Towards a youth mental health paradigm: a perspective and roadmap.

Most mental disorders have a typical onset between 12 and 25 years of age, highlighting the importance of this period for the pathogenesis, diagnosis, and treatment of mental ill-health. This perspective addresses interactions between risk and protective factors and brain development as key pillars accounting for the emergence of psychopathology in youth. Moreover, we propose that novel approaches towards early diagnosis and interventions are required that reflect the evolution of emerging psychopathology, the importance of novel service models, and knowledge exchange between science and practitioners. Taken together, we propose a transformative early intervention paradigm for research and clinical care that could significantly enhance mental health in young people and initiate a shift towards the prevention of severe mental disorders.

Digital phenotyping data and anomaly detection methods to assess changes in mood and anxiety symptoms across a transdiagnostic clinical sample.

INTRODUCTION: Clinical assessment of mood and anxiety change often relies on clinical assessment or self-reported scales. Using smartphone digital phenotyping data and resulting markers of behavior (e.g., sleep) to augment clinical symptom scores offers a scalable and potentially more valid method to understand changes in patients' state. This paper explores the potential of using a combination of active and passive sensors in the context of smartphone-based digital phenotyping to assess mood and anxiety changes in two distinct cohorts of patients to assess the preliminary reliability and validity of this digital phenotyping method. METHODS: Participants from two different cohorts, each n = 76, one with diagnoses of depression/anxiety and the other schizophrenia, utilized mindLAMP to collect active data (e.g., surveys on mood/anxiety), along with passive data consisting of smartphone digital phenotyping data (geolocation, accelerometer, and screen state) for at least 1 month. Using anomaly detection algorithms, we assessed if statistical anomalies in the combination of active and passive data could predict changes in mood/anxiety scores as measured via smartphone surveys. RESULTS: The anomaly detection model was reliably able to predict symptom change of 4 points or greater for depression as measured by the PHQ-9 and anxiety as measured for the GAD-8 for both patient populations, with an area under the ROC curve of 0.65 and 0.80 for each respectively. For both PHQ-9 and GAD-7, these AUCs were maintained when predicting significant symptom change at least 7 days in advance. Active data alone predicted around 52% and 75% of the symptom variability for the depression/anxiety and schizophrenia populations respectively. CONCLUSION: These results indicate the feasibility of anomaly detection for predicting symptom change in transdiagnostic cohorts. These results across different patient groups, different countries, and different sites (India and the US) suggest anomaly detection of smartphone digital phenotyping data may offer a reliable and valid approach to predicting symptom change. Future work should emphasize prospective application of these statistical methods.

Social connections as determinants of cognitive health and as targets for social interventions in persons with or at risk of Alzheimer's disease and related disorders: a scoping review.

BACKGROUND: Social connections have a significant impact on health across age groups, including older adults. Loneliness and social isolation are known risk factors for Alzheimer's disease and related dementias (ADRD). Yet, we did not find a review focused on meta-analyses and systematic reviews of studies that had examined associations of social connections with cognitive decline and trials of technology-based and other social interventions to enhance social connections in people with ADRD. STUDY DESIGN: We conducted a scoping review of 11 meta-analyses and systematic reviews of social connections as possible determinants of cognitive decline in older adults with or at risk of developing ADRD. We also examined eight systematic reviews of technology-based and other social interventions in persons with ADRD. STUDY RESULTS: The strongest evidence for an association of social connections with lower risk of cognitive decline was related to social engagement and social activities. There was also evidence linking social network size to cognitive function or cognitive decline, but it was not consistently significant. A number of, though not all, studies reported a significant association of marital status with risk of ADRD. Surprisingly, evidence showing that social support reduces the risk of ADRD was weak. To varying degrees, technology-based and other social interventions designed to reduce loneliness in people with ADRD improved social connections and activities as well as quality of life but had no significant impact on cognition. We discuss strengths and limitations of the studies included. CONCLUSIONS: Social engagement and social activities seem to be the most consistent components of social connections for improving cognitive health among individuals with or at risk for ADRD. Socially focused technology-based and other social interventions aid in improving social activities and connections and deserve more research.

The Digital Navigator: Standardizing Human Technology Support in App-Integrated Clinical Care.

Background: Mental health apps offer scalable care, yet clinical adoption is hindered by low user engagement and integration challenges into clinic workflows. Human support staff called digital navigators, trained in mental health technology, could enhance care access and patient adherence and remove workflow burdens from clinicians. While the potential of this role is clear, training staff to become digital navigators and assessing their impact are primary challenges. Methods: We present a detailed manual/framework for implementation of the Digital Navigator within a short-term, cognitive-behavioral therapy-focused hybrid clinic. We analyze patient engagement, satisfaction, and digital phenotyping data quality outcomes. Data from 83 patients, for the period spanning September 2022 to September 2023, included Digital Navigator satisfaction, correlated with demographics, mindLAMP app satisfaction, engagement, and passive data quality. Additionally, average passive data across 33 clinic patients from November 2023 to January 2024 were assessed for missingness. Results: Digital Navigator satisfaction averaged 18.8/20. Satisfaction was not influenced by sex, race, gender, or education. Average passive data quality across 33 clinic patients was 0.82 at the time this article was written. Digital Navigator satisfaction scores had significant positive correlation with both clinic app engagement and perception of that app. Conclusions: Results demonstrate preliminary support and patient endorsement for the Digital Navigator role and positive outcomes around digital engagement and digital phenotyping data quality. Through sharing training resources and standardizing the role, we aim to enable clinicians and researchers to adapt and utilize the Digital Navigator for their own needs.

Digital health behaviour change interventions in severe mental illness: a systematic review.

The use of digital technologies as a method of delivering health behaviour change (HBC) interventions is rapidly increasing across the general population. However, the role in severe mental illness (SMI) remains overlooked. In this study, we aimed to systematically identify and evaluate all of the existing evidence around digital HBC interventions in people with an SMI. A systematic search of online electronic databases was conducted. Data on adherence, feasibility, and outcomes of studies on digital HBC interventions in SMI were extracted. Our combined search identified 2196 titles and abstracts, of which 1934 remained after removing duplicates. Full-text screening was performed for 107 articles, leaving 36 studies to be included. From these, 14 focused on physical activity and/or cardio-metabolic health, 19 focused on smoking cessation, and three concerned other health behaviours. The outcomes measured varied considerably across studies. Although over 90% of studies measuring behavioural changes reported positive changes in behaviour/attitudes, there were too few studies collecting data on mental health to determine effects on psychiatric outcomes. Digital HBC interventions are acceptable to people with an SMI, and could present a promising option for addressing behavioural health in these populations. Feedback indicated that additional human support may be useful for promoting adherence/engagement, and the content of such interventions may benefit from more tailoring to specific needs. While the literature does not yet allow for conclusions regarding efficacy for mental health, the available evidence to date does support their potential to change behaviour across various domains.

Digital Phenotyping in Adults with Schizophrenia: A Narrative Review.

PURPOSE OF REVIEW: As care for older adult patients with schizophrenia lacks innovation, technology can help advance the field. Specifically, digital phenotyping, the real-time monitoring of patients' behaviors through smartphone sensors and symptoms through surveys, holds promise as the method can capture the dynamicity and environmental correlates of disease. RECENT FINDINGS: Few studies have used digital phenotyping to elucidate adult patients' experiences with schizophrenia. In this narrative review, we summarized the literature using digital phenotyping on adults with schizophrenia. No study focused solely on older adult patients. Studies including all adult patients were heterogeneous in measures used, duration, and outcomes. Despite limited research, digital phenotyping shows potential for monitoring outcomes such as negative, positive, and functional symptoms, as well as predicting relapse. Future research should work to target the symptomology persistent in chronic schizophrenia and ensure all patients have the digital literacy required to benefit from digital interventions and homogenize datasets to allow for more robust conclusions.

An Introduction to Generative Artificial Intelligence in Mental Health Care: Considerations and Guidance.

PURPOSE OF REVIEW: This paper provides an overview of generative artificial intelligence (AI) and the possible implications in the delivery of mental health care. RECENT FINDINGS: Generative AI is a powerful technology that is changing rapidly. As psychiatrists, it is important for us to understand generative AI technology and how it may impact our patients and our practice of medicine. This paper aims to build this understanding by focusing on GPT-4 and its potential impact on mental health care delivery. We first introduce key concepts and terminology describing how the technology works and various novel uses of it. We then dive into key considerations for GPT-4 and other large language models (LLMs) and wrap up with suggested future directions and initial guidance to the field.

Information and communication technology-based interventions for suicide prevention implemented in clinical settings: a scoping review.

BACKGROUND: A large number of information and communication technology (ICT) based interventions exist for suicide prevention. However, not much is known about which of these ICTs are implemented in clinical settings and their implementation characteristics. In response, this scoping review aimed to systematically explore the breadth of evidence on ICT-based interventions for suicide prevention implemented in clinical settings and then to identify and characterize implementation barriers and facilitators, as well as evaluation outcomes, and measures. METHODS: We conducted this review following the Joanna Briggs Institute methodology for scoping reviews. A search strategy was applied to the following six databases between August 17-20, 2021: MEDLINE, Embase, CINAHL, PsycINFO, Web of Science, and Library, Information Science and Technology Abstracts. We also supplemented our search with Google searches and hand-searching reference lists of relevant reviews. To be included in this review, studies must include ICT-based interventions for any spectrum of suicide-related thoughts and behaviours including non-suicidal self-injury. Additionally, these ICTs must be implemented in clinical settings, such as emergency department and in-patient units. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist to prepare this full report. RESULTS: This review included a total of 75 citations, describing 70 studies and 66 ICT-based interventions for suicide prevention implemented in clinical settings. The majority of ICTs were computerized interventions and/or applications (n = 55). These ICTs were commonly used as indicated strategies (n = 49) targeting patients who were actively presenting with suicide risk. The three most common suicide prevention intervention categories identified were post-discharge follow-up (n = 27), screening and/or assessment (n = 22), and safety planning (n = 20). A paucity of reported information was identified related to implementation strategies, barriers and facilitators. The most reported implementation strategies included training, education, and collaborative initiatives. Barriers and facilitators of implementation included the need for resource supports, knowledge, skills, motivation as well as engagement with clinicians with research teams. Studies included outcomes at patient, clinician, and health system levels, and implementation outcomes included acceptability, feasibility, fidelity, and penetration. CONCLUSION: This review presents several trends of the ICT-based interventions for suicide prevention implemented in clinical settings and identifies a need for future research to strengthen the evidence base for improving implementation. More effort is required to better understand and support the implementation and sustainability of ICTs in clinical settings. The findings can also serve as a future resource for researchers seeking to evaluate the impact and implementation of ICTs.

Digital Phenotyping Data to Predict Symptom Improvement and Mental Health App Personalization in College Students: Prospective Validation of a Predictive Model.

BACKGROUND: Mental health apps offer a transformative means to increase access to scalable evidence-based care for college students. Yet low rates of engagement currently preclude the effectiveness of these apps. One promising solution is to make these apps more responsive and personalized through digital phenotyping methods able to predict symptoms and offer tailored interventions. OBJECTIVE: Following our protocol and using the exact model shared in that paper, our primary aim in this study is to assess the prospective validity of mental health symptom prediction using the mindLAMP app through a replication study. We also explored secondary aims around app intervention personalization and correlations of engagement with the Technology Acceptance Model (TAM) and Digital Working Alliance Inventory scale in the context of automating the study. METHODS: The study was 28 days in duration and followed the published protocol, with participants collecting digital phenotyping data and being offered optional scheduled and algorithm-recommended app interventions. Study compensation was tied to the completion of weekly surveys and was not otherwise tied to engagement or use of the app. RESULTS: The data from 67 participants were used in this analysis. The area under the curve values for the symptom prediction model ranged from 0.58 for the UCLA Loneliness Scale to 0.71 for the Patient Health Questionnaire-9. Engagement with the scheduled app interventions was high, with a study mean of 73%, but few participants engaged with the optional recommended interventions. The perceived utility of the app in the TAM was higher (P=.01) among those completing at least one recommended intervention. CONCLUSIONS: Our results suggest how digital phenotyping methods can be used to create generalizable models that may help create more personalized and engaging mental health apps. Automating studies is feasible, and our results suggest targets to increase engagement in future studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/37954.

Ethical Challenges in AI Approaches to Eating Disorders.

The use of artificial intelligence (AI) to assist with the prevention, identification, and management of eating disorders and body image concerns is exciting, but it is not without risk. Technology is advancing rapidly, and ensuring that responsible standards are in place to mitigate risk and protect users is vital to the success and safety of technologies and users.

Smartphone Apps for Smoking Cessation: Systematic Framework for App Review and Analysis.

BACKGROUND: Cigarette smoking is a leading cause of preventable death, and identifying novel treatment approaches to promote smoking cessation is critical for improving public health. With the rise of digital health and mobile apps, these tools offer potential opportunities to address smoking cessation, yet the functionality of these apps and whether they offer scientifically based support for smoking cessation are unknown. OBJECTIVE: The goal of this research was to use the American Psychiatric Association app evaluation model to evaluate the top-returned apps from Android and Apple app store platforms related to smoking cessation and investigate the common app features available for end users. METHODS: We conducted a search of both Android and iOS app stores in July 2021 for apps related to the keywords "smoking," "tobacco," "smoke," and "cigarette" to evaluate apps for smoking cessation. Apps were screened for relevance, and trained raters identified and analyzed features, including accessibility (ie, cost), privacy, clinical foundation, and features of the apps, using a systematic framework of 105 objective questions from the American Psychiatric Association app evaluation model. All app rating data were deposited in mindapps, a publicly accessible database that is continuously updated every 6 months given the dynamic nature of apps available in the marketplace. We characterized apps available in July 2021 and November 2022. RESULTS: We initially identified 389 apps, excluded 161 due to irrelevance and nonfunctioning, and rated 228, including 152 available for Android platforms and 120 available for iOS platforms. Some of the top-returned apps (71/228, 31%) in 2021 were no longer functioning in 2022. Our analysis of rated apps revealed limitations in accessibility and features. While most apps (179/228, 78%) were free to download, over half had costs associated with in-app purchases or full use. Less than 65% (149/228) had a privacy policy addressing the data collected in the app. In terms of intervention features, more than 56% (128/228) of apps allowed the user to set and check in on goals, and more than 46% (106/228) of them provided psychoeducation, although few apps provided evidence-based support for smoking cessation, such as peer support or skill training, including mindfulness and deep breathing, and even fewer provided evidence-based interventions, such as acceptance and commitment therapy or cognitive behavioral therapy. Only 12 apps in 2021 and 11 in 2022 had published studies supporting the feasibility or efficacy for smoking cessation. CONCLUSIONS: Numerous smoking cessation apps were identified, but analysis revealed limitations, including high rates of irrelevant and nonfunctioning apps, high rates of turnover, and few apps providing evidence-based support for smoking cessation. Thus, it may be challenging for consumers to identify relevant, evidence-based apps to support smoking cessation in the app store, and a comprehensive evaluation system of mental health apps is critically important.

Evaluating Conversational Agents for Mental Health: Scoping Review of Outcomes and Outcome Measurement Instruments.

BACKGROUND: Rapid proliferation of mental health interventions delivered through conversational agents (CAs) calls for high-quality evidence to support their implementation and adoption. Selecting appropriate outcomes, instruments for measuring outcomes, and assessment methods are crucial for ensuring that interventions are evaluated effectively and with a high level of quality. OBJECTIVE: We aimed to identify the types of outcomes, outcome measurement instruments, and assessment methods used to assess the clinical, user experience, and technical outcomes in studies that evaluated the effectiveness of CA interventions for mental health. METHODS: We undertook a scoping review of the relevant literature to review the types of outcomes, outcome measurement instruments, and assessment methods in studies that evaluated the effectiveness of CA interventions for mental health. We performed a comprehensive search of electronic databases, including PubMed, Cochrane Central Register of Controlled Trials, Embase (Ovid), PsychINFO, and Web of Science, as well as Google Scholar and Google. We included experimental studies evaluating CA mental health interventions. The screening and data extraction were performed independently by 2 review authors in parallel. Descriptive and thematic analyses of the findings were performed. RESULTS: We included 32 studies that targeted the promotion of mental well-being (17/32, 53%) and the treatment and monitoring of mental health symptoms (21/32, 66%). The studies reported 203 outcome measurement instruments used to measure clinical outcomes (123/203, 60.6%), user experience outcomes (75/203, 36.9%), technical outcomes (2/203, 1.0%), and other outcomes (3/203, 1.5%). Most of the outcome measurement instruments were used in only 1 study (150/203, 73.9%) and were self-reported questionnaires (170/203, 83.7%), and most were delivered electronically via survey platforms (61/203, 30.0%). No validity evidence was cited for more than half of the outcome measurement instruments (107/203, 52.7%), which were largely created or adapted for the study in which they were used (95/107, 88.8%). CONCLUSIONS: The diversity of outcomes and the choice of outcome measurement instruments employed in studies on CAs for mental health point to the need for an established minimum core outcome set and greater use of validated instruments. Future studies should also capitalize on the affordances made available by CAs and smartphones to streamline the evaluation and reduce participants' input burden inherent to self-reporting.

Patient Online Record Access in English Primary Care: Qualitative Survey Study of General Practitioners' Views.

BACKGROUND: In 2022, NHS England announced plans to ensure that all adult primary care patients in England would have full online access to new data added to their general practitioner (GP) record. However, this plan has not yet been fully implemented. Since April 2020, the GP contract in England has already committed to offering patients full online record access on a prospective basis and on request. However, there has been limited research into UK GPs' experiences and opinions about this practice innovation. OBJECTIVE: This study aimed to explore the experiences and opinions of GPs in England about patients' access to their full web-based health record, including clinicians' free-text summaries of the consultation (so-called "open notes"). METHODS: In March 2022, using a convenience sample, we administered a web-based mixed methods survey of 400 GPs in the United Kingdom to explore their experiences and opinions about the impact on patients and GPs' practices to offer patients full online access to their health records. Participants were recruited using the clinician marketing service Doctors.net.uk from registered GPs currently working in England. We conducted a qualitative descriptive analysis of written responses ("comments") to 4 open-ended questions embedded in a web-based questionnaire. RESULTS: Of 400 GPs, 224 (56%) left comments that were classified into 4 major themes: increased strain on GP practices, the potential to harm patients, changes to documentation, and legal concerns. GPs believed that patient access would lead to extra work for them, reduced efficiency, and increased burnout. The participants also believed that access would increase patient anxiety and incur risks to patient safety. Experienced and perceived documentation changes included reduced candor and changes to record functionality. Anticipated legal concerns encompassed fears about increased litigation risks and lack of legal guidance to GPs about how to manage documentation that would be read by patients and potential third parties. CONCLUSIONS: This study provides timely information on the views of GPs in England regarding patient access to their web-based health records. Overwhelmingly, GPs were skeptical about the benefits of access both for patients and to their practices. These views are similar to those expressed by clinicians in other countries, including Nordic countries and the United States before patient access. The survey was limited by the convenience sample, and it is not possible to infer that our sample was representative of the opinions of GPs in England. More extensive, qualitative research is required to understand the perspectives of patients in England after experiencing access to their web-based records. Finally, further research is needed to explore objective measures of the impact of patient access to their records on health outcomes, clinician workload, and changes to documentation.

Digital Phenotyping for Mood Disorders: Methodology-Oriented Pilot Feasibility Study.

BACKGROUND: In the burgeoning area of clinical digital phenotyping research, there is a dearth of literature that details methodology, including the key challenges and dilemmas in developing and implementing a successful architecture for technological infrastructure, patient engagement, longitudinal study participation, and successful reporting and analysis of diverse passive and active digital data streams. OBJECTIVE: This article provides a narrative rationale for our study design in the context of the current evidence base and best practices, with an emphasis on our initial lessons learned from the implementation challenges and successes of this digital phenotyping study. METHODS: We describe the design and implementation approach for a digital phenotyping pilot feasibility study with attention to synthesizing key literature and the reasoning for pragmatic adaptations in implementing a multisite study encompassing distinct geographic and population settings. This methodology was used to recruit patients as study participants with a clinician-validated diagnostic history of unipolar depression, bipolar I disorder, or bipolar II disorder, or healthy controls in 2 geographically distinct health care systems for a longitudinal digital phenotyping study of mood disorders. RESULTS: We describe the feasibility of a multisite digital phenotyping pilot study for patients with mood disorders in terms of passively and actively collected phenotyping data quality and enrollment of patients. Overall data quality (assessed as the amount of sensor data obtained vs expected) was high compared to that in related studies. Results were reported on the relevant demographic features of study participants, revealing recruitment properties of age (mean subgroup age ranged from 31 years in the healthy control subgroup to 38 years in the bipolar I disorder subgroup), sex (predominance of female participants, with 7/11, 64% females in the bipolar II disorder subgroup), and smartphone operating system (iOS vs Android; iOS ranged from 7/11, 64% in the bipolar II disorder subgroup to 29/32, 91% in the healthy control subgroup). We also described implementation considerations around digital phenotyping research for mood disorders and other psychiatric conditions. CONCLUSIONS: Digital phenotyping in affective disorders is feasible on both Android and iOS smartphones, and the resulting data quality using an open-source platform is higher than that in comparable studies. While the digital phenotyping data quality was independent of gender and race, the reported demographic features of study participants revealed important information on possible selection biases that may result from naturalistic research in this domain. We believe that the methodology described will be readily reproducible and generalizable to other study settings and patient populations given our data on deployment at 2 unique sites.

Resource Document on Best Practices in Synchronous Videoconferencing-Based Telemental Health.

Background: This document represents an updated collaboration between the American Psychiatric Association (APA) and the American Telemedicine Association (ATA) to create a consolidated update of the previous APA and ATA official documents and resources in telemental health, to provide a single guide on clinical best practices for providing mental health services through synchronous videoconference. Methods: A joint writing committee drawn from the APA Committee on Telepsychiatry and the ATA TMH Special Interest Group (TMH SIG). was convened to draft and finalize the guidelines. This document draws directly from the 2018 APA/ATA guide and the ATA s previous guidelines, selecting from key statements/guidelines, consolidating them across documents, and then updating them where indicated. Guideline approval was provided following internal review by the APA, the ATA, the Board of Directors of the ATA, and the Joint Reference Committee of the APA. Results: The guidelines contain requirements, recommendations, and actions that are identified by text containing the keywords "shall," "should," or "may." Conclusions: Compliance with these recommendations will not guarantee accurate diagnoses or successful outcomes. The purpose of this guide is to assist providers in providing effective and safe medical care founded on expert consensus, research evidence, available resources, and patient needs.

Piloting Smartphone Digital Phenotyping to Understand Problematic Internet Use in an Adolescent and Young Adult Sample.

Problematic Internet use (PIU) preferentially affects youth development, particularly youth with psychiatric conditions. Studies attempting to understand PIU and its impact on adolescent mental health have been limited by cross-sectional design and self-report data. Even with a small sample size, digital phenotyping (DP) methodology can address these limitations through repeated sampling and collection of survey and sensor data through personal smartphones. This study pilots a 6-week DP protocol in 28 youth in mental health treatment in order to assess relationships between PIU, mood symptoms, and daily behaviors like smartphone engagement and daily travel in this high-risk population. Our results found shared associations between depression and PIU, where symptom severity of both worsened in the setting of decreased smartphone engagement. These clinically relevant findings indicate that, rather than uniformly worsening mental health, increased digital engagement may actually provide short-term relief from negative affect in youth with psychiatric comorbidities.

Changes in telepsychiatry regulations during the COVID-19 pandemic: 17 countries and regions' approaches to an evolving healthcare landscape.

BACKGROUND: During the COVID-19 pandemic, the use of telemedicine as a way to reduce COVID-19 infections was noted and consequently deregulated. However, the degree of telemedicine regulation varies from country to country, which may alter the widespread use of telemedicine. This study aimed to clarify the telepsychiatry regulations for each collaborating country/region before and during the COVID-19 pandemic. METHODS: We used snowball sampling within a global network of international telepsychiatry experts. Thirty collaborators from 17 different countries/regions responded to a questionnaire on barriers to the use and implementation of telepsychiatric care, including policy factors such as regulations and reimbursement at the end of 2019 and as of May 2020. RESULTS: Thirteen of 17 regions reported a relaxation of regulations due to the pandemic; consequently, all regions surveyed stated that telepsychiatry was now possible within their public healthcare systems. In some regions, restrictions on prescription medications allowed via telepsychiatry were eased, but in 11 of the 17 regions, there were still restrictions on prescribing medications via telepsychiatry. Lower insurance reimbursement amounts for telepsychiatry consultations v. in-person consultations were reevaluated in four regions, and consequently, in 15 regions telepsychiatry services were reimbursed at the same rate (or higher) than in-person consultations during the COVID-19 pandemic. CONCLUSIONS: Our results confirm that, due to COVID-19, the majority of countries surveyed are altering telemedicine regulations that had previously restricted the spread of telemedicine. These findings provide information that could guide future policy and regulatory decisions, which facilitate greater scale and spread of telepsychiatry globally.

Smartphone-Based Neuropsychological Assessment in Parkinson's Disease: Feasibility, Validity, and Contextually Driven Variability in Cognition.

OBJECTIVES: The prevalence of neurodegenerative disorders demands methods of accessible assessment that reliably captures cognition in daily life contexts. We investigated the feasibility of smartphone cognitive assessment in people with Parkinson's disease (PD), who may have cognitive impairment in addition to motor-related problems that limit attending in-person clinics. We examined how daily-life factors predicted smartphone cognitive performance and examined the convergent validity of smartphone assessment with traditional neuropsychological tests. METHODS: Twenty-seven nondemented individuals with mild-moderate PD attended one in-lab session and responded to smartphone notifications over 10 days. The smartphone app queried participants 5x/day about their location, mood, alertness, exercise, and medication state and administered mobile games of working memory and executive function. RESULTS: Response rate to prompts was high, demonstrating feasibility of the approach. Between-subject reliability was high on both cognitive games. Within-subject variability was higher for working memory than executive function. Strong convergent validity was seen between traditional tests and smartphone working memory but not executive function, reflecting the latter's ceiling effects. Participants performed better on mobile working memory tasks when at home and after recent exercise. Less self-reported daytime sleepiness and lower PD symptom burden predicted a stronger association between later time of day and higher smartphone test performance. CONCLUSIONS: These findings support feasibility and validity of repeat smartphone assessments of cognition and provide preliminary evidence of the effects of context on cognitive variability in PD. Further development of this accessible assessment method could increase sensitivity and specificity regarding daily cognitive dysfunction for PD and other clinical populations.

E-Mental Health for People with Personality Disorders: A Systematic Review.

PURPOSE OF REVIEW: Provision of mental health services through digital technologies (e-mental health) can potentially expand access to treatments for personality disorders (PDs). We evaluated studies on e-mental health for PDs published over the last 3 years (2019-2022). RECENT FINDINGS: Studies published in English that used e-mental health to treat people with PDs or PD-related symptoms were identified. We identified 19 studies, including four randomized controlled trials and one meta-analysis. Most interventions were based on Dialectical Behavior Therapy and delivered through smartphone applications for adults with Borderline Personality Disorder [BPD] or related symptoms. User experiences of the interventions were generally positive. Evidence for efficacy was limited. The current literature on e-mental health for PDs is limited in scope. Research in understudied populations and randomized controlled trials designed to establish efficacy are warranted. It is not yet clear whether e-mental health may be helpful for the treatment of PDs.

Smartphone apps for eating disorders: An overview of the marketplace and research trends.

OBJECTIVE: Apps purporting to assist with the management of eating disorders are proliferating; although less is known about (a) the safety or efficacy of the apps on the marketplaces and (b) if the research evidence supports dissemination of these apps. In this research forum, we seek to synthesize the current data and provide practical considerations around the use and research of these apps. METHODS: A search of the iOS and Google Play stores was conducted in June 2021 to identify publicly available apps targeting eating disorders. A PubMed search was also conducted in June 2021 to identify relevant publications around smartphone apps for eating disorders. RESULTS: Sixty-five apps that support the treatment of eating disorders were identified and coded across 105 data points on the publicly available mindApps.org website. The literature search revealed 13 articles. Seven percent of marketplaces apps offered any research support and the 13 published studies focused on only four apps. DISCUSSION: There is a need for more translational research on smartphone apps for eating disorders. Current marketplace offerings present risks that may not be balanced by their limited evidence. Research efforts should focus on offering evidenced-based apps for the marketplace. Clinicians should weigh known and emerging risks and benefits of these apps within the context of research gaps when making decisions around use.