"Don't Just Say, 'You Got Type 2 Diabetes' and Then Tell Me Nothing Else": Exploring Self-Management Challenges and Information Needs Among Low-Income Adults With Type 2 Diabetes.

The potential of digital mental health to increase access to and quality of care has gained traction with the rise of smartphones and accelerated with the spread of telehealth during the COVID-19 pandemic. With at least 80% of the global population now owning a device able to capture digital phenotyping signals, analyze data, and run mental health apps, excitement about the imminent arrival of personalized, preventive and precision psychiatry is understandable. Yet, by nearly all outcome metrics, digital mental health is not transforming care1. Whether measured in global trends of deaths from suicide or rising rates of depression, especially among young­er people who are often the first to use digital tools, it is clear that the proclaimed paradigm shift is paused2. The very people who require mental health care the most, underserved populations, have not experienced a rise in access or boon in outcomes, and the burden of mental illness in low- and middle-income countries remains as high as ever. Billions of dollars of resources have been poured into health apps, algorithms and devices with the assumption that later, with a simple step, all people would "cross over" or "trickle across" the digital divide and catch up. However, a variety of digital disparities are now emerging, which are troubling but perhaps also addressable. A focus on supporting digital literacy, improving privacy/evidence for these tools, and creating clinical connections each provides tangible steps for more equitable and impactful digital mental health. As smartphone penetration has accelerated in all countries around the world, blaming the digital divide on a lack of access to devices has become untenable. This narrative now covers lack of Internet access, especially in rural areas. While this is indeed a barrier still requiring work today3, it is one that can and will probably be quickly addressed. But, behind access to the Internet, lies a more challenging first inequity – that concerning digital self-determination. Just as self-determination theory highlights the need for autonomy, competence and connection for psychological thriving, the same is necessary for any digital mental health tools, be they anything from smartphone apps to virtual reality headsets. While the data remain aloof as the topic has not yet been well explored, digital self-determination and the related sub-component of digital literacy remain underdeveloped in populations with the greatest mental health needs4. People may have a smartphone today, but there has not been a concomitant investment in people themselves to ensure that they can equitably engage and benefit from digital mental health tools. Evidence that older adults may find digital health tools more challenging, or that people from underserved backgrounds may engage less certainly, reflects issues with flawed designs of technology and a lack of community engagement, but may also reflect deeper inequities around educational opportunities that today's digital mental health approaches have not yet addressed5. Digital self-determination also means that people may say "no" to using technology for their mental health, and we should honor their choices and voices. A leading reason why people often say "no" is that today digital mental health tools have privacy practices compounded by limited evidence of efficacy. One of the clearest examples of inequity is the lack of privacy offered by most mental health apps. A report by the Mozilla Foundation in March 2022 highlighted ongoing privacy risks among well-known mental health apps. Around the same time in 2022, the suicide hotline service Crisis Textline agreed to stop sharing users' text messages with an outside company after public outcry. The finding that less than 15% of people in the US and UK are willing to share anonymized personal health information with a company for the purposes of improving health care provides a tangible target for improvement6. The lack of trust engendered in health care technology must be reversed, and this can occur with better practices by app developers, demands for privacy by patients and clinicians, and regulation from governments. Without trust, there is no health or mental health, and it is understandable that people do not want their most private and vulnerable information shared in today's digital mental health ecosystem. Furthermore, despite bold claims of efficacy on their websites, most studies in the mental health field do not recruit or sample from the patients with the highest unmet health care needs7. This clear lack of representativeness may explain why many digital technologies fail to offer impressive results in the real world when deployed outside clinical trial conditions. Digital mental health tools need not be perceived as second-class treatments to be utilized when a clinician is not available, but should strive for excellence that exceeds current standards of care. A more subtle but equally insidious bias rests in magnifying current inequalities when machine learning or artificial intelligence algorithms are trained on non-representative populations. As we think of the next generation of studies that can help reverse inequities, it is critical not to justify lower-quality research with the assumption that a digital intervention is better than nothing. If people have a phone, there are many free and effective interventions that can serve as an active control condition (or a digital placebo) to enable actual assessment of efficacy. Coming to the third above-mentioned inequity, connections matter. As isolation and loneliness are recognized as public health threats, digital health tools will be most impactful when they help people form strong social connections instead of motivating them to continue focusing inward. The full potential of remote monitoring innovations, such as digital phenotyping and wearable sensors, as well as digital behavioral interventions, can only be realized when these are well integrated into care and treatment plans. That means that apps, devices and programs must transfer data to and from electronic medical records and that health workers and their workflow must be part of the design process. Yet, less than 25% of apps today even allow such interoperabil­ity8, and, when supported at one major academic hospital, only 1% of people chose to link their app to their electronic health record9. Related, clinicians need training and support to incorporate such new digital health tools. A new workforce will be necessary, with a focus on peer support workers who may mirror the populations that are most impacted by a lack of access to and/or comfortability using technology, and who are ready to provide digital skill training and support. Achieving optimal health, including mental health, means that we must address social/political determinants of health. Technology literacy now is considered a social determinant of health. It also impacts important aspects of people's lives, such as access to competitive employment, education, and even supportive services such as housing or access to other people, as clearly emerging during the COVID-19 pandemic. All of these aspects directly impact mental health and are as critically important as any clinical-focused use. Acknowledgment and integration of these social determinants can make digital tools more relevant and useful to a broader swath of the population with the highest need. Thus, supporting digital self-determination should be the first priority, as it will create demand for new privacy protections, inform how the next generation of evidence will generate the highest quality of representative research, and ensure that new health care services are created to serve people with the highest needs. Developing a new generation of digital mental health tools/services to support more accessible, effective and equitable care is the true innovation ready to be stoked today by each person who becomes empowered to connect, set up, engage, start/stop, and demand more from mental health technology.

BACKGROUND High prevalence of Type 2 diabetes (T2D) and associated complications disproportionally affect low-income Latino adults with diabetes. An academic-community partnership was established to develop and evaluate ¡Salud, Salud!, an evidence-based family centered diabetes self-management education and support (DSMES) program to improve glycemic control and quality of life for low-income Latino adults. OBJECTIVE Preliminary effectiveness of ¡Salud, Salud! on primary (glycemic control and quality of life) and secondary outcomes (diabetes-related social-psychological measures) was evaluated in a single-arm quasi-experimental study. METHODS The study enrolled 81 adults (mean age 48.90, SD 12.57; 70% female; 82% Latino) with T2D or pre-diabetes. ¡Salud, Salud! incorporated evidence-based strategies and practices to empower participants in T2D self-management with social support from family and Community Health Workers (CHWs) and facilitation of digital technologies. DSEMES included family membership in YMCA, individual coaching with CHW, and family-centered T2D self-management training. Trained CHWs delivered the 12-week ¡Salud, Salud! in two YMCA locations in Central Texas. RESULTS Forty-eight participants (59%) completed the 12-week posttest. At the end of the program, the participants had a marginally significant reduction in Hemoglobin A1C (HbA1c; -0.30, p ≤ 0.09) and significant increase in proportion of reporting good to excellent health (p≤ 0.003). Significant improvement was also found in T2D self-management-related beliefs, practices and behaviors. Level of participant engagement in ¡Salud, Salud! was mixed. CONCLUSIONS Future studies should investigate how to optimize the uptake of evidence-based strategies and enhance participant engagement in T2D self-management practices in low-income adults with diabetes.

Digital health tools such as mobile apps and patient portals continue to be embedded in clinical care pathways to enhance mental health care delivery and achieve the quintuple aim of improving patient experience, population health, care team well-being, health care costs, and equity. However, a key issue that has greatly hindered the value of these tools is the suboptimal user engagement by patients and families. With only a small fraction of users staying engaged over time, there is a great need to better understand the factors that influence user engagement with digital mental health tools in clinical care settings. This review aims to identify the factors relevant to user engagement with digital mental health tools in clinical care settings using a sociotechnical approach. A scoping review methodology was used to identify the relevant factors from the literature. Five academic databases (MEDLINE, Embase, CINAHL, Web of Science, and PsycINFO) were searched to identify pertinent articles using key terms related to user engagement, mental health, and digital health tools. The abstracts were screened independently by 2 reviewers, and data were extracted using a standardized data extraction form. Articles were included if the digital mental health tool had at least 1 patient-facing component and 1 clinician-facing component, and at least one of the objectives of the article was to examine user engagement with the tool. An established sociotechnical framework developed by Sittig and Singh was used to inform the mapping and analysis of the factors. The database search identified 136 articles for inclusion in the analysis. Of these 136 articles, 84 (61.8%) were published in the last 5 years, 47 (34.6%) were from the United States, and 23 (16.9%) were from the United Kingdom. With regard to examining user engagement, the majority of the articles (95/136, 69.9%) used a qualitative approach to understand engagement. From these articles, 26 factors were identified across 7 categories of the established sociotechnical framework. These ranged from technology-focused factors (eg, the modality of the tool) and the clinical environment (eg, alignment with clinical workflows) to system-level issues (eg, reimbursement for physician use of the digital tool with patients). On the basis of the factors identified in this review, we have uncovered how the tool, individuals, the clinical environment, and the health system may influence user engagement with digital mental health tools for clinical care. Future work should focus on validating and identifying a core set of essential factors for user engagement with digital mental health tools in clinical care environments. Moreover, exploring strategies for improving user engagement through these factors would be useful for health care leaders and clinicians interested in using digital health tools in care.

Background: Developmental challenges of adolescence, such as puberty and social pressures, exacerbate the complexity of managing type 1 diabetes (T1D) as they transition from pediatric to adult care. However, there is a paucity of codesigned, evidence-based diabetes education and support programs and services to guide adolescents through this transition. Objective: This study aimed to explore the experiences, perspectives, facilitators, and barriers faced by adolescents with T1D in diabetes education and program services and to identify feasible approaches to support them as they transition from pediatric to adult care. Methods: Semistructured interviews were conducted with 13 adolescents aged 13-19 years with T1D. Thematic analysis was used to understand participants' past experiences, facilitators, barriers, and preferences regarding diabetes education programs and services. Results: Participants highly valued the opportunity to meet with peers living with T1D and the emotional support from those interactions. Participants also highlighted the need for age-appropriate content and interactive learning experiences. Suggested gamification features were well-received, with participants emphasizing the importance of interactivity. While there was not a strong preference between virtual or in-person game formats, it was suggested that online options offered flexibility and inclusiveness regardless of physical abilities. Participants were not as enthusiastic for a one-on-one live chat compared to an online community chat, again, for the opportunity for peer support. Conclusion: The study highlights the value that adolescents with T1D place on peer support that arises from opportunities to meet others through in-person events. It was evident that codesigning diabetes education programs and services with adolescents with T1D is key to develop tailored offerings for this population.

One in eight people with heart disease has poor medication adherence that, in part, is related to copayment costs. This study tested whether eliminating copayments for high-value medications among low-income older adults at high cardiovascular risk would improve clinical outcomes. This randomized 2×2 factorial trial studied 2 distinct interventions in Alberta, Canada: eliminating copayments for high-value preventive medications and a self-management education and support program (reported separately). The findings for the first intervention, which waived the usual 30% copayment on 15 medication classes commonly used to reduce cardiovascular events, compared with usual copayment, is reported here. The primary outcome was the composite of death, myocardial infarction, stroke, coronary revascularization, and cardiovascular-related hospitalizations over a 3-year follow-up. Rates of the primary outcome and its components were compared using negative binomial regression. Secondary outcomes included quality of life (Euroqol 5-dimension index score), medication adherence, and overall health care costs. A total of 4761 individuals were randomized and followed for a median of 36 months. There was no evidence of statistical interaction (P=0.99) or of a synergistic effect between the 2 interventions in the factorial trial with respect to the primary outcome, which allowed us to evaluate the effect of each intervention separately. The rate of the primary outcome was not reduced by copayment elimination, (521 versus 533 events, incidence rate ratio 0.84 [95% CI, 0.66-1.07], P=0.162). The incidence rate ratio for nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death (0.97 [95% CI, 0.67-1.39]), death (0.94 [95% CI, 0.80 to 1.11]), and cardiovascular-related hospitalizations (0.78 [95% CI, 0.57 to 1.06]) did not differ between groups. No significant between-group changes in quality of life over time were observed (mean difference, 0.012 [95% CI, -0.006 to 0.030], P=0.19). The proportion of participants who were adherent to statins was 0.72 versus 0.69 for the copayment elimination versus usual copayment groups, respectively (mean difference, 0.03 [95% CI, 0.006-0.06], P=0.016). Overall adjusted health care costs did not differ ($3575 [95% CI, -605 to 7168], P=0.098). In low-income adults at high cardiovascular risk, eliminating copayments (average, $35/mo) did not improve clinical outcomes or reduce health care costs, despite a modest improvement in adherence to medications. URL: https://www. gov; Unique identifier: NCT02579655.

Digital mental health tools: A narrative review on overcoming barriers in the age of displacement and disparities.

ABSTRACTBackground or ContextStudies reporting the use of digital tools to promote the prevention and treatment of sexually transmitted and blood borne infections (STBBIs) have proliferated in recent years. Previous reviews highlight variability in the input sought from users in tool development, and its contribution to impact.ObjectiveThis scoping review sought to describe approaches to seeking and utilising user input, with the goal of providing guidance for developers.Search StrategySearches were conducted in MEDLINE, PsycInfo, and the Social Science Citation Index and results screened by two reviewers. The reference lists of included studies and review papers were also checked.Inclusion CriteriaPeer reviewed qualitative and mixed methods studies seeking user input on digital tools promoting the prevention and treatment of STBBIs, from prototyping onwards, published from after 2014 in English, were included.Data Extraction and SynthesisReported methods and findings were charted in Excel and synthesised using content analysis to provide an overview of methods and domains of user input and utilisation of this input.Main ResultsA total of 1838 unique titles and abstracts and the full text of 50 publications were screened. Data was charted from 37 eligible studies reporting findings from 34 projects developing digital health tools, including smartphone/tablet applications, websites/web‐based applications, chatbots, interactive automated SMS, and purpose‐built tools within dating and social media applications. Studies reported on tools developed for use by diverse target populations. The most common domain of input reported was usability (n = 31), while others—namely, satisfaction (n = 27), acceptability (n = 25), formative (n = 24), impact (n = 22), accessibility (n = 17), and engagement (n = 11)—were reported less consistently. User views were sought using qualitative methods such as interviews, focus groups and open‐ended survey questions, more often in combination with quantitative measures such as participant‐rated measures and engagement analytics. User suggestions for changes were reported in relation to three in four projects studied but incorporation of changes in less than half of projects.Discussion and ConclusionsThis review demonstrates considerable homogeneity in reported user input in the development of digital health tools. Input from users as co‐designers may improve the impact of tools on their intended outcomes.Patient and Public ContributionThis literature review brought together a group of researchers who have sought user input in the development of digital sexual health tools, but, due to resource limitations, did not involve potential users themselves, who are of diverse and disparate groups.

Diabetes self-management education and support can improve outcomes in people with diabetes. Providing health interventions via digital modes of delivery can extend the reach of programs delivered through traditional means. The web-based version of the Diabetes Education and Self-Management for Ongoing and Newly Diagnosed (MyDESMOND) is a digital diabetes education and support program for people with type 2 diabetes. The program was originally developed in the United Kingdom and is evidence-based, grounded in behavioral theory, and designed through a rigorous process of intervention mapping. As such, MyDESMOND was considered an ideal candidate for adaptation to the Australian setting. Program content and the digital platform were modified to suit the local context to increase the likelihood that the revised version of MyDESMOND will deliver similar outcomes to the original program. The aim of this paper is to describe the systematic processes undertaken to adapt the digital MyDESMOND diabetes education and support program for people with type 2 diabetes to the Australian setting. The adaptation involved a multidisciplinary group with a diverse range of skills and expertise—a governance structure was established, a skilled project team was appointed, and stakeholder engagement was strategically planned. The adaptation of the program content included modifications to the clinical recommendations, the inclusion of local resources, practical changes, and revisions to optimize readability. A 2-stage independent review of the modified content was enacted. Digital adaptations were informed by relevant standards, local legislative requirements, and considerations of data sovereignty. The digital platform was extensively tested before deployment to the production setting. MyDESMOND is the first evidence-based digital diabetes education and support program for Australians with type 2 diabetes. This paper provides a road map for the adaptation of digital health interventions to new contexts.

Delays in diagnosis and detection of skin neglected tropical diseases (NTDs) pose obstacles to prompt treatment, which is crucial in preventing disability. Recent developments in digital health have given rise to approaches that could increase access to diagnosis in resource-poor areas affected by skin NTDs. This scoping review provides an overview of current digital health approaches that aim to aid in the diagnosis of skin NTDs and provides an insight into the diverse functionalities of current digital health tools, their feasibility, usability, and the current gaps in research around these digital health approaches. This scoping review included a comprehensive literature search on PubMed, EMBASE and SCOPUS, following the PRISMA guidelines. Eleven studies were included in the review and were analysed using a descriptive thematic approach. Most digital tools were found to be mobile-phone based, such as mobile Health (mHealth) apps, store-and-forward tele-dermatology, and Short Messaging Service (SMS) text-messaging. Other digital approaches were based on computer software, such as tele-dermatopathology, computer-based telemedicine, and real-time tele-dermatology. Digital health tools commonly facilitated provider-provider interactions, which helped support diagnoses of skin NTDs at the community level. Articles which focused on end-user user experience reported that users appreciated the usefulness and convenience of these digital tools. However, the results emphasized the existing lack of data regarding the diagnostic precision of these tools, and highlighted various hurdles to their effective implementation, including insufficient infrastructure, data security issues and low adherence to the routine use of digital health tools. Digital health tools can help ascertain diagnosis of skin NTDs through remote review or consultations with patients, and support health providers in the diagnostic process. However, further research is required to address the data security issues associated with digital health tools. Developers should consider adapting digital health tools to diverse socio-cultural and technical environments, where skin NTDs are endemic. Researchers are encouraged to assess the diagnostic accuracy of digital health tools and conduct further qualitative studies to inform end-user experience. Overall, future studies should consider expanding the geographical and disease scope of research on digital health tools which aid the diagnosis of skin NTDs.

BackgroundAs mental illness continues to affect 1 in 5 individuals, and the need for support has increased during the COVID-19 pandemic, the promise of digital mental health tools remains largely unrealized due to a lack of uptake by patients and providers. Currently, most efforts on supporting the uptake of digital mental health tools remain fragmented across organizations and geography. There is a critical need to synthesize these efforts in order to provide a coordinated strategy of supporting the adoption of digital mental health tools.ObjectiveThe specific aim of this project is to develop a web-based resource document to support the engagement of mental health providers and patients in the use of digital mental health tools.MethodsThe web-based resource was developed using a multimethod approach. A grey literature review was conducted in 2019 to identify relevant toolkits that are available in the public domain. This was supplemented with an environmental scan where individuals with expertise in the development, acquisition, implementation, and evaluation of digital mental health tools were invited to contribute additional tools or documents not identified in the grey literature search. An engagement workshop was held with stakeholders to explore how the resource document should be developed and delivered. These findings were collectively used to develop the final iteration of the resource document.ResultsBased on a gray literature review and environmental scan with 27 experts, 25 resources were identified and included in the resource guide. These resources were developed for patients and providers by organizations from 5 countries. An engagement workshop was held with 14 stakeholders, and barriers related to cultural sensitivity, sustainability, and accessibility of the toolkit were identified. The final iteration of the resource document was developed by the research team using findings from the gray literature review, environmental scan, and engagement workshop. The contents of the 45-page resource guide are directed at mental health care providers, administrators, and patients (inclusive of families and caregivers).ConclusionsThe use of a multimethod approach led to the development of a resource guide that builds on existing evidence on digital mental health tools and was co-designed with stakeholders and end-users. The resource guide is now publicly available online for free and is being promoted through digital health and mental health websites. Future work should explore how this document can be integrated into clinical care delivery and pathways.

Food Insecurity, Dietary Quality, and Health Care Utilization in Lower-Income Adults: A Cross-Sectional Study

Despite overwhelming and disparate needs, the use of supportive healthcare programs is lower among Chinese American caregivers, in large part due to the lack of accessible and culturally and linguistically appropriate care. Digital health tools have the potential to support caregivers’ needs. In collaboration with community partners, we conducted a qualitative study to identify opportunities using digital health tools to address caregiving needs among families caring for Chinese American older adults. Four focus groups with 21 staff from four local community-based organizations serving Chinese American families were conducted to explore staff’s experience supporting Chinese American families and discuss their perspectives on opportunities to use digital health tools to support caregiving needs. Inductive thematic analysis revealed that digital health tools have the potential to support Chinese American families caring for older adults by (1) offering real-time and trustworthy informational support on caregiving, (2) guiding caregivers through system navigation and service discovery, (3) sharing caregiving stories for scenario-based learning, (4) suggesting communication strategies for adult children caregivers, and (5) enabling family check-ins before or between case manager consultations. Additionally, staff raised concerns regarding digital health tools’ capacity to offer culturally sensitive emotional support, alongside skepticism about its potential to substitute valuable human social interactions. The findings from this study lay the foundation for future research on culturally adapting digital health tools for promoting the mental health and well-being of Chinese American family caregivers.

Positive behavior support (PBS) is an evidence-based approach for supporting adaptive behavior and addressing behavioral challenges. It is critical that families have access to effective evidence-based behavior support practices for both intervention and prevention because they lead to better outcomes for families, and counter-productive family management practices have been shown to further escalate children’s behavioral challenges. PBS has been demonstrated to be effective with individual children with serious behavior challenges in family homes and features of PBS are evident in common family-based intervention approaches. Unfortunately, complete application of PBS in family contexts has not been fully explored or conceptualized. The purpose of this paper is to define the core features of PBS including lifestyle enhancement, assessment-based intervention, and comprehensive support plans (i.e., including strategies for prevention, teaching, and management). Examples of how the features of PBS are currently being employed within the field of PBS and within other evidence-based parent education and support programs are provided. Suggestions for how collaboration, assessment, data-based decision making, comprehensive intervention, and tiered approaches to service delivery may be used to enhance behavioral support for families are offered. Lastly, future directions for research and practice are recommended.

BackgroundDigital health tools (WeChat or mobile health apps) provide opportunities for new methods of hypertension management for hypertensive patients. However, the willingness of these patients to use social media and mobile health apps for hypertension management remains unclear. This study explored the characteristics and requirements of patients willing to use digital health (WDH) tools to manage hypertension.MethodsFrom February to March 2018, we administered questionnaires to 1089 patients with hypertension at eight Chinese primary medical units. We assessed independent risk factors of WDH and requirement among WDH patients.ResultsOverall, 43% (465/1089) of participants were WDH patients, who were younger (58 ± 12 vs 61 ± 13 years) and had a greater proportion of employed individuals (31% vs 14%) and higher education levels (65% vs 52%) than the non-WDH patients (all P < 0.0001). After adjusting for other risk factors, higher education (OR: 0.52; 95% CI: 0.34–0.79), good medicine adherence (OR: 1.5; 95% CI: 1.0–2.3) and blood pressure self-monitoring (OR: 1.6; 95% CI: 1.2–2.3) remained significantly associated with WDH (all P < 0.05). WDH patients responded that digital health tools should try to provide a platform for blood pressure monitoring (42%), medication reminders (41%), hypertension knowledge (39%) and doctor-patient communication (32%).ConclusionOur survey suggested that among hypertensive patients, willingness to use digital health tools was significantly associated with education, medicine adherence and blood pressure self-monitoring. Digital health tool developers and researchers should pay particular attention to recruiting older, less educated and unemployed patients with less willingness and who are less technologically savvy and research the requirements of WDH patients (blood pressure monitoring, medication reminders, and knowledge education) in the future.

Low income adults with substance use disorders (SUDs) have a high prevalence of tobacco use and often limited access to tobacco cessation treatment. This study examines the relationship between low-income SUD patient census (i.e., percentage of patients whose treatment costs are covered by Medicaid and Federal block grants) and SUD programs' availability of three evidence-based tobacco cessation services: behavioral treatments, system-level support, and pharmacotherapy. Data were collected from a random sample of 1,006 program administrators in 2010. Mixed-effects models results show that the percentage of low-income patients is significantly positively associated with the availability of behavioral treatments and system-level support but not pharmacotherapy. Thus, low-income patients may have similar access to tobacco cessation pharmacotherapy but greater access to behavioral treatments and system-level support. However, the availability of tobacco cessation services is not widespread overall, which may hamper access to extensive services to address low-income SUD patients' high smoking rates.