Evidence

Aledavood, T., Torous, J., Hoyos, A. M. T., Naslund, J. A., Onnela, J.-P., & Keshavan, M. (2019). Smartphone-Based Tracking of Sleep in Depression, Anxiety, and Psychotic Disorders, Current Psychiatry Reports, 21(7), 1–9. https://doi.org/10.1007/s11920-019-1043-y

Chen, Z., Lin, M., Chen, F., Lane, N., Cardone, G., Wang, R., et al. (2013). Unobtrusive Sleep Monitoring using Smartphones (pp. 1–8). Presented at the ICTs for improving Patients Rehabilitation Research Techniques, IEEE. http://doi.org/10.4108/icst.pervasivehealth.2013.252148

Aledavood, T., Torous, J., Hoyos, A. M. T., Naslund, J. A., Onnela, J.-P., & Keshavan, M. (2019). Smartphone-Based Tracking of Sleep in Depression, Anxiety, and Psychotic Disorders, Current Psychiatry Reports, 21(7), 1–9. https://doi.org/10.1007/s11920-019-1043-y

Chen, Z., Lin, M., Chen, F., Lane, N., Cardone, G., Wang, R., et al. (2013). Unobtrusive Sleep Monitoring using Smartphones (pp. 1–8). Presented at the ICTs for improving Patients Rehabilitation Research Techniques, IEEE. http://doi.org/10.4108/icst.pervasivehealth.2013.252148

Nelson, B. W., & Allen, N. B. (2019). Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation Study. JMIR mHealth and uHealth, 7(3), e10828–16. http://doi.org/10.2196/10828

Escobar-Viera, C. G., Shensa, A., Bowman, N. D., Sidani, J. E., Knight, J., James, A. E., & Primack, B. A. (2018). Passive and active social media use and depressive symptoms among United States adults. Cyberpsychology, Behavior, and Social Networking, 21(7), 437-443. https://doi.org/10.1089/cyber.2017.0668

Kim, S., Favotto, L., Halladay, J., Wang, L., Boyle, M. H., & Georgiades, K. (2020). Differential associations between passive and active forms of screen time and adolescent mood and anxiety disorders. Social Psychiatry and Psychiatric Epidemiology, 55(11), 1469–1478. https://doi.org/10.1007/s00127-020-01833-9

Liang, P. P., Liu, T., Cai, A., Muszynski, M., Ishii, R., Allen, N., Auerbach, R., Brent, D., Salakhutdinov, R., & Morency, L.-P. (2021). Learning language and multimodal privacy-preserving markers of mood from Mobile Data. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). https://doi.org/10.18653/v1/2021.acl-long.322

Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among U.S. young adults. Computers in Human Behavior, 69, 1–9. https://doi.org/10.1016/j.chb.2016.11.013

Thorisdottir, I. E., Sigurvinsdottir, R., Asgeirsdottir, B. B., Allegrante, J. P., & Sigfusdottir, I. D. (2019). Active and passive social media use and symptoms of anxiety and depressed mood among Icelandic adolescents. Cyberpsychology, Behavior, and Social Networking, 22(8), 535–542. https://doi.org/10.1089/cyber.2019.0079

Bei, B., Manber, R., Allen, N. B., Trinder, J., & Wiley, J. F. (2016). Too long, too short, or too variable? Sleep intraindividual variability and its associations with perceived sleep quality and mood in adolescents during naturalistically unconstrained sleep. Sleep, 40(2), zsw067. https://doi.org/10.1093/sleep/zsw067

Blake, M. J., Trinder, J. A., & Allen, N. B. (2018). Mechanisms underlying the association between insomnia, anxiety, and depression in adolescence: Implications for behavioral sleep interventions. Clinical Psychology Review, 63, 25–40. https://doi.org/10.1016/j.cpr.2018.05.006

Blake, M. J., Snoep, L., Raniti, M., Schwartz, O., Waloszek, J. M., Simmons, J. G., Murray, G., Blake, L., Landau, E. R., Dahl, R. E., Bootzin, R., McMakin, D. L., Dudgeon, P., Trinder, J., & Allen, N. B. (2017). A cognitive-behavioral and mindfulness-based group sleep intervention improves behavior problems in at-risk adolescents by improving perceived sleep quality. Behaviour Research and Therapy, 99, 147–156. https://doi.org/10.1016/j.brat.2017.10.006

Littlewood, D. L., Kyle, S. D., Carter, L. A., Peters, S., Pratt, D., & Gooding, P. (2019). Short sleep duration and poor sleep quality predict next-day suicidal ideation: an ecological momentary assessment study. Psychological medicine, 49(3), 403-411. https://doi.org/10.1017/s0033291718001009

Al-Mosaiwi, M., & Johnstone, T. (2018). In an Absolute State: Elevated Use of Absolutist Words Is a Marker Specific to Anxiety, Depression, and Suicidal Ideation. Clinical Psychological Science, 6(4), 529–542. https://doi.org/10.1177/2167702617747074

Coppersmith, G., Leary, R., Crutchley, P., & Fine, A. (2018). Natural Language Processing of Social Media as Screening for Suicide Risk. Biomedical Informatics Insights, 10, 1–11. https://doi.org/10.1177/1178222618792860

Edwards, T., & Holtzman, N. S. (2017). A meta-analysis of correlations between depression and first person singular pronoun use. Journal of Research in Personality, 68, 63–68. https://doi.org/10.1016/j.jrp.2017.02.005

Eichstaedt, J. C., Smith, R. J., Merchant, R. M., Ungar, L. H., Crutchley, P., Preoţiuc-Pietro, D., et al. (2018). Facebook language predicts depression in medical records. Proceedings of the National Academy of Sciences, 115(44), 11203–11208. http://doi.org/10.1073/pnas.1802331115

Merchant, R. M., Asch, D. A., Crutchley, P., Ungar, L. H., Guntuku, S. C., Eichstaedt, J. C., et al. (2019). Evaluating the predictability of medical conditions from social media posts. PLoS ONE, 14(6), e0215476–12. https://doi.org/10.1371/journal.pone.0215476

Liu, T., Meyerhoff, J., Eichstaedt, J. C., Karr, C. J., Kaiser, S. M., Kording, K. P., Mohr, D. C., & Ungar, L. H. (2022). The relationship between text message sentiment and self-reported depression. Journal of Affective Disorders, 302, 7–14. https://doi.org/10.1016/j.jad.2021.12.048

Vine, V., Boyd, R. L., & Pennebaker, J. W. (2020). Natural emotion vocabularies as windows on distress and well-being. Nature Communications, 11(1), 4525. https://doi.org/10.1038/s41467-020-18349-0

Schuch, F. B., Vancampfort, D., Firth, J., Rosenbaum, S., Ward, P. B., Silva, E. S., Hallgren, M., Ponce De Leon, A., Dunn, A. L., Deslandes, A. C., Fleck, M. P., Carvalho, A. F., & Stubbs, B. (2018). (2018). Physical activity and incident depression: a meta-analysis of prospective cohort studies. American Journal of Psychiatry, 175(7), 631-648. https://doi.org/10.1176/appi.ajp.2018.17111194

Stavrakakis, N., Booij, S. H., Roest, A. M., de Jonge, P., Oldehinkel, A. J., & Bos, E. H. (2015). Temporal dynamics of physical activity and affect in depressed and nondepressed individuals. Health Psychology, 34(Suppl), 1268–1277. https://doi.org/10.1037/hea0000303

Harvey, S., Hotopf, M., Øverland, S., & Mykletun, A. (2010). Physical activity and common mental disorders. British Journal of Psychiatry, 197(5), 357-364. https://doi.org/10.1192/bjp.bp.109.075176

Chow PI, Fua K, Huang Y, Bonelli W, Xiong H, Barnes LE, et al. (2017). Using mobile sensing to test clinical models of depression, social anxiety, state affect, and social isolation among college students. J Med Internet Res. 19(3):e62. https://doi.org/10.2196/jmir.6820

Engemann, K., Pedersen, C. B., Arge, L., Tsirogiannis, C., Mortensen, P. B., & Svenning, J.-C. (2019). Residential green space in childhood is associated with lower risk of psychiatric disorders from adolescence into adulthood. Proceedings of the National Academy of Sciences, 116(11), 5188–5193. https://doi.org/10.1073/pnas.1807504116

Rohani, D. A., Faurholt-Jepsen, M., Kessing, L. V., & Bardram, J. E. (2018). Correlations between objective behavioral features collected from mobile and wearable devices and depressive mood symptoms in patients with affective disorders: systematic review. JMIR mHealth and uHealth, 6(8), e165. https://doi.org/10.2196/mhealth.9691

Saeb, S., Lattie, E. G., Kording, K. P., & Mohr, D. C. (2017). Mobile phone detection of semantic location and its relationship to depression and anxiety. JMIR mHealth and uHealth, 5(8), e112. https://doi.org/10.2196/mhealth.7297

Park, M., Thom, J., Mennicken, S., Cramer, H., & Macy, M. (2019). Global music streaming data reveal diurnal and seasonal patterns of affective preference. Nature Human Behaviour, 3(3), 230–236. https://doi.org/10.1038/s41562-018-0508-z

Schriewer K, Bulaj G. Music streaming services as adjunct therapies for depression, anxiety, and bipolar symptoms: convergence of digital technologies, mobile apps, emotions, and global mental health. Frontiers in Public Health. 2016;4:217. https://doi.org/10.3389/fpubh.2016.00217

Lambert, M. J., Whipple, J. L., Smart, D. W., Vermeersch, D. A., Nielsen, S. L., & Hawkins, E. J. (2001). The effects of providing therapists with feedback on patient progress during psychotherapy: Are Outcomes Enhanced? Psychotherapy Research, 11(1), 49–68. https://doi.org/10.1093/ptr/11.1.49

Lambert, M. J., Whipple, J. L., & Kleinstäuber, M. (2018). Collecting and delivering progress feedback: A meta-analysis of routine outcome monitoring. Psychotherapy, 55(4), 520-537. https://doi.org/10.1037/pst0000167

Pérez-Jover, V., Sala-González, M., Guilabert, M., & Mira, J. J. (2019). Mobile Apps for Increasing Treatment Adherence: Systematic Review. Journal of Medical Internet Research, 21(6), e12505–14. http://doi.org/10.2196/12505

Tang, W., & Kreindler, D. (2017). Supporting Homework Compliance in Cognitive Behavioural Therapy: Essential Features of Mobile Apps. JMIR Mental Health, 4(2), e20–10. http://doi.org/10.2196/mental.5283

Klasnja, P., Smith, S., Seewald, N. J., Lee, A., Hall, K., Luers, B., et al. (2018). Efficacy of Contextually Tailored Suggestions for Physical Activity: A Micro-randomized Optimization Trial of HeartSteps. Annals of Behavioral Medicine, 53(6), 573–582. http://doi.org/10.1093/abm/kay067.

Rathbone, A. L., & Prescott, J. (2017). The Use of Mobile Apps and SMS Messaging as Physical and Mental Health Interventions: Systematic Review. Journal of Medical Internet Research, 19(8), e295–13. http://doi.org/10.2196/jmir.7740.

Kazantzis, N., Whittington, C., Zelencich, L., Kyrios, M., Norton, P. J., & Hofmann, S. G. (2016). Quantity and quality of homework compliance: a meta-analysis of relations with outcome in cognitive behavior therapy. Behavior Therapy, 47(5), 755-772. http://doi.org/10.1016/j.beth.2016.05.002