A randomized controlled trial of a digital cognitive-behavioral therapy program (COMPASS) for managing depression and anxiety related to living with a long-term physical health condition.

BACKGROUND: To evaluate the clinical efficacy of COMPASS, a therapist-supported digital therapeutic for reducing psychological distress (anxiety/depression) in people living with long-term physical health conditions (LTCs). METHODS: A two-armed randomized-controlled trial recruiting from LTC charities. Participants with anxiety and/or depression symptoms related to their LTC(s) were randomized (concealed allocation via independent administrator) to COMPASS (access to 11 tailored modules plus five thirty-minute therapist support sessions) or standard charity support (SCS). Assessments were completed online pre-randomization, at 6- and 12-weeks post-randomization. Primary outcome was Patient Health Questionnaire Anxiety and Depression Scale; PHQ-ADS measured at 12-weeks. Analysis used intention-to-treat principles with adjusted mean differences estimated using linear mixed-effects models. Data-analyst was blinded to group allocation. RESULTS: 194 participants were randomized to COMPASS (N = 94) or SCS (N = 100). At 12-weeks, mean level of psychological distress was 6.82 (95% confidence interval; CI 4.55-9.10) points lower (p < 0.001) in the COMPASS arm compared with SCS (standardized mean difference of 0.71 (95% CI 0.48-0.95)). The COMPASS arm also showed moderate significant treatment effects on secondary outcomes including depression, anxiety and illness-related distress and small significant effects on functioning and quality-of-life. Rates of adverse events were comparable across the arms. Deterioration in distress at 12-weeks was observed in 2.2% of the SCS arm, and no participants in the COMPASS arm. CONCLUSION: Compared with SCS, COMPASS digital therapeutic with minimal therapist input reduces psychological distress at post-treatment (12-weeks). COMPASS offers a potentially scalable implementation model for health services but its translation to these contexts needs further evaluating. TRIAL REGISTRATION: NCT04535778.

The clinical effect of digital cognitive behavioural therapy for insomnia in subgroups with depressive and anxiety symptoms: A secondary analysis of a randomized-controlled trial.

Insomnia is a highly prevalent mental disorder, and is often co-occurring with depression and anxiety disorders. Cognitive behavioural therapy for insomnia as treatment of choice for insomnia can also be applied digitally (digital cognitive behavioural therapy for insomnia), making it more accessible. This is a secondary data analysis of a two-armed parallel randomized-controlled trial. In the primary publication, N = 238 participants meeting criteria for the 5th edition of Diagnostic and Statistical Manual of Mental Disorders chronic insomnia disorder were randomly assigned to either 8 weeks of digital cognitive behavioural therapy for insomnia + treatment-as-usual, or waitlist + treatment-as-usual. To determine the clinical effects of digital cognitive behavioural therapy for insomnia in populations with comorbid anxiety and depression symptoms, this secondary analysis focused on two subgroups: (1) participants with high initial depressive symptoms; and (2) participants with high initial anxiety symptoms. Symptoms of insomnia, depression and anxiety as primary outcome measures were obtained at baseline, 8 weeks post-randomization and, in the intervention group only, at 6- and 12-months follow-up. At 8 weeks post-randomization, the use of digital cognitive behavioural therapy for insomnia in both subgroups was associated with large reductions in insomnia severity in comparison to control (depression subgroup: d = 2.37; anxiety subgroup: d = 2.13). Between-group treatment effects were also observed for symptoms of depression in the depression subgroup (d = 1.59), and for symptoms of anxiety in the anxiety subgroup (d = 1.28). Within-group effects were stable over time (d = 0.64-1.63). This secondary analysis shows that digital cognitive behavioural therapy for insomnia reduces insomnia and comorbid symptoms in participants with high initial symptoms of either depression or anxiety with sustained long-term effects.

The Effectiveness of a Digital App for Reduction of Clinical Symptoms in Individuals With Panic Disorder: Randomized Controlled Trial.

BACKGROUND: Panic disorder is a common and important disease in clinical practice that decreases individual productivity and increases health care use. Treatments comprise medication and cognitive behavioral therapy. However, adverse medication effects and poor treatment compliance mean new therapeutic models are needed. OBJECTIVE: We hypothesized that digital therapy for panic disorder may improve panic disorder symptoms and that treatment response would be associated with brain activity changes assessed with functional near-infrared spectroscopy (fNIRS). METHODS: Individuals (n=50) with a history of panic attacks were recruited. Symptoms were assessed before and after the use of an app for panic disorder, which in this study was a smartphone-based app for treating the clinical symptoms of panic disorder, panic symptoms, depressive symptoms, and anxiety. The hemodynamics in the frontal cortex during the resting state were measured via fNIRS. The app had 4 parts: diary, education, quest, and serious games. The study trial was approved by the institutional review board of Chung-Ang University Hospital (1041078-202112-HR-349-01) and written informed consent was obtained from all participants. RESULTS: The number of participants with improved panic symptoms in the app use group (20/25, 80%) was greater than that in the control group (6/21, 29%; χ21=12.3; P=.005). During treatment, the improvement in the Panic Disorder Severity Scale (PDSS) score in the app use group was greater than that in the control group (F1,44=7.03; P=.01). In the app use group, the total PDSS score declined by 42.5% (mean score 14.3, SD 6.5 at baseline and mean score 7.2, SD 3.6 after the intervention), whereas the PDSS score declined by 14.6% in the control group (mean score 12.4, SD 5.2 at baseline and mean score 9.8, SD 7.9 after the intervention). There were no significant differences in accumulated oxygenated hemoglobin (accHbO2) at baseline between the app use and control groups. During treatment, the reduction in accHbO2 in the right ventrolateral prefrontal cortex (VLPFC; F1,44=8.22; P=.006) and the right orbitofrontal cortex (OFC; F1,44=8.88; P=.005) was greater in the app use than the control group. CONCLUSIONS: Apps for panic disorder should effectively reduce symptoms and VLPFC and OFC brain activity in patients with panic disorder. The improvement of panic disorder symptoms was positively correlated with decreased VLPFC and OFC brain activity in the resting state. TRIAL REGISTRATION: Clinical Research Information Service KCT0007280; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=21448.

Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments.

OBJECTIVE: To investigate the trajectories of work and activity impairments among people participating in a digital self-management program for osteoarthritis (OA). METHODS: We conducted an observational longitudinal study using data for baseline, 3, 6, 9 and 12 months follow ups from people participating in a digital OA treatment between June 2018 and September 2021. The Work Productivity and Activity Impairment-Osteoarthritis (WPAI-OA) questionnaire was used to measure work and activity impairments. We applied linear mixed models and group-based trajectory modelling (GBTM) to assess the trajectories of work and activity impairments and their variability. Dominance analysis was performed to explore the relative importance of baseline characteristics in predicting the trajectory subgroup membership. RESULTS: A total of 14,676 participants with mean (± standard deviation) age 64.0 (± 9.1) years and 75.5% females were included. The adjusted mean improvements in work impairment from baseline were 5.8% (95% CI 5.3, 6.4) to 6.1% (95% CI 5.5, 6.8). The corresponding figures for activity impairment were 9.4% (95% CI 9.0, 9.7) to 11.3% (95% CI 10.8, 11.8). GBTM identified five (low baseline-declining, moderate baseline-declining, high baseline-declining, very high baseline-substantially declining, and very high baseline-persistent) and three (low baseline-declining, mild baseline-declining, high baseline-declining) subgroups with distinct trajectories of activity and work impairments. Dominance analysis showed that baseline pain was the most important predictor of membership in trajectory subgroups. CONCLUSION: While participation in a digital self-management program for OA was, on average, associated with improvements in work and activity impairments, there were substantial variations among the participants. Baseline pain may provide useful insights to predict trajectories of work and activity impairments.

Predictors of Dropout Among Psychosomatic Rehabilitation Patients During the COVID-19 Pandemic: Secondary Analysis of a Longitudinal Study of Digital Training.

BACKGROUND: High dropout rates are a common problem reported in web-based studies. Understanding which risk factors interrelate with dropping out from the studies provides the option to prevent dropout by tailoring effective strategies. OBJECTIVE: This study aims to contribute an understanding of the predictors of web-based study dropout among psychosomatic rehabilitation patients. We investigated whether sociodemographics, voluntary interventions, physical and mental health, digital use for health and rehabilitation, and COVID-19 pandemic-related variables determine study dropout. METHODS: Patients (N=2155) recruited from 4 psychosomatic rehabilitation clinics in Germany filled in a web-based questionnaire at T1, which was before their rehabilitation stay. Approximately half of the patients (1082/2155, 50.21%) dropped out at T2, which was after the rehabilitation stay, before and during which 3 voluntary digital trainings were provided to them. According to the number of trainings that the patients participated in, they were categorized into a comparison group or 1 of 3 intervention groups. Chi-square tests were performed to examine the differences between dropout patients and retained patients in terms of sociodemographic variables and to compare the dropout rate differences between the comparison and intervention groups. Logistic regression analyses were used to assess what factors were related to study dropout. RESULTS: The comparison group had the highest dropout rate of 68.4% (173/253) compared with the intervention groups' dropout rates of 47.98% (749/1561), 50% (96/192), and 42.9% (64/149). Patients with a diagnosis of combined anxiety and depressive disorder had the highest dropout rate of 64% (47/74). Younger patients (those aged <50 y) and patients who were less educated were more likely to drop out of the study. Patients who used health-related apps and the internet less were more likely to drop out of the study. Patients who remained in their jobs and patients who were infected by COVID-19 were more likely to drop out of the study. CONCLUSIONS: This study investigated the predictors of dropout in web-based studies. Different factors such as patient sociodemographics, physical and mental health, digital use, COVID-19 pandemic correlates, and study design can correlate with the dropout rate. For web-based studies with a focus on mental health, it is suggested to consider these possible dropout predictors and take appropriate steps to help patients with a high risk of dropping out overcome difficulties in completing the study.

Examining Diversity in Digital Therapeutics Clinical Trials: Descriptive Analysis.

BACKGROUND: Digital therapeutics (DTx) are an emerging class of software-based medical therapies helping to improve care access and delivery. As we leverage these digital health therapies broadly in clinical care, it is important to consider sociodemographic representation underlying clinical trials data to ensure broad application to all groups. OBJECTIVE: We review current sociodemographic representation in DTx clinical trials using data from the Digital Therapeutics Alliance Product Library database. METHODS: We conducted a descriptive analysis of DTx products. We analyzed 15 manuscripts associated with 13 DTx products. Sociodemographic information was retrieved and compared with the US population's demographic distribution. RESULTS: The median study size and age of participants were 252 and 43.3 years, respectively. Of the 15 studies applicable to this study, 10 (67%) reported that females made up 65% or greater of the study cohort. A total of 14 studies reported race data with Black or African American and Asian American individuals underrepresented in 9 and 11 studies, respectively. In 7 studies that reported ethnicity, Hispanics were underrepresented in all 7 studies. Furthermore, 8 studies reported education levels, with 5 studies reporting populations in which 70% or greater had at least some college education. Only 3 studies reported health insurance information, each reporting a study cohort in which 100% of members were privately insured. CONCLUSIONS: Our findings indicate opportunities for improved sociodemographic representation in DTx clinical trials, especially for underserved populations typically underrepresented in clinical trials. This review is a step in examining sociodemographic representation in DTx clinical trials to help inform the path forward for DTx development and testing.

Effects of a Nonwearable Digital Therapeutic Intervention on Preschoolers With Autism Spectrum Disorder in China: Open-Label Randomized Controlled Trial.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that can cause difficulty with communication and social interactions as well as complicated family dynamics. Digital health interventions can reduce treatment costs and promote healthy lifestyle changes. These therapies can be adjunctive or replace traditional treatments. However, issues with cooperation and compliance prevent preschool patients with ASD from applying these tools. In this open-label, randomized controlled trial, we developed a nonwearable digital therapy called virtual reality-incorporated cognitive behavioral therapy (VR-CBT). OBJECTIVE: The aim of this study was to assess the adjunctive function of VR-CBT by comparing the effects of VR-CBT plus learning style profile (LSP) intervention with those of LSP-only intervention in preschool children with ASD. METHODS: This trial was performed in China on 78 preschool children (age 3-6 years, IQ>70) diagnosed with ASD who were randomized to receive a 20-week VR-CBT plus LSP intervention (intervention group, 39/78, 50%) or LSP intervention only (control group, 39/78, 50%). The primary outcome was the change of scores from baseline to week 20, assessed by using the parent-rated Autism Behavior Checklist (ABC). Secondary outcomes included the Childhood Autism Rating Scale (CARS), Attention-Deficit/Hyperactivity Disorder Rating Scale-IV (ADHD-RS-IV), and behavioral performance data (accuracy and reaction time) in go/no-go tasks. All primary and secondary outcomes were analyzed in the intention-to-treat population. RESULTS: After the intervention, there was an intervention effect on total ABC (ß=-5.528; P<.001) and CARS scores (ß=-1.365; P=.02). A similar trend was observed in the ABC subscales: sensory (ß=-1.133; P=.047), relating (ß=-1.512; P=.03), body and object use (ß=-1.211; P=.03), and social and self-help (ß=-1.593; P=.03). The intervention also showed statistically significant effects in improving behavioral performance (go/no-go task, accuracy, ß=2.923; P=.04). Moreover, a significant improvement of ADHD hyperactivity-impulsivity symptoms was observed in 53 children with comorbid ADHD based on ADHD-RS-IV (ß=-1.269; P=.02). No statistically significant intervention effect was detected in the language subscale of ABC (ß=-.080; P=.83). Intervention group girls had larger improvements in ABC subscales, that is, sensory and body and object use and in the CARS score and accuracy of go/no-go task (all P<.05) than the control group girls. Statistically significant intervention effects could be observed in hyperactivity-impulsivity symptoms in the intervention group boys with comorbid ADHD compared with those in the control group boys (ß=-1.333; P=.03). CONCLUSIONS: We found potentially positive effects of nonwearable digital therapy plus LSP on core symptoms associated with ASD, leading to a modest improvement in the function of sensory, motor, and response inhibition, while reducing impulsivity and hyperactivity in preschoolers with both ASD and ADHD. VR-CBT was found to be an effective and feasible adjunctive digital tool. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2100053165; http://www.chictr.org.cn/showproj.aspx?proj=137016.

Effectiveness and therapeutic compliance of digital therapy in shoulder rehabilitation: a randomized controlled trial.

BACKGROUND: Interactive videogames, virtual reality, and robotics represent a new opportunity for multimodal treatments in many rehabilitation contexts. However, several commercial videogames are designed for leisure and are not oriented toward definite rehabilitation goals. Among the many, Playball® (Playwork, Alon 10, Ness Ziona, Israel) is a therapeutic ball that measures both movement and pressure applied on it while performing rehabilitation games. This study aimed: (i) to evaluate whether the use of this novel digital therapy gaming system was clinically effective during shoulder rehabilitation; (ii) to understand whether this gaming rehabilitation program was effective in improving patients' engagement (perceived enjoyment and self-efficacy during therapy; attitude and intention to train at home) in comparison to a control non-gaming rehabilitation program. METHODS: A randomized controlled experimental design was outlined. Twenty-two adults with shoulder pathologies were recruited for a rehabilitation program of ten consecutive sessions. A control (CTRL; N = 11; age: 62.0 ± 10.9 yrs) and an intervention group (PG; N = 11; age: 59.9 ± 10.2 yrs) followed a non-digital and a digital therapy, respectively. The day before (T0) and after (T1) the rehabilitation program, pain, strength, and mobility assessments were performed, together with six questionnaires: PENN shoulder Score, PACES-short, Self-efficacy, Attitudes to train at home, Intention to train at home, and System usability scale (SUS). RESULTS: MANOVA analysis showed significant improvements in pain (p < 0.01), strength (p < 0.05), and PENN Shoulder Score (p < 0.001) in both groups. Similarly, patients' engagement improved, with significant increments in Self-efficacy (p < 0.05) and attitude (p < 0.05) scores in both groups after the rehabilitation. Pearson correlation showed significant correlations of the Δ scores (T1 - T0) between PACES and Self-efficacy (r = 0.623; p = 0.041) and between PACES and Intention to train at home (r = 0.674; p = 0.023) only in the PG. SUS score after the rehabilitation (74.54 ± 15.60) overcame the cut-off value of 68, representative of good usability of a device. CONCLUSIONS: The investigated digital therapy resulted as effective as an equivalent non-digital therapy in shoulder rehabilitation. The reported positive relationship between the subject's enjoyment during digital therapy and intention to train at home suggests promising results in possible patient's exercise engagement at home after the rehabilitation in the medical center. RETROSPECTIVELY REGISTERED: NCT05230056.

[Development Opportunities and Challenges of Digital Therapy in China].

With the development of new technologies such as the Internet, big data, and AI, digital therapy has gradually developed into an emerging sector in digital diagnosis and treatment. Even 6 years after the global development of digital therapy, numerous problems that need to be solved have been identified through research and investigation. Through comparative analysis of the current development status of digital therapy both domestically and internationally, this study proposes opportunities for its development in China from both policy and technology perspectives, as well as corresponding challenges from the perspectives of cognition, classification, and quality. In response to these challenges, it proposes prospects and suggestions for the future development of digital therapy.

[Application of Digital Therapy in Post-operative Rehabilitation of Knee Anterior Cruciate Ligament Reconstruction].

OBJECTIVE: Digital therapy is important in treating motor system disease. The outcome of digital therapy in post-operative rehabilitation of knee anterior cruciate ligament (ACL) reconstruction is assessed. METHODS: 142 patients are treated with digital rehabilitation therapy after ACL reconstruction. Patients' pain score, joint motion, lower limb function score, anxiety score are statistically analyzed. Patients' satisfaction, device usage and adverse events are documented. RESULTS: At post-operative 1st day, 8th weeks, 12th weeks, pain score are 4, 2, 1, knee joint range of motion are 55°, 110°, 143°, lower limb function score are 18, 56, 76, anxiety score are 32.5, 26, 23.5 respectively. Patients' satisfaction are 9.4. Mean duration of device usage is (177.6±38.0) minutes per week. Rehabilitation-related and device-related adverse event does not happen. CONCLUSIONS: Digital therapy promotes post-operative rehabilitation after ACL reconstruction.

Screening and assessment for post-acute COVID-19 syndrome (PACS), guidance by personal pilots and support with individual digital trainings within intersectoral care: a study protocol of a randomized controlled trial.

BACKGROUND: Because the clinical patterns and symptoms that persist after a COVID-19 infection are diverse, a diagnosis of post-acute COVID-19 syndrome (PACS) is difficult to implement. The current research project therefore aims to evaluate the feasibility and the practicability of a comprehensive, interdisciplinary, and cross-sectoral treatment program consisting of a low-threshold online screening and holistic assessment for PACS. Furthermore, it aims to evaluate digital interventions and the use of so-called personal guides that may help to facilitate the recovery of PACS. METHODS: This German study consists of a low-threshold online screening for PACS where positively screened participants will be supported throughout by personal pilots. The personal pilots are aimed at empowering patients and helping them to navigate through the study and different treatment options. Patients will then be randomly assigned either to an intervention group (IG) or an active control group (ACG). The IG will receive a comprehensive assessment of physiological and psychological functioning to inform future treatment. The ACG does not receive the assessment but both groups will receive a treatment consisting of an individual digital treatment program (digital intervention platform and an intervention via a chatbot). This digital intervention is based on the needs identified during the assessment for participants in the IG. Compared to that, the ACG will receive a more common digital treatment program aiming to reduce PACS symptoms. Importantly, a third comparison group (CompG) will be recruited that does not receive any treatment. A propensity score matching will take place, ensuring comparability between the participants. Primary endpoints of the study are symptom reduction and return to work. Secondary outcomes comprise, for example, social participation and activities in daily life. Furthermore, the feasibility and applicability of the online screening tool, the holistic assessment, digital trainings, and personal pilots will be evaluated. DISCUSSION: This is one of the first large-scale studies to improve the diagnosis and the care of patients with PACS by means of empowerment. It is to be evaluated whether the methods utilized can be used for the German and international population. Trial registration ClinicalTrials.gov Identifier: NCT05238415; date of registration: February 14, 2022.

Telerehabilitation of acute musculoskeletal multi-disorders: prospective, single-arm, interventional study.

BACKGROUND: Acute musculoskeletal (MSK) pain is very common and associated with impaired productivity and high economic burden. Access to timely and personalized, evidence-based care is key to improve outcomes while reducing healthcare expenditure. Digital interventions can facilitate access and ensure care scalability. OBJECTIVE: Present the feasibility and results of a fully remote digital care program (DCP) for acute MSK conditions affecting several body areas. METHODS: Interventional single-arm study of individuals applying for digital care programs for acute MSK pain. Primary outcome was the mean change between baseline and end-of-program in self-reported Numerical Pain Rating Scale (NPRS) score and secondary outcomes were change in analgesic consumption, intention to undergo surgery, anxiety (GAD-7), depression (PHQ-9), fear-avoidance beliefs (FABQ-PA), work productivity (WPAI-GH) and engagement. RESULTS: Three hundred forty-three patients started the program, of which 300 (87.5%) completed the program. Latent growth curve analysis (LGCA) revealed that changes in NPRS between baseline and end-of-program were both statistically (p < 0.001) and clinically significant: 64.3% reduction (mean - 2.9 points). Marked improvements were also noted in all secondary outcomes: 82% reduction in medication intake, 63% reduction in surgery intent, 40% in fear-avoidance beliefs, 54% in anxiety, 58% in depression and 79% recovery in overall productivity. All outcomes had steeper improvements in the first 4 weeks, which paralleled higher engagement in this period (3.6 vs 3.2 overall weekly sessions, p < 0.001). Mean patient satisfaction score was 8.7/10 (SD 1.26). STRENGTHS AND LIMITATIONS: This is the first longitudinal study demonstrating the feasibility of a DCP for patients with acute MSK conditions involving several body areas. Major strengths of this study are the large sample size, the wide range of MSK conditions studied, the breadth of outcomes measured, and the very high retention rate and adherence level. The major limitation regards to the absence of a control group. CONCLUSIONS: We observed very high completion and engagement rates, as well as clinically relevant changes in all health-related outcomes and productivity recovery. We believe this DCP holds great potential in the delivery of effective and scalable MSK care. TRIAL REGISTRATION: NCT, NCT04092946 . Registered 17/09/2019.

Racial and Ethnic Differences in Outcomes of a 12-Week Digital Rehabilitation Program for Musculoskeletal Pain: Prospective Longitudinal Cohort Study.

BACKGROUND: Musculoskeletal (MSK) pain disproportionately affects people from different ethnic backgrounds through higher burden and less access to care. Digital care programs (DCPs) can improve access and help reduce inequities. However, the outcomes of such programs based on race and ethnicity have yet to be studied. OBJECTIVE: We aimed to assess the impact of race and ethnicity on engagement and outcomes in a multimodal DCP for MSK pain. METHODS: This was an ad hoc analysis of an ongoing decentralized single-arm investigation into engagement and clinical-related outcomes after a multimodal DCP in patients with MSK conditions. Patients were stratified by self-reported racial and ethnic group, and their engagement and outcome changes between baseline and 12 weeks were compared using latent growth curve analysis. Outcomes included program engagement (number of sessions), self-reported pain scores, likelihood of surgery, Generalized Anxiety Disorder 7-item scale, Patient Health Questionnaire 9-item, and Work Productivity and Activity Impairment. A minimum clinically important difference (MCID) of 30% was calculated for pain, and multivariable logistic regression was performed to evaluate race as an independent predictor of meeting the MCID. RESULTS: A total of 6949 patients completed the program: 65.5% (4554/6949) of them were non-Hispanic White, 10.8% (749/6949) were Black, 9.7% (673/6949) were Asian, 9.2% (636/6949) were Hispanic, and 4.8% (337/6949) were of other racial or ethnic backgrounds. The population studied was diverse and followed the proportions of the US population. All groups reported high engagement and satisfaction, with Hispanic and Black patients ranking first among satisfaction despite lower engagement. Black patients had a higher likelihood to drop out (odds ratio [OR] 1.19, 95% CI 1.01-1.40, P=.04) than non-Hispanic White patients. Hispanic and Black patients reported the highest level of pain, surgical intent, work productivity, and impairment in activities of daily living at baseline. All race groups showed a significant improvement in all outcomes, with Black and Hispanic patients reporting the greatest improvements in clinical outcomes. Hispanic patients also had the highest response rate for pain (75.8%) and a higher OR of meeting the pain MCID (OR 1.74, 95% CI 1.24-2.45, P=.001), when compared with non-Hispanic White patients, independent of age, BMI, sex, therapy type, education level, and employment status. No differences in mental health outcomes were found between race and ethnic groups. CONCLUSIONS: This study advocates for the utility of a DCP in improving access to MSK care and promoting health equity. Engagement and satisfaction rates were high in all the groups. Black and Hispanic patients had higher MSK burden at baseline and lower engagement but also reported higher improvements, with Hispanic patients presenting a higher likelihood of pain improvement.

Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint.

The ability to objectively measure aspects of performance and behavior is a fundamental pillar of digital health, enabling digital wellness products, decentralized trial concepts, evidence generation, digital therapeutics, and more. Emerging multimodal technologies capable of measuring several modalities simultaneously and efforts to integrate inputs across several sources are further expanding the limits of what digital measures can assess. Experts from the field of digital health were convened as part of a multi-stakeholder workshop to examine the progress of multimodal digital measures in two key areas: detection of disease and the measurement of meaningful aspects of health relevant to the quality of life. Here we present a meeting report, summarizing key discussion points, relevant literature, and finally a vision for the immediate future, including how multimodal measures can provide value to stakeholders across drug development and care delivery, as well as three key areas where headway will need to be made if we are to continue to build on the encouraging progress so far: collaboration and data sharing, removal of barriers to data integration, and alignment around robust modular evaluation of new measurement capabilities.

Artificial Intelligence and Chatbots in Psychiatry.

The utilization of artificial intelligence (AI) in psychiatry has risen over the past several years to meet the growing need for improved access to mental health solutions. Additionally, shortages of mental health providers during the COVID-19 pandemic have continued to exacerbate the burden of mental illness worldwide. AI applications already in existence include those enabled to assist with psychiatric diagnoses, symptom tracking, disease course prediction, and psychoeducation. Modalities of AI mental health care delivery include availability through the internet, smartphone applications, and digital gaming. Here we review emerging AI-based interventions in the form of chat and therapy bots, specifically conversational applications that teach the user emotional coping mechanisms and provide support for people with communication difficulties, computer generated images of faces that form the basis of avatar therapy, and intelligent animal-like robots with new advances in digital psychiatry. We discuss the implications of incorporating AI chatbots into clinical practice and offer perspectives on how these AI-based interventions will further impact the field of psychiatry.

The digital divide: factors impacting on uptake of remote therapy in a South London psychological therapy service for people with psychosis.

BACKGROUND: Remote therapy promises a cost-effective way of increasing delivery of psychological-therapy in underserved populations. However, research shows a "digital divide", with some groups experiencing digital exclusion. AIMS: To assess whether technology, accessibility, and demographic factors influence remote therapy uptake among individuals with psychosis, and whether demographic factors are associated with digital exclusion. METHODS: Remote therapy uptake and demographics were assessed in people (n = 51) within a psychology-led service for psychosis, using a survey of access to digital hardware, data and private space. RESULTS: The majority of individuals had access to digital devices, but 29% did not meet minimum requirements for remote therapy. Nineteen (37%) individuals declined remote therapy. Those who accepted were significantly younger and more likely to have access to technology than those who declined. The mean age of those with access to smartphones and large screen devices was younger than those without access. CONCLUSIONS: A subgroup of people with psychosis face barriers to remote therapy and a significant minority are digitally excluded. Older age is a key factor influencing remote therapy uptake, potentially related to less access to digital devices. Services must minimize exclusion through provision of training, hardware and data, whilst promoting individual choice.

Brief Online Cognitive Behavioural Intervention for Dysfunctional Worry Related to the COVID-19 Pandemic: A Randomised Controlled Trial.

INTRODUCTION: Worries about the immediate and long-term consequences of the COVID-19 pandemic may for some individuals develop into pervasive worry that is disproportionate in its intensity or duration and significantly interferes with everyday life. OBJECTIVE: The aim of this study was to investigate if a brief self-guided, online psychological intervention can reduce the degree of dysfunctional worry related to the COVID-19 pandemic and associated symptoms. METHODS: 670 adults from the Swedish general population reporting daily uncontrollable worry about CO-VID-19 and its possible consequences (e.g., illness, death, the economy, one's family) were randomised (1:1 ratio) to a 3-week self-guided, online cognitive behavioural intervention targeting dysfunctional COVID-19 worry and associated symptoms, or a waiting list of equal duration. The primary outcome measure was a COVID-19 adapted version of the Generalised Anxiety Disorder 7-item scale administered at baseline and weeks 1-3 (primary endpoint). Follow-up assessments were conducted 1 month after treatment completion. The trial was registered on ClinicalTrials.gov (NCT04341922) before inclusion of the first participant. RESULTS: The main pre-specified intention-to-treat analysis indicated significant reductions in COVID-19-related worry for the intervention group compared to the waiting list (ß = 1.14, Z = 9.27, p < 0.001), corresponding to a medium effect size (bootstrapped d = 0.74 [95% CI: 0.58-0.90]). Improvements were also seen on all secondary measures, including mood, daily functioning, insomnia, and intolerance of uncertainty. Participant satisfaction was high. No serious adverse events were recorded. CONCLUSIONS: A brief digital and easily scalable self-guided psychological intervention can significantly reduce dysfunctional worry and associated behavioural symptoms related to the COVID-19 pandemic.

Virtual Reality Smartphone-Based Intervention for Smoking Cessation: Pilot Randomized Controlled Trial on Initial Clinical Efficacy and Adherence.

BACKGROUND: Obstacles to current tobacco cessation programs include limited access and adherence to effective interventions. Digital interventions offer a great opportunity to overcome these difficulties, yet virtual reality has not been used as a remote and self-administered tool to help increase adherence and effectiveness of digital interventions for tobacco cessation. OBJECTIVE: This study aimed to evaluate participant adherence and smoking cessation outcomes in a pilot randomized controlled trial of the digital intervention Mindcotine (MindCotine Inc) using a self-administered treatment of virtual reality combined with mindfulness. METHODS: A sample of 120 participants was recruited in the city of Buenos Aires, Argentina (mean age 43.20 years, SD 9.50; 57/120, 47.5% female). Participants were randomly assigned to a treatment group (TG), which received a self-assisted 21-day program based on virtual reality mindful exposure therapy (VR-MET) sessions, daily surveys, and online peer-to-peer support moderated by psychologists, or a control group (CG), which received the online version of the smoking cessation manual from the Argentine Ministry of Health. Follow-up assessments were conducted by online surveys at postintervention and 90-day follow-up. The primary outcome was self-reported abstinence at postintervention, with missing data assumed as still smoking. Secondary outcomes included sustained abstinence at 90-day follow-up, adherence to the program, and readiness to quit. RESULTS: Follow-up rates at day 1 were 93% (56/60) for the TG and 100% (60/60) for the CG. At postintervention, the TG reported 23% (14/60) abstinence on that day compared with 5% (3/60) in the CG. This difference was statistically significant (χ21=8.3; P=.004). The TG reported sustained abstinence of 33% (20/60) at 90 days. Since only 20% (12/60) of participants in the CG completed the 90-day follow-up, we did not conduct a statistical comparison between groups at this follow-up time point. Among participants still smoking at postintervention, the TG was significantly more ready to quit compared to the CG (TG: mean 7.71, SD 0.13; CG: mean 7.16, SD 0.13; P=.005). A total of 41% (23/56) of participants completed the treatment in the time frame recommended by the program. CONCLUSIONS: Results provide initial support for participant adherence to and efficacy of Mindcotine and warrant testing the intervention in a fully powered randomized trial. However, feasibility of trial follow-up assessment procedures for control group participants needs to be improved. Further research is needed on the impact of VR-MET on long-term outcomes. TRIAL REGISTRATION: ISRCTN Registry ISRCTN50586181; http://www.isrctn.com/ISRCTN50586181.

Toward Continuous Social Phenotyping: Analyzing Gaze Patterns in an Emotion Recognition Task for Children With Autism Through Wearable Smart Glasses.

BACKGROUND: Several studies have shown that facial attention differs in children with autism. Measuring eye gaze and emotion recognition in children with autism is challenging, as standard clinical assessments must be delivered in clinical settings by a trained clinician. Wearable technologies may be able to bring eye gaze and emotion recognition into natural social interactions and settings. OBJECTIVE: This study aimed to test: (1) the feasibility of tracking gaze using wearable smart glasses during a facial expression recognition task and (2) the ability of these gaze-tracking data, together with facial expression recognition responses, to distinguish children with autism from neurotypical controls (NCs). METHODS: We compared the eye gaze and emotion recognition patterns of 16 children with autism spectrum disorder (ASD) and 17 children without ASD via wearable smart glasses fitted with a custom eye tracker. Children identified static facial expressions of images presented on a computer screen along with nonsocial distractors while wearing Google Glass and the eye tracker. Faces were presented in three trials, during one of which children received feedback in the form of the correct classification. We employed hybrid human-labeling and computer vision-enabled methods for pupil tracking and world-gaze translation calibration. We analyzed the impact of gaze and emotion recognition features in a prediction task aiming to distinguish children with ASD from NC participants. RESULTS: Gaze and emotion recognition patterns enabled the training of a classifier that distinguished ASD and NC groups. However, it was unable to significantly outperform other classifiers that used only age and gender features, suggesting that further work is necessary to disentangle these effects. CONCLUSIONS: Although wearable smart glasses show promise in identifying subtle differences in gaze tracking and emotion recognition patterns in children with and without ASD, the present form factor and data do not allow for these differences to be reliably exploited by machine learning systems. Resolving these challenges will be an important step toward continuous tracking of the ASD phenotype.

Effects of a 12-Week Digital Care Program for Chronic Knee Pain on Pain, Mobility, and Surgery Risk: Randomized Controlled Trial.

BACKGROUND: Chronic knee pain, most commonly caused by knee osteoarthritis, is a prevalent condition which in most cases can be effectively treated through conservative, non-surgical care involving exercise therapy, education, psychosocial support, and weight loss. However, most people living with chronic knee pain do not receive adequate care, leading to unnecessary use of opiates and surgical procedures. OBJECTIVE: Assess the efficacy of a remotely delivered digital care program for chronic knee pain. METHODS: We enrolled 162 participants into a randomized controlled trial between January and March 2017. Participants were recruited from participating employers using questionnaires for self-assessment of their knee pain, and randomized into treatment (n=101) and control (n=61) groups. Participants in the treatment group were enrolled in the Hinge Health digital care program for chronic knee pain. This is a remotely delivered, home-based 12-week intervention that includes sensor-guided exercise therapy, education, cognitive behavioral therapy, weight loss, and psychosocial support through a personal coach and team-based interactions. The control group received three education pieces regarding self-care for chronic knee pain. Both groups had access to treatment-as-usual. The primary outcome was the Knee Injury and Osteoarthritis Outcome Score (KOOS) Pain subscale and KOOS Physical Function Shortform (KOOS-PS). Secondary outcomes were visual analog scales (VAS) for pain and stiffness respectively, surgery intent, and self-reported understanding of the condition and treatment options. Outcome measures were analyzed by intention to treat (excluding 7 control participants who received the digital care program due to administrative error) and per protocol. RESULTS: In an intent-to-treat analysis the digital care program group had a significantly greater reduction in KOOS Pain compared to the control group at the end of the program (greater reduction of 7.7, 95% CI 3.0 to 12.3, P=.002), as well as a significantly greater improvement in physical function (7.2, 95% CI 3.0 to 11.5, P=.001). This was also reflected in the secondary outcomes VAS pain (12.3, 95% CI 5.4 to 19.1, P<.001) and VAS stiffness (13.4, 95% CI 5.6 to 21.1, P=.001). Participants' self-reported likelihood (from 0% to 100%) of having surgery also reduced more strongly in the digital care program group compared to the control group over the next 1 year (-9.4 percentage points, pp, 95% CI -16.6 to -2.2, P=.01), 2 years (-11.3 pp, 95% CI -20.1 to -2.5, P=.01), and 5 years (-14.6 pp, 95% CI -23.6 to -5.5, P=.002). Interest in surgery (from 0 to 10) also reduced more so in the digital care program compared to control group (-1.0, 95% CI -1.7 to -0.2, P=.01). Participants' understanding of the condition and treatment options (on a scale from 0 to 4) increased more substantially for participants in the digital care program than those in the control group (0.9, 95% CI 0.6 to 1.3, P<.001). In an analysis on participants that completed the intervention (per protocol analysis) all primary and secondary outcomes remained significant at greater effect magnitudes compared to intention to treat, with those completing the program showing a 61% (95% CI 48 to 74) reduction in VAS pain compared to 21% (95% CI 5 to 38) in the control group (P<.001). Accounting for the cost of administering the program, we estimate net cost savings on surgery alone of US $4340 over 1 year and $7900 over 5 years for those participants completing the digital care program compared to those in the control group receiving treatment-as-usual. In an exploratory subgroup analysis including only participants exhibiting clinical symptoms of osteoarthritis the program proved equally effective. CONCLUSIONS: This trial provides strong evidence that a comprehensive 12-week digital care program for chronic knee pain, including osteoarthritis, yields significantly improved outcomes for pain, physical function, stiffness, surgery risk, and understanding of the condition, compared to a control group. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN) 13307390; http://www.isrctn.com/ISRCTN13307390 (Archived by WebCite at http://www.webcitation.org/6ycwjGL73).