Traditionally, implementation science has focused on mental health staff as the key agents of interest (Gray-Burrows et al., 2018). However, as digital interventions increasingly go home with people, so it makes sense to understand what makes interventions usable, feasible, and safe from the service user’s point of view.

All clinical interventions can create adverse events (Peryer et al., 2019) and these are usually monitored when interventions are trialled by using formal adverse event reporting. It is important to evaluate the current evidence for digital health technologies and understand the barriers and facilitators for implementation in mental healthcare. We also need to consider safety for participants as these technologies grow and develop which is why monitoring adverse events is one of the key considerations of this paper.

Methods

The study did not use any formal data synthesis methods and rather presents an overall literature review of the “state of the field” of digital health technologies (DHTs) in psychosis which includes some reference to adverse events reporting.

Results

The authors give an overall view that adverse events reporting is rare within this area, and as such, it is currently hard to tell if digital health technologies are safe. Specifically, when it comes to psychosis, the authors state “adverse events related to paranoia are nearly non-existent”. The authors conclude that there is a need for robust measurement in adverse event reporting.

DHTs present the unique opportunity for increased adverse event reporting and assessment of user experience due to the flexibility and adaptability of these technologies. For example, an app could have an in-built adverse event reporting procedure to allow users to report an issue throughout a trial. In a sense, DHTs may elicit more adverse events than other standard therapeutic trials, but this should be viewed as a positive rather than a negative. By providing participants with more options/avenues to report adverse events these trials are ultimately going to be safer and more beneficial for those participating.

Table 1 Summary points related to common digital health technologies in mental health (Torous et al., 2021)

Technology	Main uses	Future potential	Key issues	Priority actions
Digitally delivered psychological therapies	Self-management of symptoms of depression and anxiety	Precision interventions; preventative treatments	Lack of engagement; saturated consumer marketplace; claims outpacing clinical evidence	Establishing evidence base for use in people with diagnosed mental disorders
Smartphone data (active + passive)	Tracking mood and lifestyle in people with major depression, bipolar disorder and psychosis	Machine learning towards individualised risk prediction and delivery of targeted “just in time” interventions	Lack of validation across studies; establishing trust around data usage	Data standards for interoperability and validation; industry-academic partnerships around access
Social media	Population level monitoring of mood and anxiety	Real time monitoring of mental health state; accessible peer support	Sampling bias; access to data from social media companies; privacy	Industry-academic partnerships and privacy standards
Virtual reality	Exposure therapies	Higher engagement and potentially higher efficacy than apps	Increased accessibility	Low-cost headsets; expanded targets
Chatbots		Increased access to care	Limited range of responses	Establishing evidence base for use in people with diagnosed mental disorders

Conclusions

This paper demonstrates that the development and introduction of Digital Health Technologies (DHT), such as smartphone apps, social media, chatbots, and virtual reality, have increased access to some level of responsive care for users with mental health problems. A particular example has been during the COVID-19 pandemic when in-person appointments were suspended.

The initial data is supportive of the benefits and efficacy of these technologies. However, more attention is currently needed to build user and clinician trust in these tools, as well as improve the robustness of these technologies, particularly as these tools grow and develop.

One key suggestion to move the field forward would be for researchers to openly share data about adverse events that have occurred in research trials. This is relevant to the work of the International Collaboration for Harmonising Adverse Events Reporting in Technology for Schizophrenia (iCHARTS) which aims to understand which adverse events occur in digital trials for psychosis and improve reporting of these events and training procedures. The group (including Cara and Steph – the authors of this blog) is currently welcoming submissions of anonymised adverse event data and adverse event reporting procedures from researchers investigating digital mental health in psychosis.

The authors (Torous et al, 2021) state:

Overall, it now seems inevitable that digital technologies will change the face of mental health research and treatment. The extent to which these changes are genuinely beneficial for those with mental disorders will depend on equitable access, robust research, and ethical, evidence-based implementation of these new technologies within global mental health care.

Strengths and limitations

The authors have provided an overview of DHTs and evaluated the evidence of these tools in people who have received a diagnosis of depression, anxiety, bipolar disorder, and schizophrenia. The authors have a clear research question which is to explore the available research evidence and challenges to the implementation of digital health technologies in mental healthcare. However, due to the lack of a formal systematic review methodology, it is not clear if this is a truly comprehensive overview. Particularly as the quality of the research evidence was not evaluated, which could be the focus of a future systematic review.

Implications for practice

The authors have provided an overview of the factors, identified from the literature review, to consider regarding implementing DHTs in clinical practice:

Recipients of innovation: patient factors

It is important to look beyond smartphone ownership rates in a population when considering implementing DHTs. For example, a study from 2018 showed that, although smartphone ownership is above 80% in the United States, only 61% of the general population have access to a contract that allows for wireless access. Lack of wireless access is also more common in those who are older, less educated, and Black or Hispanic background (Roberts & Mehrotra, 2020).

Engagement is crucial when evaluating DHT efficacy. A recent study found that in the popular mental health apps (over 100,000 downloads) on the App store/Google Play store, 90% of users stopped engaging with the apps within 10 days (Baumel et al., 2019). When it comes to DHTs the research is inconsistent regarding the impact of age and educational attainment on engagement (Arnold et al., 2021) which spells out a need for further research to understand how demographics relate to engagement.

The digital divide, defined as the gap between those with or without technological literacy, should also be considered particularly if DHTs become part of routine clinical care. DHTs cannot alienate the service user it has been designed to support, so it is essential that service users are provided with help and ongoing support to be able to navigate these technologies and access care.

Service users are often excluded from assessing the quality and usability of the digital interventions they are expected to use (Azad-Khaneghah et al., 2021). Co-designing and co-producing DHTs with users and stakeholders from the beginning will help to ensure that these tools are addressing the needs and preferences of the intended beneficiaries (Hetrick et al., 2018; Morton et al., 2020).

Recipients of innovation: clinical and clinician factors

The needs of clinicians and services when introducing DHTs are also crucial and include factors such as app safety and concerns regarding a therapeutic alliance with DHTs (Lattie et al., 2020; LEDERMAN & D’ALFONSO, n.d.). Clinicians are often not trained in using DHTs in the context of clinical practice (Wisniewski et al., 2020) and may feel hesitant to recommend these to service users.

Wisniewski and colleagues (2020) have recommended the introduction of a “digital navigator” in services, whose role is to support clinicians and service users in introducing a DHT to services and help with a range of things including technological needs, troubleshooting problems with the technology, and interpreting data flows.

A recent study from 2020 noted that when Kaiser Permanente Health offered training to clinicians about integrating DHTs into clinical care, the number of service users referred to DHTs by clinicians doubled from January 2020 to March 2020 (from 20,000 to 44,000) (Mordecai et al., 2021). This suggests that DHTs can be acceptable to service users, but staff need to receive the right training to feel comfortable and knowledgeable about recommending them.

Contextual factors

Contextual factors can impact the introduction of DHTs into clinical practice. For example, the COVID-19 pandemic led to the mass adoption of telehealth in a short space of time. Swift reduction in licensing requirements and waiving of certain liability concerns helped deal with the unprecedented challenges in our healthcare system by making DHTs quickly available (Torous et al., 2021).

Trust in DHTs is another important factor for not only clinicians when recommending DHTs, but also to service users who use these tools. For example, (Gordon et al., 2020) noted that only 1% of service users at a large hospital agreed to link their app data with their medical records and that 1% were more likely to be younger, male, and speak English. This highlights those service users who may fall through the cracks, such as those who are unfamiliar with technology or do not speak English. The need for more transparent processes for privacy enforcement and legislation is crucial to advance the use of DHTs. The vast amount of misinformation on the internet also has a role here and this has been accelerated by the COVID-19 pandemic.

Education on the risks and benefits of DHTs will allow clinicians and users to have a more nuanced view of these tools and these education programmes can grow and develop alongside DHT development.

Technical integration of DHTs into existing systems would also aid integration into existing systems and inform clinical care, but trust from users may be a barrier to this.

Statement of interests

Cara Richardson and Steph Allan both work on the iCHARTS project as writing group co-leads and Cara works with Prof Sandra Bucci at the University of Manchester, but neither of them were involved in this piece of work that they are blogging about.

Links

Primary paper

Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt‐Jepsen, M., Whelan, P., Carvalho, A. F., Keshavan, M., Linardon, J., & Firth, J. (2021). The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry, 20(3), 318–335.

Other references

Arnold, C., Farhall, J., Villagonzalo, K.-A., Sharma, K., & Thomas, N. (2021). Engagement with online psychosocial interventions for psychosis: A review and synthesis of relevant factors. Internet Interventions, 25, 100411. https://www.sciencedirect.com/science/article/pii/S2214782921000518

Baumel, A., Muench, F., Edan, S., & Kane, J. M. (2019). Objective user engagement with mental health apps: systematic search and panel-based usage analysis. Journal of Medical Internet Research, 21(9), e14567. https://www.jmir.org/2019/9/e14567/

Gordon, W. J., Patel, V., Thornhill, W., Bates, D. W., & Landman, A. (2020). Characteristics of Patients Using Patient-Facing Application Programming Interface Technology at a US Health Care System. JAMA Network Open, 3(10), e2022408–e2022408. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2772247

Gray-Burrows, K. A., Willis, T. A., Foy, R., Rathfelder, M., Bland, P., Chin, A., Hodgson, S., Ibegbuna, G., Prestwich, G., & Samuel, K. (2018). Role of patient and public involvement in implementation research: a consensus study. BMJ Quality & Safety, 27(10), 858–864.

Hetrick, S. E., Robinson, J., Burge, E., Blandon, R., Mobilio, B., Rice, S. M., Simmons, M. B., Alvarez-Jimenez, M., Goodrich, S., & Davey, C. G. (2018). Youth codesign of a mobile phone app to facilitate self-monitoring and management of mood symptoms in young people with major depression, suicidal ideation, and self-harm. JMIR Mental Health, 5(1), e9041. https://pubmed.ncbi.nlm.nih.gov/29362208/

Lattie, E. G., Nicholas, J., Knapp, A. A., Skerl, J. J., Kaiser, S. M., & Mohr, D. C. (2020). Opportunities for and tensions surrounding the use of technology-enabled mental health services in community mental health care. Administration and Policy in Mental Health and Mental Health Services Research, 47(1), 138–149. https://pubmed.ncbi.nlm.nih.gov/31535235/

LEDERMAN, R., & D’ALFONSO, S. (n.d.). Insights on the Therapeutic Alliance in Digital Mental Health. https://www.researchgate.net/profile/Reeva-Lederman/publication/335600822_Insights_on_the_Therapeutic_Alliance_in_Digital_Mental_Health/links/5d6f4bd5a6fdccf93d387e03/Insights-on-the-Therapeutic-Alliance-in-Digital-Mental-Health.pdf

Mordecai, D., Histon, T., Neuwirth, E., Heisler, W. S., Kraft, A., Bang, Y., Franchino, K., Taillac, C., & Nixon, J. P. (2021). How Kaiser Permanente created a mental health and wellness digital ecosystem. NEJM Catalyst Innovations in Care Delivery, 2(1). https://catalyst.nejm.org/doi/abs/10.1056/CAT.20.0295

Morton, E., Barnes, S. J., & Michalak, E. E. (2020). Participatory digital health research: a new paradigm for mHealth tool development. General Hospital Psychiatry, 66, 67. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354771/

Peryer, G., Golder, S., Junqueira, D. R., Vohra, S., Loke, Y. K., & Cochrane Adverse Effects Methods Group. (2019). Adverse effects. Cochrane Handbook for Systematic Reviews of Interventions, 493–505. https://training.cochrane.org/handbook/current/chapter-19

Roberts, E. T., & Mehrotra, A. (2020). Assessment of disparities in digital access among Medicare beneficiaries and implications for telemedicine. JAMA Internal Medicine, 180(10), 1386–1389.

Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt‐Jepsen, M., Whelan, P., Carvalho, A. F., Keshavan, M., Linardon, J., & Firth, J. (2021). The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry, 20(3), 318–335. https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2768771

Wisniewski, H., Gorrindo, T., Rauseo-Ricupero, N., Hilty, D., & Torous, J. (2020). The role of digital navigators in promoting clinical care and technology integration into practice. Digital Biomarkers, 4(1), 119–135. https://www.karger.com/Article/Fulltext/510144#:~:text=The%20concept%20of%20a%20new,and%20face%20to%20face%20care.

Photo credits

• Photo by ThisisEngineering RAEng on Unsplash
• Photo by Ales Nesetril on Unsplash
• Photo by JESHOOTS.COM on Unsplash
• Photo by Jason Goodman on Unsplash