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Paranoia, or fear of deliberate harm from others, is among the most common symptoms of schizophrenia-spectrum psychoses, and it also occurs in emotional disorders and other severe mental illnesses, placing 

 on the lives of patients and their families.

 Innovative therapeutic interventions are desperately needed to overcome paranoia and improve outcomes.

Existing therapies, whether pharmacological or psychotherapeutic, have widely recognized limitations in engagement, adherence, and effectiveness. Antipsychotic medication is the mainstay of treatment for most patients. However, distressing symptoms persist in 

 of those who take them, functional outcomes are frequently poor, and many discontinue treatment periodically or permanently, concerned about adverse effects, such as weight gain and metabolic syndrome.

 Psychological therapies, such as cognitive behavioral therapy for psychosis (CBTp), have been shown to improve psychotic symptoms, including paranoia, when added to treatment as usual in large clinical trials.

 But effects need to be improved, and implementation in routine care is poor. Individuals are often not willing or able to access and make use of therapy, particularly those from minoritized groups. There is a scarcity of trained therapists, with estimates suggesting only 0.3% of mental health consumers in the United States have access to CBTp.

A transformation in psychosis care is needed; digital technology has the potential to deliver it by improving the patient experience, therapy effectiveness, and 

 Digital interfaces can be designed to support personalization and accessibility, and they can assist engagement and adherence. Web and mobile technologies are also more readily scaled up than traditional interventions and can be designed to reduce training demands.

A New Frontier: Digital Therapeutics for Paranoia

To the best of our knowledge, metacognitive training (MCT), developed by Steffen Moritz, PhD, MSc, and colleagues, was the first psychological intervention for delusional beliefs that incorporated technology. It used desktop programming and presentation software to provide illustrative games and tasks. Group versions of this training approach were shown to have small to moderate effects on delusions, although it is important to note that patients with severe delusions were excluded and the basic digital materials were not personalized, limiting its ability to address challenges to therapy accessibility and adherence. More recently, individualized delivery of metacognitive therapy (MCT+) has been developed and evidence suggests it may have better effects on delusions, though there are only a few relatively

Building on this pioneering work, recent digital therapeutics for psychosis have sought to harness innovative technology such as virtual reality, social networking, mobile apps, and web-based therapies. Whilst preliminary findings are encouraging, few of these have been tested in large clinical trials, and those 

 In 1 of the largest trials to date, Depp et al (2019)

 investigated the effects of augmenting a single session of CBTp with an app, CBT2Go, compared to a single session of self-monitoring supported by an app or treatment as usual (TAU), in individuals with severe mental illness (N = 255). They found a small effect on general symptomatology favoring the CBT2Go and self-monitoring conditions over TAU. However, the impact on paranoia was not specifically examined, and the authors also note that baseline levels of psychosis symptoms were low. The FOCUS mobile app adopts a similar therapeutic approach, although it was investigated as a standalone app to support self-management in its most rigorous evaluation. Ben-Zeev et al (2019)

 compared FOCUS to a recovery group intervention in 163 patients with severe mental illness. They found no between-group differences on clinical outcomes, nor any within-group changes in psychosis symptoms.

These trials suggest that app-based technologies may safely and acceptably augment therapy for paranoia although, but they have yet to demonstrate meaningful clinical outcomes in robust designs. Crucially, there is little evidence that digital therapeutics have been designed to address healthcare inequalities. Indeed, emerging findings indicate digital therapies may actually exacerbate exclusion, with those from privileged demographic groups more likely to access and benefit from them.

In addressing the challenge of transforming psychosis care, we have developed SlowMo, an innovative digitally supported therapy for paranoia. SlowMo is based on the principles of CBTp and leverages technology to address health care inequalities, through enhancing therapy appeal and user friendliness for a 

 SlowMo therapy targets an evidence-based mechanism, or active ingredient, that we and others have shown can fuel paranoia.

 Drawing on the term popularized by Daniel Kahneman, PhD,

, comprising of a jumping to conclusions bias (forming rapid judgements using limited information) and belief inflexibility bias (reduced capacity for reflecting on one’s own beliefs, changing them in the light of new evidence, and considering alternatives). SlowMo is designed to help patients to slow down for a moment, encouraging awareness of a tendency to jump to conclusions and find new ways of feeling safer.

We followed human-centered design principles in the hopes of improving the user experience of therapy and radically enhancing engagement and adherence.

 Our multidisciplinary collaboration of individuals with lived experience, industrial designers, software developers, clinicians, and researchers developed SlowMo over 3 years through 7 cycles of prototyping. To address health care inequalities, we codesigned with stakeholders from diverse demographic backgrounds, who could identify therapy barriers and facilitators, and optimize the inclusivity of the design. SlowMo therapy consists of a web app delivered on a touchscreen laptop to support the delivery of face-to-face individual cognitive-behavioral therapy sessions, which is synchronized with a mobile app for use in daily life (

A Journey of Visualizing Thoughts and Thinking Habits

SlowMo uses new, responsive technologies to support the visualization of thoughts—as bubbles—and their associated thinking habits. This visual concept aims to enhance cognitive therapy by providing an appealing and tangible means of communicating subjective experience. The design minimizes the information processing demands, thereby lowering a significant barrier to engagement with traditional talking therapies. Patients interact with their personalized SlowMo thought bubbles using a touchscreen, altering speed, size, and transparency to reflect related thinking habits, distress, and conviction.

The SlowMo webapp used during sessions presents therapy as a journey, with interactive features including information, animated stories, and games. As well as tailoring worry and positive thought bubbles, patients record key learning points and future plans, with all content synchronized to the mobile phone app for access outside of sessions. The mobile app allows patients to notice their fears and thinking habits as they occur in daily life and helps them to find other ways of managing distressing experiences. It consists of a redesigned CBT thought record for managing paranoia and attempts to overcome the limitations of paper versions, which can be an inaccessible means of support during peak moments of distress. SlowMo uses a native mobile app with opt-in data transfer, addressing patients’ privacy concerns, which was a salient theme during the design research. The mobile app relies on user-initiated interaction and optional push notifications, to accommodate those who wish to have control over their data and find passive monitoring intrusive.

Delivering Evidence-Based Benefits for Recovery in Psychosis

SlowMo therapy has been iteratively developed over the past 10 years, with a number of studies demonstrating the efficacy of previous versions of the 

a large-scale randomized controlled trial

 with N = 362 participants recruited from United Kingdom (UK) clinical psychosis services (

, compared to the minimum 16 sessions recommended by the UK’s National Institute of Health and Care Excellence guidelines for schizophrenia treatment.

Remarkably, despite being half the minimum recommended length, SlowMo had a moderate effect on the measures of delusion severity commonly used in trials (Scales for Assessment of Positive Symptoms, SAPS

 and Psychotic Symptom Rating Scales, PSYRATS

)—for which meta-analyses have found only small effects.

 These positive effects sustained or grew over 6 months, with benefits cascading into other areas, including self-concept, wellbeing, and quality of life. Less consistent improvements were found for referential delusions, meaning that the Green Paranoid Thoughts Scale (GPTS)

 total, which is comprised of ideas of reference and persecution subscales, was not significant at 6 months. However, a psychometrically improved version of this measure, published whilst the trial was being conducted, did reach conventional levels of 

 Importantly, the SlowMo software design appeared to work as intended and was inclusive for a wide range of individuals. Whilst Black people and older patients were found to be less confident and less frequent users of mobile phones prior to doing SlowMo, these differences did not translate to their experience of the therapy, with paranoia outcomes, adherence, and patient experience comparable across groups.

 SlowMo is one of the first digital therapeutics for paranoia to overcome the digital divide associated with age and ethnicity.

The trial also had limitations. First, despite clear improvements in more severe persecutory delusions, consistent improvements were not found in milder referential delusions. One explanation is that SlowMo helped patients manage ideas of reference and their experiential components (eg, being watched by others), which prevented their elaboration into persecutory delusions (eg, being hunted by the mafia) but had less of an effect on directly modifying these underlying ideas of reference. This suggests that digital therapeutics for paranoia need to consider the broader phenomenological context fueling worries.

Accordingly, future versions of SlowMo will incorporate content on how to notice, understand, and manage the sensory-perceptual experiences (including altered salience and anomalous experiences) that are common obstacles to therapeutic change. The trial also did not control for effects of time with a therapist. TAU was chosen as the comparator condition because there is a low penetration of evidence-based psychological treatment in mental health care, thus the key question is whether SlowMo therapy confers benefits over and above standard care. Further, we had previously established the superiority of an earlier brief version of the intervention against an active control intervention, suggesting SlowMo’s positive effects are 

To illustrate SlowMo, Alex (name changed to protect their identity) has kindly agreed to us sharing their experience of therapy. Alex (a Black British Caribbean man in his late 20s) came to therapy reporting a strongly held distressing belief that he was being followed by a past acquaintance who intended to harm him and his family. In early sessions, he used the webapp to visualize these fears as personalized worry bubbles, and to build a picture of his fast thinking, including triggers and the impact on his life (

Alex could view and modify his personalized worry bubbles on the mobile app, which helped him develop an awareness of times when he thought fast. The SlowMo sessions then supported Alex to find ways to slow down for a moment and feel safer.

Alex connected with interactive stories of others discussing their own worries and tendency to jump to conclusions in everyday life. Reflecting on how these stories related to his own experiences, Alex audio-recorded messages to remind him how to slow down his worries. Using SlowMo tips, he created colorful, safer thought bubbles as he progressed through the therapy. Crucially, the synchronization of the web app with the mobile app meant that he could access this personalized helpful content (SlowMo strategies, messages and safer thoughts) when he needed them most. This helped him to consider alternative explanations when fast thoughts were triggered in daily life, for example recognizing that screams and laughter on the street could just be “people having fun” and not specifically related to him (see 

). Alex described how the principle of slowing down his thinking became “almost automatic” through early and regular use of the mobile app. By the end of therapy, Alex reported reduced fast thinking, distress, and conviction related to the fear of harm from others. He described how SlowMo therapy had helped him to “slow down…think different, act different, and feel different.”

As discussed in this article and exemplified by the SlowMo approach, therapy is likely to be most effective when it targets evidence-based processes that maintain distress (eg, fast thinking) whilst also being tailored to individual needs. Close attention to the patient experience of therapy is critical to deliver interventions that are accessible, engaging, and memorable.

A guiding principle of SlowMo is that assessment and intervention should include working with the patient in real-life environments, where fears of others are triggered (eg, public transport or crowded markets). This allows therapeutic targets to be understood in the broader context of the individual’s life, including relevant social factors such as experiences of poverty and discrimination.

It is crucial to promote and consolidate helpful learning and embed this into daily life, and digital tools represent a powerful method of achieving this. While SlowMo utilizes carefully designed digital tools, aspects reported by people as helpful (eg, recording and accessing helpful messages) may be replicated in simplified form using functions typically available on mobile devices.

Having found evidence for SlowMo’s efficacy and user friendliness, we are developing a new version for rollout in mental health services, which will build on its strengths while also addressing some of its limitations. We are encouraged by our findings to date, but the reality is that most digital therapeutics fail to be implemented outside of clinical contexts, due to organizational, provider, and consumer barriers.

 Further development is therefore required to deliver the benefits of SlowMo in routine care. Some challenges are beyond the direct control of developers and require governmental and provider intervention, such as access to hardware and data, and opportunities to acquire digital literacy skills. In line with these concerns, the next version of SlowMo will provide training on how to use the software, focus on a broader range of worries, and include additional tools to support therapists in providing evidence-based strategies to their patients. Implementation research is now required to establish whether efficacious digital therapeutics for paranoia can deliver on their promise of being a solution for transforming psychosis care.

is a professor of clinical psychology at the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. She is one of the pioneers of cognitive-behavioural therapy for psychosis and has led evaluations of innovative digital therapeutics for psychosis, including AVATAR and SlowMo therapy. 

 is a clinical psychologist lecturer at the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. She led on the development of SlowMo therapy and investigates the user experience of digital therapeutics. 

 is a research clinical psychologist at the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. He is the therapy lead for the AVATAR and SlowMo therapy teams.

1. The abandoned illness: a report from the Schizophrenia Commission. The Schizophrenia Commission. Rethink Mental Illness. November 2012. Accessed August 10, 2021. 

2. Leucht S, Cipriani A, Spineli L, et al. Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. 

. 2013;382(9896):951-962. Epub 2013. Erratum in: 

3. Turner DT, Burger S, Smit F, et al. What constitutes sufficient evidence for case formulation-driven CBT for psychosis? Cumulative meta-analysis of the effect on hallucinations and delusions. 

4. Kopelovich SL, Strachan E, Sivec H, Kreider V. Stepped care as an implementation and service delivery model for cognitive behavioral therapy for psychosis. 

5. Mohr DC, Riper H, Schueller SM. A solution-focused research approach to achieve an implementable revolution in digital mental health. 

6. Liu YC, Tang CC, Hung TT, et al. The efficacy of metacognitive training for delusions in patients with schizophrenia: a meta-analysis of randomized controlled trials informs evidence-based practice. 

7. Aref-Adib G, McCloud T, Ross J, et al. Factors affecting implementation of digital health interventions for people with psychosis or bipolar disorder, and their family and friends: a systematic review. 

8. Depp CA, Perivoliotis D, Holden J, et al. Single-session mobile-augmented intervention in serious mental illness: a three-arm randomized controlled trial.

9. Ben-Zeev D, Brian RM, Jonathan G, et al. Mobile health (mHealth) versus clinic-based group intervention for people with serious mental illness: A randomized controlled trial. 

10. Hardy A, Wojdecka A, West J, et al. How inclusive, user-centered design research can improve psychological therapies for psychosis: development of SlowMo. 

11. Kendler KS, Campbell J. Interventionist causal models in psychiatry: repositioning the mind-body problem. 

12. Ward T, Garety PA. Fast and slow thinking in distressing delusions: a review of the literature and implications for targeted therapy. 

14. Garety P, Ward T, Emsley R, et al. Effects of SlowMo, a blended digital therapy targeting reasoning, on paranoia among people with psychosis: a randomized clinical trial. 

15. Garety P, Ward T, Emsley R, , et al

 Digitally supported CBT to reduce paranoia and improve reasoning for people with schizophrenia-spectrum psychosis: the SlowMo RCT. 

16. Haddock G, McCarron J, Tarrier N, Faragher EB. Scales to measure dimensions of hallucinations and delusions: the psychotic symptom rating scales (PSYRATS). 

17. Andreasen NC. The scale for the assessment of positive symptoms (SAPS). The University of Iowa; 1984.

18. Green CE, Freeman D, Kuipers E, et al. Measuring ideas of persecution and social reference: the Green et al. Paranoid Thought Scales (GPTS). 

19. Freeman D, Loe BS, Kingdon D, et al. The revised Green 

, Paranoid Thoughts Scale (R-GPTS): psychometric properties, severity ranges, and clinical cut-offs. 

20. Garety P, Waller H, Emsley R, et al. Cognitive mechanisms of change in delusions: an experimental investigation targeting reasoning to effect change in paranoia. 

21. Hardy A, Ward T, Emsley R, et al. Bridging the ‘digital divide’ in psychological therapies for paranoia in psychosis: The user experience of the SlowMo mobile app. 

22. Greenhalgh T, Wherton J, Papoutsi C, et al. Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. 

A new digital therapeutic helps patients with psychosis to slow down and manage their fears.

Psychiatry’s Problem With Paranoia—Is Digital Part of the Solution? 

As the need grows for equitable, accessible, and affordable mental health treatment, digital therapeutics—app-based treatments—show promise for filling these gaps, particularly to target anxiety. The high prevalence of anxiety disorders “vastly exceeds the capacities of mental health services” to 

Anxiety has risen since the beginning of the COVID-19 pandemic. The US Census Bureau reported that adults were 3 times more likely to screen positive for anxiety disorders in 2020 compared with 2019 (31% vs 8%). A cross-sectional 

of individuals conducted in China February 2020 found the prevalence of generalized anxiety disorder (GAD) to be 35.1%; a meta-analysis found an average anxiety prevalence of 32% during the pandemic (17 studies, n = 63,439).

 A study of patients diagnosed with COVID-19 between January and August 2020 (n = 62,000+) found that 1 in 5 patients with no psychiatric history received a new mental health diagnosis, with the greatest health risk being for anxiety disorders.

Digital therapeutics can be designed to specifically target a behavioral or psychological mechanism of action, and they can be developed with user-centered design principles to maximize engagement. However, to date, very few digital therapeutics have been tested for efficacy, and even fewer have been studied regarding mechanism of action. There seem to be 2 categories of digital therapeutics emerging: those that are commercially developed with little supporting evidence or plans for evaluation and those with academic or government backing (and often not easily available to consumers).

 The former has the advantage of maximizing curb appeal: Resources can be devoted toward developing engaging user experiences using the latest design techniques, and companies can push a digital therapeutic to market rapidly. Scientists have developed evidence-based digital therapeutics, yet few are publicly available. They appear more slowly than their commercial counterparts, and those that do appear usually fail to attract users and user engagement.

 However, both face the same fate: No matter how shiny an app is, it still takes time to run rigorous clinical trials to determine efficacy (and mechanism).

John Torous, MD, Digital Section Editor for 

 and chair of the American Psychiatric Association’s Smartphone App Evaluation Task Force, put it bluntly when interviewed for an article on digital therapeutics in Nature: “Right now it almost feels like the Wild West of health care.”

How can the busy health care clinician keep up-to-date on the latest trends, determine which digital therapeutics are evidence based, and give informed answers when patients ask which apps to use? Is there enough evidence for prescribers to pull out their proverbial digital prescription pad to recommend an app-based treatment for anxiety?

After considering the recent literature, there are a few questions clinicians should consider.

Why Should There Be an Effect? What Mechanism Is Being Targeted?

A good place to start is to consider if a digital therapeutic is mechanistically based. Although many apps assert that they are scientifically based, very few live up to this claim. The National Institutes of Health established a 

 called the Science of Behavior Change (SOBC) to focus on mechanisms of change in behavioral interventions as a way to both strengthen intervention development and “increase rigor, transparency, and dissemination of common terminology, methods, and measures.”

 The basic idea behind SOBC is to measure if a behavioral intervention engages a hypothesized mechanism of change and if engaging that target leads to change in a health outcome. If this approach sounds similar to that taken for the development of any new drug, it should, because it is. It was modeled after the experimental medicine approach. However, a significant research-practice gap exists in the digital mental health field, especially in the field of anxiety interventions.

Findings of a recent study looking at the frequency of evidence-based treatment elements in apps for anxiety showed that the most commonly included elements were psychoeducation (53%), relaxation (47%), meditation (41%), and mindfulness (29%) (

 Yet, the inclusion of an element does not automatically translate to targeting a specific mechanism or therapeutic benefit. Another recent review found that 67% of apps for anxiety lacked involvement of any health professional in their development, and just 4% had been empirically evaluated.

This unfortunate lack of focus on mechanism is not due to an absence of information on how anxiety can develop and be perpetuated. For example, decades-old research has suggested potential mechanisms of action, such as targeting worry-driven negative reinforcement, yet 

 have these been incorporated into digital therapeutic devopment.

With apps that can reach thousands, and even millions, of potential patients, it is much easier to collect data from a convenience sample, look for reductions in some type of scale, and then claim it to be an evidence-based treatment for anxiety. However, there is a world of difference between someone who is mildly anxious (after all, who is not these days?), and someone whose anxiety is severe enough to land them firmly in the realm of needing treatment for a DSM-diagnosed anxiety disorder. For example, a 

 of randomized controlled trials of mindfulness apps reported significant effect sizes for reductions in anxiety, but every study recruited individuals from app users and the general population and specific nonclinical groups (largely students and employees).

 Of these, only a single study included individuals with mild to moderate anxiety using the General Anxiety Disorder-7 (GAD-7) cutoff of 14 to exclude individuals who reported severe anxiety (GAD-7: 5-9, mild; 10-14, moderate; 15+, severe anxiety).

 of internet-based cognitive behavioral therapy (iCBT) used GAD-7 scores of ≥ 8 as a minimum cutoff to recruit individuals with mild to moderate symptoms of anxiety, individuals in the United Kingdom’s National Health System (NHS) and “who may be eligible and require iCBT” as part of the Improving Access to Psychological Therapies (IAPT) program.

 Additionally, 2 studies of app-based mindfulness training for anxiety (Unwinding Anxiety) have used GAD-7 scores of ≥ 10 as minimum cutoff for inclusion of anxious physicians and individuals with GAD, respectively.

 Taken together, these results suggest that the majority of studies are drawing convenience samples from nonclinical populations, and that can lead to problematic inferences on the efficacy and utility of digital therapeutics in individuals with moderate to severe anxiety—those that would be most likely to seek or be referred to treatment—unless they have been specifically studied in these populations.

What Is the Evidence? Is There a Clinically Relevant Reduction in Symptoms?

Popularity does not equal evidence for efficacy. A number of app-based programs have put a primary focus on increasing their user base rather than developing digital therapeutics for anxiety. Although there is nothing inherently wrong with this approach—it is just a different focus—seeing a lot of individuals use an app can lead to a false sense of efficacy. Most studies to date are small pilot studies, often run by the app developers rather than by independent researchers, and the results have yet to be replicated. Additionally, many studies are run relative to wait-list control groups. Although this is better than no control group, it does not assess basic confounding components that are covered by a treatment as usual control group, such as receiving some type of treatment and expectancy effects (which, if performed well, will include the usual clinical care delivered by their therapist or doctor).

As previously mentioned, only a few published studies have examined digital therapeutics in individuals with moderate to severe anxiety: 1 in the general population (mainly recruited from users who were already signed up for the app Pacifica) with baseline GAD-7 scores of between 5 and 14; 1 (iCBT) in the UK’s NHS in individuals with baseline GAD-7 scores of ≥ 8; 1 (Unwinding Anxiety) in anxious physicians with baseline GAD-7 scores of ≥ 10; and 1 (Unwinding Anxiety) in individuals with GAD with baseline GAD-7 scores of ≥ 10.

In the first study, a randomized controlled trial that compared the Pacifica app to a wait-list control, only 35% of the app and 47% of wait-list participants completed the study. A composite anxiety score, using an average score of standardized GAD-7 and Depression and Anxiety Stress Scale-21 (anxiety component) scores, showed a statistically significant drop in both groups after 4 weeks (wait-list control, 0.23 composite point; Pacifica, 0.66 composite point), which was reported as statistically significantly different. In the second study, a randomized controlled trial of iCBT (Silvercloud) vs wait-list control, individuals in the iCBT group showed a statistically significant 35% reduction in GAD-7 scores at 8 weeks (baseline, 12.7; 8-week follow-up, 8.2) relative to a 15% reduction in the control group (baseline, 12.7; 8-week follow-up, 10.8). Retention was 82% and 76%, respectively.

In the third study, a single-arm trial of the Unwinding Anxiety app, anxious physicians demonstrated a statistically significant reduction in GAD-7 scores of 48% and 57% after 1 and 3 months, respectively (baseline, 11.5; 1-month, follow-up, 6.0; 3-month follow-up, 5.0). Retention was 60%. In the fourth randomized controlled trial looking at Unwinding Anxiety vs treatment as usual (TAU), individuals randomized to Unwinding Anxiety showed a statistically significant 67% reduction in GAD-7 scores (baseline, 12.0; 2-month follow-up, 3.0) relative to a 14% reduction in the TAU group at 2 months (baseline, 13.0; 2-month follow-up, 10.0). Retention was 88% for the Unwinding Anxiety group and 100% for the TAU group.

When prescribing a medication or suggesting that a patient try a behavioral treatment, we fall back on the ideals of the Hippocratic oath that we took at the beginning of medical school: First, do no harm. Although digital therapeutics do not carry the traditional adverse effect risk profile of a medication, it is important to approach information in a parallel manner: Ingesting information is not free of unintended consequences. For example, 

 for bipolar disorder found the presentation of information that could lead to harm (eg, encouraging individuals to drink liquor to help them sleep during manic episodes).

 Additionally, privacy is a concern, as apps can easily collect personal information ranging from symptoms to geolocation.

Digital therapeutics have the potential to live up to their promise: Mechanistic and evidence-based treatments that can be widely disseminated at low cost. To date, very few have demonstrated efficacy, and these studies would benefit from replication and extension of their findings. As clinicians consider recommending app-based treatments, it is important to stay abreast of emerging study results, and as they evaluate apps for their patients, they must keep those aforementioned important questions in mind (

is an associate professor of psychiatry at the Warren Alpert Medical School of Brown University, executive medical director of behavioral health at Sharecare Inc, and author of Unwinding Anxiety. Twitter: @judbrewer. He owns stock in, and serves as a paid consultant for, Sharecare Inc, the company that owns the Unwinding Anxiety app described in this article. The financial interest has been disclosed to and is being managed by his institution, Brown University, in accordance with its Conflict of Interest and Conflict of Commitment policies.

1. Firth J, Torous J, Carney R, et al. Digital technologies in the treatment of anxiety: recent innovations and future directions. 

2. Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey. 

3. Salari N, Hosseinian-Far A, Jalali R, et al. Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis. 

4. Taquet M, Luciano S, Geddes JR, Harrison PJ. Bidirectional associations between COVID-19 and psychiatric disorder: retrospective cohort studies of 62 354 COVID-19 cases in the USA. 

5. Bowland S, Hensley M, Johnson B, Fleming A. Consumer focus groups: a key to transforming behavioral health systems?

6. Anthes E. Mental health: there’s an app for that. 

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8. Wasil AR, Venturo-Conerly KE, Shingleton RM, Weisz JR. A review of popular smartphone apps for depression and anxiety: assessing the inclusion of evidence-based content. 

9. Sucala M, Cuijpers P, Muench F, et al. Anxiety: there is an app for that. A systematic review of anxiety apps. 

10. Brewer JA. Why targeting entrenched habits can treat anxiety. 

 March 19, 2021. Accessed June 21, 2021. 

11. Brewer JA, Roy A, Deluty A, et al. Can mindfulness mechanistically target worry to improve sleep disturbances? Theory and study protocol for app-based anxiety program. 

Unwinding Anxiety: New Science Shows How to Break the Cycles of Worry and Fear to Heal Your Mind

13. Janes AC, Datko M, Roy A, et al. Clinical efficacy and psychological mechanisms of an app-based digital therapeutic for generalized anxiety disorder. Under review.

14. Gál É, Ştefan S, Cristea IA. The efficacy of mindfulness meditation apps in enhancing users’ well-being and mental health related outcomes: a meta-analysis of randomized controlled trials. 

15. Richards D, Enrique A, Eilert N, et al. A pragmatic randomized waitlist-controlled effectiveness and cost-effectiveness trial of digital interventions for depression and anxiety. 

16. Roy A, Druker S, Hoge EA, Brewer JA. Physician anxiety and burnout: symptom correlates and a prospective pilot study of app-delivered mindfulness training. 

17. Moberg C, Niles A, Beermann D. Guided self-help works: randomized waitlist controlled trial of Pacifica, a mobile app integrating cognitive behavioral therapy and mindfulness for stress, anxiety, and depression. 

18. Nicholas J, Larsen ME, Proudfoot J, Christensen H. Mobile apps for bipolar disorder: a systematic review of features and content quality. 

Key questions to consider when evaluating a digital therapeutic for anxiety. 

Anxiety Treatment at Your Fingertips

I am delighted to introduce this important supplement of 

™. In the context of the COVID-19 pandemic, telepsychiatry has passed its tipping point and now become a mainstream method of providing mental health services. In contrast, more complex solutions such as artificial intelligence, technology-enabled care, and smartphone applications are not yet mainstream.

However, the integration of digital technologies into psychiatric care has only just begun. Looking ahead, I believe that technology-enabled care will be the defining advancement of mental health services in this generation. I believe there are 3 key trends that have shaped how we got here and give us clues to what the future holds.

Rapid Erosion of Stigma and Surging Demand

The COVID-19 pandemic created a series of conditions that both increased the overall risk for mental illness and triggered specific episodes: uncertainty about life or death, bereavement of loved ones, chronic isolation, job loss, financial uncertainty, and loss of numerous life events (prom, graduation, weddings, etc). The result has been a rapid increase in anxiety, depression, and alcohol use, with a whopping 40% of Americans reporting at least 1 mental health condition, and more than 10% seriously considering 

At the same time, the pandemic circumstances have made it easier to talk about these experiences of depression and anxiety, in part, because they were understandable reactions to the various facets of a global crisis. On top of that, celebrities and other influencers have been speaking about their own mental health challenges, thereby normalizing the experience and providing hope for treatment.

For examples, 23-time Olympic gold medalist swimmer Michael Phelps, and singer-songwriter Demi Lovato have both shared their experiences as part of serving as marketing ambassadors for Talkspace. Similarly, tennis player Naomi Osaka, the highest-paid female athlete in the world, recently shared her experience with depression and anxiety in an Instagram post, explaining why she did not want to participate in postmatch conferences.

These are not isolated events, and they make a huge impression on individuals everywhere who have their own struggles with mental health. As a result, an increasing number of people are seeking treatment than ever before.

Great Influx of Private Investment in Mental Health

Observing the decline in stigma and rise in demand, investors have been pouring money into mental health. For instance, earlier this year I published a discussion on this topic after finding that venture capital investors dedicated a record breaking $637 million to 

 in 2019, which was a 23-fold increase from 2013.

 Estimates now suggest that venture capital 

 in 2020 and is poised to surpass $2 billion in 2021.

In addition to venture capital, private equity companies are also investing in mental health; they are focusing on consolidating addiction facilities, residential treatment centers, and outpatient mental health clinics. In June 2021, LifeStance Health, one of the nation’s largest providers of outpatient psychiatric services, joined the Nasdaq stock exchange in an initial public offering 

You may be wondering why private investment is relevant to technology. We know technologies provide opportunities for mental health treatments to be scaled up. For investors, technology is attractive, as it is the key to driving larger returns. As we see more and more investment in mental health from private investors, I expect to see a greater focus on digital technologies, ranging from the basics like appointment scheduling and messaging between patients and clinicians, to more advanced features like chatbots and do-it-yourself smartphone applications as initial or complementary treatments. For psychiatrists, these technologies will enable us to treat more patients and disseminate care more widely than ever before.

Toward a Post–COVID-19 Future: Hybrid Care

The big question is: How will we get from where we are now, which is a loose combination of telepsychiatry and traditional care, to this futuristic digitally enabled care model?

Like all sustainable innovation, I predict that technologies will advance incrementally, steadily marching toward the day when digitally enabled care will be the norm (

). Just as telepsychiatry is now a patient expectation, patients will also expect appointment rescheduling, billing, and documents (including signature) to be fully digital in the next 10 years. In addition, the ability to send asynchronous messages to the provider in a secure format will be common. Finally, as insurance companies play a role in how care is reimbursed and delivered, there will be a growing expectation that digital tools (ie, smartphone application modules for cognitive behavioral therapy) will help to reduce either the length or number of sessions needed for milder conditions and treatments.

The world is digitally powered, and our treatments will have to be digitally enabled if we are going to meet patients where they are: on their smartphones. Demand is surging, stigma is declining, and private investors will continue to push technologies that scale up our treatments. The field of psychiatry is poised to take advantage of this brave new world to better care for patients. I have never been as excited to be a psychiatrist as I am today. Happy reading—our future awaits!

is the Chief Innovation Officer at Columbia Psychiatry and assistant professor of psychiatry at Columbia University Irving Medical Center. He is an advisor and holds equity in the following mental health startups: Two Chairs, Mantra Health, Tempest, and GroupWell. These companies are not referenced in this article.

1. Czeisler MÉ, Lane RI, Petrosky E, et al. Mental health, substance use, and suicidal ideation during the COVID-19 pandemic - United States, June 24-30, 2020. 

2. Shah RN, Berry OO. The rise of venture capital investing in mental health. 

3. Thorne J. Driven by pandemic demand, mental health startups surpass 2019 funding. 

. October 14, 2020. Accessed June 29, 2021. 

4. Landi H. Mental health provider LifeStance Health valued at more than $7B as stock jumps following IPO. 

. June 15, 2021. Accessed June 29, 2021. 

What will psychiatric practice look like in the year 2030? 

Technology-Enabled Care: The Future of Our Field

In the United States, the Centers for Disease Control and Prevention (CDC) 

that in 2019, 4.7% of adults aged 18 years or older reported regular feelings of depression, and 11.2% reported regular feelings of worry, nervousness, or anxiety.

 Forty percent of Americans with a 12-month history of severe mental disorders 

 Disorders were assessed by structured diagnostic interview using the World Health Organization’s World Mental Health Composite International Diagnostic following DSM-IV criteria. The analyzed disorders included mood (ie, major depressive disorder, dysthymia, or bipolar disorder type I or II), anxiety (ie, generalized anxiety disorder, panic disorder, agoraphobia, social phobia, specific phobia), posttraumatic stress disorder, and substance use disorders (ie, alcohol or drug abuse or dependence). In lower- and middle-income countries, this figure can exceed 75%.

The ongoing COVID-19 pandemic has increased mental health care needs while simultaneously restricting access, with unknown long-term consequences. From August 2020 to February 2021, the CDC 

an increase in the proportion of adults reporting recent symptoms of anxiety or depression from 36.4% to 41.5%, with the fraction reporting unmet mental health care needs increasing from 9.2% to 11.7%.

 Among children and adolescents, the proportion of mental health–related 

visits for those aged 5 to 11 years and 12 to 17 years increased 24% and 31%, respectively, compared with 2019.

is a clinical research psychologist, an adjunct faculty member in the Department of Psychiatry and Behavioral Sciences at Stanford University School of Medicine, and the founder and president of

is a practicing psychiatrist, an adjunct assistant professor of psychiatry and human behavior at the Warren Alpert Medical School of Brown University, and vice president and medical director of

1. Norris T, Clark TC, Boersma P, Schiller JS. Technical notes for early release of selected estimates based on data from the National Health Interview Survey. National Center for Health Statistics. February 2021. Accessed June 25, 2021. 

2. Wang PS, Aguilar-Gaxiola S, Alonso J, et al. Use of mental health services for anxiety, mood, and substance disorders in 17 countries in the WHO world mental health surveys. 

3. Vahratian A, Blumberg SJ, Terlizzi EP, Schiller JS. Symptoms of anxiety or depressive disorder and use of mental health care among adults during the COVID-19 pandemic – United States, August 2020-February 2021. 

4. Leeb RT, Bitsko RH, Radhakrishnan L, et al. Mental health–related emergency department visits among children aged <18 years during the COVID-19 pandemic – United States, January 1-October 17, 2020. 

What are the greatest unmet mental health needs in the United States today? Recent statistics from the Centers for Disease Control may hold the answers. 

Mental Health in America: A Growing Crisis

Around the world, 5 billion individuals have mobile devices, half of which are 

 It is therefore unsurprising that mobile technology has become a core component of digital therapeutics (DTx). Today’s mobile technology allows mental health DTx to be more than simple remote assessment tools that report patient outcomes like those of the Patient Health Questionnaire-9. Rather, the latest DTx aim to deliver medical interventions directly to patients, using software intended to treat, manage, and potentially prevent disease.

Although care access is a key issue that digital solutions can improve, DTx also create an opportunity for genuine innovation. In fact, DTx are not necessarily diluted versions of in-person psychotherapy. Rather, in some cases they give rise to a mechanism of action enabled by the digital medium itself. For example, Akili’s EndeavorRx uses video game dynamics to train attentional processes in an intervention for children with attention-deficit/hyperactivity disorder. Omada Health delivers a digital version of the evidence-based Diabetes Prevention Program because it is a lifestyle intervention, including a support component enabled by technology and weight monitoring through connected devices. Pear Therapeutics’ reSET and reSET-O are prescription DTx for substance use disorder and opioid use disorder, respectively, intended to provide cognitive behavioral therapy (CBT) as an adjunct to outpatient treatment.

Innovations, however, are not good simply because they exist. Clinicians will need to carefully and thoughtfully consider different DTx offerings, their claimed mechanisms of action, evidence for their efficacy and ease of use, and other relative strengths and weaknesses.

Why Are Mental Health DTx Primarily Based on CBT?

CBT lends itself to digitization because the way in which individuals interact with their devices—and the devices’ ubiquitous presence—matches, and even facilitates, the core principles of change that underpin the therapy. Hence, most DTx assert that they are based on CBT.

However, in order to claim theoretical foundations in CBT, an intervention must promote behavioral adaptation through 

: context engagement, attention change, and cognitive change.

 Context engagement helps promote adaptive associative learning beyond what is currently perceived by the person. Examples of context engagement strategies include behavioral activation and exposure therapies; in the latter case, virtual reality is being explored as a potential component of DTx for posttraumatic stress disorder.

 Attention change refers to a shift in attention to adaptive, relevant, nondistressing stimuli. This includes therapeutic processes such as attention training, acceptance or tolerance training, and mindfulness techniques. Cognitive change refers to a shift in one’s perspective on an event, which then affects the emotional significance and meaning of that event. This includes metacognitive awareness and cognitive distancing, which are promoted through therapeutic processes such as cognitive reframing or reappraisal.

These 3 principles all have in common the need to draw awareness to, record, and evaluate how the patient experiences and interacts with the world. In this model, anything that facilitates these practices in an ecologically valid way may amplify their therapeutic effect. The therapeutic relationship in CBT is characterized by collaborative empiricism, wherein the therapist encourages symptom self-monitoring with a view to constructing experiments and opportunities to challenge one’s world view. In traditional therapist-delivered CBT, data have shown that the more a patient adheres to these tasks between sessions, the better their 

 Well-designed DTx have the potential to make those homework tasks easy. Beyond being a simple matter of convenience, making homework easy may have particular potency in some diagnoses, like major depressive disorder, in which lack of motivation (anhedonia) and a sense of disconnection are pervasive. Setting up the patient for success with tasks that facilitate therapeutic processes, especially in a way that is achievable and minimizes cognitive burden, can build self-efficacy and could accelerate time to recovery. While many such DTx are still in development, some have demonstrated potential to meaningfully reduce symptoms in just 2 weeks of use compared with a psychoeducation control group.

The overall contribution of these 3 foundational CBT principles to the treatment of an individual will depend on that individual and the issues with which they present. Some patients will have more insight or self-awareness of their emotional state or of their negative automatic thoughts and, therefore, may need to work less on attention change. Similarly, a patient with a specific phobia may need to work more on context engagement, using exposure techniques to relearn and diffuse previously learned negative associations. An experienced CBT therapist will make these modifications instinctively. Although the earlier waves of digital CBT were mostly one-size-fits-all applications, more recent digital solutions can include an innumerable number of skills and techniques from several therapeutic approaches (ie, CBT, interpersonal therapy, and dialectical behavior therapy) and adaptively meet patients where they are clinically.

As artificial intelligence (AI) and machine learning (ML) technology advances, DTx have an opportunity to grow beyond limited and inflexible content streams and become responsive to the patient’s present emotional state and circumstances (

). This is especially important, because maintaining user engagement over time proves challenging for many DTx. One approach is to use a relational agent, which is a specialized type of chatbot purpose-built to replicate some of the unique traits and dynamics of human interpersonal relationships. One such chatbot—Woebot—demonstrated Working Alliance Inventory – Short Revised scores comparable with those reported in the literature for traditional outpatient individual and group CBT. These results demonstrate that DTx can establish a 

Additionally, research has shown that individuals are more willing to disclose personal information to a virtual human, as doing so lowers fear of self-disclosure and impression management.

 This may be particularly important in adolescents, who prefer online or mobile tools over face-to-face interactions and tend to fear the stigma associated with seeking traditional mental health services.

Why are mental health digital therapeutics primarily based on CBT?

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Technology-Enabled Care: The Future of Our Field

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DTx and Cognitive Behavioral Therapy: Opportunities, Benefits, and Challenges of an Evolving Landscape

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