Redeveloping a Digital Sexual Health Intervention for Adolescents to Allow for Broader Dissemination: Implications for HIV and STD Prevention.

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

Background“Digital public health” has emerged from an interest in integrating digital technologies into public health. However, significant challenges which limit the scale and extent of this digital integration in various public health domains have been described. We summarized the literature about these challenges and identified strategies to overcome them.MethodsWe adopted Arksey and O’Malley's framework (2005) integrating adaptations by Levac et al. (2010). OVID Medline, Embase, Google Scholar, and 14 government and intergovernmental agency websites were searched using terms related to “digital” and “public health.” We included conceptual and explicit descriptions of digital technologies in public health published in English between 2000 and June 2020. We excluded primary research articles about digital health interventions. Data were extracted using a codebook created using the European Public Health Association's conceptual framework for digital public health.Results and analysisOverall, 163 publications were included from 6953 retrieved articles with the majority (64%, n = 105) published between 2015 and June 2020. Nontechnical challenges to digital integration in public health concerned ethics, policy and governance, health equity, resource gaps, and quality of evidence. Technical challenges included fragmented and unsustainable systems, lack of clear standards, unreliability of available data, infrastructure gaps, and workforce capacity gaps. Identified strategies included securing political commitment, intersectoral collaboration, economic investments, standardized ethical, legal, and regulatory frameworks, adaptive research and evaluation, health workforce capacity building, and transparent communication and public engagement.ConclusionDeveloping and implementing digital public health interventions requires efforts that leverage identified strategies to overcome diverse challenges encountered in integrating digital technologies in public health.

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.

BackgroundAlthough gamification continues to be a popular approach to increase engagement, motivation, and adherence to behavioral interventions, empirical studies have rarely focused on this topic. There is a need to empirically evaluate gamification models to increase the understanding of how to integrate gamification into interventions.ObjectiveThe model of gamification principles for digital health interventions proposes a set of five independent yet interrelated gamification principles. This study aimed to examine the validity and reliability of this model to inform its use in Web- and mobile-based apps.MethodsA total of 17 digital health interventions were selected from a curated website of mobile- and Web-based apps (PsyberGuide), which makes independent and unbiased ratings on various metrics. A total of 133 independent raters trained in gamification evaluation techniques were instructed to evaluate the apps and rate the degree to which gamification principles are present. Multiple ratings (n≥20) were collected for each of the five gamification principles within each app. Existing measures, including the PsyberGuide credibility score, mobile app rating scale (MARS), and the app store rating of each app were collected, and their relationship with the gamification principle scores was investigated.ResultsApps varied widely in the degree of gamification implemented (ie, the mean gamification rating ranged from 0.17≤m≤4.65 out of 5). Inter-rater reliability of gamification scores for each app was acceptable (κ≥0.5). There was no significant correlation between any of the five gamification principles and the PsyberGuide credibility score (P≥.49 in all cases). Three gamification principles (supporting player archetypes, feedback, and visibility) were significantly correlated with the MARS score, whereas three principles (meaningful purpose, meaningful choice, and supporting player archetypes) were significantly correlated with the app store rating. One gamification principle was statistically significant with both the MARS and the app store rating (supporting player archetypes).ConclusionsOverall, the results support the validity and potential utility of the model of gamification principles for digital health interventions. As expected, there was some overlap between several gamification principles and existing app measures (eg, MARS). However, the results indicate that the gamification principles are not redundant with existing measures and highlight the potential utility of a 5-factor gamification model structure in digital behavioral health interventions. These gamification principles may be used to improve user experience and enhance engagement with digital health programs.

Objectives Trust has been identified as a key factor associated with supporting access to sexual health interventions and digital healthcare. We aimed to explore and synthesize factors that may cultivate trust for young people (10–24-year-old) when accessing digital sexual healthcare. Methods A total of 5950 articles were extracted from 5 databases (Scopus, PubMed, Embase, PsycINFO and CINAHL) and independently assessed for relevance by two researchers. Trust descriptions were analyzed using a narrative synthesis approach, extracted tabularly and synthesized into themes through conceptual mapping. Results Thirteen papers between 2011 and 2021 from the United States (n = 5), Australia (n = 3), United Kingdom (n = 2), Canada (n = 2), and Netherlands (n = 1) were reviewed. Young people (n = 462), varying in gender identity and sexuality, were aged between 14 and 29 years old. Four areas cultivating trust in digital sexual healthcare were described: (1) Esthetics, language, tone: Trusted digital sexual healthcare was easy to navigate, had limited sexually explicit content or pop-up ads, was not overly teen-friendly and used a professional tone and language, reflecting communication reportedly expected from healthcare providers. (2) Privacy, anonymity, safety: Safety features that preserved young people’s anonymity were important for their trust, particularly amid fear of shame or stigma. (3) Authors’ expertise, authenticity, reputation: Personal accounts online which reflected the young person’s own lived experience were trusted for topics considered subjective (e.g., dating and relationships). (4) Consistency: Cross-checking personal accounts and scientific information to confirm the consistency of content helped with young people’s evaluation of trust. Conclusions Considering the factors cultivating trust when designing digital sexual health interventions may improve access and use. However, given the nuance in lived experience and needs, young people should be meaningfully engaged in the design of digital sexual health interventions. Particularly as sexual health intervention and resources are increasingly being delivered and accessed online by young people.

BackgroundUser dropout is a widespread concern in the delivery and evaluation of digital (ie, web and mobile apps) health interventions. Researchers have yet to fully realize the potential of the large amount of data generated by these technology-based programs. Of particular interest is the ability to predict who will drop out of an intervention. This may be possible through the analysis of user journey data—self-reported as well as system-generated data—produced by the path (or journey) an individual takes to navigate through a digital health intervention.ObjectiveThe purpose of this study is to provide a step-by-step process for the analysis of user journey data and eventually to predict dropout in the context of digital health interventions. The process is applied to data from an internet-based intervention for insomnia as a way to illustrate its use. The completion of the program is contingent upon completing 7 sequential cores, which include an initial tutorial core. Dropout is defined as not completing the seventh core.MethodsSteps of user journey analysis, including data transformation, feature engineering, and statistical model analysis and evaluation, are presented. Dropouts were predicted based on data from 151 participants from a fully automated web-based program (Sleep Healthy Using the Internet) that delivers cognitive behavioral therapy for insomnia. Logistic regression with L1 and L2 regularization, support vector machines, and boosted decision trees were used and evaluated based on their predictive performance. Relevant features from the data are reported that predict user dropout.ResultsAccuracy of predicting dropout (area under the curve [AUC] values) varied depending on the program core and the machine learning technique. After model evaluation, boosted decision trees achieved AUC values ranging between 0.6 and 0.9. Additional handcrafted features, including time to complete certain steps of the intervention, time to get out of bed, and days since the last interaction with the system, contributed to the prediction performance.ConclusionsThe results support the feasibility and potential of analyzing user journey data to predict dropout. Theory-driven handcrafted features increased the prediction performance. The ability to predict dropout at an individual level could be used to enhance decision making for researchers and clinicians as well as inform dynamic intervention regimens.

Divorce is prevalent and often leads to adverse social outcomes among divorcees and their children. Digital platforms offering online post-divorce help may provide scalable, affordable, and accessible support for divorcees during this transition. The study examined the long-term effects (five years) of a post-divorce targeted digital mental health intervention on divorcee’s labor market attachment and income. Participants (n = 1,856) were divorcees from a nationally administered randomized controlled trial (RCT) tracked over a five-year period post their RCT participation using Danish national register data. Cumulative and by-year effects of treatment on labor market income, weeks on sick leave benefits, weeks on welfare benefits, and share of year unemployed were obtained using linear and count models. The study protocol was preregistered. Over the follow up period, participants in the treatment group spent fewer weeks on sick leave benefits and accumulated higher labor market income. By-year estimates for labor market income passed preregistered significance levels, but accumulated effects estimates and estimates for sick leave benefits did not. Digital health interventions may be a low-cost, high scalability way to address negative life consequences of divorce. However, more – and higher powered – research projects are needed to obtain better knowledge of their full potential.

BackgroundOlder adults experience a high risk of adverse events during hospital-to-home transitions. Implementation barriers have prevented widespread clinical uptake of the various digital health technologies that aim to support hospital-to-home transitions.ObjectiveTo guide the development of a digital health intervention to support transitions from hospital to home (the Digital Bridge intervention), the specific objectives of this review were to describe the various roles and functions of health care providers supporting hospital-to-home transitions for older adults, allowing future technologies to be more targeted to support their work; describe the types of digital health interventions used to facilitate the transition from hospital to home for older adults and elucidate how these interventions support the roles and functions of providers; describe the lessons learned from the design and implementation of these interventions; and identify opportunities to improve the fit between technology and provider functions within the Digital Bridge intervention and other transition-focused digital health interventions.MethodsThis 2-phase rapid review involved a selective review of providers’ roles and their functions during hospital-to-home transitions (phase 1) and a structured literature review on digital health interventions used to support older adults’ hospital-to-home transitions (phase 2). During the analysis, the technology functions identified in phase 2 were linked to the provider roles and functions identified in phase 1.ResultsIn phase 1, various provider roles were identified that facilitated hospital-to-home transitions, including navigation-specific roles and the roles of nurses and physicians. The key transition functions performed by providers were related to the 3 categories of continuity of care (ie, informational, management, and relational continuity). Phase 2, included articles (n=142) that reported digital health interventions targeting various medical conditions or groups. Most digital health interventions supported management continuity (eg, follow-up, assessment, and monitoring of patients’ status after hospital discharge), whereas informational and relational continuity were the least supported. The lessons learned from the interventions were categorized into technology- and research-related challenges and opportunities and informed several recommendations to guide the design of transition-focused digital health interventions.ConclusionsThis review highlights the need for Digital Bridge and other digital health interventions to align the design and delivery of digital health interventions with provider functions, design and test interventions with older adults, and examine multilevel outcomes.International Registered Report Identifier (IRRID)RR2-10.1136/bmjopen-2020-045596

Digital health interventions (DHIs) show promise for delivering effective mental health interventions at scale, however significant issues with sustained engagement have been observed. Current efforts to understand, predict, and prevent poor engagement have yielded little success due to the insufficient consideration of how engagement, and the factors driving it, can fluctuate in intensity across the user journey. One under-explored but highly relevant theoretical framework that can be applied in this context is self-regulated learning (SRL), due to the core emphasis on self-guided psychoeducation in digital mental health. SRL refers to the ability to regulate one’s emotions, cognitions, and behaviours to enhance learning outcomes. To investigate the utility and potential of this framework for advancing our knowledge of engagement with DHIs, we conducted semi-structured interviews with digital health users (n = 14) and explored the role of common SRL variables (i.e., drivers) in shaping engagement across the user journey. A template analysis identified four major themes of drivers: (i) motivational beliefs, feelings, and strategies, (ii) metacognitive feedback and control, (iii) emotional experiences, and (iv) physical and social environment. Participants broadly agreed that higher levels across one or more SRL drivers would enhance engagement behaviours, and that the importance of different drivers for shaping engagement can vary temporally. These preliminary findings highlight the relevance of SRL constructs in describing, understanding, and predicting engagement with DHIs, offering insight into potential opportunities for targeted intervention across the user journey to promote engagement. However, further research to quantitatively assess the relationships between SRL drivers and various metrics of engagement in a DHI trial is needed.

BackgroundDigital health interventions have become increasingly common across health care, both before and during the COVID-19 pandemic. Health inequalities, particularly with respect to ethnicity, may not be considered in frameworks that address the implementation of digital health interventions. We considered frameworks to include any models, theories, or taxonomies that describe or predict implementation, uptake, and use of digital health interventions.ObjectiveWe aimed to assess how health inequalities are addressed in frameworks relevant to the implementation, uptake, and use of digital health interventions; health and ethnic inequalities; and interventions for cardiometabolic disease.MethodsSCOPUS, PubMed, EMBASE, Google Scholar, and gray literature were searched to identify papers on frameworks relevant to the implementation, uptake, and use of digital health interventions; ethnically or culturally diverse populations and health inequalities; and interventions for cardiometabolic disease. We assessed the extent to which frameworks address health inequalities, specifically ethnic inequalities; explored how they were addressed; and developed recommendations for good practice.ResultsOf 58 relevant papers, 22 (38%) included frameworks that referred to health inequalities. Inequalities were conceptualized as society-level, system-level, intervention-level, and individual. Only 5 frameworks considered all levels. Three frameworks considered how digital health interventions might interact with or exacerbate existing health inequalities, and 3 considered the process of health technology implementation, uptake, and use and suggested opportunities to improve equity in digital health. When ethnicity was considered, it was often within the broader concepts of social determinants of health. Only 3 frameworks explicitly addressed ethnicity: one focused on culturally tailoring digital health interventions, and 2 were applied to management of cardiometabolic disease.ConclusionsExisting frameworks evaluate implementation, uptake, and use of digital health interventions, but to consider factors related to ethnicity, it is necessary to look across frameworks. We have developed a visual guide of the key constructs across the 4 potential levels of action for digital health inequalities, which can be used to support future research and inform digital health policies.

BackgroundDigital Health Interventions (DHIs) refers to the utilization of digital and mobile technology to support the health system in service delivery. Over the recent years, advanced computing, genomics, and artificial intelligence are considered part of digital health. In the context of the World Health Organization (WHO) global strategy 2020–2025, digital health is defined as “the field of knowledge and practice associated with the development and use of digital technologies to improve health.” The scoping review protocol details the procedure for developing a comprehensive list of DHIs in Sub-Saharan Africa and documenting their roles in strengthening health systems.Method and AnalysisA scoping review will be done according to the Joanne Briggs institute reviewers manual and following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist and explanation. The protocol has been registered at the Open Science Framework (OSF) database at https://osf.io/5kzq7. The review will include DHIs conceptualized/developed/designed, adapted, piloted, deployed, scaled up, and addressing health challenges in Sub-Saharan Africa. We will retrieve data from the global DHI repository-the WHO Digital Health Atlas (DHA)- and supplement it with information from the WHO eHealth Observatory, eHealth Survey (2015), and eHealth country profiles report. Additional searches will be conducted in four (4) electronic databases: PubMed, HINARI-Reasearch4Life, Cochrane Library, and Google Scholar. The review will also include gray literature and reference lists of selected studies. Data will be organized in conceptual categories looking at digital health interventions' distinct function toward achieving health sector objectives.DiscussionSub-Saharan Africa is an emerging powerhouse in DHI innovations with rapid expansion and evolvement. The enthusiasm for digital health has experienced challenges including an escalation of short-lived digital health interventions, duplication, and minimal documentation of evidence on their impact on the health system. Efficient use of resources is important when striving toward the use digital health interventions in health systems strengthening. This can be achieved through documenting successes and lessons learnt over time.ConclusionThe review will provide the evidence to guide further investments in DHIs, avoid duplication, circumvent barriers, focus on gaps, and scale-up successful interventions.

Digital (mental) health interventions have the potential to address barriers in mental health care. However, attitudes towards these interventions are a crucial factor to their successful implementation. Therefore, this study aims to assess those in a representative sample of the German adult population. A total of N = 2,519 participants took part in the survey as part of a larger study. Following a structured face-to-face interview, participants completed a self-administered questionnaire under the supervision of the interviewer. The questionnaire was based on the E-Therapy Attitudes Measure (ETAM) and the Attitudes towards Psychological Interventions Questionnaire (APOI). Results were analyzed by means of Pearson's product moment correlation coefficients and Spearman's ρ statistics. Supplementary open-ended questions explored participants' utilization of digital health interventions for specific conditions, the conditions they perceived as suitable for those, and the perceived barriers to their adoption. Replies on open-ended questions are summarized descriptively. While a majority of participants (34.0%-41.5%) indicated partial agreement with the potential usefulness and advantages of digital health interventions (Items 1-3), a substantial proportion (45.8%, 95% CI [43.8%, 47.7%]) expressed an entire refusal to use them for future psychological problems (Item 4). Older individuals and those with lower educational status expressed particular critical views. Key barriers identified by participants comprised the absence of personal contact, technical issues, and concerns related to data privacy and security. The results of this study indicate that while participants acknowledge the potential benefits of digital health interventions, the observed limited acceptance rates and identified barriers are to be addressed, in order to fully harness their potential.

BackgroundDigital health interventions have revolutionized multiple sclerosis (MS) care by supporting people with MS to better self-manage their disease. It is now understood that the technological elements that comprise this category of digital health interventions can influence participant engagement in self-management programs, and people with MS can experience significant barriers, influenced by these elements, to remaining engaged during a period of learning. It is essential to explore the influence of technological elements in mitigating attrition.ObjectiveThis study aimed to examine the study design and technological elements of documented digital health interventions targeted at people with MS—digital health interventions that were intended to support a program of engagement over a defined period—and to explore how these correlated with attrition among participants of randomized controlled trials (RCTs).MethodsWe conducted a systematic review and meta-analysis of RCTs (n=32) describing digital health self-management interventions for people with MS. We analyzed attrition in included studies, using a random-effects model and meta-regression to measure the association between potential moderators.ResultsThere were no measured differences in attrition between the intervention and control arms; however, some of the heterogeneity observed was explained by the composite technological element score. The pooled attrition rates for the intervention and control arms were 14.7% and 15.6%, respectively.ConclusionsThis paper provides insight into the technological composition of digital health interventions designed for people with MS and describes the degree of attrition in both study arms. This paper will aid in the design of future studies in this area, particularly for digital health interventions of this type.

BackgroundThe COVID-19 pandemic has shifted mental health care delivery to digital platforms, videoconferencing, and other mobile communications. However, existing reviews of digital health interventions are narrow in scope and focus on a limited number of mental health conditions.ObjectiveTo address this gap, we conducted a comprehensive systematic meta-review of the literature to assess the state of digital health interventions for the treatment of mental health conditions.MethodsWe searched MEDLINE for secondary literature published between 2010 and 2021 on the use, efficacy, and appropriateness of digital health interventions for the delivery of mental health care.ResultsOf the 3022 records identified, 466 proceeded to full-text review and 304 met the criteria for inclusion in this study. A majority (52%) of research involved the treatment of substance use disorders, 29% focused on mood, anxiety, and traumatic stress disorders, and >5% for each remaining mental health conditions. Synchronous and asynchronous communication, computerized therapy, and cognitive training appear to be effective but require further examination in understudied mental health conditions. Similarly, virtual reality, mobile apps, social media platforms, and web-based forums are novel technologies that have the potential to improve mental health but require higher quality evidence.ConclusionsDigital health interventions offer promise in the treatment of mental health conditions. In the context of the COVID-19 pandemic, digital health interventions provide a safer alternative to face-to-face treatment. However, further research on the applications of digital interventions in understudied mental health conditions is needed. Additionally, evidence is needed on the effectiveness and appropriateness of digital health tools for patients who are marginalized and may lack access to digital health interventions.

IntroductionOlder adults with hip fracture often require extensive post-surgery care across multiple sectors, making follow-up care even more important to ensure an ideal recovery. With the increased adoption of technology, patient-clinician digital health interventions can potentially improve post-surgery outcomes of hip fracture patients by helping them and their caregivers better understand the various aspects of their care, post-hip fracture surgery. The purpose of this study was to examine the available literature on the impact of hip fracture-specific, patient-clinician digital health interventions on patient outcomes and health care delivery processes. We also aimed to identify the barriers and enablers to the uptake and implementation of these technologies and to provide strategies for improved use of these digital health interventions.MethodsWe conducted a scoping review following the six stages of Arksey and O’Malley’s framework and following the PRISMA-ScR reporting format. Searches were conducted in five databases. In addition to hand searching for relevant studies from the references of all included studies, we also conducted a grey literature search to identify relevant primary studies. Screening of titles and abstracts as well as full texts were performed independently by two reviewers. Two reviewers also performed the data extraction of the included studies.ResultsAfter screening 3,638 records, 20 articles met the criteria and 1 article was identified through hand searching. Various patient-clinician digital health interventions were described including telehealth /telerehabilitation programs (n = 6), care transition /follow-up interventions (n = 5), online resources (n = 2), and wearable devices /sensor monitoring (n = 1). Outcomes were varied and included functional status, gait/mobility, quality of life, psychological factors, satisfaction, survival/complications, caregiver outcomes, compliance, technology-user interactions, and feedback on the use of the digital health interventions. For clinicians, a key barrier to the use of the digital health interventions was the acceptability of the technology. However, the usefulness of the digital health intervention by clinicians was seen as both a barrier and an enabler. For patients and caregivers, all the themes were seen as both a barrier and an enabler depending on the study. These themes included: 1) availability and access, 2) usability, 3) knowledge and skills, 4) acceptability, and 5) usefulness of the digital health intervention.ConclusionMany behavioural factors affect the use of patient-clinician digital health interventions. However, a specific attention should be focused on the acceptability of the technology by the clinicians to encourage uptake of the digital health interventions. The results of this scoping review can help to better understand the factors that may be targeted to increase the use of these technologies by clinicians, patients, and caregivers.