How New Technologies Can Improve Prediction, Assessment, and Intervention in Obsessive-Compulsive Disorder (e-OCD): Review

Personalized exposure and experience sampling method feedback versus exposure as usual for obsessive-compulsive disorder: a study protocol for a randomized controlled trial

BACKGROUND

Patients with obsessive-compulsive disorder (OCD) suffer from repetitive fearful intrusions which they try to neutralize by performing compulsions. OCD is considered to be the most resistant anxiety disorder with a remission rate of only 53% after a year of an evidence-based treatment. Therefore, it remains an obligation to develop and investigate more effective treatment interventions. This study aims to compare personalized exposure with response prevention (ERP) using experience sampling methodology-based feedback to ERP as usual in patients with OCD. Personalized exposure will be provided screen-to-screen in an ecologically valid (real time and real place) context by means of a smartphone application. This app will also be used to collect both objective and subjective data by means of experience sampling methodology (ESM). This ESM data will be used to identify triggers and protective factors for symptom severity, provide personalized feedback and optimize the effect of ERP. The primary goal of this RCT is to compare the effectiveness of personalized ERP to ERP as usual in the traditional context of a therapist's room in patients with OCD in OCD symptom severity, as well as differences in quality of life, depressive symptoms and anxiety states. Since both self-efficacy and experiential avoidance are known to influence symptom severity in OCS, a secondary goal is to examine if a possible treatment effect is mediated by self-efficacy or experiential avoidance.

METHODS

This study involves a randomized controlled trial with 20 weekly sessions by 2 groups (ERP as usual versus personalized ERP), repeated measurements at baseline (T0), 5 weeks of treatment (T1), 10 weeks of treatment (T2), 15 weeks of treatment (T3), posttest at 20 weeks (T4), 6 weeks follow-up (T5), 3 months follow-up (T6), 6 months follow-up (T7) and a year follow-up (T8). A hundred and sixty patients with an OCD diagnosis according to DSM-5 criteria will participate. Half of the group will receive exposure with response prevention as usual, the other half will receive personalized exposure with response prevention with a smartphone application and personalized feedback sessions based on experience sampling data. Multilevel mixed modelling analysis will be used to investigate differences in treatment effect, as well as differences in quality of life, depressive symptoms and anxiety states. We will use the macro of Preacher and Hayes and apply bootstrapping methods to assess the possible mediating effect of changes in self-efficacy and experiential avoidance on subsequent treatment effects.

DISCUSSION

This randomized controlled trial is the first to assess the influence of delivering ERP through video-calling and the use of an ESM intervention on the symptom severity of OCD. Since the global pandemic COVID-19, the use of video-calling to deliver psychological treatments has become more common, increasing the relevance of this study.

TRIAL REGISTRATION

ICTRP Trial NL8254. Registered on 2019-12-24.

Predicting Obsessive-Compulsive Disorder Events in Children and Adolescents in the Wild using a Wearable Biosensor (Wrist Angel): Protocol for the Analysis Plan of a Nonrandomized Pilot Study

BACKGROUND

Physiological signals such as heart rate and electrodermal activity can provide insight into an individual's mental state, which are invaluable information for mental health care. Using recordings of physiological signals from wearable devices in the wild can facilitate objective monitoring of symptom severity and evaluation of treatment progress.

OBJECTIVE

We designed a study to evaluate the feasibility of predicting obsessive-compulsive disorder (OCD) events from physiological signals recorded using wrist-worn devices in the wild. Here, we present an analysis plan for the study to document our a priori hypotheses and increase the robustness of the findings of our planned study.

METHODS

In total, 18 children and adolescents aged between 8 and 16 years were included in this study. Nine outpatients with an OCD diagnosis were recruited from a child and adolescent mental health center. Nine youths without a psychiatric diagnosis were recruited from the catchment area. Patients completed a clinical interview to assess OCD severity, types of OCD, and number of OCD symptoms in the clinic. Participants wore a biosensor on their wrist for up to 8 weeks in their everyday lives. Patients were asked to press an event tag button on the biosensor when they were stressed by OCD symptoms. Participants without a psychiatric diagnosis were asked to press this button whenever they felt really scared. Before and after the 8-week observation period, participants wore the biosensor under controlled conditions of rest and stress in the clinic. Features are extracted from 4 different physiological signals within sliding windows to predict the distress event logged by participants during data collection. We will test the prediction models within participants across time and multiple participants. Model selection and estimation using 2-layer cross-validation are outlined for both scenarios.

RESULTS

Participants were included between December 2021 and December 2022. Participants included 10 female and 8 male participants with an even sex distribution between groups. Patients were aged between 10 and 16 years, and adolescents without a psychiatric diagnosis were between the ages of 8 and 16 years. Most patients had moderate to moderate to severe OCD, except for 1 patient with mild OCD.

CONCLUSIONS

The strength of the planned study is the investigation of predictions of OCD events in the wild. Major challenges of the study are the inherent noise of in-the-wild data and the lack of contextual knowledge associated with the recorded signals. This preregistered analysis plan discusses in detail how we plan to address these challenges and may help reduce interpretation bias of the upcoming results. If the obtained results from this study are promising, we will be closer to automated detection of OCD events outside of clinical experiments. This is an important tool for the assessment and treatment of OCD in youth.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05064527; https://clinicaltrials.gov/study/NCT05064527.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/48571.

Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review

BACKGROUND

Smartphones and wearable biosensors can continuously and passively measure aspects of behavior and physiology while also collecting data that require user input. These devices can potentially be used to monitor symptom burden; estimate diagnosis and risk for relapse; predict treatment response; and deliver digital interventions in patients with obsessive-compulsive disorder (OCD), a prevalent and disabling psychiatric condition that often follows a chronic and fluctuating course and may uniquely benefit from these technologies.

OBJECTIVE

Given the speed at which mobile and wearable technologies are being developed and implemented in clinical settings, a continual reappraisal of this field is needed. In this scoping review, we map the literature on the use of wearable devices and smartphone-based devices or apps in the assessment, monitoring, or treatment of OCD.

METHODS

In July 2022 and April 2023, we conducted an initial search and an updated search, respectively, of multiple databases, including PubMed, Embase, APA PsycINFO, and Web of Science, with no restriction on publication period, using the following search strategy: ("OCD" OR "obsessive" OR "obsessive-compulsive") AND ("smartphone" OR "phone" OR "wearable" OR "sensing" OR "biofeedback" OR "neurofeedback" OR "neuro feedback" OR "digital" OR "phenotyping" OR "mobile" OR "heart rate variability" OR "actigraphy" OR "actimetry" OR "biosignals" OR "biomarker" OR "signals" OR "mobile health").

RESULTS

We analyzed 2748 articles, reviewed the full text of 77 articles, and extracted data from the 25 articles included in this review. We divided our review into the following three parts: studies without digital or mobile intervention and with passive data collection, studies without digital or mobile intervention and with active or mixed data collection, and studies with a digital or mobile intervention.

CONCLUSIONS

Use of mobile and wearable technologies for OCD has developed primarily in the past 15 years, with an increasing pace of related publications. Passive measures from actigraphy generally match subjective reports. Ecological momentary assessment is well tolerated for the naturalistic assessment of symptoms, may capture novel OCD symptoms, and may also document lower symptom burden than retrospective recall. Digital or mobile treatments are diverse; however, they generally provide some improvement in OCD symptom burden. Finally, ongoing work is needed for a safe and trusted uptake of technology by patients and providers.

Early Identification and Intervention in Pediatric Obsessive-Compulsive Disorder

Obsessive-compulsive disorder (OCD) is a psychiatric disorder characterized by persistent thoughts with subsequent repetitive behaviors. Interventions that are effective for adult OCD cannot simply be generalized to pediatric OCD, since OCD in children and adolescents usually has a different clinical presentation, etiology and course from adult OCD. Delayed and inadequate treatment is associated with a worse prognosis, making the need for early identification and intervention in pediatric OCD very urgent. In this paper, we reflected on the current constraints that make early interventions for pediatric OCD unpromoted and reviewed the approaches with potential application for early identification and early intervention in pediatric OCD, categorized by three-level prevention stages corresponding to a clinical staging model. Since the etiology of pediatric OCD is still unclear, primary prevention is most lacking, and early interventions for pediatric OCD are currently focused on the secondary prevention stage, which aims to prevent the conversion of obsessive-compulsive symptoms into full-blown OCD; tertiary prevention mostly focuses on the alleviation of mild to moderate OCD, while interventions for co-morbidities are still in their infancy. We closed by considering the important research questions on this topic.

Development of a protocol for videoconferencing-based exposure and response prevention treatment of obsessive-compulsive disorder during the COVID-19 pandemic

BACKGROUND

The existing literature indicates that psychotherapeutic treatment, especially exposure and response prevention (ERP) is efficacious in treating obsessive-compulsive disorder (OCD). The coronavirus disease 2019 pandemic adversely impacted many patients with OCD and disrupted their usual treatment. Moreover, the pandemic forced a global switch to telemental health (TMH) services to maintain the standards and continuity of care. Consequently, clinicians are increasingly using TMH-based psychotherapeutic treatments to treat OCD. However, several challenges have made it difficult for them to implement these treatments in the changed circumstances imposed by the pandemic.

AIM

To describe the formulation, implementation, feasibility, and usefulness of videoconferencing-based ERP (VC-ERP) treatment for OCD during the coronavirus disease 2019 pandemic.

METHODS

This prospective, observational study was conducted in the psychiatric unit of a multi-specialty hospital in north India over 12 mo (July 2020-June 2021). All patients with OCD were assessed using the home-based TMH services of the department. The VC-ERP protocol for OCD was the outcome of weekly Zoom meetings with a group of clinicians involved in administering the treatment. After a systematic evaluation of the available treatment options, an initial protocol for delivering VC-ERP was developed. Guidelines for clinicians and educational materials for patients and their families were prepared. The protocol was implemented among patients with OCD attending the TMH services, and their progress was monitored. The weekly meetings were used to upgrade the protocol to meet the needs of all stakeholders. Feasibility and efficacy outcomes were examined.

RESULTS

All patients were diagnosed with OCD as a primary or a comorbid condition according to the International Classification of Diseases, 10^th version criteria. Out of 115 patients who attended the services during the study period, 37 were excluded from the final analysis. Of the remaining 78 patients, VC-ERP was initiated in 43 patients. Six patients dropped out, and three were hospitalized for inpatient ERP. Eleven patients have completed the full VC-ERP treatment. One patient completed the psychoeducation part of the protocol. VC-ERP is ongoing in 22 patients. The protocol for VC-ERP treatment was developed and upgraded online. A large proportion of the eligible patients (n = 34/43; 79%) actively engaged in the VC-ERP treatment. Drop-out rates were low (n = 6/43; 14%). Satisfaction with the treatment was adequate among patients, caregivers, and clinicians. Apart from hospitalization in 3 patients, there were no other adverse events. Hybrid care and stepped care approaches could be incorporated into the VC-ERP protocol. Therefore, the feasibility of VC-ERP treatment in terms of operational viability, service utilization, service engagement, need for additional in-person services, frequency of adverse events, and user satisfaction was adequate. The VC-ERP treatment was found to be efficacious in the 11 patients who had completed the full treatment. Significant reductions in symptoms and maintenance of treatment gains on follow-up were observed.

CONCLUSION

This study provided preliminary evidence for the feasibility and usefulness of VC-ERP in the treatment of OCD. The results suggest that VC-ERP can be a useful option in resource-constrained settings.

Psychotherapies and digital interventions for OCD in adults: What do we know, what do we need still to explore?

BACKGROUND

Despite significant advances in the understanding and treatment of obsessive compulsive disorder (OCD), current treatment options are limited in terms of efficacy for symptom remission. Thus, assessing the potential role of iterative or alternate psychotherapies is important. Also, the potential role of digital technologies to enhance the accessibility of these therapies, should not be underestimated. We also need to embrace the idea of a more personalized treatment choice, being cognisant of clinical, genetic and neuroimaging predictors of treatment response.

PROCEDURES

Non-systematic review of current literature on emerging psychological and digital therapies for OCD, as well as of potential biomarkers of treatment response.

FINDINGS

A number of 'third wave' therapies (e.g., Acceptance and Commitment Therapy, Mindfulness-Based Cognitive Therapy) have an emerging and encouraging evidence base in OCD. Other approaches entail employment of elements of other psychotherapies such as Dialectical Behaviour Therapy; or trauma-focussed therapies such as Eye Movement Desensitisation and Reprocessing, and Imagery Rescripting and Narrative Therapy. Further strategies include Danger Ideation Reduction Therapy and Habit Reversal. For these latter approaches, large-scale randomised controlled trials are largely lacking, and the precise role of these therapies in treating people with OCD, remains to be clarified. A concentrated 4-day program (the Bergen program) has shown promising short- and long-term results. Exercise, music, and art therapy have not been adequately tested in people with OCD, but may have an adjunctive role. Digital technologies are being actively investigated for enhancing reach and efficacy of psychological therapies for OCD. Biomarkers, including genetic and neuroimaging, are starting to point to a future with more 'personalised medicine informed' treatment strategizing for OCD.

CONCLUSIONS

There are a number of potential psychological options for the treatment of people with OCD who do not respond adequately to exposure/response prevention or cognitive behaviour therapy. Adjunctive exercise, music, and art therapy might be useful, albeit the evidence base for these is very small. Consideration should be given to different ways of delivering such interventions, including group-based, concentrated, inpatient, or with outreach, where appropriate. Digital technologies are an emerging field with a number of potential applications for aiding the treatment of OCD. Biomarkers for treatment response determination have much potential capacity and deserve further empirical testing.

Virtual reality in the diagnostic and therapy for mental disorders: A systematic review

BACKGROUND

Virtual reality (VR) technologies are playing an increasingly important role in the diagnostics and treatment of mental disorders.

OBJECTIVE

To systematically review the current evidence regarding the use of VR in the diagnostics and treatment of mental disorders.

DATA SOURCE

Systematic literature searches via PubMed (last literature update: 9^th of May 2022) were conducted for the following areas of psychopathology: Specific phobias, panic disorder and agoraphobia, social anxiety disorder, generalized anxiety disorder, posttraumatic stress disorder (PTSD), obsessive-compulsive disorder, eating disorders, dementia disorders, attention-deficit/hyperactivity disorder, depression, autism spectrum disorder, schizophrenia spectrum disorders, and addiction disorders.

ELIGIBILITY CRITERIA

To be eligible, studies had to be published in English, to be peer-reviewed, to report original research data, to be VR-related, and to deal with one of the above-mentioned areas of psychopathology.

STUDY EVALUATION

For each study included, various study characteristics (including interventions and conditions, comparators, major outcomes and study designs) were retrieved and a risk of bias score was calculated based on predefined study quality criteria.

RESULTS

Across all areas of psychopathology, k = 9315 studies were inspected, of which k = 721 studies met the eligibility criteria. From these studies, 43.97% were considered assessment-related, 55.48% therapy-related, and 0.55% were mixed. The highest research activity was found for VR exposure therapy in anxiety disorders, PTSD and addiction disorders, where the most convincing evidence was found, as well as for cognitive trainings in dementia and social skill trainings in autism spectrum disorder.

CONCLUSION

While VR exposure therapy will likely find its way successively into regular patient care, there are also many other promising approaches, but most are not yet mature enough for clinical application.

REVIEW REGISTRATION

PROSPERO register CRD42020188436.

FUNDING

The review was funded by budgets from the University of Bonn. No third party funding was involved.

Mapping User Engagement in Digital Psychotherapy: An Integrative Engagement Model (Preprint)

BACKGROUND

Digital mental health interventions, such as 2-way and asynchronous messaging therapy, are a growing part of the mental health care treatment ecosystem, yet little is known about how users engage with these interventions over the course of their treatment journeys. User engagement, or client behaviors and therapeutic relationships that facilitate positive treatment outcomes, is a necessary condition for the effectiveness of any digital treatment. Developing a better understanding of the factors that impact user engagement can impact the overall effectiveness of digital psychotherapy. Mapping the user experience in digital therapy may be facilitated by integrating theories from several fields. Specifically, health science's Health Action Process Approach and human-computer interaction's Lived Informatics Model may be usefully synthesized with relational constructs from psychotherapy process-outcome research to identify the determinants of engagement in digital messaging therapy.

OBJECTIVE

This study aims to capture insights into digital therapy users' engagement patterns through a qualitative analysis of focus group sessions. We aimed to synthesize emergent intrapersonal and relational determinants of engagement into an integrative framework of engagement in digital therapy.

METHODS

A total of 24 focus group participants were recruited to participate in 1 of 5 synchronous focus group sessions held between October and November 2021. Participant responses were coded by 2 researchers using thematic analysis.

RESULTS

Coders identified 10 relevant constructs and 24 subconstructs that can collectively account for users' engagement and experience trajectories in the context of digital therapy. Although users' engagement trajectories in digital therapy varied widely, they were principally informed by intrapsychic factors (eg, self-efficacy and outcome expectancy), interpersonal factors (eg, the therapeutic alliance and its rupture), and external factors (eg, treatment costs and social support). These constructs were organized into a proposed Integrative Engagement Model of Digital Psychotherapy. Notably, every participant in the focus groups indicated that their ability to connect with their therapist was among the most important factors that were considered in continuing or terminating treatment.

CONCLUSIONS

Engagement in messaging therapy may be usefully approached through an interdisciplinary lens, linking constructs from health science, human-computer interaction studies, and clinical science in an integrative engagement framework. Taken together, our results suggest that users may not view the digital psychotherapy platform itself as a treatment so much as a means of gaining access to a helping provider, that is, users did not see themselves as engaging with a platform but instead viewed their experience as a healing relationship. The findings of this study suggest that a better understanding of user engagement is crucial for enhancing the effectiveness of digital mental health interventions, and future research should continue to explore the underlying factors that contribute to engagement in digital mental health interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04507360; https://clinicaltrials.gov/ct2/show/NCT04507360.

On the automatic detection of enacted compulsive hand washing using commercially available wearable devices

BACKGROUND

Compulsive hand washing is one of the most frequent compulsions and includes highly ritualized, repetitive hand motions. Developing an algorithm that can automatically detect compulsive washing with off-the-shelf wearable devices is a first step toward developing more sophisticated sensor-based assessments and micro-interventions that might ultimately supplement cognitive behavioral therapy for obsessive-compulsive disorder (OCD).

OBJECTIVE

The main objective was to establish whether enacted compulsive hand washing can be distinguished from routine hand washing. This distinction will inform future research on the development of an algorithm that can automatically detect compulsive hand washing.

METHOD

Twenty-one participants were trained individually to wash their hands according to 1 of 5 scripted hand-washing procedures that were based on descriptions of pathological compulsive washes and additionally to wash their hands as they usually would, while wearing a smartwatch. Washes were video recorded to obtain validation data. To generate a baseline model, we opted to extract well-known features only (mean and variance of each sensor axis). We tested four classification models: linear support vector machine (SVM), SVM with radial basis functions, random forest (RF), and naive Bayes (NB). Leave-one-subject-out cross-validation was applied to gather F1, specificity, and sensitivity scores.

RESULTS

The best-performing parameters were a classification window duration of 10 s, with a mean-variance feature set calculated from quaternions, rate of turn, and magnetic flux measurements. The detection performance varied with the particular enacted compulsive hand wash (F1 range: 0.65-0.87). Overall, enacted compulsive and routine hand washing could be distinguished with an F1 score of 79% (user independent), a sensitivity of 84%, and a specificity of 30%.

CONCLUSIONS

Our analysis of the sensor data demonstrates that enacted compulsive hand washing could be distinguished from routine hand washing with acceptable sensitivity. However, specificity was low. This study is a starting point for a series of follow-ups, including the application in individuals diagnosed with OCD.

Heart rate variability in obsessive compulsive disorder in comparison to healthy controls and as predictor of treatment response

OBJECTIVE

Obsessive compulsive disorder (OCD) has a large impact on the quality of life of patients. It often takes years to get the right diagnosis and to receive treatment. Therefore, biomarkers that could inform the diagnostic process and provide information on response or non-response for first line treatment approaches are urgently needed. The aim of this study was to analyze whether (1) heart rate (HR) and heart rate variability (HRV) markers of the autonomous nervous system could distinguish between healthy controls (HC) and patients suffering from OCD and (2) HRV parameters additionally yield useful information to separate therapy-responders from non-responders.

METHODS

A fifteen-minute resting state ECG (electrocardiogram) was recorded from 51 unmedicated OCD patients before treatment and 28 HC. The function of the autonomic nervous system was assessed by using parameters of the HRV. Clinical Global Impression (CGI) scores served as baseline and outcome parameters following three to six months of therapy (cognitive behavioral therapy n = 18, selective-serotonin-reuptake-inhibitor n = 11 or combination n = 22). Differences between patients and HC and responders and non-responders were identified using analysis of covariance (ANCOVAs). Predictive values were calculated following binary regression modelling and receiver operating characteristics (ROC).

RESULTS

OCD patients revealed a significantly higher HR in comparison to HC. Although patients were thus characterized by increased sympathetic and decreased parasympathetic tone, treatment responders exhibited a larger High Frequency Power as a marker for increased parasympathetic activity at baseline. ROC-curves for OCD vs HC and R vs NR showed clinically relevant areas under curve (83%, 88% respectively).

CONCLUSIONS

These results are in line with findings of increased sympathetic and decreased parasympathetic activity in OCD in comparison to healthy subjects. The findings further provide clinically useful information on treatment response in OCD.

SIGNIFICANCE

Results may facilitate the clinical use of electrophysiological markers in OCD.

Self-directed Technology-Based Therapeutic Methods for Adult Patients Receiving Mental Health Services: Systematic Review

BACKGROUND

Technological interventions used to treat illnesses and promote health are grouped under the umbrella term of digital therapeutics. The use of digital therapeutics is becoming increasingly common in mental health. Although many technologies are currently being implemented, research supporting their usability, efficacy, and risk requires further examination, especially for those interventions that can be used without support.

OBJECTIVE

This review aims to identify the evidence-based, self-directed, technology-based methods of care that can be used in adult patients after they are discharged from mental health services. The interventions reviewed are automated with no human input required (either at the patient's or at the technology's end), so the patients can implement them without any support.

METHODS

A systematic review was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PROSPERO (International Prospective Register of Systematic Reviews) guidelines in 3 databases: PubMed, Web of Science, and OVID. The inclusion criteria were self-directed, automated, and technology-based interventions related to mental health, primarily for adults, having a solid evaluation process. The interventions had to be self-directed, in that the participants could use the technology without any external guidance.

RESULTS

We identified 36 papers that met the inclusion criteria: 26 randomized controlled trials, 9 nonrandomized controlled trial quantitative studies, and 1 qualitative study. The technologies used included websites, automated text messaging, phone apps, videos, computer software, and integrated voice response. There were 22 studies focused on internet-based cognitive behavioral therapies as a therapeutic paradigm compared with the waitlist, web-based human-delivered therapy, and other interventions. Among these studies, 14 used paradigms other than the internet-based cognitive behavioral therapy. Of the 8 studies comparing guided and unguided digital care, 3 showed no differences, 3 favored guided interventions, and 2 favored unguided interventions. The research also showed that dropout rates were as high as 80%, citing potential problems with the acceptability of the suggested technologies.

CONCLUSIONS

There is limited research on the efficacy and suitability of self-directed technology-based care options for mental health. Digital technologies have the potential to bridge the gap between ambulatory care and independent living. However, these interventions may need to be developed collaboratively with the users to encourage their acceptability and to avoid high dropout rates.

In Search of Digital Dopamine: How Apps Can Motivate Depressed Patients, a Review and Conceptual Analysis

INTRODUCTION

Depression is highly prevalent and causes considerable suffering and disease burden despite the existence of wide-ranging treatment options. Momentary assessment is a promising tool in the management of psychiatric disorders, and particularly depression. It allows for a real-time evaluation of symptoms and an earlier detection of relapse or treatment efficacy. Treating the motivational and hedonic aspects of depression is a key target reported in the literature, but it is time-consuming in terms of human resources. Digital Applications offer a major opportunity to indirectly regulate impaired motivational circuits through dopaminergic pathways.

OBJECTIVE

The main objective of this review was twofold: (1) propose a conceptual and critical review of the literature regarding the theoretical and technical principles of digital applications focused on motivation in depression, activating dopamine, and (2) suggest recommendations on the relevance of using these tools and their potential place in the treatment of depression.

MATERIAL AND METHODS

A search for words related to "dopamine", "depression", "smartphone apps", "digital phenotype" has been conducted on PubMed.

RESULTS

Ecological momentary interventions (EMIs) differ from traditional treatments by providing relevant, useful intervention strategies in the context of people's daily lives. EMIs triggered by ecological momentary assessment (EMA) are called "Smart-EMI". Smart-EMIs can mimic the "dopamine reward system" if the intervention is tailored for motivation or hedonic enhancement, and it has been shown that a simple reward (such as a digital badge) can increase motivation.

DISCUSSION

The various studies presented support the potential interest of digital health in effectively motivating depressed patients to adopt therapeutic activation behaviors. Finding effective ways to integrate EMIs with human-provided therapeutic support may ultimately yield the most efficient and effective intervention method. This approach could be a helpful tool to increase adherence and motivation.

CONCLUSION

Smartphone apps can motivate depressed patients by enhancing dopamine, offering the opportunity to enhance motivation and behavioral changes, although longer term studies are still needed.

Internet-based cognitive behavioral therapy in children and adolescents with obsessive compulsive disorder: a feasibility study

Cognitive behavioral therapy (CBT) is the first choice of treatment of obsessive–compulsive disorder (OCD) in children and adolescents. However, there is often a lack of access to appropriate treatment close to the home of the patients. An internet-based CBT via videoconferencing could facilitate access to state-of-the-art treatment even in remote areas. The aim of this study was to investigate feasibility and acceptability of this telemedical approach. A total of nine children received 14 sessions of CBT. The first session took place face-to-face, the remaining 13 sessions via videoconference. OCD symptoms were recorded with a smartphone app and therapy materials were made accessible in a data cloud. We assessed diagnostic data before and after treatment and obtained measures to feasibility, treatment satisfaction and acceptability. Outcomes showed high acceptance and satisfaction on the part of patients with online treatment (89%) and that face-to-face therapy was not preferred over an internet-based approach (67%). The majority of patients and their parents classified the quality of treatment as high. They emphasized the usefulness of exposures with response prevention (E/RP) in triggering situations at home. The app itself was rated as easy to operate and useful. In addition to feasibility, a significant decrease in obsessive–compulsive symptoms was also achieved. Internet-based CBT for pediatric OCD is feasible and well received by the patients and their parents. Furthermore, obsessive–compulsive symptomatology decreased in all patients. The results of this study are encouraging and suggest the significance of further research regarding this technology-supported approach, with a specific focus on efficacy.

Trial registration number: Clinical trials AZ53-5400.1-004/44.

The use of virtual reality in assessment and treatment of anxiety and related disorders

In recent years the development of new virtual environments has been qualitatively high and fast at the same time, but the dissemination of virtual reality (VR) in clinical practice is still scarce. The aim of this review is to give an insight into the state of the art of the use of VR as an assessment tool and treatment intervention in anxiety and related disorders as posttraumatic stress disorder and obsessive-compulsive disorders. Besides an overview into the efficacy of VR, a summary will be given on assumed working mechanisms in virtual reality exposure therapy and how this aligns with current theoretical models. Further, it will be discussed how VR is accepted by patients and research into the reluctance of therapist to use this technology during treatment with focus on the therapeutic alliance and how it may be influenced by the use of VR. Finally, we discuss clinical and future issues as, for example, dissemination into clinical practice and what VR has to offer therapists in future. This not only in adult population but as well in younger patients, as young adolescents VR has a great potential as it connects easily with its playful elements to this population and might be a low threshold step to offer treatment or preventive interventions.

Conducting a VR Clinical Trial in the Era of COVID-19

The outbreak of severe acute respiratory syndrome coronavirus 2, also known as Coronavirus Disease 2019 (COVID-19) sparked a global public health pandemic that has impacted every aspect of daily life. Medical research was affected, and many clinical trials were halted to minimize COVID-19 transmission risk and spread while the world navigated this novel virus. Here we describe the relaunch of our virtual reality (VR) pilot clinical trial that uses an in-lab brain and body training program to promote brain health in mid-to-late life older adults, in the era of COVID-19. This case series includes five healthy female participants between 51 and 76 years of age, a subset of a larger VR pilot clinical trial that started pre-pandemic. We developed a revised study protocol based on the Center for Disease Control and World Health Organization guidelines to help manage the spread of COVID-19. Since the limited resumption of clinical trials at our institution in August 2020, we successfully completed over 200 in-lab virtual reality training sessions using our revised protocol. During this time, none of the five participants or three study staff reported any COVID-19 symptoms or reported a positive COVID-19 test. More than 40 voluntary COVID-19 tests were completed by our study staff over the last 6 months. All participants rated our safety protocol as very satisfied or extremely satisfied and that they would be very likely or extremely likely to participate in a VR clinical trial during the pandemic. Based on these findings, we suggest that continued VR clinical trial research during the COVID-19 pandemic is achievable and can be safely resumed if specific safety protocols are in place to mitigate the risk of exposure and spread of COVID-19.

The Effect of Virtual Reality on Emotional Response and Symptoms Provocation in Patients With OCD: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis aimed to evaluate the effectiveness of virtual reality (VR)-based technology on emotional response and symptoms in patients with obsessive-compulsive disorder (OCD). We systematically searched major electronic databases, including PubMed/Medline, Scopus, Embase, ISI Web of Science, PsycINFO, and Cochrane central, up to April 14, 2021, with no data or language limits. We performed reference, related articles, and citation searches to find additional articles. We included original articles comparing and studying VR-based technology in patients with OCD against the control group. We observed that VR significantly increases in anxiety (SMD = 2.92; 95% CI 1.89-3.94, p < 0.0001; I ² = 95%), disgust (SMD = 2.52; 95% CI 1.36-3.68, p < 0.0001; I ² = 95%), urge to wash (SMD = 3.12; 95% CI 1.92-4.32, p < 0.0001; I ² = 94%), checking time (SMD = 1.06; 95% CI 0.71-1.4, p < 0.0001; I ² = 44%), number of checking behavior (SMD = 1.45; 95% CI 0.06-2.83, p = 0.04; I ² = 93%), and uncertainty (SMD = 2.59; 95% CI 0.90-4.27, p = 0.003; I ² = 70%) in OCD patients compared with healthy controls using a random-effect model. This meta-analysis found that this environment has a moderate enhancement in emotional response and symptoms test scores of patients with OCD. However, our findings should be generalized with caution due to the lack of standardized methods and high heterogeneity among included evidence. The appropriate mode of integrating VR-based technology for patients with OCD requires more exploration.

Clinical advances in obsessive-compulsive disorder: a position statement by the International College of Obsessive-Compulsive Spectrum Disorders

In this position statement, developed by The International College of Obsessive-Compulsive Spectrum Disorders, a group of international experts responds to recent developments in the evidence-based management of obsessive-compulsive disorder (OCD). The article presents those selected therapeutic advances judged to be of utmost relevance to the treatment of OCD, based on new and emerging evidence from clinical and translational science. Areas covered include refinement in the methods of clinical assessment, the importance of early intervention based on new staging models and the need to provide sustained well-being involving effective relapse prevention. The relative benefits of psychological, pharmacological and somatic treatments are reviewed and novel treatment strategies for difficult to treat OCD, including neurostimulation, as well as new areas for research such as problematic internet use, novel digital interventions, immunological therapies, pharmacogenetics and novel forms of psychotherapy are discussed.

Neural Decoding of Multi-Modal Imagery Behavior Focusing on Temporal Complexity

Mental imagery behaviors of various modalities include visual, auditory, and motor behaviors. Their alterations are pathologically involved in various psychiatric disorders. Results of earlier studies suggest that imagery behaviors are correlated with the modulated activities of the respective modality-specific regions and the additional activities of supramodal imagery-related regions. Additionally, despite the availability of complexity analysis in the neuroimaging field, it has not been used for neural decoding approaches. Therefore, we sought to characterize neural oscillation related to multimodal imagery through complexity-based neural decoding. For this study, we modified existing complexity measures to characterize the time evolution of temporal complexity. We took magnetoencephalography (MEG) data of eight healthy subjects as they performed multimodal imagery and non-imagery tasks. The MEG data were decomposed into amplitude and phase of sub-band frequencies by Hilbert-Huang transform. Subsequently, we calculated the complexity values of each reconstructed time series, along with raw data and band power for comparison, and applied these results as inputs to decode visual perception (VP), visual imagery (VI), motor execution (ME), and motor imagery (MI) functions. Consequently, intra-subject decoding with the complexity yielded a characteristic sensitivity map for each task with high decoding accuracy. The map is inverted in the occipital regions between VP and VI and in the central regions between ME and MI. Additionally, replacement of the labels into two classes as imagery and non-imagery also yielded better classification performance and characteristic sensitivity with the complexity. It is particularly interesting that some subjects showed characteristic sensitivities not only in modality-specific regions, but also in supramodal regions. These analyses indicate that two-class and four-class classifications each provided better performance when using complexity than when using raw data or band power as input. When inter-subject decoding was used with the same model, characteristic sensitivity maps were also obtained, although their decoding performance was lower. Results of this study underscore the availability of complexity measures in neural decoding approaches and suggest the possibility of a modality-independent imagery-related mechanism. The use of time evolution of temporal complexity in neural decoding might extend our knowledge of the neural bases of hierarchical functions in the human brain.