Digital Mental Health and COVID-19: Using Technology Today to Accelerate the Curve on Access and Quality Tomorrow

Artificial intelligence and sexual reproductive health and rights: a technological leap towards achieving sustainable development goal target 3.7

Target 3.7 of the Sustainable Development Goals (SDGs) aims for universal access to sexual and reproductive health (SRH) services by 2030, including family planning services, information, education, and integration into national strategies. In contemporary times, reproductive medicine is progressively incorporating artificial intelligence (AI) to enhance sperm cell prediction and selection, in vitro fertilisation models, infertility and pregnancy screening. AI is being integrated into five core components of Sexual Reproductive Health, including improving care, providing high-quality contraception and infertility services, eliminating unsafe abortions, as well as facilitating the prevention and treatment of sexually transmitted infections. Though AI can improve sexual reproductive health and rights by addressing disparities and enhancing service delivery, AI-facilitated components have ethical implications, based on existing human rights and international conventions. Heated debates persist in implementing AI, particularly in maternal health, as well as sexual, reproductive health as the discussion centers on a torn between human touch and machine-driven care. In spite of this and other challenges, AI's application in sexual, and reproductive health and rights is crucial, particularly for developing countries, especially those that are yet to explore the application of AI in healthcare. Action plans are needed to roll out AI use in these areas effectively, and capacity building for health workers is essential to achieve the Sustainable Development Goals' Target 3.7. This commentary discusses innovations in sexual, and reproductive health and rights in meeting target 3.7 of the SDGs with a focus on artificial intelligence and highlights the need for a more circumspective approach in response to the ethical and human rights implications of using AI in providing sexual and reproductive health services.

An international expert survey on the worldwide digitalization in psychiatry: Global findings from the WPA survey

BACKGROUND

The World Psychiatric Association (WPA) Working Group on Digital Psychiatry aims to digitally supplement, support and improve mental health and care literacy, acceptance and accessibility across WPA member countries and National Psychiatric Associations (NPAs). To help with this goal, the present study was set to explore first the global status of digital mental health and care across NPAs METHODS: An international expert survey on the digitalization level across all 145 WPA NPAs was electronically distributed through Qualtrics. Descriptive statistics were carried out on the global dataset.

RESULTS

Across all 145 responses, 57 were included for analysis (39.3 % response rate). Most NPAs reported lacking an official section on digital mental health (73.7 %), missing national (59.6 %) or regional policies (82.5 %), clinical guidelines (>60 % depending on the digital tool/program), and education/training in both medicine (77.2 %) either and psychiatry training programs (71.9 %). Telemedicine seemed to be the most regulated digital tool in more than half of all included NPAs. Telemedicine (45.6 %) and telemental healthcare (38.6 %) were generally reimbursed. The reported highest priority areas for future actions across WPA Regions were education and training, and the development of guidelines.

CONCLUSION

This study represents a benchmark in the work of the WG on Digital Psychiatry. It presents clear priority areas that will guide the delivery of targeted actions aimed to promote digital mental health and care, and ultimately, equitable mental health outcomes around the world. Overall, the highest priorities to be globally implemented are represented by education/training and evidence-based clinical practice guidelines.

Internet- and mobile-based aftercare and relapse prevention interventions for anxiety and depressive disorders: a systematic review

Background

Digital interventions present potential solutions for aftercare and relapse prevention in anxiety and depressive disorders. This systematic review synthesizes evidence on the efficacy of internet- and mobile-based interventions for post-acute care in these conditions.

Methods

A systematic search was conducted in electronic databases (MEDLINE, CENTRAL, Scopus, Web of Science, PsycINFO, PsycARTICLES, PsycEXTRA, ProQuest Dissertations and Theses Open, Open Access Theses and Dissertations, and Open Grey) for randomized controlled trials evaluating digital aftercare or relapse prevention interventions for adults with anxiety or depressive disorders. Primary outcomes included symptom severity, relapse rates, recurrence rates, and rehospitalization. Secondary outcomes included general quality of life and adherence to primary treatment. Risk of bias was assessed using the Cochrane tool.

Results

Nineteen studies (3,206 participants) met the inclusion criteria. Interventions included cognitive-behavioral therapy, mindfulness-based approaches, and supportive text messaging. Most studies focused on depression, with limited evidence for anxiety disorders. Notably, fourteen studies that reported on depressive symptoms demonstrated significant improvements following digital interventions, with effect sizes ranging from small (Cohen's d = 0.20) to large (Cohen's d = 0.80). Five studies investigated relapse or recurrence rates, yielding mixed results. Adherence rates varied significantly across studies, ranging from 50 to 92.3%, highlighting the variability in participant engagement. Methodological quality was also variable, with allocation concealment and blinding being common limitations.

Conclusion

Internet- and mobile-based interventions show promise for aftercare and relapse prevention in depression, with limited evidence for anxiety disorders. Future research should focus on optimizing engagement, personalizing interventions, standardizing outcome measures, and conducting larger trials with longer follow-up periods. These findings have important implications for integrating digital tools into existing care pathways to improve long-term outcomes for individuals with anxiety and depressive disorders.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020151336, CRD42020151336.

Post-Acute Sequelae of Covid-19: A System-wise Approach on the Effects of Long-Covid-19

The SARS-CoV-2 virus responsible for the COVID-19 pandemic has profoundly impacted global health, economics, and society. This review seeks to encompass an overview of current knowledge on COVID-19, including its transmission, pathogenesis, and clinical presentation related to various systems within the human body. COVID-19 is a highly contagious illness that has rapidly spread worldwide. As of August 4, 2023, the WHO reported over 570 million confirmed cases of COVID-19 and over 6.3 million deaths. Although the virus is most common in adults, children can also be infected. Respiratory droplets that are produced when an infected person coughs or sneezes are the primary transmission mode for COVID-19. Additionally, the virus can be disseminated via contact with contaminated surfaces or objects, as it can remain viable for several hours or days. SARS-CoV-2 is a respiratory virus that enters cells by bonding with the angiotensin-converting enzyme 2 (ACE2) receptor. Once inside the cell, the virus replicates and produces new particles that can infect other cells. Interestingly, the effects of post-acute sequelae of SARS-CoV-2 infection (PASC) encompass more than just respiratory system. The findings presented in the data suggest that PASC significantly impacts multiple organs and their respective physiological processes. In light of these observations, we aim to provide a detailed discussion of the relevant findings in this paper. Through our review, we hope to provide healthcare professionals with a deeper understanding of the effects of PASC on the human body, which could ultimately lead to improved patient outcomes and treatment strategies.

Efficacy of mental health smartphone apps on stress levels: a meta-analysis of randomised controlled trials

The management of stress has evolved in recent years due to widespread availability of mobile-device applications (apps) and their capacity to deliver psychological interventions. We evaluated the efficacy of mental health apps on stress and sought to identify characteristics associated with effect size estimates. Sixty-nine randomised controlled trials (RCTs) were included. Random effects meta-analyses were performed and putative moderators were examined at univariate and multivariate (combinations and interactions) levels. From 78 comparisons, we observed a small but significant pooled effect of apps over control conditions on perceived stress levels (g = 0.27; 95% CI = 0.20, 0.34; I2 = 68%). This effect weakened after taking into account small-study bias according to the trim-and-fill procedure (g = 0.10; 95% CI = 0.02, 0.19; I2 = 78%). Delivery of apps with stress monitoring features produced smaller efficacy estimates, although this association interacted with other trial features (small sample size and inactive control group) in multivariate analyses, suggesting that this effect may have been explained by features characteristic of low-quality trials. Mental health apps appear to have small, acute effects on reducing perceived stress. Future research should shift focus towards identifying change mechanisms, longitudinal outcomes, features that facilitate sustained app usage, and tangible pathways to integrating apps into real-world clinical settings.

Online Media Consumption, Fear, Mental Wellbeing, and Behavioral Compliance During the COVID-19 Pandemic: A Longitudinal Study

This study explored how online media consumption, fear, mental wellbeing, and behavioral compliance with COVID-19 measures were related to one another during the COVID-19 pandemic. Employing a four-wave longitudinal survey research design (n = 1,092), this study found positive relationships between online media consumption and fear of COVID-19, between fear of COVID-19 and behavioral compliance, and between behavioral compliance and mental wellbeing in the general Dutch population. Results showed a negative relationship between fear of COVID-19 and mental wellbeing. Repeated measures ANOVAs indicated that participants' online media consumption, fear of COVID-19, and behavioral compliance with COVID-19 measures all gradually decreased as the pandemic progressed, while mental wellbeing gradually recovered as the pandemic progressed. Recognizing the negative relationship between fear of COVID-19 and mental wellbeing, policymakers may be encouraged to focus on implementing interventions and communication strategies to support mental health during pandemics. Using other types of appeals (e.g. hope appeals) in addition to the commonly used fear appeals when developing online public health messages could ensure behavioral compliance during pandemics without triggering high levels of fear. This can contribute to maintaining people's mental wellbeing when they have to cope with life-threatening public health crises while still promoting behavioral compliance with necessary public health measures.

Efficacy of app-based mobile health interventions for stress management: A systematic review and meta-analysis of self-reported, physiological, and neuroendocrine stress-related outcomes

Stress is a significant mental health concern for the general population, highlighting the need for effective and scalable solutions, such as mobile health (mHealth) app interventions. This systematic review and meta-analysis aimed to investigate the effects of mHealth apps designed primarily to reduce stress and distress in non-clinical and subclinical populations. A comprehensive literature search was conducted up to August 2024, including studies that measured both self-reported and physiological stress outcomes. 80 studies were analyzed. A small but significant effect size (g = 0.33) was found for self-reported stress outcomes, with studies that used specific active controls, operated in naturalistic contexts, and had a low risk of bias showing significantly lower effect sizes. A similarly small effect size was observed for physiological outcomes (g = 0.24). Notably, studies that employed muscle and breathing relaxation, meditation strategies, personalized guidance, experimental usage settings, and measured acute stress responses demonstrated significantly higher effect sizes. Further analysis of specific physiological systems revealed small effect sizes for autonomic (g = 0.32) and cardiac outcomes (g = 0.36). The significant effects observed across both psychological and physiological outcomes support the efficacy and potential of mHealth apps for the self-management of stress responses in the broader population.

Why People Seek Obesity Care Through Digital Rather Than In-Person Services: A Quantitative Multinational Analysis of Patients From a Large Unsubsidized Digital Obesity Provider

Digital modalities have been demonstrated to improve access and adherence to various chronic care services by mitigating geographical, temporal, and psychological barriers to ongoing multidisciplinary consultations, which such diseases necessitate. The net utility of medication-supported digital weight-loss services (DWLSs) has been intensely debated over the past few years due to their rapid uptake against the backdrop of the obesity epidemic. However, research on these services in real-world settings is scarce. Patients of a large multinational DWLS were emailed a four-question survey, soliciting their reasons for using the service instead of face-to-face (F2F) alternatives. Responses were collected from 1,283 patients, including 481 from the United Kingdom, 428 from Germany, and 374 from Australia. Personal discomfort in discussing weight loss in F2F settings was the most common reason for subscribing to the Eucalyptus DWLS across the full cohort (N = 557, 43.41%), followed by the modality's flexibility (N = 441, 34.37%), patient inability to access comprehensive obesity care through a local general practitioner (GP) (N = 435, 33.90%), and marketing or brand awareness (N = 358, 27.90%). Several significant differences were observed between country, gender, ethnicity, and regular GP status across each of the subscription reasons. This study contributed another important layer to the emerging literature on DWLSs by generating preliminary quantitative evidence of their benefits to obesity care access. However, the findings also indicated that a certain number of patients may be subscribing to such services simply to access weight-loss medications rather than multidisciplinary care. To derive clearer conclusions about this concern, follow-up studies should aim to analyze health coaching engagement markers across a range of service providers.

Building Mutually Beneficial Collaborations Between Digital Navigators, Mental Health Professionals, and Clients: Naturalistic Observational Case Study

Unlabelled

Despite the efficacy of digital mental health technologies (DMHTs) in clinical trials, low uptake and poor engagement are common in real-world settings. Accordingly, digital technology experts or "digital navigators" are increasingly being used to enhance engagement and shared decision-making between health professionals and clients. However, this area is relatively underexplored and there is a lack of data from naturalistic settings. In this paper, we report observational findings from the implementation of a digital navigator in a multidisciplinary mental health clinic in Sydney, Australia. The digital navigator supported clients and health professionals to use a measurement-based DMHT (the Innowell platform) for improved multidimensional outcome assessment and to guide personalized decision-making. Observational data are reported from implementation logs, platform usage statistics, and response rates to digital navigator emails and phone calls. Ultimately, support from the digital navigator led to improved data collection and clearer communications about goals for using the DMHT to track client outcomes; however, this required strong partnerships between health professionals, the digital navigator, and clients. The digital navigator helped to facilitate the integration of DMHT into care, rather than providing a stand-alone service. Thus, collaborations between health professionals and digital navigators are mutually beneficial and empower clients to be more engaged in their own care.

Top-funded companies offering digital health interventions for the prevention and treatment of depression: a systematic market analysis

BACKGROUND

Digital innovations can reduce the global burden of depression by facilitating timely and scalable interventions. In recent years, the number of commercial Digital Health Interventions for Depression (DHIDs) has been on the rise. However, there is limited knowledge on their content and underpinning scientific evidence. This study aimed to: (i) identify the top-funded companies offering DHIDs and (ii) provide an overview of their interventions, including scientific evidence, psychotherapeutic approaches and use of novel technologies.

METHODS

A systematic search was conducted using two venture capital databases to identify the top-30 funded companies offering DHIDs. In addition, studies related to the DHIDs' were identified via academic databases and hand-searching. The methodological quality of the publications was evaluated using the Mixed Methods Appraisal Tool.

RESULTS

The top-30 funded companies offering DHIDs received a total funding of 2,592 million USD. Less than half of the companies produced any scientific research associated with their DHIDs, with a total of 83 publications identified. Twenty-five publications were randomised control trials, of which 15 reported moderate-to-large effects in reducing depression symptoms. Regarding novel technologies, few DHIDs incorporated the use of conversational agents or low-burden sensing technologies.

CONCLUSIONS

Funding received by top-funded companies was not related to the amount of scientific evidence provided on their DHIDs. There was a strong variation in the quantity of evidence produced and an overall need for more rigorous effectiveness trials. Few DHIDs used automated approaches such as conversational agents, limiting their scalability.

Large Language Models for Mental Health Applications: Systematic Review

BACKGROUND

Large language models (LLMs) are advanced artificial neural networks trained on extensive datasets to accurately understand and generate natural language. While they have received much attention and demonstrated potential in digital health, their application in mental health, particularly in clinical settings, has generated considerable debate.

OBJECTIVE

This systematic review aims to critically assess the use of LLMs in mental health, specifically focusing on their applicability and efficacy in early screening, digital interventions, and clinical settings. By systematically collating and assessing the evidence from current studies, our work analyzes models, methodologies, data sources, and outcomes, thereby highlighting the potential of LLMs in mental health, the challenges they present, and the prospects for their clinical use.

METHODS

Adhering to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, this review searched 5 open-access databases: MEDLINE (accessed by PubMed), IEEE Xplore, Scopus, JMIR, and ACM Digital Library. Keywords used were (mental health OR mental illness OR mental disorder OR psychiatry) AND (large language models). This study included articles published between January 1, 2017, and April 30, 2024, and excluded articles published in languages other than English.

RESULTS

In total, 40 articles were evaluated, including 15 (38%) articles on mental health conditions and suicidal ideation detection through text analysis, 7 (18%) on the use of LLMs as mental health conversational agents, and 18 (45%) on other applications and evaluations of LLMs in mental health. LLMs show good effectiveness in detecting mental health issues and providing accessible, destigmatized eHealth services. However, assessments also indicate that the current risks associated with clinical use might surpass their benefits. These risks include inconsistencies in generated text; the production of hallucinations; and the absence of a comprehensive, benchmarked ethical framework.

CONCLUSIONS

This systematic review examines the clinical applications of LLMs in mental health, highlighting their potential and inherent risks. The study identifies several issues: the lack of multilingual datasets annotated by experts, concerns regarding the accuracy and reliability of generated content, challenges in interpretability due to the "black box" nature of LLMs, and ongoing ethical dilemmas. These ethical concerns include the absence of a clear, benchmarked ethical framework; data privacy issues; and the potential for overreliance on LLMs by both physicians and patients, which could compromise traditional medical practices. As a result, LLMs should not be considered substitutes for professional mental health services. However, the rapid development of LLMs underscores their potential as valuable clinical aids, emphasizing the need for continued research and development in this area.

TRIAL REGISTRATION

PROSPERO CRD42024508617; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=508617.

Empowering Mental Health Monitoring Using a Macro-Micro Personalization Framework for Multimodal-Multitask Learning: Descriptive Study

BACKGROUND

The field of mental health technology presently has significant gaps that need addressing, particularly in the domain of daily monitoring and personalized assessments. Current noninvasive devices such as wristbands and smartphones are capable of collecting a wide range of data, which has not yet been fully used for mental health monitoring.

OBJECTIVE

This study aims to introduce a novel dataset for personalized daily mental health monitoring and a new macro-micro framework. This framework is designed to use multimodal and multitask learning strategies for improved personalization and prediction of emotional states in individuals.

METHODS

Data were collected from 298 individuals using wristbands and smartphones, capturing physiological signals, speech data, and self-annotated emotional states. The proposed framework combines macro-level emotion transformer embeddings with micro-level personalization layers specific to each user. It also introduces a Dynamic Restrained Uncertainty Weighting method to effectively integrate various data types for a balanced representation of emotional states. Several fusion techniques, personalization strategies, and multitask learning approaches were explored.

RESULTS

The proposed framework was evaluated using the concordance correlation coefficient, resulting in a score of 0.503. This result demonstrates the framework's efficacy in predicting emotional states.

CONCLUSIONS

The study concludes that the proposed multimodal and multitask learning framework, which leverages transformer-based techniques and dynamic task weighting strategies, is superior for the personalized monitoring of mental health. The study indicates the potential of transforming daily mental health monitoring into a more personalized app, opening up new avenues for technology-based mental health interventions.

Preferences Regarding Information Strategies for Digital Mental Health Interventions Among Medical Students: Discrete Choice Experiment

BACKGROUND

Digital mental health interventions (DMHIs) are capable of closing gaps in the prevention and therapy of common mental disorders. Despite their proven effectiveness and approval for prescription, use rates remain low. The reasons include a lack of familiarity and knowledge as well as lasting concerns. Medical students were shown to have a comparatively higher risk for common mental disorders and are thus an important target group for raising awareness about DMHIs. At best, knowledge is already imparted during medical school using context-sensitive information strategies. Yet, little is known about medical students' information preferences regarding DMHIs.

OBJECTIVE

This study aims to explore information preferences for DMHIs for personal use among medical students in Germany.

METHODS

A discrete choice experiment was conducted, which was developed using an exploratory sequential mixed methods research approach. In total, 5 attributes (ie, source, delivery mode, timing, recommendation, and quality criteria), each with 3 to 4 levels, were identified using formative research. Data were analyzed using logistic regression models to estimate preference weights and the relative importance of attributes. To identify subgroups of students varying in information preferences, we additionally performed a latent class analysis.

RESULTS

Of 309 participants, 231 (74.8%) with reliable data were included in the main analysis (women: 217/309, 70.2%; age: mean 24.1, SD 4.0 y). Overall, the conditional logit model revealed that medical students preferred to receive information about DMHIs from the student council and favored being informed via social media early (ie, during their preclinic phase or their freshman week). Recommendations from other students or health professionals were preferred over recommendations from other users or no recommendations at all. Information about the scientific evidence base was the preferred quality criterion. Overall, the timing of information was the most relevant attribute (32.6%). Latent class analysis revealed 2 distinct subgroups. Class 1 preferred to receive extensive information about DMHIs in a seminar, while class 2 wanted to be informed digitally (via email or social media) and as early as possible in their studies.

CONCLUSIONS

Medical students reported specific needs and preferences regarding DMHI information provided in medical school. Overall, the timing of information (early in medical education) was considered more important than the information source or delivery mode, which should be prioritized by decision makers (eg, members of faculties of medicine, universities, and ministries of education). Study findings suggest general and subgroup-specific information strategies, which could be implemented in a stepped approach. Easily accessible digital information may promote students' interest in DMHIs in the first step that might lead to further information-seeking behavior and the attendance of seminars about DMHIs in the second step.

The Impact of a Digital Referral Platform to Improve Access to Child and Adolescent Mental Health Services: A Prospective Observational Study with Real-World Data

(1) Background: In the UK, mental health needs for children and young people (CYP) are rising, whilst access to care is declining, particularly in the North of England and post-COVID-19. However, Health Information Technologies (HITs) can simplify access to Child and Adolescent Mental Health Services (CAMHS), reduce waiting times, and provide anonymous support and reliable information. (2) Methods: A single-centre prospective observational study examined the impact of "CYP as One"-a digital referral point to CAMHS-on waiting times and referral rejection rates. (3) Results: Waiting times during the first 12 months of "CYP as One" implementation were compared to the 12 months prior using non-parametric tests. "CYP as One" demonstrated an increase of 1314 referrals, with self-referrals rising by 71%. Initial implementation showed an increase in waiting times by 16.13 days (53.89 days) compared to pre-implementation (37.76 days) (p < 0.001). However, months 10 (M = 16.18, p < 0.001), 11 (M = 17.45, p < 0.001), and 12 (M = 31.45, p < 0.001) implementation showed reduced waiting times. Rejection rates rose due to a 108% increase in referral volume. "CYP as One" improved access and reduced waiting times after the initial phase. (4) Conclusions: Further research is needed to assess its long-term impact and cost-effectiveness, particularly regarding specific mental health conditions and staff time.

Immersive Virtual Reality Cognitive Training for Improving Cognition and Depressive Symptoms Among Older Adults. Current Evidence and Future Recommendations. A Systematic Review

Older adults, particularly impacted by the pandemic, are anticipated to face considerable challenges to their cognitive and psychological health. Various cognitive training methods have been proposed to improve their cognitive decline through regular practice. Immersive virtual reality (IVR) offers a promising avenue to bolster cognitive and mental health care accessibility for older adults and has shown potential in augmenting traditional cognitive training methods. This systematic review aims to assess the efficacy of IVR-based cognitive training on improving cognitive impairments and depressive symptoms among older adults, irrespective of their level of cognitive decline. Systematic searches were conducted across MEDLINE-PubMed, EMBASE, and Web of Science databases from inception to December 2022. Only peer-reviewed articles reporting results from randomized controlled trials and pilot studies, focusing on the effects of VR-based cognitive training on adults aged 55 or older, were deemed eligible. Using the Cochrane Handbook for Systematic Reviews of Interventions, the risk of bias was appraised for each selected study. Out of 3,835 studies identified, 9 met the inclusion criteria. The qualitative analyses concluded that IVR cognitive training interventions enhanced certain cognitive functions and well-being among older adults, notably those with mild cognitive impairments. These interventions were particularly effective in boosting memory, visuospatial abilities, and measures related to depressive symptoms and overall well-being. However, enhancements were less pronounced for executive functions, attention, and global cognition. Based on these findings, we propose a set of tailored, inclusive, and evidence-based recommendations to adapt emerging technologies to better accommodate the needs of older adults.

Leveraging Personal Technologies in the Treatment of Schizophrenia Spectrum Disorders: Scoping Review

BACKGROUND

Digital mental health is a rapidly growing field with an increasing evidence base due to its potential scalability and impacts on access to mental health care. Further, within underfunded service systems, leveraging personal technologies to deliver or support specialized service delivery has garnered attention as a feasible and cost-effective means of improving access. Digital health relevance has also improved as technology ownership in individuals with schizophrenia has improved and is comparable to that of the general population. However, less digital health research has been conducted in groups with schizophrenia spectrum disorders compared to other mental health conditions, and overall feasibility, efficacy, and clinical integration remain largely unknown.

OBJECTIVE

This review aims to describe the available literature investigating the use of personal technologies (ie, phone, computer, tablet, and wearables) to deliver or support specialized care for schizophrenia and examine opportunities and barriers to integrating this technology into care.

METHODS

Given the size of this review, we used scoping review methods. We searched 3 major databases with search teams related to schizophrenia spectrum disorders, various personal technologies, and intervention outcomes related to recovery. We included studies from the full spectrum of methodologies, from development papers to implementation trials. Methods and reporting follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

This search resulted in 999 studies, which, through review by at least 2 reviewers, included 92 publications. Included studies were published from 2010 to 2023. Most studies examined multitechnology interventions (40/92, 43%) or smartphone apps (25/92, 27%), followed by SMS text messaging (16/92, 17%) and internet-based interventions (11/92, 12%). No studies used wearable technology on its own to deliver an intervention. Regarding the stage of research in the field, the largest number of publications were pilot studies (32/92, 35%), followed by randomized control trials (RCTs; 20/92, 22%), secondary analyses (16/92, 17%), RCT protocols (16/92, 17%), development papers (5/92, 5%), and nonrandomized or quasi-experimental trials (3/92, 3%). Most studies did not report on safety indices (55/92, 60%) or privacy precautions (64/92, 70%). Included studies tend to report consistent positive user feedback regarding the usability, acceptability, and satisfaction with technology; however, engagement metrics are highly variable and report mixed outcomes. Furthermore, efficacy at both the pilot and RCT levels report mixed findings on primary outcomes.

CONCLUSIONS

Overall, the findings of this review highlight the discrepancy between the high levels of acceptability and usability of these digital interventions, mixed efficacy results, and difficulties with sustained engagement. The discussion highlights common patterns that may underscore this observation in the field; however, as this was a scoping review, a more in-depth systematic review or meta-analysis may be required to better understand the trends outlined in this review.

Testing the Effectiveness of a Mobile Smartphone App Designed to Improve the Mental Health of Junior Physicians: Protocol for a Randomized Controlled Trial

BACKGROUND

Shift (Black Dog Institute) is the first mobile health smartphone app created to support the mental health of junior physicians. Junior physicians experience demanding work conditions, leading to high levels of psychological distress and burnout. However, they are often concerned about the potential career impacts of seeking mental health support. The confidentiality and ease of access of digital interventions may be particularly suited to address these concerns. The Shift app provides therapeutic and psychoeducational content and strategies contextualized for the specific needs of physicians in training. App content includes information on mental health, help seeking, mindfulness, and common workplace-related concerns of junior physicians.

OBJECTIVE

This study aims to test, at scale, the effectiveness of Shift among junior physicians working in Australia using a randomized controlled trial design. The primary aim is to examine whether junior physicians using Shift experience a reduction in depressive symptoms compared with a waitlist control group. The secondary aim is to examine whether the app intervention group experiences improvements in anxiety, work and social functioning, help seeking, quality of life, and burnout compared with the control group.

METHODS

A total of 778 junior physicians were recruited over the internet through government and nongovernment medical organizations across Australia, as well as through paid social media advertisements. They were randomly allocated to one of 2 groups: (1) the intervention group, who were asked to use the Shift app for a period of 30 days, or (2) the waitlist control group, who were placed on a waitlist and were asked to use the app after 3 months. Participants completed psychometric measures for self-assessing mental health and wellbeing outcomes, with assessments occurring at baseline, 1 month after completing the baseline period, and 3 months after completing the baseline period. Participants in the waitlist control group were asked to complete an additional web-based questionnaire 1 month after receiving access to the app or 4 months after completing the baseline survey. Participants took part in the study on the internet; the study was completely automated.

RESULTS

The study was funded from November 2022 to December 2024 by the New South Wales Ministry of Health. Data collection for the study occurred between January and August 2024, with 780 participants enrolling in the study during this time. Data analysis is underway; the effectiveness of the intervention will be estimated on an intention-to-treat basis using a mixed-model, repeated measures analysis. Results are expected to be submitted for publication in 2025.

CONCLUSIONS

To the best of our knowledge, this is the first randomized controlled trial to examine the effectiveness of a mobile health smartphone app specifically designed to support the mental health of junior physicians.

TRIAL REGISTRATION

Australia and New Zealand Clinical Trials Registry ACTRN12623000664640; https://tinyurl.com/7xt24dhk.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/58288.

Digital Health Technology Use Across Socioeconomic Groups Prior to and During the COVID-19 Pandemic: Panel Study

BACKGROUND

Digital technologies have become more important in the health care sector in the past decades. This transition from conventional to digital health care has been accelerated by the impact of the COVID-19 pandemic, which poses the risk of creating a "digital divide," inadvertently placing those who are older, economically disadvantaged, and have a lower level of education at a disadvantage.

OBJECTIVE

This study focuses on the influence of socioeconomic factors on the adoption of digital health technology in the Frisian population and how this relation is affected by the COVID-19 pandemic.

METHODS

In 2019 and 2020, a panel study was conducted on digital health in the Frisian population in the Netherlands. In the survey, the use of digital health technology was operationalized in a broad sense, going beyond the care context by also including preventative health-promoting solutions generally available on the consumer market, such as wearables and lifestyle apps. First, to assess the influence of socioeconomic factors on the total use of digital health apps, a generalized linear model was fitted with use of digital health app as the dependent variable and socioeconomic factors as between-subject factors on the 2019 data. Second, to analyze whether the use of separate health apps increased from 2019 to 2020, we conducted chi-square tests on different digital health app types. Third, to examine the influence of COVID-19 on the use of digital health apps, a generalized linear mixed model was fitted with the use of digital health apps as the dependent variable, COVID-19 as the within-subject variable, and socioeconomic factors as between-subject factors.

RESULTS

The results indicated that prior to the COVID-19 pandemic, digital health technology use was higher in women, younger people, and those who are well educated and economically more privileged. Moreover, the percentage of people who reported using digital health technology rose from 70% (1580/2258) to 82.5% (1812/2197) due to the COVID-19 pandemic. This increase was significant for all separate types of digital health technology (all P<.001). In addition, we found the interaction effects of COVID-19 with age and education attainment, indicating that the lower total use among older people and people with lower education attainment became slightly less apparent from 2019 to 2020.

CONCLUSIONS

These findings on the influence of the COVID-19 pandemic on the digital divide indicated that the use of all types of digital health apps increased and that older individuals and people with a lower level of education caught up a little during COVID-19. Future research should gain more insight into this effect and examine whether it persists beyond the COVID-19 pandemic. Additionally, future endeavors should focus on vulnerable groups, ensuring they receive adequate attention to guarantee access to health care, preventative health-promoting solutions, and social services.

The coronavirus pandemic: Accessible technology for education, employment, and livelihoods

During the 2020 coronavirus pandemic, the use of technology to continue societal functions, maintain daily living, and gather information became near ubiquitous overnight. In the United States, universities moved to remote online education, non-essential personnel were asked to work from home, many businesses were forced to rapidly embrace online purchasing and even entertainers held concerts on social media platforms. Professional medical personnel, as well as state and local officials, held daily press briefings about the virus on television, radio, and social media. Disaster research has shown that often disasters exacerbate preexisting inequalities during all-hazards and therefore there are several populations likely to be more at risk, such as people with disabilities, and older adults. While complications from the coronavirus were more severe for older adults and those with preexisting health conditions, the preparedness and response efforts to contain the virus lessened the resiliency of other populations during the US outbreaks, potentially hampering their ability to recover at the same rate. For example, several press conferences from officials failed to include or display ASL interpreters. This would put some Americans at a disadvantage since they may have been unable to receive all of the pertinent information on how to keep safe. Furthermore, with nearly 22% of households without broadband internet access (per Pew Research Center), several individuals will not be able to take advantage of the rapid remote learning and work-from-home recommendations. Even when individuals have access to the Internet, older adults have been found to be less knowledgeable about privacy and security tools than younger adults.

Disability and Adverse Effects of Oral Versus Long-Acting Injectable Antipsychotics in Schizophrenia-Spectrum and Bipolar Disorder: A Comparison Based on Data-Driven Taxonomy

BACKGROUND

Patients undergoing antipsychotic treatment for psychiatric disorders may experience challenges in functioning, either stemming from the severity of the illness or from the tolerability issues of prescribed medications.

OBJECTIVES

The aims of this cross-sectional study are to investigate the impact of adverse effects of antipsychotic drugs on patients' daily life functioning, comparing oral and long-acting injectable (LAI) antipsychotics, and further dividing antipsychotics by receptor-binding profiles based on recently defined data-driven taxonomy.

METHODS

This study involved patients with schizophrenia and bipolar spectrum disorders taking oral or LAI antipsychotics. Disability and functioning levels were assessed using the World Health Organization Disability Assessment Schedule 2.0 (WHODAS), and the adverse effects of medications were evaluated using the Udvalg for Kliniske Undersogelser (UKU) Side Effect Rating Scale and its subscales.

RESULTS

The total sample consisted of 126 participants with a diagnosis of schizophrenia-spectrum or bipolar disorder, and included 54 males and 72 females ranging from 18 to 78 years of age (mean 45.1, standard deviation 14); 78 patients were taking oral antipsychotics and 48 were taking LAI antipsychotics, with subcategories of muscarinic (31), adrenergic/low dopamine (25), serotonergic/dopaminergic (23), dopaminergic (1), LAI muscarinic (15), LAI adrenergic (6), and LAI serotonergic/dopaminergic (25). The UKU total score for adverse effects showed significant correlations with WHODAS total score (ρ = 0.475; p < 0.001). Compared with oral antipsychotics, LAIs showed significantly lower scores in psychological (p = 0.014), autonomic (p = 0.008), other (p = 0.004), and sexual adverse effects (p = 0.008), as well as the UKU total score (p = 0.002). The Kruskal-Wallis test showed a significant difference in adverse effects between LAI and oral muscarinic subgroups, with LAIs having lower scores compared with antipsychotics binding to muscarinic receptors (p = 0.043).

CONCLUSION

These findings indicate clinically relevant differences in adverse effects among formulations, warranting further investigation for future observational studies.

A multimodal group-based immersive virtual reality intervention for improving cognition and mental health in patients with post-covid-19 condition. A quasi-experimental design study

Introduction

Adults with Post-COVID-19 Condition (PCC) may show cognitive impairments in attention, processing speed, memory, and executive function. Multimodal programs that combine cognitive training, physical activity and emotional tasks, such as mindfulness-based interventions (MBIs), may offer a suitable alternative for improving PCC treatments. Immersive Virtual Reality (IVR) is a promising technology that can enhance traditional cognitive training, physical activity, and MBIs. The use of IVR technology may increase engagement with these interventions and potentially enhance the individual benefits of cognitive training, exercise and MBIs. The current study evaluated the impact of a multimodal IVR intervention, comparing this with a usual care intervention (control group), in order to assess changes in cognition and mental health in adults with PCC. We also aimed to assess user experience factors such as enjoyment, perceived improvement, and fatigue following each multimodal IVR session within the experimental group.

Method

Thirty-one participants with PCC symptoms were assigned to either the experimental group (IVR, n = 15) or the control group (usual care intervention, n = 16) in a quasi-experimental design study. The multimodal IVR intervention consisted of MBI, cognitive training and physical exercise and was delivered in a 60-min group session with 5 participants, twice a week, for 8 weeks (16 sessions in total). Measures of global cognition, attention, processing speed, verbal episodic memory and subjective memory complaints (primary measures), and depressive and anxiety symptoms and fatigue (secondary measures) were assessed at baseline and also after 8 weeks (post-intervention).

Results

Mixed between-group (group) and within-group (pre-post assessments) ANOVAs revealed significant group*time interactions in global cognition, simple attention, processing speed, memory and depressive symptoms, with large effect sizes (p < 0.05; partial η2 > 0.14). There was also a marginally significant group*time interaction for executive function (p = 0.05). Follow-up analyses comparing pre-and post-intervention outcomes for each group separately showed that the experimental group significantly improved in global cognition, processing speed, memory and depressive symptoms, while the control group showed no significant pre-post changes. Friedman tests showed a significant main effect of time (χ2(2) = 6.609, p = 0.04), with a gradual increase in enjoyment from the first, to the mid, and then to the final session. In addition, perceived improvement scores remained high throughout the intervention, and patient-reported fatigue levels did not fluctuate significantly throughout the intervention.

Conclusion

To our knowledge, no previous research has combined cognitive training, physical exercise and MBI using an IVR paradigm in adults with PCC. Despite their inherent limitations, our findings mark a pioneering step toward improving cognition and mental health outcomes in PCC through the innovative use of new technology and multimodal approaches. This first study should be accompanied by more extensive, randomized clinical trials aimed at further exploring and refining these interventions.

The relationship between university student help-seeking intentions and well-being outcomes

University represents a time of both great uncertainty and change as well as a time of opportunity and learning. University students represent a population both at a higher risk of experiencing poor mental health and diagnosis and a population with relatively greater access and communication of both mental health literacy resources and mental health support services. Despite this, we consistently see low intention of help-seeking for mental health services or health services, with a clear preference shown for personal contacts such as friends or parents. To understand help-seeking intentions and their relationship with well-being, the current study explored two core hypotheses, when assessing a broad range of help-seeking options, the likelihood of seeking support from a range of sources will cluster together to create help-seeking groupings that can be further explored (1) and that across these help-seeking factors, there would be difference in intention score across students who fall within "at-risk," "low," or "normal to high" well-being groupings (2). Through a series of exploratory factor analysis (EFA) on a subsample (N = 178) and final confirmatory factor analysis (N = 1597) identified five help-seeking factors: Intimate Partner (single item), Personal Relations (friends, parents, and other relatives), External Health Service (external mental health provider and health provider), University Health Service (university mental health and health provider), and Digital and Distal Professional (digital apps, websites or forums, telehealth, religious leaders, and phone or online emergency services). To address hypothesis 2, a multivariate analysis of covariance was run to assess help-seeking intentions across factors between students with "at-risk" (N = 453), "low" (N = 484), or "normal to high" (N = 563) well-being scores. Although significant differences were found between groups on almost all help-seeking factors (except External Health Service), the differences between groups were small. However, consistently those with "normal to high" well-being demonstrated higher intention to seek help compared to "low" and "at-risk" groups. Across all groups, Personal Relations demonstrated the highest average help-seeking intention score and, in addition to supporting findings in previous literature, represents a potential "lowest hanging fruit" of help-seeking source for university students.

Prevalence and 20-year trends in meditation, yoga, guided imagery and progressive relaxation use among US adults from 2002 to 2022

Meditation, yoga, guided imagery, and progressive relaxation are promoted as complementary approaches for health and wellbeing in the United States, but their uptake by different sociodemographic groups is unclear. This study assessed the prevalence and 20 year trends in the use of these practices in US adults between 2002-2022. We examined practice use and associations with sociodemographic and health factors in a population-weighted analysis of n = 134,959 participants across 5 cycles of the National Health Interview Survey. The overall use of meditation (18.3%, 60.53 million), yoga (16.8%, 55.78 million) and guided imagery/progressive relaxation (6.7%, 22.22 million) increased significantly from 2002 to 2022. Growth was consistent across most sociodemographic and health strata, however users of 'Other' race (comprising 54% Indigenous Americans, Odds Ratios; ORs = 1.28-1.70) and users with moderate (ORs = 1.19-1.29) psychological distress were overrepresented across all practices, and those with severe psychological distress were overrepresented in meditation (OR = 1.33) and guided imagery/progressive relaxation (OR = 1.42). Meditation use has accelerated over time for 65 + year olds (OR = 4.22), people not accessing mental health care (OR = 1.39), and less educated (OR = 4.02) groups, potentially reflecting unmet health needs. Health professionals should consider the extensive use of complementary practices in service and treatment planning and consider their risks and benefits.

Improvement and Maintenance of Clinical Outcomes in a Digital Mental Health Platform: Findings From a Longitudinal Observational Real-World Study

BACKGROUND

Digital mental health services are increasingly being provided by employers as health benefit programs that can improve access to and remove barriers to mental health care. Stratified care models, in particular, offer personalized care recommendations that can offer clinically effective interventions while conserving resources. Nonetheless, clinical evaluation is needed to understand their benefits for mental health and their use in a real-world setting.

OBJECTIVE

This study aimed to examine the changes in clinical outcomes (ie, depressive and anxiety symptoms and well-being) and to evaluate the use of stratified blended care among members of an employer-sponsored digital mental health benefit.

METHODS

In a large prospective observational study, we examined the changes in depressive symptoms (9-item Patient Health Questionnaire), anxiety symptoms (7-item Generalized Anxiety Disorder scale), and well-being (5-item World Health Organization Well-Being Index) for 3 months in 509 participants (mean age 33.9, SD 8.7 years; women: n=312, 61.3%; men: n=175, 34.4%; nonbinary: n=22, 4.3%) who were newly enrolled and engaged in care with an employer-sponsored digital mental health platform (Modern Health Inc). We also investigated the extent to which participants followed the recommendations provided to them through a stratified blended care model.

RESULTS

Participants with elevated baseline symptoms of depression and anxiety exhibited significant symptom improvements, with a 37% score improvement in depression and a 29% score improvement in anxiety (P values <.001). Participants with baseline scores indicative of poorer well-being also improved over the study period (90% score improvement; P=.002). Furthermore, over half exhibited clinical improvement or recovery for depressive symptoms (n=122, 65.2%), anxiety symptoms (n=127, 59.1%), and low well-being (n=82, 64.6%). Among participants with mild or no baseline symptoms, we found high rates of maintenance for low depressive (n=297, 92.2%) and anxiety (n=255, 86.7%) symptoms and high well-being (n=344, 90.1%). In total, two-thirds of the participants (n=343, 67.4%) used their recommended care, 16.9% (n=86) intensified their care beyond their initial recommendation, and 15.7% (n=80) of participants underused care by not engaging with the highest level of care recommended to them.

CONCLUSIONS

Participants with elevated baseline depressive or anxiety symptoms improved their mental health significantly from baseline to follow-up, and most participants without symptoms or with mild symptoms at baseline maintained their mental health over time. In addition, engagement patterns indicate that the stratified blended care model was efficient in matching individuals with the most effective and least costly care while also allowing them to self-determine their care and use combinations of services that best fit their needs. Overall, the results of this study support the clinical effectiveness of the platform for improving and preserving mental health and support the utility and effectiveness of stratified blended care models to improve access to and use of digitally delivered mental health services.

Advancing equitable access to digital mental health in the Asia-Pacific region in the context of the COVID-19 pandemic and beyond: A modified Delphi consensus study

The COVID-19 pandemic had an unprecedented impact on global mental health and well-being, including across the Asia-Pacific. Efforts to mitigate virus spread led to far-reaching disruption in the delivery of health and social services. In response, there was a rapid shift to the use of digital mental health (DMH) approaches. Though these technologies helped to improve access to care for many, there was also substantial risk of access barriers leading to increased inequities in access to mental health care, particularly among at-risk and equity-deserving populations. The objective of this study was to conduct a needs assessment and identify priorities related to equitable DMH access among at-risk and equity-deserving populations in the Asia Pacific region during the first year of the COVID-19 pandemic. The study consisted of a modified Delphi consensus methodology including two rounds of online surveys and online consultations with stakeholders from across the region. Study participants included policy makers, clinicians and service providers, and people with lived experience of mental health conditions. Results demonstrate that vulnerabilities to negative mental health impacts and access barriers were compounded during the pandemic. Access barriers included a lack of linguistically and culturally appropriate DMH options, low mental health literacy and poor access to technological infrastructure and devices, low levels of awareness and trust of DMH options, and lack of policies and guidelines to support effective and equitable delivery of DMH. Recommendations to improve equitable access include ensuring that diverse people with lived experience are engaged in research, co-design and policy development, the development and implementation of evidence-based and equity-informed guidelines and frameworks, clear communication about DMH evidence and availability, and the integration of DMH into broader health systems. Study results can inform the development and implementation of equitable DMH as its use becomes more widespread across health systems.

Comparison of the Working Alliance in Blended Cognitive Behavioral Therapy and Treatment as Usual for Depression in Europe: Secondary Data Analysis of the E-COMPARED Randomized Controlled Trial

BACKGROUND

Increasing interest has centered on the psychotherapeutic working alliance as a means of understanding clinical change in digital mental health interventions in recent years. However, little is understood about how and to what extent a digital mental health program can have an impact on the working alliance and clinical outcomes in a blended (therapist plus digital program) cognitive behavioral therapy (bCBT) intervention for depression.

OBJECTIVE

This study aimed to test the difference in working alliance scores between bCBT and treatment as usual (TAU), examine the association between working alliance and depression severity scores in both arms, and test for an interaction between system usability and working alliance with regard to the association between working alliance and depression scores in bCBT at 3-month assessments.

METHODS

We conducted a secondary data analysis of the E-COMPARED (European Comparative Effectiveness Research on Blended Depression Treatment versus Treatment-as-usual) trial, which compared bCBT with TAU across 9 European countries. Data were collected in primary care and specialized services between April 2015 and December 2017. Eligible participants aged 18 years or older and diagnosed with major depressive disorder were randomized to either bCBT (n=476) or TAU (n=467). bCBT consisted of 6-20 sessions of bCBT (involving face-to-face sessions with a therapist and an internet-based program). TAU consisted of usual care for depression. The main outcomes were scores of the working alliance (Working Alliance Inventory-Short Revised-Client [WAI-SR-C]) and depressive symptoms (Patient Health Questionnaire-9 [PHQ-9]) at 3 months after randomization. Other variables included system usability scores (System Usability Scale-Client [SUS-C]) at 3 months and baseline demographic information. Data from baseline and 3-month assessments were analyzed using linear regression models that adjusted for a set of baseline variables.

RESULTS

Of the 945 included participants, 644 (68.2%) were female, and the mean age was 38.96 years (IQR 38). bCBT was associated with higher composite WAI-SR-C scores compared to TAU (B=5.67, 95% CI 4.48-6.86). There was an inverse association between WAI-SR-C and PHQ-9 in bCBT (B=-0.12, 95% CI -0.17 to -0.06) and TAU (B=-0.06, 95% CI -0.11 to -0.02), in which as WAI-SR-C scores increased, PHQ-9 scores decreased. Finally, there was a significant interaction between SUS-C and WAI-SR-C with regard to an inverse association between higher WAI-SR-C scores and lower PHQ-9 scores in bCBT (b=-0.030, 95% CI -0.05 to -0.01; P=.005).

CONCLUSIONS

To our knowledge, this is the first study to show that bCBT may enhance the client working alliance when compared to evidence-based routine care for depression that services reported offering. The working alliance in bCBT was also associated with clinical improvements that appear to be enhanced by good program usability. Our findings add further weight to the view that the addition of internet-delivered CBT to face-to-face CBT may positively augment experiences of the working alliance.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02542891, https://clinicaltrials.gov/study/NCT02542891; German Clinical Trials Register DRKS00006866, https://drks.de/search/en/trial/DRKS00006866; Netherlands Trials Register NTR4962, https://www.onderzoekmetmensen.nl/en/trial/25452; ClinicalTrials.Gov NCT02389660, https://clinicaltrials.gov/study/NCT02389660; ClinicalTrials.gov NCT02361684, https://clinicaltrials.gov/study/NCT02361684; ClinicalTrials.gov NCT02449447, https://clinicaltrials.gov/study/NCT02449447; ClinicalTrials.gov NCT02410616, https://clinicaltrials.gov/study/NCT02410616; ISRCTN Registry ISRCTN12388725, https://www.isrctn.com/ISRCTN12388725?q=ISRCTN12388725&filters=&sort=&offset=1&totalResults=1&page=1&pageSize=10; ClinicalTrials.gov NCT02796573, https://classic.clinicaltrials.gov/ct2/show/NCT02796573.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s13063-016-1511-1.

Effectiveness of cannabis use and cannabis use disorder interventions: a European and international data synthesis

This data synthesis examined the effectiveness of behavioural and pharmacological approaches for cannabis treatment. We integrated findings from high level evidence studies and prioritised data from Europe when available. The synthesis found that only a relatively small number of published behavioural and pharmacological studies on cannabis interventions have been conducted in Europe. Applying both European and non-European data, it was found that Cognitive Behavioural Therapy (CBT) and/or Motivational Enhancement Therapy (MET) improved short-term outcomes in the frequency of cannabis use and dependency severity, although abstinence outcomes were less consistent. These improvements were typically not maintained nine months after treatment. CBT and MET (or combined CBT + MET) treatments that extend beyond four sessions were more effective than fewer sessions over a shorter duration. Combining CBT or MET (or combined CBT + MET) with adjunctive Contingency Management (CM) improved therapeutic outcomes. No pharmacotherapies have been approved for the management of cannabis use, cannabis use disorders or cannabis withdrawal. Despite only weak evidence to support the use of pharmacological agents, some are used 'off-label' to manage withdrawal symptoms outside clinical trials.

A mixed methods analysis of existing assessment and evaluation tools (AETs) for mental health applications

Introduction

Mental health Applications (MH Apps) can potentially improve access to high-quality mental health care. However, the recent rapid expansion of MH Apps has created growing concern regarding their safety and effectiveness, leading to the development of AETs (Assessment and Evaluation Tools) to help guide users. This article provides a critical, mixed methods analysis of existing AETs for MH Apps by reviewing the criteria used to evaluate MH Apps and assessing their effectiveness as evaluation tools.

Methods

To identify relevant AETs, gray and scholarly literature were located through stakeholder consultation, Internet searching via Google and a literature search of bibliographic databases Medline, APA PsycInfo, and LISTA. Materials in English that provided a tool or method to evaluate MH Apps and were published from January 1, 2000, to January 26, 2021 were considered for inclusion.

Results

Thirteen relevant AETs targeted for MH Apps met the inclusion criteria. The qualitative analysis of AETs and their evaluation criteria revealed that despite purporting to focus on MH Apps, the included AETs did not contain criteria that made them more specific to MH Apps than general health applications. There appeared to be very little agreed-upon terminology in this field, and the focus of selection criteria in AETs is often IT-related, with a lesser focus on clinical issues, equity, and scientific evidence. The quality of AETs was quantitatively assessed using the AGREE II, a standardized tool for evaluating assessment guidelines. Three out of 13 AETs were deemed 'recommended' using the AGREE II.

Discussion

There is a need for further improvements to existing AETs. To realize the full potential of MH Apps and reduce stakeholders' concerns, AETs must be developed within the current laws and governmental health policies, be specific to mental health, be feasible to implement and be supported by rigorous research methodology, medical education, and public awareness.

Examining the role of AI technology in online mental healthcare: opportunities, challenges, and implications, a mixed-methods review

Introduction

Online mental healthcare has gained significant attention due to its effectiveness, accessibility, and scalability in the management of mental health symptoms. Despite these advantages over traditional in-person formats, including higher availability and accessibility, issues with low treatment adherence and high dropout rates persist. Artificial intelligence (AI) technologies could help address these issues, through powerful predictive models, language analysis, and intelligent dialogue with users, however the study of these applications remains underexplored. The following mixed methods review aimed to supplement this gap by synthesizing the available evidence on the applications of AI in online mental healthcare.

Method

We searched the following databases: MEDLINE, CINAHL, PsycINFO, EMBASE, and Cochrane. This review included peer-reviewed randomized controlled trials, observational studies, non-randomized experimental studies, and case studies that were selected using the PRISMA guidelines. Data regarding pre and post-intervention outcomes and AI applications were extracted and analyzed. A mixed-methods approach encompassing meta-analysis and network meta-analysis was used to analyze pre and post-intervention outcomes, including main effects, depression, anxiety, and study dropouts. We applied the Cochrane risk of bias tool and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) to assess the quality of the evidence.

Results

Twenty-nine studies were included revealing a variety of AI applications including triage, psychotherapy delivery, treatment monitoring, therapy engagement support, identification of effective therapy features, and prediction of treatment response, dropout, and adherence. AI-delivered self-guided interventions demonstrated medium to large effects on managing mental health symptoms, with dropout rates comparable to non-AI interventions. The quality of the data was low to very low.

Discussion

The review supported the use of AI in enhancing treatment response, adherence, and improvements in online mental healthcare. Nevertheless, given the low quality of the available evidence, this study highlighted the need for additional robust and high-powered studies in this emerging field.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=443575, identifier CRD42023443575.

Digital Interventions to Understand and Mitigate Stress Response: Protocol for Process and Content Evaluation of a Cohort Study

BACKGROUND

Staffing and resource shortages, especially during the COVID-19 pandemic, have increased stress levels among health care workers. Many health care workers have reported feeling unable to maintain the quality of care expected within their profession, which, at times, may lead to moral distress and moral injury. Currently, interventions for moral distress and moral injury are limited.

OBJECTIVE

This study has the following aims: (1) to characterize and reduce stress and moral distress related to decision-making in morally complex situations using a virtual reality (VR) scenario and a didactic intervention; (2) to identify features contributing to mental health outcomes using wearable, physiological, and self-reported questionnaire data; and (3) to create a personal digital phenotype profile that characterizes stress and moral distress at the individual level.

METHODS

This will be a single cohort, pre- and posttest study of 100 nursing professionals in Ontario, Canada. Participants will undergo a VR simulation that requires them to make morally complex decisions related to patient care, which will be administered before and after an educational video on techniques to mitigate distress. During the VR session, participants will complete questionnaires measuring their distress and moral distress, and physiological data (electrocardiogram, electrodermal activity, plethysmography, and respiration) will be collected to assess their stress response. In a subsequent 12-week follow-up period, participants will complete regular assessments measuring clinical outcomes, including distress, moral distress, anxiety, depression, and loneliness. A wearable device will also be used to collect continuous data for 2 weeks before, throughout, and for 12 weeks after the VR session. A pre-post comparison will be conducted to analyze the effects of the VR intervention, and machine learning will be used to create a personal digital phenotype profile for each participant using the physiological, wearable, and self-reported data. Finally, thematic analysis of post-VR debriefing sessions and exit interviews will examine reoccurring codes and overarching themes expressed across participants' experiences.

RESULTS

The study was funded in 2022 and received research ethics board approval in April 2023. The study is ongoing.

CONCLUSIONS

It is expected that the VR scenario will elicit stress and moral distress. Additionally, the didactic intervention is anticipated to improve understanding of and decrease feelings of stress and moral distress. Models of digital phenotypes developed and integrated with wearables could allow for the prediction of risk and the assessment of treatment responses in individuals experiencing moral distress in real-time and naturalistic contexts. This paradigm could also be used in other populations prone to moral distress and injury, such as military and public safety personnel.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05923398; https://clinicaltrials.gov/study/NCT05923398.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/54180.

Ethical and Equitable Digital Health Research: Ensuring Self-Determination in Data Governance for Racialized Communities

Recent studies highlight the need for ethical and equitable digital health research that protects the rights and interests of racialized communities. We argue for practices in digital health that promote data self-determination for these communities, especially in data collection and management. We suggest that researchers partner with racialized communities to curate data that reflects their wellness understandings and health priorities, and respects their consent over data use for policy and other outcomes. These data governance approach honors and builds on Indigenous Data Sovereignty (IDS) decolonial scholarship by Indigenous and non-indigenous researchers and its adaptations to health research involving racialized communities from former European colonies in the global South. We discuss strategies to practice equity, diversity, inclusion, accessibility and decolonization (EDIAD) principles in digital health. We draw upon and adapt the concept of Precision Health Equity (PHE) to emphasize models of data sharing that are co-defined by racialized communities and researchers, and stress their shared governance and stewardship of data that is generated from digital health research. This paper contributes to an emerging research on equity issues in digital health and reducing health, institutional, and technological disparities. It also promotes the self-determination of racialized peoples through ethical data management.

Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health

Digital mental health (DMH) interventions, such as text-message-based lessons and activities, offer immense potential for accessible mental health support. While these interventions can be effective, real-world experimental testing can further enhance their design and impact. Adaptive experimentation, utilizing algorithms like Thompson Sampling for (contextual) multi-armed bandit (MAB) problems, can lead to continuous improvement and personalization. However, it remains unclear when these algorithms can simultaneously increase user experience rewards and facilitate appropriate data collection for social-behavioral scientists to analyze with sufficient statistical confidence. Although a growing body of research addresses the practical and statistical aspects of MAB and other adaptive algorithms, further exploration is needed to assess their impact across diverse real-world contexts. This paper presents a software system developed over two years that allows text-messaging intervention components to be adapted using bandit and other algorithms while collecting data for side-by-side comparison with traditional uniform random non-adaptive experiments. We evaluate the system by deploying a text-message-based DMH intervention to 1100 users, recruited through a large mental health non-profit organization, and share the path forward for deploying this system at scale. This system not only enables applications in mental health but could also serve as a model testbed for adaptive experimentation algorithms in other domains.

Online peer-led intervention to improve adolescent wellbeing during the COVID-19 pandemic: a randomised controlled trial

BACKGROUND

The COVID-19 pandemic and associated lockdown measures have posed a major risk to young people's wellbeing, which might be ameliorated by peer-led programmes. Using a randomised controlled trial (ISRCTN registry, number ISRCTN77941736 https://doi.org/10.1186/ISRCTN77941736 ), we tested the short-term efficacy of an online peer-led intervention designed to equip young people with skills to support their mental health and wellbeing during the COVID-19 pandemic.

METHODS

Through schools and social media ads, we recruited one hundred young people (aged 16-18) in the UK, focusing on areas with the highest incidence of COVID cases. In December 2020, participants were randomly allocated (1:1) to immediate 5 day Coping during COVID course (n = 49) or a wait-list (n = 51) through a survey software automated randomisation tool. Our primary outcome was self-reported mental wellbeing, and secondary outcomes included self-reported social connectedness, coping skills, sense of purpose, self-esteem, and self-compassion. We also collected qualitative reports of participants' perceived impact of the course and intentions to use what they have learnt from the course in their life moving forward. Assessments were completed at baseline, 1 week post randomisation (primary endpoint), and 2-weeks post-randomisation.

RESULTS

Young people allocated to the peer-led intervention reported significantly greater wellbeing, social connectedness, coping skills, sense of purpose, self-esteem, and self-compassion 1 week and 2 weeks post-randomisation (medium-large effect sizes). Specific benefits to mental health, sense of purpose and connectedness were also emphasised in qualitative reports.

CONCLUSIONS

An online, peer-led intervention targeting youth wellbeing during the context of the COVID-19 pandemic brought benefits across a range of outcomes, suggesting that structured programmes that incorporate peer-to-peer support can be a valuable approach to promote young people's wellbeing and foster psychological resources during a health crisis.

Development of a Multiplatform Tool for the Prevention of Prevalent Mental Health Pathologies in Adults: Protocol for a Randomized Control Trial

BACKGROUND

The prevalence of depression and anxiety has increased in recent years, with many individuals having trouble accessing mental health support. Smartphones have become an integral part of modern life, with apps offering new ways to deliver evidence-based self-help strategies to cope with common mental health symptoms. However, most of them do not have empirical evidence of their overall effectiveness or the effectiveness of their components, which could pose a risk for users.

OBJECTIVE

The aim of this study is to evaluate the effectiveness of the modules of evaluation, psychoeducation, and emotional regulation strategies in a multiplatform self-help mental health mobile app in the Maule region of Chile.

METHODS

A sample of 196 adults will be selected, who will be randomly assigned to different components of the app for a fixed period to assess its ability to reduce symptomatology.

RESULTS

The trial is not yet recruiting and is expected to end in October 2024. The first results are expected in April 2024.

CONCLUSIONS

This is the first study in Chile to develop and test the effectiveness of a mobile app to manage anxiety and depression symptoms in adults. The intervention proposed is based on evidence suggesting that the internet or remote intervention tools and self-management of prevalent symptomatology could be the future of mental health care systems in the digital era. If the effects of the intervention are positive, wide implementation in Chile and other Spanish-speaking countries could be possible in the future.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/52324.

Implementation of a Childcare-Based Obesity Prevention Program for Vulnerable Families During the COVID-19 Pandemic: Lessons for School Nurses

COVID-19 brought significant changes to the role of school nurses, necessitating the development of remote health education programs. However, there is a lack of evidence and pedagogical lessons for digitally transforming education for socially vulnerable children. This qualitative study analyzes the health educational needs and barriers faced by children and service providers in a childcare-based obesity prevention program during the pandemic in South Korea. Through a thematic content analysis, four core themes emerged: (a) heightened concerns about obesity and the pandemic's impact on facilities, (b) unexpected positive outcomes of the program, (c) digital readiness gaps, and (d) insufficient program satisfaction (better than nothing). When designing a digital-based health education program for vulnerable children, assessing individual readiness and facility suitability is crucial. Additionally, school nurses should incorporate hybrid pedagogy, integrating technology-mediated activities. By leveraging technology effectively and considering individual and environmental factors, educators can provide comprehensive and accessible health education.

Mobile applications in adolescent psychotherapy during the COVID-19 pandemic: a systematic review

Background

To bridge the gap in adolescent psychotherapy created by the increasing need for mental health interventions and the limited possibilities of in-person treatment during the pandemic, many health care providers opted to offer online mental health care programs. As a result, the number of mental health apps available in app stores experienced a sharp increase during the COVID-19 pandemic.

Objective

The aim of the current review is to provide an overview of feasibility and effectiveness studies testing mobile applications in adolescent psychotherapy during the peak phase of the COVID-19 pandemic.

Methods

We conducted a literature search in Pubmed, PsychInfo, Google Scholar, OpenSIGLE and OpenGREY for papers published from June 2020 to June 2023. Studies were included if they evaluated app-based interventions intended for psychotherapeutic treatment and targeted adolescents between 12 and 27 years of age with symptoms of psychological disorders. The quality of each study was assessed using the Systematic Assessment of Quality in Observational Research (SAQOR). Effectiveness outcomes were analyzed by vote counting and calculating a binomial probability test.

Results

The search yielded 31 relevant studies that examined 27 different apps with a total of 1,578 adolescent participants. Nine articles were primary effectiveness studies and 22 focused on feasibility measures as primary outcome. There was evidence that mental health apps influenced adolescents' psychotherapy, with 83% of the studies with effectiveness outcomes favoring the intervention (p = 0.002). Sixty-one percent of the included studies were rated at low or very low quality.

Conclusions

The pandemic has given apps a firm and important role in healthcare that will probably continue to expand in the future. To ensure that mental health apps are truly effective and beneficial for adolescents' psychotherapy, we need a standardized measurement of quality features of mental health apps and higher quality app evaluation studies.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=406455, PROSPERO International Prospective Register of Systematic Reviews [CRD42023406455].

Pragmatic Approach to the Assessment and Use of Digital Mental Health Interventions for Health Workers

Symptoms of poor mental health among working people, especially health workers, are on the rise in the United States, contributing to a burgeoning market of thousands of mental health technology products, few of which have undergone rigorous evaluation. Most research on these products focuses on deploying digital mental health interventions as ancillary support in clinical practice and community settings. Little is known of the effectiveness of these tools when employers offer them. We describe the landscape of digital mental health interventions, providing an overview of mental health conditions that are addressed with technology-based solutions in the workplace and the products and services available. We argue for employers to apply a methodical approach to evaluating and selecting technologies for their organizations, and we review relevant frameworks for evaluation. Considering the rapidly evolving landscape of digital mental health interventions, we offer evidence-informed recommendations to organizations and decision-makers seeking to support workplace mental health and well-being, and we advocate the development of products that help organizations assess how they can mitigate workplace conditions that may contribute to poorer mental health. (Am J Public Health. 2024;114(S2):S171-S179. https://doi.org/10.2105/AJPH.2023.307505).

Current evidence on the efficacy of mental health smartphone apps for symptoms of depression and anxiety. A meta-analysis of 176 randomized controlled trials

The mental health care available for depression and anxiety has recently undergone a major technological revolution, with growing interest towards the potential of smartphone apps as a scalable tool to treat these conditions. Since the last comprehensive meta-analysis in 2019 established positive yet variable effects of apps on depressive and anxiety symptoms, more than 100 new randomized controlled trials (RCTs) have been carried out. We conducted an updated meta-analysis with the objectives of providing more precise estimates of effects, quantifying generalizability from this evidence base, and understanding whether major app and trial characteristics moderate effect sizes. We included 176 RCTs that aimed to treat depressive or anxiety symptoms. Apps had overall significant although small effects on symptoms of depression (N=33,567, g=0.28, p<0.001; number needed to treat, NNT=11.5) and generalized anxiety (N=22,394, g=0.26, p<0.001, NNT=12.4) as compared to control groups. These effects were robust at different follow-ups and after removing small sample and higher risk of bias trials. There was less variability in outcome scores at post-test in app compared to control conditions (ratio of variance, RoV=-0.14, 95% CI: -0.24 to -0.05 for depressive symptoms; RoV=-0.21, 95% CI: -0.31 to -0.12 for generalized anxiety symptoms). Effect sizes for depression were significantly larger when apps incorporated cognitive behavioral therapy (CBT) features or included chatbot technology. Effect sizes for anxiety were significantly larger when trials had generalized anxiety as a primary target and administered a CBT app or an app with mood monitoring features. We found evidence of moderate effects of apps on social anxiety (g=0.52) and obsessive-compulsive (g=0.51) symptoms, a small effect on post-traumatic stress symptoms (g=0.12), a large effect on acrophobia symptoms (g=0.90), and a non-significant negative effect on panic symptoms (g=-0.12), although these results should be considered with caution, because most trials had high risk of bias and were based on small sample sizes. We conclude that apps have overall small but significant effects on symptoms of depression and generalized anxiety, and that specific features of apps - such as CBT or mood monitoring features and chatbot technology - are associated with larger effect sizes.

Deep breathing in your hands: designing and assessing a DTx mobile app

Digital Therapeutics (DTx) are experiencing rapid advancements within mobile and mental healthcare sectors, with their ubiquity and enhanced accessibility setting them apart as uniquely effective solutions. In this evolving context, our research focuses on deep breathing, a vital technique in mental health management, aiming to optimize its application in DTx mobile platforms. Based on well-founded theories, we introduced a gamified and affordance-driven design, facilitating intuitive breath control. To enhance user engagement, we deployed the Mel Frequency Cepstral Coefficient (MFCC)-driven personalized machine learning method for accurate biofeedback visualization. To assess our design, we enlisted 70 participants, segregating them into a control and an intervention group. We evaluated Heart Rate Variability (HRV) metrics and collated user experience feedback. A key finding of our research is the stabilization of the Standard Deviation of the NN Interval (SDNN) within Heart Rate Variability (HRV), which is critical for stress reduction and overall health improvement. Our intervention group observed a pronounced stabilization in SDNN, indicating significant stress alleviation compared to the control group. This finding underscores the practical impact of our DTx solution in managing stress and promoting mental health. Furthermore, in the assessment of our intervention cohort, we observed a significant increase in perceived enjoyment, with a notable 22% higher score and 10.69% increase in positive attitudes toward the application compared to the control group. These metrics underscore our DTx solution's effectiveness in improving user engagement and fostering a positive disposition toward digital therapeutic efficacy. Although current technology poses challenges in seamlessly incorporating machine learning into mobile platforms, our model demonstrated superior effectiveness and user experience compared to existing solutions. We believe this result demonstrates the potential of our user-centric machine learning techniques, such as gamified and affordance-based approaches with MFCC, which could contribute significantly to the field of mobile mental healthcare.

An integrated knowledge translation (iKT) approach to advancing community-based depression care in Vietnam: lessons from an ongoing research-policy collaboration

BACKGROUND

Evidence-based mental health policies are key to supporting the expansion of community-based mental health care and are increasingly being developed in low and middle-income countries (LMICs). Despite this, research on the process of mental health policy development in LMICs is limited. Engagement between researchers and policy makers via an integrated Knowledge Translation (iKT) approach can help to facilitate the process of evidence-based policy making. This paper provides a descriptive case study of a decade-long policy and research collaboration between partners in Vietnam, Canada and Australia to advance mental health policy for community-based depression care in Vietnam.

METHODS

This descriptive case study draws on qualitative data including team meeting minutes, a focus group discussion with research team leaders, and key informant interviews with two Vietnamese policy makers. Our analysis draws on Murphy et al.'s (2021) findings and recommendations related to stakeholder engagement in global mental health research.

RESULTS

Consistent with Murphy et al.'s findings, facilitating factors across three thematic categories were identified. Related to 'the importance of understanding context', engagement between researchers and policy partners from the formative research stage provided a foundation for engagement that aligned with local priorities. The COVID-19 pandemic acted as a catalyst to further advance the prioritization of mental heath by the Government of Vietnam. 'The nature of engagement' is also important, with findings demonstrating that long-term policy engagement was facilitated by continuous funding mechanisms that have enabled trust-building and allowed the research team to respond to local priorities over time. 'Communication and dissemination' are also crucial, with the research team supporting mental health awareness-raising among policy makers and the community, including via capacity building initiatives.

CONCLUSIONS

This case study identifies factors influencing policy engagement for mental health system strengthening in an LMIC setting. Sustained engagement with policy leaders helps to ensure alignment with local priorities, thus facilitating uptake and scale-up. Funding agencies can play a crucial role in supporting mental health system development through longer term funding mechanisms. Increased research related to the policy engagement process in global mental health will further support policy development and improvement in mental health care in LMICs.

Best practice for integrating digital interventions into clinical care for young people at risk of suicide: a Delphi study

BACKGROUND

Digital tools have the capacity to complement and enhance clinical care for young people at risk of suicide. Despite the rapid rise of digital tools, their rate of integration into clinical practice remains low. The poor uptake of digital tools may be in part due to the lack of best-practice guidelines for clinicians and services to safely apply them with this population.

METHODS

A Delphi study was conducted to produce a set of best-practice guidelines for clinicians and services on integrating digital tools into clinical care for young people at risk of suicide. First, a questionnaire was developed incorporating action items derived from peer-reviewed and grey literature, and stakeholder interviews with 17 participants. Next, two independent expert panels comprising professionals (academics and clinical staff; n = 20) and young people with lived experience of using digital technology for support with suicidal thoughts and behaviours (n = 29) rated items across two consensus rounds. Items reaching consensus (rated as "essential" or "important" by at least 80% of panel members) at the end of round two were collated into a set of guidelines.

RESULTS

Out of 326 individual items rated by the panels, 188 (57.7%) reached consensus for inclusion in the guidelines. The endorsed items provide guidance on important topics when working with young people, including when and for whom digital tools should be used, how to select a digital tool and identify potentially harmful content, and identifying and managing suicide risk conveyed via digital tools. Several items directed at services (rather than individual clinicians) were also endorsed.

CONCLUSIONS

This study offers world-first evidence-informed guidelines for clinicians and services to integrate digital tools into clinical care for young people at risk of suicide. Implementation of the guidelines is an important next step and will hopefully lead to improved uptake of potentially helpful digital tools in clinical practice.

Adapting the ADVANCE group program for digitally-supported delivery to reduce intimate partner violence by men in substance use treatment: a feasibility study

Introduction

COVID-19 restrictions created barriers to "business as usual" in healthcare but also opened the door to innovation driven by necessity. This manuscript (1) describes how ADVANCE, an in-person group perpetrator program to reduce intimate partner violence (IPV) against female (ex)partners by men in substance use treatment, was adapted for digitally-supported delivery (ADVANCE-D), and (2) explores the feasibility and acceptability of delivering ADVANCE-D to men receiving substance use treatment.

Methods

Firstly, the person-based approach and mHealth development framework were used to iteratively adapt ADVANCE for digitally-supported delivery including conceptualization, formative research, and pre-testing. Then, a non-randomized feasibility study was conducted to assess male participants' eligibility, recruitment, and attendance rates and uptake of support offered to their (ex)partners. Exploratory analyses on reductions in IPV perpetration (assessed using the Abusive Behavior Inventory; ABI) and victimization (using the revised ABI; ABI-R) at the end of the program were performed. Longitudinal qualitative interviews with participants, their (ex)partners, and staff provided an understanding of the program's implementation, acceptability, and outcomes.

Results

The adapted ADVANCE-D program includes one goal-setting session, seven online groups, 12 self-directed website sessions, and 12 coaching calls. ADVANCE-D includes enhanced risk management and support for (ex)partners. Forty-five participants who had perpetrated IPV in the past 12 months were recruited, forty of whom were offered ADVANCE-D, attending 11.4 (SD 9.1) sessions on average. Twenty-one (ex)partners were recruited, 13 of whom accepted specialist support. Reductions in some IPV perpetration and victimization outcome measures were reported by the 25 participants and 11 (ex)partners interviewed pre and post-program, respectively. Twenty-two participants, 11 (ex)partners, 12 facilitators, and 7 integrated support service workers were interviewed at least once about their experiences of participation. Overall, the program content was well-received. Some participants and facilitators believed digital sessions offered increased accessibility.

Conclusion

The digitally-supported delivery of ADVANCE-D was feasible and acceptable. Remote delivery has applicability post-pandemic, providing greater flexibility and access. Given the small sample size and study design, we do not know if reductions in IPV were due to ADVANCE-D, time, participant factors, or chance. More research is needed before conclusions can be made about the efficacy of ADVANCE-D.

Trends in forgone medical care and unmet needs among Medicare beneficiaries with a history of depression during the COVID-19 pandemic: a national, repeated cross-sectional study

OBJECTIVES

To investigate trends in forgone medical care, basic needs disruption, financial and mental health disruption, engagement of preventive behaviours guidelines, and perceived severity of COVID-19 among community-living Medicare beneficiaries in the USA with and without a self-reported history of depression from Summer 2020 to Winter 2021.

DESIGN/SETTING

A repeated cross-sectional study using a nationally representative sample of Medicare beneficiaries of three rounds of survey data from the Medicare Current Beneficiary Survey COVID-19 Supplement Public Use Files: Summer 2020, Fall 2020 and Winter 2021.

PARTICIPANTS

A total of 28 480 community-dwelling Medicare beneficiaries.

MAIN OUTCOME MEASURES

Forgone medical care, basic needs disruption, financial and mental health disruption, engagement of preventive behaviours guidelines, and perceived severity of COVID-19.

RESULTS

In the study sample, 7629 (27%) had a history of depression. After adjusting for potential confounders, weighted multivariable logistic regression models showed that Medicare beneficiaries with a history of depression had higher odds of foregone medical care (OR: 1.29, 95% CI 1.16 to 1.42, p<0.001), of basic need disruption (OR: 1.49, 95% CI 1.33 to 1.67, p<0.001), and of financial and mental health disruption (OR: 1.75, 95% CI 1.60 to 1.91, p<0.001) during the COVID-19 pandemic when compared with those without a history of depression. No statistically significant differences were observed in engagement of essential preventive behaviours or perception of COVID-19 severity.

CONCLUSIONS

COVID-19 pandemic may exacerbate existing barriers to healthcare access and financial and social needs, possibly leading to persistent unmet needs among Medicare beneficiaries with a history of depression beyond the pandemic.

Telehealth uptake among middle-aged and older Americans during COVID-19: chronic conditions, social media communication, and race/ethnicity

OBJECTIVES

This study investigated whether and to what extent constructs of the protection motivation theory of health (PMT)-threat appraisal (perceived vulnerability/severity) and coping appraisal (response efficacy and self-efficacy)-are related to telehealth engagement during the COVID-19 pandemic, and how these associations differ by race/ethnicity among middle-aged and older Americans.

METHODS

Data were from the 2020 Health and Retirement Study. Multivariable ordinary least-squares regression analyses were computed adjusting for health and sociodemographic factors.

RESULTS

Some PMT constructs are useful in understanding telehealth uptake. Perceived vulnerability/severity, particularly comorbidity (b = 0.13, 95% confidence interval (CI) [0.11, 0.15], p < 0.001), and response efficacy, particularly participation in communication via social media (b = 0.24, 95% CI [0.21, 0.27], p < 0.001), were significantly and positively associated with higher telehealth uptake during the COVID-19 pandemic among middle-aged and older Americans. Non-Hispanic Black adults were more likely to engage in telehealth during the pandemic than their non-Hispanic White counterparts (b = 0.20, 95% CI [0.12, 0.28], p < 0.001). Multiple moderation analyses revealed the significant association between comorbidity and telehealth uptake was similar across racial/ethnic groups, whereas the significant association between social media communication and telehealth uptake varied by race/ethnicity. Specifically, the association was significantly less pronounced for Hispanic adults (b = -0.11, 95% CI [-0.19, -0.04], p < 0.01) and non-Hispanic Asian/other races adults (b = -0.13, 95% CI [-0.26, -0.01], p < 0.05) than it was for their non-Hispanic White counterparts.

CONCLUSION

Results suggest the potential of using social media and telehealth to narrow health disparities, particularly serving as a bridge for members of underserved communities to telehealth uptake.

Mental health provider and youth service users' perspectives regarding implementation of a digital mental health platform for youth: A survey study

Background

For youth and young adults (YYAs) with mental health concerns, digital mental health (dMH) can improve access to care and support collaboration with providers. Measurement-based care using a dMH platform may further optimize YYA outcomes by individualizing treatment approaches. Engaging service providers and YYA provides an opportunity to better understand how to mitigate implementation challenges.

Aim

Explore the experiences of mental health care providers and YYAs regarding the implementation of a dMH platform for YYAs accessing mental health care in multiple care settings.

Methods

Mental health care providers and YYA service users completed an electronic survey exploring their experiences and perceptions of implementing a dMH platform. Survey design, data analysis, and reporting were informed by the Consolidated Framework for Implementation Research (CFIR).

Results

A total of 195 individuals (100 providers, 95 YYAs) responded. Of those, 48 providers and 79 YYAs reported using the platform at least once. Both groups identified several important factors supporting implementation including collaborative relationships between providers and YYAs, the ability to monitor mental health outcomes, and increased YYA engagement in care. The need for increased provider training and automatic reminders for YYAs to use the platform were common barriers. Each group perceived the other to be uninterested in using the platform, highlighting the importance of using all stakeholder views to inform implementation planning.

Conclusions

Successful implementation of dMH for care of YYA requires ongoing, user-informed training, integration into existing workflows, and alignment with YYA priorities for care. Future work exploring provider and youth perceptions of the others' "buy-in" is needed to inform future implementation strategies.

Perceptions of mental health providers of the barriers and facilitators of using and engaging youth in digital mental-health-enabled measurement based care

Objectives

Increased rates of mental health disorders and substance use among youth and young adults have increased globally, furthering the strain on an already burdened mental health system. Digital solutions have been proposed as a potential option for the provision of timely mental health services for youth, with little research exploring mental health professional views about using such innovative tools. In Alberta, Canada, we are evaluating the implementation and integration of a digital mental health (dMH) platform into existing service pathways. Within this paper we seek to explore mental health professionals' perceptions of the barriers and facilitators that may influence their utilization of digital MH-enabled measurement-based care (MBC) with the youth who access their services.

Methods

A qualitative, descriptive methodology was used to inductively generate themes from focus groups conducted with mental health professionals from specialized mental health services and primary care networks in Alberta.

Results

As mental health professionals considered the barriers and facilitators of using dMH with youth, they referenced individual and family barriers and facilitators to consider. Providers highlighted perceived barriers, including: first, cultural stigma, family apprehension about mental health care, and parental access to dMH and MBC as deterrents to providers adopting digital platforms in routine care; second, perceptions of increased responsibility and liability for youth in crisis; third, perception that some psychiatric and neurodevelopmental disorders in youth are not amenable to dMH; fourth, professionals contemplated youth readiness to engage with dMH-enabled MBC. Participants also highlighted pertinent facilitators to dMH use, noting: first, the suitability of dMH for youth with mild mental health concerns; second, youth motivated to report their changes in mental health symptoms; and lastly, youth proficiency and preference for dMH options.

Conclusions

By identifying professionals' perceptions of barriers and facilitators for youth users, we may better understand how to address misconceptions about who is eligible and appropriate for dMH through training and education.

Artificial Intelligence and Decision-Making in Healthcare: A Thematic Analysis of a Systematic Review of Reviews

Introduction

The use of artificial intelligence (AI), which can emulate human intelligence and enhance clinical results, has grown in healthcare decision-making due to the digitalization effects and the COVID-19 pandemic. The purpose of this study was to determine the scope of applications of AI tools in the decision-making process in healthcare service delivery networks.

Materials and methods

This study used a qualitative method to conduct a systematic review of the existing reviews. Review articles published between 2000 and 2024 in English-language were searched in PubMed, Scopus, ProQuest, and Cochrane databases. The CASP (Critical Appraisal Skills Programme) Checklist for Systematic Reviews was used to evaluate the quality of the articles. Based on the eligibility criteria, the final articles were selected and the data extraction was done independently by 2 authors. Finally, the thematic analysis approach was used to analyze the data extracted from the selected articles.

Results

Of the 14 219 identified records, 18 review articles were eligible and included in the analysis, which covered the findings of 669 other articles. The quality assessment score of all reviewed articles was high. And, the thematic analysis of the data identified 3 main themes including clinical decision-making, organizational decision-making, and shared decision-making; which originated from 8 subthemes.

Conclusions

This study revealed that AI tools have been applied in various aspects of healthcare decision-making. The use of AI can improve the quality, efficiency, and effectiveness of healthcare services by providing accurate, timely, and personalized information to support decision-making. Further research is needed to explore the best practices and standards for implementing AI in healthcare decision-making.

Acceptance and Commitment Therapy for Major Depressive Disorder: Navigating Depression Treatment in Traditional and Digital Settings with Insights from Current Research

Given the shortcomings of a mechanistic assumption of traditional cognitive behavioral therapy (CBT), a newer generation of CBT-grounded interventions focusing on process-orientated emotional and motivational aspects has emerged. These so-called third-wave CBTs emphasize function and context of inner experience over form and content, and have become evidence-based practice in the past four decades. Among these approaches, acceptance and commitment therapy (ACT) has both a large body of research for various (mental) health conditions, including major depressive disorder (MDD) in particular. ACT is a transdiagnostic approach that intends to increase psychological flexibility (PF) of clients as a universal mechanism of behavior change and a value-driven orientation in life. By focusing on present-moment awareness, acceptance, defusion, establishing a stable sense of self, clarifying personal valued life directions, and committing to behaviors consistent to these values, ACT targets the core processes of PF. Meta-analyses have indicated the efficacy and effectiveness of ACT in reducing depressive symptoms and increasing well-being, with mainly moderate effect sizes in clinical trials. ACT for MDD has been shown to be effective across different delivery modes (e.g., individual, group, digital). ACT can also be applied using self-help formats (e.g., mobile apps) and combined with features from compatible approaches like behavioral activation. There is also evidence for a high acceptability of ACT and adherence rates comparable to classic CBT. Moreover, process research has shown that ACT works specifically through the mediator of PF and by addressing its suggested core therapeutic processes. Given the essential role of offering a personalized therapeutic strategy in treatment outcomes and adherence, it is central to provide more effective options that match clients' needs and preferences. This chapter illustrates different applications of ACT for adults with MDD and the current evidence base to promote informed decisions on using ACT as additional or stand-alone therapeutic approach.

Assessing the Impact of Evidence-Based Mental Health Guidance During the COVID-19 Pandemic: Systematic Review and Qualitative Evaluation

BACKGROUND

During the COVID-19 pandemic, the Oxford Precision Psychiatry Lab (OxPPL) developed open-access web-based summaries of mental health care guidelines (OxPPL guidance) in key areas such as digital approaches and telepsychiatry, suicide and self-harm, domestic violence and abuse, perinatal care, and vaccine hesitancy and prioritization in the context of mental illness, to inform timely clinical decision-making.

OBJECTIVE

This study aimed to evaluate the practice of creating evidence-based health guidelines during health emergencies using the OxPPL guidance as an example. An international network of clinical sites and colleagues (in Australia, New Zealand, and the United Kingdom) including clinicians, researchers, and experts by experience aimed to (1) evaluate the clinical impact of the OxPPL guidance, as an example of an evidence-based summary of guidelines; (2) review the literature for other evidence-based summaries of COVID-19 guidelines regarding mental health care; and (3) produce a framework for response to future global health emergencies.

METHODS

The impact and clinical utility of the OxPPL guidance were assessed using clinicians' feedback via an international survey and focus groups. A systematic review (protocol registered on Open Science Framework) identified summaries or syntheses of guidelines for mental health care during and after the COVID-19 pandemic and assessed the accuracy of the methods used in the OxPPL guidance by identifying any resources that the guidance had not included.

RESULTS

Overall, 80.2% (146/182) of the clinicians agreed or strongly agreed that the OxPPL guidance answered important clinical questions, 73.1% (133/182) stated that the guidance was relevant to their service, 59.3% (108/182) said that the guidelines had or would have a positive impact on their clinical practice, 42.9% (78/182) that they had shared or would share the guidance, and 80.2% (146/182) stated that the methodology could be used during future health crises. The focus groups found that the combination of evidence-based knowledge, clinical viewpoint, and visibility was crucial for clinical implementation. The systematic review identified 2543 records, of which 2 syntheses of guidelines met all the inclusion criteria, but only 1 (the OxPPL guidance) used evidence-based methodology. The review showed that the OxPPL guidance had included the majority of eligible guidelines, but 6 were identified that had not been included.

CONCLUSIONS

The study identified an unmet need for web-based, evidence-based mental health care guidance during the COVID-19 pandemic. The OxPPL guidance was evaluated by clinicians as having a real-world clinical impact. Robust evidence-based methodology and expertise in mental health are necessary, but easy accessibility is also needed, and digital technology can materially help. Further health emergencies are inevitable and now is the ideal time to prepare, including addressing the training needs of clinicians, patients, and carers, especially in areas such as telepsychiatry and digital mental health. For future planning, guidance should be widely disseminated on an international platform, with allocated resources to support adaptive updates.