptive Interventions (JITAI): A Meta-Analytical Review. Health Communication 2020;35(12):1531 View
  201. Mohr D, Burns M, Schueller S, Clarke G, Klinkman M. Behavioral Intervention Technologies: Evidence review and recommendations for future research in mental health. General Hospital Psychiatry 2013;35(4):332 View
  202. khan Z, Alotaibi S. Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective. Journal of Healthcare Engineering 2020;2020:1 View
  203. Amichai-Hamburger Y, Klomek A, Friedman D, Zuckerman O, Shani-Sherman T. The future of online therapy. Computers in Human Behavior 2014;41:288 View
  204. Marley J, Farooq S. Mobile telephone apps in mental health practice: uses, opportunities and challenges. BJPsych Bulletin 2015;39(6):288 View
  205. Wentura D, Bermeitinger C, Eder A, Giesen C, Michalkiewicz M, Hartwigsen G, Röder B, Lischke A, Kübler A, Pauli P, Renner K, Ziegler M, Spengler M, Christiansen H, Richter T, Souvignier E, Heyder A, Kunina-Habenicht O, Hertel S, Sparfeldt J, Bischof N, Glück J, Haun D, Liebal K, Amici F, Bender A, Bohn M, Bräuer J, Buttelmann D, Burkart J, Cacchione T, DeTroy S, Faßbender I, Fichtel C, Fischer J, Gampe A, Gray R, Horn L, Oña L, Kärtner J, Kaminski J, Kanngießer P, Keller H, Köster M, Kopp K, Kornadt H, Rakoczy H, Schuppli C, Stengelin R, Trommsdorff G, Leeuwen E, Schaik C, Jüttemann G, Loh W, Paulus M. Kommentare zu Daum, M. M., Greve, W., Pauen, S., Schuhrke, B. und Schwarzer, G. (2020). Positionspapier der Fachgruppe Entwicklungspsychologie: Ein Versuch einer Standortbestimmung. Psychologische Rundschau 2020;71(1):24 View
  206. Seppälä J, De Vita I, Jämsä T, Miettunen J, Isohanni M, Rubinstein K, Feldman Y, Grasa E, Corripio I, Berdun J, D'Amico E, Bulgheroni M. Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review. JMIR Mental Health 2019;6(2):e9819 View
  207. Lan A, Lee A, Munroe K, McRae C, Kaleis L, Keshavjee K, Guergachi A. Review of cognitive behavioural therapy mobile apps using a reference architecture embedded in the patient-provider relationship. BioMedical Engineering OnLine 2018;17(1) View
  208. Kamel Boulos M, Peng G, VoPham T. An overview of GeoAI applications in health and healthcare. International Journal of Health Geographics 2019;18(1) View
  209. Taki S, Russell C, Lymer S, Laws R, Campbell K, Appleton J, Ong K, Denney-Wilson E. A Mixed Methods Study to Explore the Effects of Program Design Elements and Participant Characteristics on Parents' Engagement With an mHealth Program to Promote Healthy Infant Feeding: The Growing Healthy Program. Frontiers in Endocrinology 2019;10 View
  210. Thewissen V, Gunther N. E-mental health: state of the art. Tijdschrift voor Psychotherapie 2015;41(6):374 View
  211. Morgan A, Jorm A, Mackinnon A. Usage and reported helpfulness of self-help strategies by adults with sub-threshold depression. Journal of Affective Disorders 2012;136(3):393 View
  212. White G, Caine K, Connelly K, Selove R, Doub T. Designing Consumer Health Technologies for the Treatment of Patients With Depression: A Health Practitioner's Perspective. interactive Journal of Medical Research 2014;3(1):e2 View
  213. Van Ameringen M, Turna J, Khalesi Z, Pullia K, Patterson B. There is an app for that! The current state of mobile applications (apps) for DSM-5 obsessive-compulsive disorder, posttraumatic stress disorder, anxiety and mood disorders. Depression and Anxiety 2017;34(6):526 View
  214. Turvey C, Roberts L. Recent developments in the use of online resources and mobile technologies to support mental health care. International Review of Psychiatry 2015;27(6):547 View
  215. Schootman M, Nelson E, Werner K, Shacham E, Elliott M, Ratnapradipa K, Lian M, McVay A. Emerging technologies to measure neighborhood conditions in public health: implications for interventions and next steps. International Journal of Health Geographics 2016;15(1) View
  216. Kirwan M, Duncan M, Vandelanotte C, Mummery W. Using Smartphone Technology to Monitor Physical Activity in the 10,000 Steps Program: A Matched Case–Control Trial. Journal of Medical Internet Research 2012;14(2):e55 View
  217. Hekler E, Klasnja P, Traver V, Hendriks M. Realizing Effective Behavioral Management of Health: The Metamorphosis of Behavioral Science Methods. IEEE Pulse 2013;4(5):29 View
  218. Ben-Zeev D, Schueller S, Begale M, Duffecy J, Kane J, Mohr D. Strategies for mHealth Research: Lessons from 3 Mobile Intervention Studies. Administration and Policy in Mental Health and Mental Health Services Research 2015;42(2):157 View
  219. Turvey C, Fortney J. The Use of Telemedicine and Mobile Technology to Promote Population Health and Population Management for Psychiatric Disorders. Current Psychiatry Reports 2017;19(11) View
  220. Kumar S, Chong I. Correlation Analysis to Identify the Effective Data in Machine Learning: Prediction of Depressive Disorder and Emotion States. International Journal of Environmental Research and Public Health 2018;15(12):2907 View
  221. Aguilera A. Digital Technology and Mental Health Interventions: Opportunities and Challenges. Arbor 2015;191(771):a210 View
  222. Renner K, Klee S, von Oertzen T. Bringing Back the Person into Behavioural Personality Science Using Big Data. European Journal of Personality 2020;34(5):670 View
  223. Bruen A, Wall A, Haines-Delmont A, Perkins E. Exploring Suicidal Ideation Using an Innovative Mobile App-Strength Within Me: The Usability and Acceptability of Setting up a Trial Involving Mobile Technology and Mental Health Service Users. JMIR Mental Health 2020;7(9):e18407 View
  224. Chaix B, Lobre G, Mahboub S, Delamon G, Bibault J, Brouard B. Le chatbot, outil d’accompagnement thérapeutique de la dépression chez les patientes atteintes d’un cancer du sein. Psycho-Oncologie 2020;14(1-2):17 View
  225. Mukhiya S, Wake J, Inal Y, Pun K, Lamo Y. Adaptive Elements in Internet-Delivered Psychological Treatment Systems: Systematic Review. Journal of Medical Internet Research 2020;22(11):e21066 View
  226. Fosso Wamba S, Bawack R, Guthrie C, Queiroz M, Carillo K. Are we preparing for a good AI society? A bibliometric review and research agenda. Technological Forecasting and Social Change 2021;164:120482 View
  227. Wang Y, Ren X, Liu X, Zhu T. Examining the Correlation Between Depression and Social Behavior on Smartphones Through Usage Metadata: Empirical Study. JMIR mHealth and uHealth 2021;9(1):e19046 View
  228. Taeger J, Bischoff S, Hagen R, Rak K. Utilization of Smartphone Depth Mapping Cameras for App-Based Grading of Facial Movement Disorders: Development and Feasibility Study. JMIR mHealth and uHealth 2021;9(1):e19346 View
  229. Bastiaansen J, Ornée D, Meurs M, Oldehinkel A. An evaluation of the efficacy of two add-on ecological momentary intervention modules for depression in a pragmatic randomized controlled trial (ZELF-i). Psychological Medicine 2022;52(13):2731 View
  230. Patoz M, Hidalgo-Mazzei D, Blanc O, Verdolini N, Pacchiarotti I, Murru A, Zukerwar L, Vieta E, Llorca P, Samalin L. Patient and physician perspectives of a smartphone application for depression: a qualitative study. BMC Psychiatry 2021;21(1) View
  231. Mendu S, Baglione A, Baee S, Wu C, Ng B, Shaked A, Clore G, Boukhechba M, Barnes L. A Framework for Understanding the Relationship between Social Media Discourse and Mental Health. Proceedings of the ACM on Human-Computer Interaction 2020;4(CSCW2):1 View
  232. Gharani P, Karimi H, Syzdykbayev M, Burke L, Rathbun S, Davis E, Gary-Webb T, Mendez D. Geographically-explicit Ecological Momentary Assessment (GEMA) Architecture and Components: Lessons Learned from PMOMS. Informatics for Health and Social Care 2021;46(2):158 View
  233. Maharjan S, Poudyal A, van Heerden A, Byanjankar P, Thapa A, Islam C, Kohrt B, Hagaman A. Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability. BMC Medical Informatics and Decision Making 2021;21(1) View
  234. Sheikh M, Qassem M, Kyriacou P. Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring. Frontiers in Digital Health 2021;3 View
  235. Shim Y, Scotney V, Tay L. Conducting mobile-enabled ecological momentary intervention research in positive psychology: key considerations and recommended practices. The Journal of Positive Psychology 2022;17(5):708 View
  236. Loo Gee B, Batterham P, Gulliver A, Reynolds J, Griffiths K. An Ecological Momentary Intervention for people with social anxiety: A descriptive case study. Informatics for Health and Social Care 2021;46(4):370 View
  237. Planas R, Yuguero O. Technological prescription: evaluation of the effectiveness of mobile applications to improve depression and anxiety. Systematic review. Informatics for Health and Social Care 2021;46(3):273 View
  238. Chan A, Honey M. User perceptions of mobile digital apps for mental health: Acceptability and usability ‐ An integrative review. Journal of Psychiatric and Mental Health Nursing 2022;29(1):147 View
  239. Balaskas A, Schueller S, Cox A, Doherty G, Myers B. Ecological momentary interventions for mental health: A scoping review. PLOS ONE 2021;16(3):e0248152 View
  240. Hilty D, Armstrong C, Luxton D, Gentry M, Krupinski E. A Scoping Review of Sensors, Wearables, and Remote Monitoring For Behavioral Health: Uses, Outcomes, Clinical Competencies, and Research Directions. Journal of Technology in Behavioral Science 2021;6(2):278 View
  241. Opoku Asare K, Terhorst Y, Vega J, Peltonen E, Lagerspetz E, Ferreira D. Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study. JMIR mHealth and uHealth 2021;9(7):e26540 View
  242. Lekkas D, Jacobson N. Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma. Scientific Reports 2021;11(1) View
  243. Everitt N, Broadbent J, Richardson B, Smyth J, Heron K, Teague S, Fuller-Tyszkiewicz M. Exploring the features of an app-based just-in-time intervention for depression. Journal of Affective Disorders 2021;291:279 View
  244. Gooding P, Kariotis T. Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review. JMIR Mental Health 2021;8(6):e24668 View
  245. Lee S, Kim H, Park M, Jeon H. Current Advances in Wearable Devices and Their Sensors in Patients With Depression. Frontiers in Psychiatry 2021;12 View
  246. Mehta A, Niles A, Vargas J, Marafon T, Couto D, Gross J. Acceptability and Effectiveness of Artificial Intelligence Therapy for Anxiety and Depression (Youper): Longitudinal Observational Study. Journal of Medical Internet Research 2021;23(6):e26771 View
  247. Tønning M, Faurholt-Jepsen M, Frost M, Bardram J, Kessing L. Mood and Activity Measured Using Smartphones in Unipolar Depressive Disorder. Frontiers in Psychiatry 2021;12 View
  248. Taliaz D, Souery D. A New Characterization of Mental Health Disorders Using Digital Behavioral Data: Evidence from Major Depressive Disorder. Journal of Clinical Medicine 2021;10(14):3109 View
  249. Dao K, De Cocker K, Tong H, Kocaballi A, Chow C, Laranjo L. Smartphone-Delivered Ecological Momentary Interventions Based on Ecological Momentary Assessments to Promote Health Behaviors: Systematic Review and Adapted Checklist for Reporting Ecological Momentary Assessment and Intervention Studies. JMIR mHealth and uHealth 2021;9(11):e22890 View
  250. Mhasawade V, Zhao Y, Chunara R. Machine learning and algorithmic fairness in public and population health. Nature Machine Intelligence 2021;3(8):659 View
  251. van Genugten C, Schuurmans J, van Ballegooijen W, Hoogendoorn A, Smit J, Riper H. Discovering different profiles in the dynamics of depression based on real–time monitoring of mood: a first exploration. Internet Interventions 2021;26:100437 View
  252. Orr M, MacLeod L, Bagnell A, McGrath P, Wozney L, Meier S. The comfort of adolescent patients and their parents with mobile sensing and digital phenotyping. Computers in Human Behavior 2023;140:107603 View
  253. Ferrás Sexto C, García Y. Los datos georreferenciados con teléfonos móviles para las terapias psicosociales. MEDICA REVIEW. International Medical Humanities Review / Revista Internacional de Humanidades Médicas 2019;7(2):83 View
  254. Wang X, Feng Z. A Narrative Review of Empirical Literature of Behavioral Activation Treatment for Depression. Frontiers in Psychiatry 2022;13 View
  255. Langener A, Stulp G, Kas M, Bringmann L. Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review. JMIR Mental Health 2023;10:e42646 View
  256. Wang Z, Xiong H, Zhang J, Yang S, Boukhechba M, Zhang D, Barnes L, Dou D. From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques. IEEE Internet of Things Journal 2022;9(17):15413 View
  257. Bos F, von Klipstein L, Emerencia A, Veermans E, Verhage T, Snippe E, Doornbos B, Hadders-Prins G, Wichers M, Riese H. A Web-Based Application for Personalized Ecological Momentary Assessment in Psychiatric Care: User-Centered Development of the PETRA Application. JMIR Mental Health 2022;9(8):e36430 View
  258. Akin-Sari B, Inozu M, Haciomeroglu A, Trak E, Tufan D, Doron G. Cognitive training using a mobile app as a coping tool against COVID-19 distress: A crossover randomized controlled trial. Journal of Affective Disorders 2022;311:604 View
  259. Maurice V, Didillon A, Purper-Ouakil D, Kerbage H. Adapting a parent training program to the COVID-19 crisis in a mental health care setting in France. L'Encéphale 2022;48(3):354 View
  260. Yoon S, Lee S, Suh H, Chung S, Kim J. Effects of mobile mindfulness training on mental health of employees: A CONSORT-compliant pilot randomized controlled trial. Medicine 2022;101(35):e30260 View
  261. Brogly C, Bauer M, Lizotte D, Press M, MacDougall A, Speechley M, Huner E, Mitchell M, Anderson K, Pila E. An App-Based Surveillance System for Undergraduate Students’ Mental Health During the COVID-19 Pandemic: Protocol for a Prospective Cohort Study. JMIR Research Protocols 2021;10(9):e30504 View
  262. Molloy A, Anderson P. Engagement with mobile health interventions for depression: A systematic review. Internet Interventions 2021;26:100454 View
  263. Dulin P, Mertz R, Edwards A, King D. Contrasting a Mobile App With a Conversational Chatbot for Reducing Alcohol Consumption: Randomized Controlled Pilot Trial. JMIR Formative Research 2022;6(5):e33037 View
  264. Dias L, Vianna H, Barbosa J. Human behaviour data analysis and noncommunicable diseases: a systematic mapping study. Behaviour & Information Technology 2023;42(14):2485 View
  265. Ma X, Yang X, Gao J, Xu C. Health Status Prediction with Local-Global Heterogeneous Behavior Graph. ACM Transactions on Multimedia Computing, Communications, and Applications 2021;17(4):1 View
  266. Mendes J, Moura I, Van de Ven P, Viana D, Silva F, Coutinho L, Teixeira S, Rodrigues J, Teles A. Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review. Journal of Medical Internet Research 2022;24(2):e28735 View
  267. Sigrist C, Resch F, Kaess M, Koenig J. Eine mehrdimensionale Untersuchung der Emotionsregulation im Kontext Nicht-Suizidaler Selbstverletzung im Jugendalter. Praxis der Kinderpsychologie und Kinderpsychiatrie 2021;70(8):699 View
  268. Kamath J, Barriera R, Jain N, Keisari E, Wang B. Digital phenotyping in depression diagnostics: Integrating psychiatric and engineering perspectives. World Journal of Psychiatry 2022;12(3):393 View
  269. Watanabe K, Tsutsumi A. The Passive Monitoring of Depression and Anxiety Among Workers Using Digital Biomarkers Based on Their Physical Activity and Working Conditions: 2-Week Longitudinal Study. JMIR Formative Research 2022;6(11):e40339 View
  270. Elfghi M, Dunne D, Jones J, Gibson I, Flaherty G, McEvoy J, Sultan S, Jordan F, Tawfick W. Mobile health technologies to improve walking distance in people with intermittent claudication. Cochrane Database of Systematic Reviews 2021;2021(8) View
  271. Khare M, Zimmermann K, Lyons R, Locklin C, Gerber B. Feasibility of promoting physical activity using mHEALTH technology in rural women: the step-2-it study. BMC Women's Health 2021;21(1) View
  272. Safiee L, Rough D, Whitford H. Barriers to and Facilitators of Using eHealth to Support Gestational Diabetes Mellitus Self-management: Systematic Literature Review of Perceptions of Health Care Professionals and Women With Gestational Diabetes Mellitus. Journal of Medical Internet Research 2022;24(10):e39689 View
  273. De Angel V, Lewis S, White K, Oetzmann C, Leightley D, Oprea E, Lavelle G, Matcham F, Pace A, Mohr D, Dobson R, Hotopf M. Digital health tools for the passive monitoring of depression: a systematic review of methods. npj Digital Medicine 2022;5(1) View
  274. Kim S, Lee K. Screening for Depression in Mobile Devices Using Patient Health Questionnaire-9 (PHQ-9) Data: A Diagnostic Meta-Analysis via Machine Learning Methods. Neuropsychiatric Disease and Treatment 2021;Volume 17:3415 View
  275. Oyebode O, Fowles J, Steeves D, Orji R. Machine Learning Techniques in Adaptive and Personalized Systems for Health and Wellness. International Journal of Human–Computer Interaction 2023;39(9):1938 View
  276. Leertouwer I, Cramer A, Vermunt J, Schuurman N. A Review of Explicit and Implicit Assumptions When Providing Personalized Feedback Based on Self-Report EMA Data. Frontiers in Psychology 2021;12 View
  277. Rohani D, Faurholt-Jepsen M, Kessing L, Bardram J. Benefits of Using Activity Recommender Technology for Self-management of Depressive Symptoms. ACM Transactions on Computing for Healthcare 2021;2(4):1 View
  278. Mouchabac S, Maatoug R, Conejero I, Adrien V, Bonnot O, Millet B, Ferreri F, Bourla A. In Search of Digital Dopamine: How Apps Can Motivate Depressed Patients, a Review and Conceptual Analysis. Brain Sciences 2021;11(11):1454 View
  279. Zarate D, Stavropoulos V, Ball M, de Sena Collier G, Jacobson N. Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence. BMC Psychiatry 2022;22(1) View
  280. Gual-Montolio P, Jaén I, Martínez-Borba V, Castilla D, Suso-Ribera C. Using Artificial Intelligence to Enhance Ongoing Psychological Interventions for Emotional Problems in Real- or Close to Real-Time: A Systematic Review. International Journal of Environmental Research and Public Health 2022;19(13):7737 View
  281. Torous J, Bucci S, Bell I, Kessing L, Faurholt‐Jepsen M, Whelan P, Carvalho A, Keshavan M, Linardon J, Firth J. The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry 2021;20(3):318 View
  282. Liu Y, Kang K, Doe M. HADD: High-Accuracy Detection of Depressed Mood. Technologies 2022;10(6):123 View
  283. Christopoulou S. Impacts on Context Aware Systems in Evidence-Based Health Informatics: A Review. Healthcare 2022;10(4):685 View
  284. Rout A, Nitoslawski S, Ladle A, Galpern P. Using smartphone-GPS data to understand pedestrian-scale behavior in urban settings: A review of themes and approaches. Computers, Environment and Urban Systems 2021;90:101705 View
  285. Buda T, Guerreiro J, Omana Iglesias J, Castillo C, Smith O, Matic A. Foundations for fairness in digital health apps. Frontiers in Digital Health 2022;4 View
  286. Yue Z, Zhang R, Xiao J. Passive social media use and psychological well-being during the COVID-19 pandemic: The role of social comparison and emotion regulation. Computers in Human Behavior 2022;127:107050 View
  287. Tag B, Sarsenbayeva Z, Cox A, Wadley G, Goncalves J, Kostakos V. Emotion trajectories in smartphone use: Towards recognizing emotion regulation in-the-wild. International Journal of Human-Computer Studies 2022;166:102872 View
  288. Bonilla-Escribano P, Ramirez D, Sedano-Capdevila A, Campana-Montes J, Baca-Garcia E, Courtet P, Artes-Rodriguez A. Assessment of e-Social Activity in Psychiatric Patients. IEEE Journal of Biomedical and Health Informatics 2019;23(6):2247 View
  289. Rahmani A, Lai J, Jafarlou S, Azimi I, Yunusova A, Rivera A, Labbaf S, Anzanpour A, Dutt N, Jain R, Borelli J. Personal mental health navigator: Harnessing the power of data, personal models, and health cybernetics to promote psychological well-being. Frontiers in Digital Health 2022;4 View
  290. Lekkas D, Price G, McFadden J, Jacobson N. The Application of Machine Learning to Online Mindfulness Intervention Data: a Primer and Empirical Example in Compliance Assessment. Mindfulness 2021;12(10):2519 View
  291. Eghdami S, Ahmadkhaniha H, Baradaran H, Hirbod-Mobarakeh A. Ecological momentary interventions for smoking cessation: a systematic review and meta-analysis. Social Psychiatry and Psychiatric Epidemiology 2023;58(10):1431 View
  292. Shin J, Bae S. A Systematic Review of Location Data for Depression Prediction. International Journal of Environmental Research and Public Health 2023;20(11):5984 View
  293. Lim J, Lee S, Noh J, Lee W, Su P, Yoon Y. Effectiveness of Mental Health Care by Using Machine Learning on Manufacturing Worker. International Journal of Precision Engineering and Manufacturing-Smart Technology 2023;1(2):227 View
  294. Abdallah S, Khalil A. Using a hybrid methodology for literature review: a case study in depression research. Information Discovery and Delivery 2024;52(3):305 View
  295. Chan G, Alslaity A, Wilson R, Orji R. Feeling Moodie: Insights from a Usability Evaluation to Improve the Design of mHealth Apps. International Journal of Human–Computer Interaction 2024;40(19):5857 View
  296. S Annamalai A, Vijayakumar R, Vellaisamy P, Nagarajan M. Impact of Health Information Technology Tools on Patient Safety in the Indian Healthcare Industry. The Open Biomedical Engineering Journal 2023;17(1) View
  297. Wang Z, Larrazabal M, Rucker M, Toner E, Daniel K, Kumar S, Boukhechba M, Teachman B, Barnes L. Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2023;7(3):1 View
  298. Forbes A, Keleher M, Venditto M, DiBiasi F. Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review. Journal of Medical Internet Research 2023;25:e43727 View
  299. Zon M, Ganesh G, Deen M, Fang Q. Context-Aware Medical Systems within Healthcare Environments: A Systematic Scoping Review to Identify Subdomains and Significant Medical Contexts. International Journal of Environmental Research and Public Health 2023;20(14):6399 View
  300. Frank A, Li R, Peterson B, Narayanan S. Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review. JMIR Mental Health 2023;10:e45572 View
  301. Darharaj M, Roshanpajouh M, Amini M, Shrier L, Habibi Asgarabad M. The effectiveness of mobile-based ecological momentary motivational enhancement therapy in reducing craving and severity of cannabis use disorder: Study protocol for a randomized controlled trial. Internet Interventions 2023;34:100669 View
  302. Gaidai A, Kadyrov R, Kapustina T. Mobile Apps for mental health: Literature review. Психолог 2023;(5):100 View
  303. Kulikov V, Crosthwaite P, Hall S, Flannery J, Strauss G, Vierra E, Koepsell X, Lake J, Padmanabhan A. A CBT-based mobile intervention as an adjunct treatment for adolescents with symptoms of depression: a virtual randomized controlled feasibility trial. Frontiers in Digital Health 2023;5 View
  304. Giannopoulou P, Vrahatis A, Papalaskari M, Vlamos P. The RODI mHealth app Insight: Machine-Learning-Driven Identification of Digital Indicators for Neurodegenerative Disorder Detection. Healthcare 2023;11(22):2985 View
  305. Pozuelo J, Moffett B, Davis M, Stein A, Cohen H, Craske M, Maritze M, Makhubela P, Nabulumba C, Sikoti D, Kahn K, Sodi T, van Heerden A, O’Mahen H. User-Centered Design of a Gamified Mental Health App for Adolescents in Sub-Saharan Africa: Multicycle Usability Testing Study. JMIR Formative Research 2023;7:e51423 View
  306. Jeong S, Cha C, Nam S, Song J. The effects of mobile technology-based support on young women with depressive symptoms: A block randomized controlled trial. Medicine 2024;103(1):e36748 View
  307. M V, GNK G, D R, T V, Rao G. Neuro Receptor Signal Detecting and Monitoring Smart Devices for Biological Changes in Cognitive Health Conditions. Annals of Neurosciences 2024;31(3):225 View
  308. Bell I, Lim M, Rossell S, Thomas N. Ecological Momentary Assessment and Intervention in the Treatment of Psychotic Disorders: A Systematic Review. Psychiatric Services 2017;68(11):1172 View
  309. Gopalakrishnan A, Gururajan R, Zhou X, Venkataraman R, Chan K, Higgins N. A survey of autonomous monitoring systems in mental health. WIREs Data Mining and Knowledge Discovery 2024;14(3) View
  310. Gültekin M, Şahin M. The use of artificial intelligence in mental health services in Turkey: What do mental health professionals think?. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2024;18(1) View
  311. Zhou S, Levinson A, Zhang X, Portz J, Moore S, Gore M, Ford K, Li Q, Bull S. A Pilot Study and Ecological Model of Smoking Cues to Inform Mobile Health Strategies for Quitting Among Low-Income Smokers. Health Promotion Practice 2021;22(6):850 View
  312. Elfghi M, Dunne D, Jones J, Gibson I, Flaherty G, McEvoy J, Sultan S, Jordan F, Tawfick W. Mobile health technologies to improve walking distance in people with intermittent claudication. Cochrane Database of Systematic Reviews 2024;2024(2) View
  313. Killian J, Jain M, Jia Y, Amar J, Huang E, Tambe M. New Approach to Equitable Intervention Planning to Improve Engagement and Outcomes in a Digital Health Program: Simulation Study. JMIR Diabetes 2024;9:e52688 View
  314. Zafar F, Fakhare Alam L, Vivas R, Wang J, Whei S, Mehmood S, Sadeghzadegan A, Lakkimsetti M, Nazir Z. The Role of Artificial Intelligence in Identifying Depression and Anxiety: A Comprehensive Literature Review. Cureus 2024 View
  315. González Bermúdez A, Carramiñana D, Bernardos A, Bergesio L, Besada J. A fusion architecture to deliver multipurpose mobile health services. Computers in Biology and Medicine 2024;173:108344 View
  316. Brännström A, Nieves J. Towards control in agents for human behavior change: an autism case. Journal of Intelligent & Fuzzy Systems 2024:1 View
  317. Alikhanov J, Zhang P, Noh Y, Kim H. Design of Contextual Filtered Features for Better Smartphone-User Receptivity Prediction. IEEE Internet of Things Journal 2024;11(7):11707 View
  318. Kataria A, Desai R, Kapadia H, Patel R, Maru A, Shah B, Pandya D. SENTI Aid: Sentiment Analysis on Personal Relations and Aiding Mental Health. International Journal of Innovative Science and Research Technology (IJISRT) 2024:1699 View
  319. Gutierrez G, Stephenson C, Eadie J, Asadpour K, Alavi N. Examining the role of AI technology in online mental healthcare: opportunities, challenges, and implications, a mixed-methods review. Frontiers in Psychiatry 2024;15 View
  320. Walsh S, Golden E, Priebe S. Systematic review of patients' participation in and experiences of technology-based monitoring of mental health symptoms in the community. BMJ Open 2016;6(6):e008362 View
  321. Postma M, Vrancken S, Daemen M, Meulen I, Volbragt N, Delespaul P, Haan L, Pluijm M, Breedvelt J, Gaag M, Lindauer R, Berg D, Bockting C, Amelsvoort T, Schwannauer M, Doi L, Reininghaus U. Working mechanisms of the use and acceptability of ecological momentary interventions: a realist evaluation of a guided self-help ecological momentary intervention targeting self-esteem. BMC Public Health 2024;24(1) View
  322. McDevitt-Murphy M, Luciano M, Zakarian R. Use of Ecological Momentary Assessment and Intervention in Treatment With Adults. Focus 2018;16(4):370 View
  323. Pour Rezaei P, Jokela T, Vetek A, Salmimaa M. Informing the Design of Intervention Solutions for Body-Focused Repetitive Behaviors. Proceedings of the ACM on Human-Computer Interaction 2024;8(MHCI):1 View
  324. Heinz M, Lekkas D, Abreu V, Lee C, Marsch L, Jacobson N. Evaluating a mobile app’s effects on depression and anxiety in medication-treated opioid use disorder. npj Mental Health Research 2024;3(1) View
  325. Lau C, Saad A, Camara B, Rahman D, Bolea-Alamanac B. Acceptability of Digital Mental Health Interventions for Depression and Anxiety: Systematic Review. Journal of Medical Internet Research 2024;26:e52609 View
  326. Oewel B, Azizan N, Arean P, Agapie E. Technology's Role in Fostering Therapist-Client Collaboration and Engagement with Goals. Proceedings of the ACM on Human-Computer Interaction 2024;8(CSCW2):1 View
  327. Hsu T, Whelan P, Gandrup J, Armitage C, Cordingley L, McBeth J. Personalized interventions for behaviour change: A scoping review of just‐in‐time adaptive interventions. British Journal of Health Psychology 2024 View

Books/Policy Documents

  1. Bardram J, Frost M. Designing Healthcare That Works. View
  2. Pouliakis A, Archondakis S, Margari N, Karakitsos P. M-Health Innovations for Patient-Centered Care. View
  3. Pouliakis A, Margari N, Karakitsou E, Archondakis S, Karakitsos P. Emerging Developments and Practices in Oncology. View
  4. Parks A. Positive Psychology in Practice. View
  5. Laranjo L, Lau A, Coiera E. Cognitive Informatics in Health and Biomedicine. View
  6. Duarte J. The Wiley Blackwell Handbook of Positive Psychological Interventions. View
  7. Colombo D, Suso-Ribera C, Fernández-Álvarez J, Cipresso P, García-Palacios A, Riva G, Botella C. Comprehensive Clinical Psychology. View
  8. Musyimi C, Lai Y, Mutiso V, Ndetei D. Innovations in Global Mental Health. View
  9. Rajagopalan A, Ho R. Major Depressive Disorder. View
  10. Pedrelli P, Bentley K, Howe E, Shapero B. The Massachusetts General Hospital Guide to Depression. View
  11. Tamposis I, Pouliakis A, Fezoulidis I, Karakitsos P. M-Health Innovations for Patient-Centered Care. View
  12. Jacob M, Storch E. Mental Health Practice in a Digital World. View
  13. Yang P, Chang C, Chen Y, Chiang J, Hung G. Health Information Science. View
  14. Doryab A. Technology and Adolescent Mental Health. View
  15. Pouliakis A, Karakitsou E, Margari N. Mobile Health Applications for Quality Healthcare Delivery. View
  16. Saad A. Complex, Intelligent, and Software Intensive Systems. View
  17. Fang Y, Mao R. Depressive Disorders: Mechanisms, Measurement and Management. View
  18. Aranki D, Kurillo G, Bajcsy R. Handbook of Large-Scale Distributed Computing in Smart Healthcare. View
  19. Kellmeyer P. Machine Learning. View
  20. Manațe B, Fortiş F, Moore P. Securing the Internet of Things. View
  21. Becker D. Advances in Information and Communication Networks. View
  22. Apolinário-Hagen J, Fritsche L, Albers L, Salewski C. Treatment Resistance in Psychiatry. View
  23. Tuena C, Chiappini M, Repetto C, Riva G. Comprehensive Clinical Psychology. View
  24. Koumpouros Y, Georgoulas A. Mobile Health Applications for Quality Healthcare Delivery. View
  25. Campise R, Kinn J, Cooper D. Handbook of Military Psychology. View
  26. Lee H, Cho A, Jo Y, Whang M. Advances in Computer Science and Ubiquitous Computing. View
  27. Brown C, Mason W, Brown E. Defining Prevention Science. View
  28. Wang R, Chen F, Chen Z, Li T, Harari G, Tignor S, Zhou X, Ben-Zeev D, Campbell A. Mobile Health. View
  29. Ebert D, Harrer M, Apolinário-Hagen J, Baumeister H. Frontiers in Psychiatry. View
  30. Stütz T, Kowar T, Kager M, Tiefengrabner M, Stuppner M, Blechert J, Wilhelm F, Ginzinger S. User Modeling, Adaptation and Personalization. View
  31. Chan S, Torous J, Hinton L, Yellowlees P. e-Mental Health. View
  32. Kauer S, Reid S. Encyclopedia of Mobile Phone Behavior. View
  33. Piwek L, Joinson A. Behavior Change Research and Theory. View
  34. Vailati Riboni F, Pagnini F. Comprehensive Clinical Psychology. View
  35. Ferguson S, Jahnel T, Elliston K, Shiffman S. The Cambridge Handbook of Research Methods in Clinical Psychology. View
  36. Pouliakis A, Archondakis S, Margari N, Karakitsos P. Data Analytics in Medicine. View
  37. Luxton D, June J, Sano A, Bickmore T. Artificial Intelligence in Behavioral and Mental Health Care. View
  38. Tamposis I, Pouliakis A, Fezoulidis I, Karakitsos P. Medical Imaging. View
  39. Konrath S. Encyclopedia of Mobile Phone Behavior. View
  40. Iyawa G, Langan-Martin J, Sevalie S, Masikara W. Impacts of Information Technology on Patient Care and Empowerment. View
  41. . The Cambridge Handbook of Research Methods in Clinical Psychology. View
  42. Cerrato P, Halamka J. The Transformative Power of Mobile Medicine. View
  43. Hegerl U, Dogan E, Oehler C, Sander C, Stöber F. Gesundheit digital. View
  44. Zhang R, Kornfield R. The International Encyclopedia of Media Psychology. View
  45. Burns M, Mohr D. Encyclopedia of Behavioral Medicine. View
  46. Rosenfeld A, Benrimoh D, Armstrong C, Mirchi N, Langlois-Therrien T, Rollins C, Tanguay-Sela M, Mehltretter J, Fratila R, Israel S, Snook E, Perlman K, Kleinerman A, Saab B, Thoburn M, Gabbay C, Yaniv-Rosenfeld A. Applications of Big Data in Healthcare. View
  47. Pouliakis A, Margari N, Karakitsou E, Archondakis S, Karakitsos P. Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing. View
  48. Iyawa G, Langan-Martin J, Sevalie S, Masikara W. Research Anthology on Mental Health Stigma, Education, and Treatment. View
  49. Vaid S, Abdullah S, Thomaz E, Harari G. Measuring and Modeling Persons and Situations. View
  50. Mao S, Khalifa Y, Zhang Z, Shu K, Suri A, Bouzid Z, Sejdic E. Digital Health. View
  51. Sulaiman M, Håkansson A, Karlsen R. ICT for Health, Accessibility and Wellbeing. View
  52. Ahmed M, Zubair S. Explainable Artificial Intelligence for Cyber Security. View
  53. Marchionatti L, Mastella N, Bouvier V, Passos I. Digital Mental Health. View
  54. Tugade M, Tan T, Wachsmuth L, Bradley E. The Cambridge Handbook of Community Psychology. View
  55. Musyimi C, Lai Y, Mutiso V, Ndetei D. Innovations in Global Mental Health. View
  56. Pramanik H, Pal A, Kirtania M, Chakravarty T, Ghose A. Smartphone-Based Detection Devices. View
  57. Koumpouros Y, Georgoulas A. M-Health Innovations for Patient-Centered Care. View
  58. . The Cambridge Handbook of Community Psychology. View
  59. Llera S, Shin K, Erickson T, Przeworski A, Newman M. Comprehensive Clinical Psychology. View
  60. Koumpouros Y, Georgoulas A. Gaming and Technology Addiction. View
  61. Christopoulou S. Digital Identity in the New Era of Personalized Medicine. View
  62. Harrer M, Terhorst Y, Baumeister H, Ebert D. Digitale Gesundheitsinterventionen. View
  63. Collecchia G, De Gobbi R. AI in Clinical Practice. View
  64. Chan G, Alslaity A, Wilson R, Rajeshsingh P, Orji R. Intelligent Systems and Applications. View
  65. Cho C, Lee H, Kim Y. Recent Advances and Challenges in the Treatment of Major Depressive Disorder. View