Published on 21.09.16 in Vol 4, No 3 (2016): Jul-Sept
Works citing "Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild"
According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.5960):
(note that this is only a small subset of citations)
- Kerst A, Zielasek J, Gaebel W. Smartphone applications for depression: a systematic literature review and a survey of health care professionals’ attitudes towards their use in clinical practice. European Archives of Psychiatry and Clinical Neuroscience 2019;CrossRef
- Faurholt-Jepsen M, Busk J, Þórarinsdóttir H, Frost M, Bardram JE, Vinberg M, Kessing LV. Objective smartphone data as a potential diagnostic marker of bipolar disorder. Australian & New Zealand Journal of Psychiatry 2019;53(2):119CrossRef
- Miralles I, Granell C. Considerations for Designing Context-Aware Mobile Apps for Mental Health Interventions. International Journal of Environmental Research and Public Health 2019;16(7):1197CrossRef
- 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):e9819CrossRef
- Shatte ABR, Hutchinson DM, Teague SJ. Machine learning in mental health: a scoping review of methods and applications. Psychological Medicine 2019;:1CrossRef
- Pratap A, Atkins DC, Renn BN, Tanana MJ, Mooney SD, Anguera JA, Areán PA. The accuracy of passive phone sensors in predicting daily mood. Depression and Anxiety 2019;36(1):72CrossRef
- Majumder S, Deen MJ. Smartphone Sensors for Health Monitoring and Diagnosis. Sensors 2019;19(9):2164CrossRef
- Pham Q, Graham G, Carrion C, Morita PP, Seto E, Stinson JN, Cafazzo JA. A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review. JMIR mHealth and uHealth 2019;7(1):e11941CrossRef
- Sarda A, Munuswamy S, Sarda S, Subramanian V. Using Passive Smartphone Sensing for Improved Risk Stratification of Patients With Depression and Diabetes: Cross-Sectional Observational Study. JMIR mHealth and uHealth 2019;7(1):e11041CrossRef
- Boukhechba M, Chow P, Fua K, Teachman BA, Barnes LE. Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study. JMIR Mental Health 2018;5(3):e10101CrossRef
- Lind MN, Byrne ML, Wicks G, Smidt AM, Allen NB. The Effortless Assessment of Risk States (EARS) Tool: An Interpersonal Approach to Mobile Sensing. JMIR Mental Health 2018;5(3):e10334CrossRef
- 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):168CrossRef
- Dias LPS, Barbosa JLV, Vianna HD. Gamification and serious games in depression care: A systematic mapping study. Telematics and Informatics 2018;35(1):213CrossRef
- Chung K, Jeon M, Park J, Lee S, Kim CO, Park JY, Guloksuz S. Development and evaluation of a mobile-optimized daily self-rating depression screening app: A preliminary study. PLOS ONE 2018;13(6):e0199118CrossRef
- Wang R, Wang W, daSilva A, Huckins JF, Kelley WM, Heatherton TF, Campbell AT. Tracking Depression Dynamics in College Students Using Mobile Phone and Wearable Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018;2(1):1CrossRef
- Guo Y, Hong YA, Qiao J, Xu Z, Zhang H, Zeng C, Cai W, Li L, Liu C, Li Y, Zhu M, Harris NA, Yang C. Run4Love, a mHealth (WeChat-based) intervention to improve mental health of people living with HIV: a randomized controlled trial protocol. BMC Public Health 2018;18(1)CrossRef
- Stieger M, Nißen M, Rüegger D, Kowatsch T, Flückiger C, Allemand M. PEACH, a smartphone- and conversational agent-based coaching intervention for intentional personality change: study protocol of a randomized, wait-list controlled trial. BMC Psychology 2018;6(1)CrossRef
- Renn BN, Pratap A, Atkins DC, Mooney SD, Areán PA. Smartphone-based passive assessment of mobility in depression: Challenges and opportunities. Mental Health and Physical Activity 2018;14:136CrossRef
- Rohani DA, Tuxen N, Quemada Lopategui A, Kessing LV, Bardram JE. Data-Driven Learning in High-Resolution Activity Sampling From Patients With Bipolar Depression: Mixed-Methods Study. JMIR Mental Health 2018;5(2):e10122CrossRef
- Goodspeed R, Yan X, Hardy J, Vydiswaran VV, Berrocal VJ, Clarke P, Romero DM, Gomez-Lopez IN, Veinot T. Comparing the Data Quality of Global Positioning System Devices and Mobile Phones for Assessing Relationships Between Place, Mobility, and Health: Field Study. JMIR mHealth and uHealth 2018;6(8):e168CrossRef
- Hardy J, Veinot TC, Yan X, Berrocal VJ, Clarke P, Goodspeed R, Gomez-Lopez IN, Romero D, Vydiswaran VV. User acceptance of location-tracking technologies in health research: Implications for study design and data quality. Journal of Biomedical Informatics 2018;79:7CrossRef
- Cornet VP, Holden RJ. Systematic review of smartphone-based passive sensing for health and wellbeing. Journal of Biomedical Informatics 2018;77:120CrossRef
- Aledavood T, Triana Hoyos AM, Alakörkkö T, Kaski K, Saramäki J, Isometsä E, Darst RK. Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype. JMIR Research Protocols 2017;6(6):e110CrossRef
- Chan S, Godwin H, Gonzalez A, Yellowlees PM, Hilty DM. Review of Use and Integration of Mobile Apps Into Psychiatric Treatments. Current Psychiatry Reports 2017;19(12)CrossRef
- Tsanas A, Saunders K, Bilderbeck A, Palmius N, Goodwin G, De Vos M. Clinical Insight Into Latent Variables of Psychiatric Questionnaires for Mood Symptom Self-Assessment. JMIR Mental Health 2017;4(2):e15CrossRef
- Saeb S, Lattie EG, Kording KP, Mohr DC. Mobile Phone Detection of Semantic Location and Its Relationship to Depression and Anxiety. JMIR mHealth and uHealth 2017;5(8):e112CrossRef
- 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):e262CrossRef
- 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):526CrossRef
- Wahle F, Bollhalder L, Kowatsch T, Fleisch E. Toward the Design of Evidence-Based Mental Health Information Systems for People With Depression: A Systematic Literature Review and Meta-Analysis. Journal of Medical Internet Research 2017;19(5):e191CrossRef
- Price J. What Can Big Data Offer the Pharmacovigilance of Orphan Drugs?. Clinical Therapeutics 2016;38(12):2533CrossRef
- Jang JS, Cho SH. Mobile Health (m-health) on Mental Health. Korean Journal of Stress Research 2016;24(4):231CrossRef
According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.5960)
:- Sengupta S, Adragna M. Psychiatric Nonadherence. 2019. Chapter 14:201CrossRef
- Hegerl U, Dogan E, Oehler C, Sander C, Stöber F. Gesundheit digital. 2019. Chapter 4:47CrossRef
- Senders JT, Maher N, Hulsbergen AFC, Lamba N, Bredenoord AL, Broekman MLD. Ethics of Innovation in Neurosurgery. 2019. Chapter 14:129CrossRef
- Castro LA, Rodríguez MD, Martínez F, Rodríguez L, Andrade G, Cornejo R. Intelligent Data Sensing and Processing for Health and Well-Being Applications. 2018. :3CrossRef