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The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality
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As the COVID‐19 pandemic has largely increased the utilization of telehealth, mobile mental health technologies – such as smartphone apps, virtual reality, chatbots, and social media – have also gained attention. These digital health technologies offer the potential of accessible and scalable interventions that can augment traditional care. In this paper, we provide a comprehensive update on the overall field of digital psychiatry, covering three areas. First, we outline the relevance of recent technological advances to mental health research and care, by detailing how smartphones, social media, artificial intelligence and virtual reality present new opportunities for “digital phenotyping” and remote intervention. Second, we review the current evidence for the use of these new technological approaches across different mental health contexts, covering their emerging efficacy in self‐management of psychological well‐being and early intervention, along with more nascent research supporting their use in clinical management of long‐term psychiatric conditions – including major depression; anxiety, bipolar and psychotic disorders; and eating and substance use disorders – as well as in child and adolescent mental health care. Third, we discuss the most pressing challenges and opportunities towards real‐world implementation, using the Integrated Promoting Action on Research Implementation in Health Services (i‐PARIHS) framework to explain how the innovations themselves, the recipients of these innovations, and the context surrounding innovations all must be considered to facilitate their adoption and use in mental health care systems. We conclude that the new technological capabilities of smartphones, artificial intelligence, social media and virtual reality are already changing mental health care in unforeseen and exciting ways, each accompanied by an early but promising evidence base. We point out that further efforts towards strengthening implementation are needed, and detail the key issues at the patient, provider and policy levels which must now be addressed for digital health technologies to truly improve mental health research and treatment in the future.
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“In particular, widespread access to technology has not been accompanied by sufficient mental health advocacy, leaving the detrimental effects of technological exposure unaddressed [49].”
From SAFEvR MentalVeRse.app: Development of a Free Immersive Virtual Reality Exposure Therapy for Acrophobia and Claustrophobia (2024) · cites this paper as [49]
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“Mobile health interventions, such as smartphone applications and text messaging, are commonly used to target a wide range of health behaviors in adults and rep resent a rapidly growing area among youth 290 .”
From Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention (2023) · cites this paper as [290]
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“Virtual reality (VR) is an emerging technology with the potential to transform mental health treatment [1-3].”
From A Virtual Reality–Based Cognitive Defusion Application for Youth Depression and Anxiety: Mixed Methods Experimental Study. (2025) · cites this paper as [3]
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“Digital mental health interventions have the potential to decrease barriers to mental health treatment.185”
From Digital Ecosystems, Children, and Adolescents: Technical Report (2026) · cites this paper as [185]
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“Research into problem gaming has advanced particularly in the areas of epidemiology, neurobiology and interventions, and has also stimulated scientific interest in problematic engagement in other online activities (e.g., social networking sites, Internet pornography use, and ecommerce) 213,214 .”
From Emerging experience with selected new categories in the ICD‐11: complex PTSD, prolonged grief disorder, gaming disorder, and compulsive sexual behaviour disorder (2022) · cites this paper as [214]
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“Moreover, analysis of text messages on social media, in combination with machine and deep-learning techniques, may provide novel ways of identifying emerging mental disorders [131].”
From Towards a youth mental health paradigm: a perspective and roadmap (2023) · cites this paper as [131]
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“User‐facing apps coupled with assistance from coaches, and other telepsychiatry tools, can help address the treatment gap, but barriers related to culture, policy and funding issues remain195, 238.”
From Mental health care for older adults: recent advances and new directions in clinical practice and research (2022) · cites this paper as [238]
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“An increasing number of CAIs have emerged in recent years, as the digital medical and mobile health fields have grown [26], solving and improving a larger range of mental health issues in addition to depression and anxiety.”
From Conversational Agent Interventions for Mental Health Problems: Systematic Review and Meta-analysis of Randomized Controlled Trials (2023) · cites this paper as [26]
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“Nonadherence to ADTs is associated with increased severity of depressive symptoms, risk of relapse (ie, early return of symptoms within the expected duration of a current episode) and recurrence (ie, a new major depressive episode following a full-episode remission), and healthcare resource utilization, as well as significantly higher”
From Digital health technologies and major depressive disorder (2023) · cites this paper as [43]
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“With the widespread, everyday use of smartphones, these emerging digital tools could function as efficient, widely available mental health resources for orthopedic clinicians to offer their patients [16,20-22].”
From A Digital Mental Health Intervention in an Orthopedic Setting for Patients With Symptoms of Depression and/or Anxiety: Feasibility Prospective Cohort Study (2022) · cites this paper as [22]
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Eisner, E., Faulkner, S., Allan, S., Ball, H., Basilio, D. D., Nicholas, J., Priyam, A., Wilson, P. M., Zhang, X., & Bucci, S. (2025) · JMIR Mental Health · doi:10.2196/65246 · Cited by 67
“Digital mental health interventions (DMHIs) can help people with psychosis or bipolar disorder monitor, manage, and improve their symptoms and health [3-6].”
Self-citationLinguistic features of suicidal thoughts and behaviors: A systematic review
Homan, S., Gabi, M., Klee, N., Bachmann, S., Moser, A.-M., Duri', M., Michel, S., Bertram, A.-M., Maatz, A., Seiler, G., et al. (2022) · Clinical Psychology Review · doi:10.1016/j.cpr.2022.102161 · Cited by 73
Bos, F. M., von Klipstein, L., Emerencia, A. C., Veermans, E., Verhage, T., Snippe, E., Doornbos, B., Hadders-Prins, G., Wichers, M., & Riese, H. (2022) · JMIR Mental Health · doi:10.2196/36430 · Cited by 70
“Similarly, mental health treatment may benefit from the self-monitoring of daily symptoms, (social) contextual experiences, and treatment-related factors [13].”
Advancing digital health equity: Directions for behavioral and social science research
Jaworski, B. K., Hooper, M. W., Aklin, W. M., Jean‐Francois, B., Elwood, W. N., Belis, D., Riley, W. T., & Hunter, C. M. (2022) · Translational Behavioral Medicine · doi:10.1093/tbm/ibac088 · Cited by 62
Spiegel, B. M. R., Liran, O., Clark, A., Samaan, J. S., Khalil, C., Chernoff, R. A., Reddy, K., & Mehra, M. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01011-0 · Cited by 60
Halkiopoulos, C., & Gkintoni, E. (2025) · Electronics · doi:10.3390/electronics14061110 · Cited by 68
Sensors and Devices Guided by Artificial Intelligence for Personalized Pain Medicine
Xing, Y., Yang, K., Lu, A., Mackie, K., & Guo, F. (2024) · Cyborg and Bionic Systems · doi:10.34133/cbsystems.0160 · Cited by 68
“…programs not only become more engaging and targeted but also provide real-time monitoring of patient responses, offering essential feedback that aids healthcare professionals in optimizing personalized pain medicine strategies [153] and significantly improves the patient’s therapeutic experience.”
BackgroundFord, T. J., Buchanan, D. M., Azeez, A., Benrimoh, D. A., Kaloiani, I., Bandeira, I. D., Hunegnaw, S. A., Lan, L., Gholmieh, M., Buch, V., et al. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1146806 · Cited by 65
Rogan, J., Bucci, S., & Firth, J. (2024) · JMIR Mental Health · doi:10.2196/49577 · Cited by 69
“In addition, digital tools that allow for passive sensing can support service users’self-management of symptoms and access to digitally delivered therapies [4].”
BackgroundSelf-citationDavies, J. N., Faschinger, A., Galante, J., & Dam, N. T. V. (2024) · Scientific Reports · doi:10.1038/s41598-024-64562-y · Cited by 68
“The use of 32,33,53 , and research into 31 meditation apps has increased sharply in recent years, with recent cross-sectional data suggesting that between 58–75% of meditators in the US have used a meditation app at least once, with 21–23% using them regularly 43,45,52 .”
BackgroundSmith, A., Hachen, S., Schleifer, R., Bhugra, D., Buadze, A., & Liebrenz, M. (2023) · International Journal of Social Psychiatry · doi:10.1177/00207640231178451 · Cited by 57
“Albeit nascent in their development and with attendant limitations (Deshpande & Warren, 2021; Torous et al., 2021), chatbots could assist with various psychiatric disorders (e.g. Abd-Alrazaq et al., 2019; B. Sharma et al., 2018).”
BackgroundVolpe, U., Orsolini, L., Salvi, V., Albert, U., Carmassi, C., Carrà, G., Cirulli, F., Dell’Osso, B., Luciano, M., Menculini, G., et al. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19031539 · Cited by 57
“In addition, a positive correlation was found between the IAT, IGDS and BSMS, by underlining the potential mediatory role of the internet in incenting online addictive behaviors such as PVGD and social media addiction [70].”
BackgroundLee, H. S., Wright, C., Ferranto, J., Buttimer, J., Palmer, C. E., Welchman, A., Mazor, K. M., Fisher, K. A., Smelson, D., O’Connor, L., et al. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1505024 · Cited by 55
Hipgrave, L., Goldie, J., Dennis, S. J., & Coleman, A. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1606291 · Cited by 72
Chung, O. S., Robinson, T., Johnson, A. M., Dowling, N. L., Ng, C. H., Yücel, M., & Segrave, R. A. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.791123 · Cited by 53
“the potential consumer benefits, may also alleviate identified workforce concerns by reinforcing professional values, including altruistic motivations to help patients (21, 47, 53).”
BackgroundBell, I. H., Eisner, E., Allan, S., Cartner, S., Torous, J. B., Bucci, S., & Thomas, N. (2023) · Schizophrenia Bulletin · doi:10.1093/schbul/sbad127 · Cited by 52
“5 15 EMA has been used within psychosis research for several decades.”
MethodSelf-citationCOVID-19 and the global acceleration of digital psychiatry
Stein, D. J., Naslund, J. A., & Bantjes, J. R. (2021) · The Lancet Psychiatry · doi:10.1016/s2215-0366(21)00474-0 · Cited by 50
Evaluating Digital Health Services Quality via Social Media
Liu, Y., Wang, X., Chen, Z., Zhang, Y., Zhao, S., Devici, M., Jin, L., & Skibniewski, M. J. (2023) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2023.3298906 · Cited by 49
Different components of cognitive-behavioral therapy affect specific cognitive mechanisms
Norbury, A., Hauser, T. U., Fleming, S. M., Dolan, R. J., & Huys, Q. J. M. (2024) · Science Advances · doi:10.1126/sciadv.adk3222 · Cited by 63
“In conclusion, digital therapies can help reduce the treatment gap in mental health service provision ( 58 , 59 ), in particular for un-derserved populations ( 60 ).”
Luciano, M., Vincenzo, M. D., Brandi, C., Tretola, L., Toricco, R., Perris, F., Volpicelli, A., Torella, M., Verde, M. L., Fiorillo, A., et al. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1082762 · Cited by 54
Büscher, R., Beisemann, M., Doebler, P., Micklitz, H. M., Kerkhof, A. J. F. M., Cuijpers, P. J., Batterham, P. J., Calear, A. L., Christensen, H. M., Jaegere, E. D., et al. (2022) · Evidence-Based Mental Health · doi:10.1136/ebmental-2022-300540 · Cited by 49
Fong, T. C. T., & Yip, P. S. F. (2023) · International Journal of Social Psychiatry · doi:10.1177/00207640231174376 · Cited by 46
“From the practical perspective, the COVID-19 pandemic has resulted in shifts in the help-seeking behaviors (Junus et al., 2023; Yonemoto & Kawashima, 2023) and rapid expansion in telehealth and mhealth technologies (Torous et al., 2021).”
BackgroundStamatis, C. A., Meyerhoff, J., Meng, Y., Lin, Z. C. C., Cho, Y. M., Liu, T., Karr, C. J., Liu, T., Curtis, B. L., Ungar, L., et al. (2024) · npj Mental Health Research · doi:10.1038/s44184-023-00041-y · Cited by 56
The role of gamification in digital mental health
Fleming, T., Poppelaars, M., & Thabrew, H. (2023) · World Psychiatry · doi:10.1002/wps.21041 · Cited by 45
Cameron, G., Mulvenna, M. D., Ennis, E., O’Neill, S. M., Bond, R., Cameron, D., & Bunting, A. (2024) · JMIR Mental Health · doi:10.2196/67785 · Cited by 45
“Implementation of evidence-based digital mental health interventions into real-world care is therefore lacking, resulting in the need to prioritize research exploring workflow considerations [6].”
Mental Health and Substance Use Disorders
Mundt, A. P., Rozas-Serri, E., Beigel, L., Irarrázaval, M., Cabieses, B., V, & Baranyi, G. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-99967-0.00193-9 · Cited by 45
Systematic review and meta-analysis of adverse events in clinical trials of mental health apps
Linardon, J., Fuller-Tyszkiewicz, M., Firth, J., Goldberg, S. B., Anderson, C., McClure, Z., & Torous, J. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01388-y · Cited by 44
Self-citationFeng, T., Wang, B., Mi, M., Ren, L., Wu, L., Wang, H., Liu, X., & Wang, X. (2025) · Heliyon · doi:10.1016/j.heliyon.2025.e41869 · Cited by 43
LLMs for Financial Advisement: A Fairness and Efficacy Study in Personal Decision Making
Lakkaraju, K., Jones, S. E., Vuruma, S. K. R., Pallagani, V., Muppasani, B. C., & Srivastava, B. (2023) · 4th ACM International Conference on AI in Finance · doi:10.1145/3604237.3626867 · Cited by 42
“Lastly, [24] provides a comprehensive update on the overall field of digital psychiatry, including using chatbots.”
BackgroundRoy, A., Hoge, E. A., Abrante, P., Druker, S., Liu, T., & Brewer, J. A. (2021) · Journal of Medical Internet Research · doi:10.2196/26987 · Cited by 41
Digitalized transcranial electrical stimulation: A consensus statement
Brunoni, A. R., Ekhtiari, H., Antal, A., Auvichayapat, P., Baeken, C., Benseñor, I. M., Bikson, M., Boggio, P. S., Borroni, B., Brighina, F., et al. (2022) · Clinical Neurophysiology · doi:10.1016/j.clinph.2022.08.018 · Cited by 42
Smith, K., Hardy, A., Vinnikova, A., Blease, C., Milligan, L., Hidalgo‐Mazzei, D., Lambe, S., Marzano, L., Uhlhaas, P. J., Ostinelli, E. G., et al. (2024) · JMIR Mental Health · doi:10.2196/57155 · Cited by 44
“The concept of optimal use may be a more representative indicator but needs to be defined a priori in research studies [38].”
BackgroundSelf-citationKozelka, E. E., Acquilano, S. C., Al‐Abdulmunem, M., Guarino, S., Elwyn, G. J., Drake, R. E., & Carpenter-Song, E. A. (2023) · SSM - Mental Health · doi:10.1016/j.ssmmh.2023.100241 · Cited by 50
McClure, Z., Fuller‐Tyszkiewicz, M., Messer, M., & Linardon, J. (2023) · International Journal of Eating Disorders · doi:10.1002/eat.24078 · Cited by 41
Self-citationAssche, E. V., Ramos‐Quiroga, J. A., Pariante, C. M., Sforzini, L., Young, A. H., Flossbach, Y., Gold, S. M., Hoogendijk, W. J. G., Baune, B. T., & Maron, E. (2022) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2022.05.007 · Cited by 40
Digital health technologies and major depressive disorder
McIntyre, R. S., Greenleaf, W., Bulaj, G., Taylor, S. T., Mitsi, G., Saliu, D., Czysz, A., Silvesti, G., Garcia, M., & Jain, R. (2023) · CNS Spectrums · doi:10.1017/s1092852923002225 · Cited by 38
“70 71-73 There are also opportunities to develop online and mobile apps for the prevention of depression.”
BackgroundThe Digital Navigator: Standardizing Human Technology Support in App-Integrated Clinical Care
Chen, K., Lane, E., Burns, J., Macrynikola, N., Chang, S. M., & Torous, J. B. (2024) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2024.0023 · Cited by 35
“21,22 The digital navigator can help ensure that everyone now has access to digital literacy so that they can use their devices for health and can help focus on the right apps that are safer and more effective, all while driving engagement.”
Self-citationSelaskowski, B., Steffens, M., Schulze, M., Lingen, M., Aslan, B., Rosén, H., Kannen, K., Wiebe, A., Wallbaum, T., Boll, S., et al. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.114802 · Cited by 45
Qin, X., Liu, C., Zhu, W. D., Chen, Y., & Wang, Y. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192416824 · Cited by 45
“Although app-based programs provide accessible and scalable mental health interventions, the low user engagement of the programs is still an issue [41].”
BackgroundThe Role of Artificial Intelligence in Mental Health: A Review
Shimada, K. (2023) · Science Insights · doi:10.15354/si.23.re820 · Cited by 44
“Through the examination of extensive amounts of data, encompassing social media posts, internet behaviors, and physiological measurements, AI systems possess T the capability to discern nuanced patterns and indicators linked to diverse mental diseases (1).”
BackgroundStroud, A. M., Curtis, S., Weir, I. B., Stout, J., Barry, B. A., Bobo, W. V., Athreya, A. P., & Sharp, R. R. (2025) · JMIR Mental Health · doi:10.2196/64414 · Cited by 44
Metadata
- Authors
- Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt‐Jepsen, M., Whelan, P., Carvalho, A. F., Keshavan, M., Linardon, J., & Firth, J.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- Greater Manchester Mental Health NHS Foundation Trust (GB)
- The University of Melbourne (AU)
- Rigshospitalet (DK)
- Centre for Addiction and Mental Health (CA)
- Deakin University (AU)
- University of Manchester (GB)
- ORCID
- Venue
- World Psychiatry
- Publisher
- Wiley
- Published
- 2021-09-09
- Volume
- 20
- Issue
- 3
- Pages
- 318-335
- ISSN
- 1723-8617 (ISSN-L)
- 2051-5545
- PMC
- PMC8429349
- OpenAlex
- W3197232629
- Cited by
- 1,199
- References
- 227
- Citations by year
- 2026: 314 · 2025: 328 · 2024: 236 · 2023: 206 · 2022: 106 · 2021: 9
- FWCI
- 123.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- World Psychiatry (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Deakin Research Online (Deakin University) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Research Explorer (The University of Manchester) (submittedVersion, other-oa)
- Funders
- American Psychiatric Association Foundation
- UK Research and Innovation (P123958)
- National Institute for Health and Care Research (NIHR300794)
- National Institute of Mental Health (K23MH116130)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- digital psychiatry, mental health apps, virtual reality, chatbots, social media, digital phenotyping, artificial intelligence, telemedicine, remote intervention, i-PARIHS framework, implementation research, major depressive disorder, anxiety disorders, bipolar disorder, psychosis, eating disorders, substance use disorders, child and adolescent mental health, early intervention
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