Peer Support: a Human Factor to Enhance Engagement in Digital Health Behavior Change Interventions

Digital health technology provides opportunities to leverage artificial intelligence and other digital applications to promote cardiovascular health. Digital health technologies include artificial intelligence (such as machine learning [ML], neural networks),1 analytic systems, mobile apps, wearables, email, text messaging, and telemedicine.2 In this article, we review the role of digital technology in cardiovascular health and a selection of recent studies to evaluate the evidence of its effectiveness. Artificial intelligence is broadly defined as the capability of computer systems to perform tasks similar to humans.3 Examples include vision, speech, pattern recognition, and decision making. Machine learning is the ability of the computer program to learn from experience. This typically occurs from analysis of large sets of data processed through human-derived algorithms to enhance, predict, and explain outcomes.4 An example of the use of ML in clinical care is cardiovascular disease (CVD) prediction and electrocardiographic interpretation. Neural networks, named after the human nervous system, are nonlinear statistic models that control where signals are sent. Neural networks can be used for decision making such as cardiovascular diagnosis confirmation. Digital Technology Use in Cardiovascular Risk Assessment Several studies have demonstrated improved CVD risk factor identification using ML compared with traditional risk assessment tools. Researchers developed an ML risk calculator and compared it with the American College of Cardiology/American Heart Association CVD risk calculator in 6459 participants from the Multi-Ethnic Study of Atherosclerosis.5 Study participants were free of CVD at baseline and followed for 13 years. Results revealed that the American College of Cardiology/American Heart Association risk calculator was less precise: statin therapy was recommended to 46% of the sample, with 23.8% of CVD events occurring in those not recommended a statin. In comparison, the ML risk calculator recommended a statin to 11% of the sample, with 14.4% of CVD events occurring in those not recommended a statin.5 Similarly in 3 cohorts from Australia, 4 ML models were developed and compared with the 2008 Framingham model. The ML models provided 2.7% to 5.2% better predictions across all 3 cohorts.6 Taken together, the authors of these studies suggest ML provides promise in providing more precise estimates of CVD risk. Digital Health Interventions for Cardiovascular Disease Prevention Digital health interventions have the potential to provide a personalized approach to promote cardiovascular health. Behavior change theory is a key component of digital interventions and includes theoretical frameworks such as supportive accountability,7 self-efficacy theory,8 social cognitive theory, and the health belief model.9 Precision healthcare has been promoted for decades. Many of the challenges in operationalizing precision healthcare are healthcare accessibility, scheduling, care continuity, and inadequate knowledge exchange between provides and patients.10 Thus, promotion of healthy lifestyles and lifestyle risk factor reduction remain inadequately addressed in patients with CVD.11 To achieve sustainable change, individual-level personalized strategies may be leveraged through digital health interventions. Evidence of the effectiveness of digital health interventions has varied but is promising overall. Text messaging has been successfully used to provide information regarding healthy diet and physical activity recommendations, monitoring, and individual feedback. Text messaging has resulted in improvements in diet and activity in many (TextMe,12 Mobile MyPlate,13 MyQuest,14 Text-To-Move15), but not all studies.16 Smartphone/mobile apps have been designed to improve dietary and physical activity behavior. Examples include apps that track dietary patterns and activity through user input of text or visual images.17,18 Users can set their own goals and receive feedback on progress toward goals. Reviews of smartphone apps have had variable results with many demonstrating short-term improvement. Villinger et al19 conducted a systematic review and meta-analysis of the effectiveness of mobile app interventions on nutrition behaviors (41 studies, 27 randomized controlled trials [RCTs]). Findings revealed significantly improved nutrition behaviors and nutrition-related outcomes (P = .004 and P = .043, respectively). A second systematic review of 27, primarily RCTs, found significant between-group improvements in 19 of the 27 studies.20 A meta-analysis of 6 RCTs in adults using a smartphone app as the primary component of the intervention revealed a trend for more steps per day in the intervention compared with the control groups, with programs lasting less than 3 months more effective than longer programs.21 Taken together, text messaging and smartphone/mobile apps have the potential to improve lifestyle behaviors associated with cardiovascular health. The addition of strategies to increase sustainability of the effects needs to be assessed. Digital Health Interventions: Primary and Secondary Prevention Widmer et al2 conducted a meta-analysis of 51 RCTs and cohort studies using digital health interventions for the prevention of CVD events and risk factor modification. Subgroup analyses of primary prevention studies (2 studies) did not provide evidence of a statistically significant reduction in CVD outcomes. However, evaluation of individual risk factors in primary prevention studies found a significant reduction in weight (11 studies; −3.35 lb), systolic blood pressure (23 studies; mean difference, −2.12 mm Hg), total cholesterol (13 studies; mean difference, −5.19 mg/dL), low-density lipoprotein cholesterol (8 studies; mean difference, −4.96 mg/dL), and glucose (6 studies; mean difference, −1.38 mg/dL).2 A subgroup analysis of secondary prevention studies demonstrated a significant impact of digital interventions on CVD outcomes (relative risk, 0.60; a 40% relative risk reduction), improvement in body mass index (6 studies; mean difference, −0.31 kg/m2) but no improvement in weight, systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, and glucose. Taken together, this meta-analysis suggested that digital interventions were beneficial not only in lowering CVD events in higher-risk patients but also in lowering risk factors in primary prevention approaches.2 In a second meta-analysis conducted by Akinosun et al,11 researchers analyzed 25 RCTs in patients with traditional CVD risk factors who received a digital intervention versus usual care.11 Findings revealed benefits in total cholesterol (mean difference, −0.29), high-density lipoprotein cholesterol (mean difference, −0.09), low-density lipoprotein (mean difference, 0.18), physical activity (mean difference 0.23), physical inactivity (relative risk, 0.54), and diet (relative risk, 0.79). There was no significant improvement in body mass index, systolic and diastolic blood pressure, hemoglobin A1C, alcohol intake, smoking, and medication adherence. Authors concluded that digital interventions were more effective at improving healthy behaviors than reducing unhealthy behaviors. In patients who experienced a myocardial infarction, a digital health intervention providing medication reminders, vital sign and activity tracking, education, and outpatient care coordination resulted in a 52% lower 30-day readmission rate compared with usual care.22 Sociodemographic characteristics (age, sex, and race) did not influence use of the digital intervention, highlighting a potential role for digital interventions in the promotion of equity in social determinants of health.23 Digital Health Interventions in Cardiac Rehabilitation Cardiac rehabilitation is an essential component of secondary prevention of CVD.24 Some patients face barriers in participation in cardiac rehabilitation due to physical accessibility, time, and travel.25 Digital health interventions have the potential to bridge these barriers and increase participation. Digital delivery of cardiac rehabilitation therapy with real-time personalized support has several advantages.26 In a systematic review of 31 studies in which authors examined digital health interventions for cardiac rehabilitation, the results revealed that cardiac rehabilitation program adherence was greater in patients using digital interventions than traditional methods alone. Secondary benefits were found in self-efficacy, weight management, diet, and quality of life. Taken together, digital cardiac rehabilitation was feasible and effective whether used alone or in combination with traditional cardiac rehabilitation.26 Conclusion Digital health technology is an evolving field with tremendous potential to improve cardiovascular health. Cardiovascular disease remains the major cause of death in the United States. The age-adjusted mortality rate has increased in the last decade. More people died from CVD causes in 2020 (nearly 900 000 deaths) than any year since 2003.27 Opportunities to reduce CVD and CVD risk have not been fully leveraged, and digital technology interventions have the potential to meet this need. Digital health technology also has the potential to provide equitable and personalized care. Device data, electronic medical record data, and social determinants of health data provide an opportunity to combine and identify longitudinal trends and risk factors before CVD begins. In the future, large data sets can be created that can be analyzed using ML to identify patterns and structures within and among the data to provide a more robust risk assessment to promote CVD prevention.

Adolescents with type 1 diabetes (T1D) experience higher rates of psychological disorders compared with their healthy peers. As poor psychological health has been associated with suboptimal glycaemic control and more frequent complications, there is an urgent need to develop more 'clinically usable' interventions. Digital mental health interventions offer unique advantages compared with in-person interventions; however, what adolescents with T1D want in terms of content and functionality is poorly understood. Accordingly, the current study conducted focus groups to examine the views of adolescents with T1D regarding digital mental health interventions. Four focus groups were conducted, including 16 adolescents with T1D, ranging from 13 to 17years in age (69% female). Transcripts were analysed using directed content analysis to examine (1) 'what adolescents dislike about existing digital mental health interventions?' and (2) 'what adolescents want in future digital mental health interventions?'. Findings provide a preliminary understanding of what adolescents dislike and also the type of content and functional features, which may be important to include in digital mental health programs for this population, such as a peer support feature (reported by 16 of 16), emotion and diabetes check-in feature (11 of 16) and diabetes-relevant content (12 of 16). Early data suggest that digital mental health interventions should include a significant peer support element, diabetes-relevant content and examples, and check-in on their mental health and diabetes self-management regularly, while avoiding fixed responses or modules and non-age-appropriate content. Based on these findings, a digital intervention is currently being developed.

BackgroundThere is a high prevalence of children and young people (CYP) experiencing mental health (MH) problems. Owing to accessibility, affordability, and scalability, an increasing number of digital health interventions (DHIs) have been developed and incorporated into MH treatment. Studies have shown the potential of DHIs to improve MH outcomes. However, the modes of delivery used to engage CYP in digital MH interventions may differ, with implications for the extent to which findings pertain to the level of engagement with the DHI. Knowledge of the various modalities could aid in the development of interventions that are acceptable and feasible.ObjectiveThis review aimed to (1) identify modes of delivery used in CYP digital MH interventions, (2) explore influencing factors to usage and implementation, and (3) investigate ways in which the interventions have been evaluated and whether CYP engage in DHIs.MethodsA literature search was performed in the Cochrane Library, Excerpta Medica dataBASE (EMBASE), Medical Literature Analysis and Retrieval System Online (MEDLINE), and PsycINFO databases using 3 key concepts “child and adolescent mental health,” “digital intervention,” and “engagement.” Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed using rigorous inclusion criteria and screening by at least two reviewers. The selected articles were assessed for quality using the mixed methods appraisal tool, and data were extracted to address the review aims. Data aggregation and synthesis were conducted and presented as descriptive numerical summaries and a narrative synthesis, respectively.ResultsThis study identified 6 modes of delivery from 83 articles and 71 interventions for engaging CYP: (1) websites, (2) games and computer-assisted programs, (3) apps, (4) robots and digital devices, (5) virtual reality, and (6) mobile text messaging. Overall, 2 themes emerged highlighting intervention-specific and person-specific barriers and facilitators to CYP’s engagement. These themes encompassed factors such as suitability, usability, and acceptability of the DHIs and motivation, capability, and opportunity for the CYP using DHIs. The literature highlighted that CYP prefer DHIs with features such as videos, limited text, ability to personalize, ability to connect with others, and options to receive text message reminders. The findings of this review suggest a high average retention rate of 79% in studies involving various DHIs.ConclusionsThe development of DHIs is increasing and may be of interest to CYP, particularly in the area of MH treatment. With continuous technological advancements, it is important to know which modalities may increase engagement and help CYP who are facing MH problems. This review identified the existing modalities and highlighted the influencing factors from the perspective of CYP. This knowledge provides information that can be used to design and evaluate new interventions and offers important theoretical insights into how and why CYP engage in DHIs.

BackgroundDigital mental health interventions are increasingly prevalent in the current context of rapidly evolving technology, and research indicates that they yield effectiveness outcomes comparable to in-person treatment. Integrating professionals (ie, psychologists and physicians) into digital mental health interventions has become common, and the inclusion of guidance within programs can increase adherence to interventions. However, employing professionals to enhance mental health programs may undermine the scalability of digital interventions. Therefore, delegating guidance tasks to paraprofessionals (peer supporters, technicians, lay counsellors, or other nonclinicians) can help reduce costs and increase accessibility.ObjectiveThis systematic review and meta-analysis evaluates the effectiveness, adherence, and other process outcomes of nonclinician-guided digital mental health interventions.MethodsFour databases (MEDLINE, Embase, CINAHL, and PsycINFO) were searched for randomized controlled trials published between 2010 and 2020 examining digital mental health interventions. Three journals that focus on digital intervention were hand searched; gray literature was searched using ProQuest and the Cochrane Central Register of Control Trials (CENTRAL). Two researchers independently assessed risk of bias using the Cochrane risk-of-bias tool version 2. Data were collected on effectiveness, adherence, and other process outcomes, and meta-analyses were conducted for effectiveness and adherence outcomes. Nonclinician-guided interventions were compared with treatment as usual, clinician-guided interventions, and unguided interventions.ResultsThirteen studies qualified for inclusion. Nonclinician-guided interventions yielded higher posttreatment effectiveness outcomes when compared to conditions involving control programs (eg, online psychoeducation and monitored attention control) or wait-list controls (k=7, Hedges g=–0.73; 95% CI –1.08 to –0.38). There were also significant differences between nonclinician-guided interventions and unguided interventions (k=6, Hedges g=–0.17; 95% CI –0.23 to –0.11). In addition, nonclinician-guided interventions did not differ in effectiveness from clinician-guided interventions (k=3, Hedges g=0.08; 95% CI –0.01 to 0.17). These results suggest that guided digital mental health interventions are helpful to improve mental health outcomes regardless of the qualifications of the individual performing the intervention, and that the presence of a nonclinician guide improves effectiveness outcomes compared to having no guide. Nonclinician-guided interventions did not yield significantly different adherence outcomes when compared with unguided interventions (k=3, odds ratio 1.58; 95% CI 0.51 to 4.92), although a general trend of improved adherence was observed within nonclinician-guided interventions.ConclusionsIntegrating paraprofessionals and nonclinicians appears to improve the outcomes of digital mental health interventions, and may also enhance adherence outcomes (though this trend was nonsignificant). Further research should focus on the specific types of tasks these paraprofessionals can successfully provide (ie, psychosocial support, therapeutic alliance, and technical augmentation) and their associated outcomes.Trial RegistrationPROSPERO International Prospective Register of Systematic Reviews CRD42020191226; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=191226

BackgroundAn estimated 1 in 5 adolescents experience a mental health disorder each year; yet because of barriers to accessing and seeking care, most remain undiagnosed and untreated. Furthermore, the early emergence of psychopathology contributes to a lifelong course of challenges across a broad set of functional domains, so addressing this early in the life course is essential. With increasing digital connectivity, including in low- and middle-income countries, digital health technologies are considered promising for addressing mental health among adolescents and young people. In recent years, a growing number of digital health interventions, including more than 2 million web-based mental health apps, have been developed to address a range of mental health issues.ObjectiveThis review aims to synthesize the current evidence on digital health interventions targeting adolescents and young people with mental health conditions, aged between 10-24 years, with a focus on effectiveness, cost-effectiveness, and generalizability to low-resource settings (eg, low- and middle-income countries).MethodsWe searched MEDLINE, PubMed, PsycINFO, and Cochrane databases between January 2010 and June 2020 for systematic reviews and meta-analyses on digital mental health interventions targeting adolescents and young people aged between 10-24 years. Two authors independently screened the studies, extracted data, and assessed the quality of the reviews.ResultsIn this systematic overview, we included 18 systematic reviews and meta-analyses. We found evidence on the effectiveness of computerized cognitive behavioral therapy on anxiety and depression, whereas the effectiveness of other digital mental health interventions remains inconclusive. Interventions with an in-person element with a professional, peer, or parent were associated with greater effectiveness, adherence, and lower dropout than fully automatized or self-administered interventions. Despite the proposed utility of digital interventions for increasing accessibility of treatment across settings, no study has reported sample-specific metrics of social context (eg, socioeconomic background) or focused on low-resource settings.ConclusionsAlthough digital interventions for mental health can be effective for both supplementing and supplanting traditional mental health treatment, only a small proportion of existing digital platforms are evidence based. Furthermore, their cost-effectiveness and effectiveness, including in low- and middle-income countries, have been understudied. Widespread adoption and scale-up of digital mental health interventions, especially in settings with limited resources for health, will require more rigorous and consistent demonstrations of effectiveness and cost-effectiveness vis-à-vis the type of service provided, target population, and the current standard of care.

Rapid developments and implementation of digital technologies in public health domains throughout the last decades have changed the landscape of health delivery and disease prevention globally. Many countries introduce digital interventions to their health systems to improve their populations’ health and make access to health care more accessible. Despite multiple definitions for digital public health and the development of different digital interventions, no study has analysed whether the used technologies fit the definition and the core characteristics of digital public health interventions. Digital public health for us means using digital tools to achieve public health goals. We conducted a scoping review to map the characteristics of digital public health interventions, see how the understanding of specific interventions differs between countries, and how they fit in the theoretical framework of digital public health definitions. Our review is the first to display the landscape of worldwide existing digital public health interventions that use information- and communication technologies. The study’s protocol was published in March 2022 in JMIR Research Protocols (DOI 10.2196/33404). We searched five databases (PubMed, Web of Science, CENTRAL, Ieee, and ACM) for publications. Given the broad search string, we retrieved 13,869 results screened for eligibility. A total of 1,429 publications were included for full-text screening. The study showed that the terms for specific interventions are related to the context in which they are used. Scandinavian countries displayed a different understanding of electronic health records (EHRs) than South American countries. We also identified that the separation between digital health and digital public health is blurry in praxis. Although interventions such as EHRs target individuals to improve their health, the collected data can also be pooled to allow research and the development of interventions on a public health level.Key messages• When comparing interventions internationally, it’s best to compare based on the characteristics of the intervention rather than on the name.• Although, in theory, the distinguishment between digital health, digital public health, and public health became more precise in recent years, the practical reality between them remains still blurry.

BackgroundThe majority of people with a chronic disease (e.g., diabetes, hypertension, COPD) have more than one concurrent condition and are also at higher risk for developing comorbidities in mental health, including anxiety and depression. There is an urgent need for more relevant and accurate data on digital interventions in this area to prepare for an increase demand for mental health services. The aim of this study was to conduct a meta-analysis of the digital mental health interventions for people with comorbid physical and mental chronic diseases to compare the effect of technology systems and level of support.MethodsThis secondary meta-analysis follows a rapid review of systematic reviews, a virtual workshop with knowledge users to identify research questions and a modified Delphi study to guide research methods: What types of digital health interventions (according to a recognized categorization) are the most effective for the management of concomitant mental health and chronic disease conditions in adults? We conducted a secondary analysis of the primary studies identified in the rapid review. Two reviewers independently screened the titles and abstracts and applied inclusion criteria: RCT design using a digital mental health intervention in a population of adults with another chronic condition, published after 2010 in French or English, and including an outcome measurement of anxiety or depression.ResultsSeven hundred eight primary studies were extracted from the systematic reviews and 84 primary studies met the inclusion criteria Digital mental health interventions were significantly more effective than in-person care for both anxiety and depression outcomes. Online messaging was the most effective technology to improve anxiety and depression scores; however, all technology types were effective. Interventions partially supported by healthcare professionals were more effective than self-administered.ConclusionsWhile our meta-analysis identifies digital intervention’s characteristics are associated with better effectiveness, all technologies and levels of support could be used considering implementation context and population.Trial registrationThe protocol for this review is registered in the National Collaborating Centre for Methods and Tools (NCCMT) COVID-19 Rapid Evidence Service (ID 75).

The potential of digital technology for improving the health of individuals, communities, and populations is unprecedented. Technological advancements empower individuals to engage in self-monitoring and self-management of their chronic conditions or health and well-being. There is an unparalleled opportunity to reform prevention, health promotion, and healthcare services with lower cost and better reach and accessibility. However, health technologies are often developed without supportive evidence or a user-centred design. This leads to a lack of long-term user engagement in digital public health interventions. Our workshop aims to facilitate a mutual understanding of the specific properties of digital public health tools by creating a space for discussing the various perspectives of such technologies. We want to start a conversation of essential steps for conceptualising, implementing, and evaluating needs-based and society-centred digital public health interventions to improve the acceptability and sustainability of such interventions in users. The workshop will address digital public health tools on different steps and describe the progression as an iterative approach to highlight where these aspects are linked. The first speaker will provide a theory-guided overview of digitalisation in health to create a shared understanding of the terminology for the workshop. This includes the differentiation between digital health and digital public health. The talk will highlight the importance of digital tools for surveillance, monitoring, healthcare, health promotion, and their significant meaning for society. Following this input, the other panellists will guide us through different aspects of digital public health tools: The second speaker will discuss the importance of society-centred designs based on users’ needs rather than on technological advancements for interventions. Our third speaker will present a meta-framework of extended criteria for developing and evaluating digital technologies for public health. The fourth panellist will share Malta's COVID-19 contact tracing app as a case study. He will discuss the challenges and facilitators in implementing and evaluating digital public health interventions. The last presentation will cover the need for governmental support in the future to ensure the success of digital public health interventions and holistic systems. The workshop will take place as a round table discussion. Each panellist will give a short (7 minute) input talk on the specific properties of digital public health tools. After the panellists present their opinion, we will open the floor for a discussion. Here, the audience is invited to share their knowledge and experiences to build a mutual understanding of the crucial steps in digital public health interventions. After the workshop, we will create a white paper on digital public health based on the panellists’ input and the discussion results. Key messages • A mutual understanding of digital public health may facilitate public sector cooperation and aim towards needs-based and society-centred technology development to improve the population's health. • Digital public health offers unique challenges, and there is an opportunity to outline these specific nuances to ensure maximum success in implementing such projects.

BACKGROUND Racialized immigrant youth face a multitude of challenges that heighten their vulnerability to mental illness. Digital mental health has increasingly been recognized as an effective method to improve accessibility to mental health services for communities with limited access to inclusive care, particularly among youth. However, despite the growing emphasis on cultural inclusivity in interventions targeting racialized and marginalized populations, there remains a gap in empirical evidence regarding how culturally inclusive elements are integrated into digital mental health practices and their impact on the effectiveness of these interventions. OBJECTIVE Focusing on Asian immigrant youth in Canada, this protocol outlines our community-engaged project, which aims to assess whether current digital mental health interventions provide effective and culturally accessible support, and how we can collaboratively develop a framework for creating innovative, inclusive, and effective digital interventions to promote youth mental health. METHODS A two-phase community-engaged approach will be used to involve Asian immigrant youth facing mental health challenges, youth leaders, service providers, and stakeholders from East, Southeast, and South Asian communities. Phase one includes scoping reviews on the technology, access, and cultural inclusivity of digital mental health interventions for Asian and racialized newcomer youth in Canada. In phase two, 15 diverse Asian youth leaders and 15 service providers will participate in a 3.5-hour online session to discuss the need for effective digital mental health interventions, share results from the reviews, co-identify key elements of an inclusive and innovative intervention, and outline next steps for forming a community-campus research partnership focused on mental health promotion for Asian immigrant youth. RESULTS This project is expected to yield a co-developed framework outlining key elements of culturally inclusive and effective digital mental health interventions for Asian immigrant youth in Canada. Anticipated outcomes include enhanced understanding of cultural accessibility gaps in existing digital interventions and strengthened community-campus partnerships to support youth mental health. CONCLUSIONS This research aims to improve access to culturally safe and effective digital mental health interventions for Asian immigrant youth. Benefits include enhanced mental health support for this population, increased awareness of mental health issues among stakeholders, and the development of a framework for culturally inclusive mental health services

BackgroundDigital mental health interventions stand to play a critical role in managing the mental health impact of the COVID-19 pandemic. Thus, enhancing their uptake is a key priority. General practitioners (GPs) are well positioned to facilitate access to digital interventions, but tools that assist GPs in identifying suitable patients are lacking.ObjectiveThis study aims to evaluate the suitability of a web-based mental health screening and treatment recommendation tool (StepCare) for improving the identification of anxiety and depression in general practice and, subsequently, uptake of digital mental health interventions.MethodsStepCare screens patients for symptoms of depression (9-item Patient Health Questionnaire) and anxiety (7-item Generalized Anxiety Disorder scale) in the GP waiting room. It provides GPs with stepped treatment recommendations that include digital mental health interventions for patients with mild to moderate symptoms. Patients (N=5138) from 85 general practices across Australia were invited to participate in screening.ResultsScreening identified depressive or anxious symptoms in 43.09% (1428/3314) of patients (one-quarter were previously unidentified or untreated). The majority (300/335, 89.6%) of previously unidentified or untreated patients had mild to moderate symptoms and were candidates for digital mental health interventions. Although less than half were prescribed a digital intervention by their GP, when a digital intervention was prescribed, more than two-thirds of patients reported using it.ConclusionsImplementing web-based mental health screening in general practices can provide important opportunities for GPs to improve the identification of symptoms of mental illness and increase patient access to digital mental health interventions. Although GPs prescribed digital interventions less frequently than in-person psychotherapy or medication, the promising rates of uptake by GP-referred patients suggest that GPs can play a critical role in championing digital interventions and maximizing the associated benefits.

BackgroundDepression and anxiety disorders are common, and treatment often includes psychological interventions. Digital health interventions, delivered through technologies such as web-based programs and mobile apps, are increasingly used in mental health treatment. Acceptability, the extent to which an intervention is viewed positively, has been identified as contributing to patient adherence and engagement with digital health interventions. Acceptability, therefore, impacts the benefit derived from using digital health interventions in treatment. Understanding the acceptability of digital mental health interventions among patients with depression or anxiety disorders is essential to maximize the effectiveness of their treatment.ObjectiveThis review investigated the acceptability of technology-based interventions among patients with depression or anxiety disorders.MethodsA systematic review was performed based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PROSPERO (International Prospective Register of Systematic Reviews) guidelines. We searched PubMed, Web of Science, and Ovid in May 2022. Studies were included if they evaluated digital interventions for the treatment of depression or anxiety disorders and investigated their acceptability among adult patients. Studies were excluded if they targeted only specific populations (eg, those with specific physical health conditions), investigated acceptability in healthy individuals or patients under the age of 18 years, involved no direct interaction between patients and technologies, used technology only as a platform for traditional care (eg, videoconferencing), had patients using technologies only in clinical or laboratory settings, or involved virtual reality technologies. Acceptability outcome data were narratively synthesized by the direction of acceptability using vote counting. Included studies were evaluated using levels of evidence from the Oxford Centre for Evidence-Based Medicine. The risk of bias was assessed using a tool designed for this review and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation).ResultsA total of 143 articles met the inclusion criteria, comprising 67 (47%) articles on interventions for depression, 65 (45%) articles on interventions for anxiety disorders, and 11 (8%) articles on interventions for both. Overall, 90 (63%) were randomized controlled trials, 50 (35%) were other quantitative studies, and 3 (2%) were qualitative studies. Interventions used web-based programs, mobile apps, and computer programs. Cognitive behavioral therapy was the basis of 71% (102/143) of the interventions. Digital mental health interventions were generally acceptable among patients with depression or anxiety disorders, with 88% (126/143) indicating positive acceptability, 8% (11/143) mixed results, and 4% (6/143) insufficient information to categorize the direction of acceptability. The available research evidence was of moderate quality.ConclusionsDigital mental health interventions seem to be acceptable to patients with depression or anxiety disorders. Consistent use of validated measures for acceptability would enhance the quality of evidence. Careful design of acceptability as an evaluation outcome can further improve the quality of evidence and reduce the risk of bias.Trial RegistrationOpen Science Framework Y7MJ4; https://doi.org/10.17605/OSF.IO/SPR8M

Digital interventions for depression and anxiety in older adults: a systematic review of randomised controlled trials

There is potential for digital mental health interventions to provide affordable, efficient, and scalable support to individuals. Digital interventions, including cognitive behavioral therapy, stress management, and mindfulness programs, have shown promise when applied in workplace settings. The aim of this study is to conduct an umbrella review of systematic reviews in order to critically evaluate, synthesize, and summarize evidence of various digital mental health interventions available within a workplace setting. A systematic search was conducted to identify systematic reviews relating to digital interventions for the workplace, using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis). The review protocol was registered in the Open Science Framework. The following databases were searched: PubMed, Web of Science, MEDLINE, PsycINFO, and Cochrane Library. Data were extracted using a predefined extraction table. To assess the methodological quality of a study, the AMSTAR-2 tool was used to critically appraise systematic reviews of health care interventions. The literature search resulted in 11,875 records, which was reduced to 14 full-text systematic literature reviews with the use of Covidence to remove duplicates and screen titles and abstracts. The 14 included reviews were published between 2014 and 2023, comprising 9 systematic reviews and 5 systematic reviews and meta-analyses. AMSTAR-2 was used to complete a quality assessment of the reviews, and the results were critically low for 7 literature reviews and low for the other 7 literature reviews. The most common types of digital intervention studied were cognitive behavioral therapy, mindfulness/meditation, and stress management followed by other self-help interventions. Effectiveness of digital interventions was found for many mental health symptoms and conditions in employee populations, such as stress, anxiety, depression, burnout, and psychological well-being. Factors such as type of technology, guidance, recruitment, tailoring, and demographics were found to impact effectiveness. This umbrella review aimed to critically evaluate, synthesize, and summarize evidence of various digital mental health interventions available within a workplace setting. Despite the low quality of the reviews, best practice guidelines can be derived from factors that impact the effectiveness of digital interventions in the workplace. OSF Registries osf.io/rc6ds; https://doi.org/10.17605/OSF.IO/RC6DS.

Although many digital mental health interventions are available, clinicians do not routinely use them in clinical practice. In this pilot survey, we review the factors that supported the rapid transition to televisits during the COVID-19 pandemic, and we explore the barriers that continue to prevent clinicians from using other digital mental health interventions, such as mindfulness applications, mood trackers, and digital therapy programs. We conducted a pilot survey of mental health clinicians in different practice environments in the USA. Survey respondents (n = 51) were primarily psychiatrists working in academic medical centers. Results indicated that systemic factors, including workplace facilitation and insurance reimbursement, were primary reasons motivating clinicians to use televisits to provide remote patient care. The shift to televisits during the pandemic was not accompanied by increased use of other digital mental health interventions in patient care. Nine clinicians reported that they have never used digital interventions with patients. Among the 42 clinicians who did report some experience using digital interventions, the majority reported no change in the use of digital applications since transitioning to televisits. Our preliminary findings lend insight into the perspective of mental health clinicians regarding the factors that supported their transition to televisits, including institutional support and insurance reimbursement, and indicate that this shift to virtual patient care has not been accompanied by increased use of other digital mental health interventions. We contend that the same systemic factors that supported the shift toward virtual visits in the COVID-19 pandemic may be applied to support the incorporation of other digital interventions in mental healthcare.Supplementary InformationThe online version contains supplementary material available at 10.1007/s41347-022-00260-8.

BackgroundDepression and anxiety frequently coexist with chronic musculoskeletal pain and can negatively impact patients’ responses to standard orthopedic treatments. Nevertheless, mental health is not routinely addressed in the orthopedic care setting. If effective, a digital mental health intervention may be a feasible and scalable method of addressing mental health in an orthopedic setting.ObjectiveWe aimed to compare 2-month changes in mental and physical health between orthopedic patients who received a digital mental health intervention in addition to usual orthopedic care, those who received usual orthopedic care only (without a specific mental health intervention), and those who received in-person care with a psychologist as part of their orthopedic treatment plan.MethodsIn this single-center retrospective cohort study involving ancillary analysis of a pilot feasibility study, 2-month self-reported health changes were compared between a cohort of orthopedic patients who received access to a digital mental health intervention (Wysa) and 2 convenience sample comparison cohorts (patients who received usual orthopedic care without a specific mental health intervention and patients who received in-person care with a psychologist as part of their orthopedic treatment plan). All patients were 18 years or older and reported elevated symptoms of depression or anxiety at an orthopedic clinic visit (Patient-Reported Outcomes Measurement Information System [PROMIS] Depression or Anxiety score ≥55). The digital intervention was a multi-component mobile app that used chatbot technology and text-based access to human counselors to provide cognitive behavioral therapy, mindfulness training, and sleep tools, among other features, with an emphasis on behavioral activation and pain acceptance. Outcomes of interest were between-cohort differences in the 2-month longitudinal changes in PROMIS Depression and Anxiety scores (primary outcomes) and PROMIS Pain Interference and Physical Function scores (secondary outcomes).ResultsAmong 153 patients (mean age 55, SD 15 years; 128 [83.7%] female; 51 patients per cohort), patients who received the digital mental health intervention showed clinically meaningful improvements at the 2-month follow-up for all PROMIS measures (mean longitudinal improvement 2.8-3.7 points; P≤.02). After controlling for age and BMI, the improvements in PROMIS Depression, Pain Interference, and Physical Function were meaningfully greater than longitudinal changes shown by patients who received usual orthopedic care (mean between-group difference 2.6-4.8 points; P≤.04). Improvements in PROMIS Physical Function were also meaningfully greater than longitudinal changes shown by patients who received in-person psychological counseling (mean between-group difference 2.4 points; P=.04).ConclusionsPatients who received a digital mental health intervention as part of orthopedic care reported greater 2-month mean improvements in depression, pain interference, and physical function than patients who received usual orthopedic care. They also reported a greater mean improvement in physical function and comparable improvements in depression, anxiety, and pain interference compared with orthopedic patients who received in-person psychological counseling.