Literature Collection

BACKGROUND: Posttraumatic stress disorder (PTSD) and substance use disorder (SUD) co-occur frequently and have deleterious impact. Seeking Safety (SS) - an evidence-based, present-focused, coping skills model - lends itself to mobile app delivery. OBJECTIVES: A novel SS mobile app is compared to a control app that lacks the interactivity, social engagement, and feature-richness of the SS app. We hypothesized that the SS app would outperform the control on primary outcome variables (substance use, trauma symptoms) and at least two secondary variables. METHODS: Outpatients with current PTSD and SUD (n = 116) were randomized to the apps; assessed were pre, post (12 weeks), and 3-month follow-up in this online study. RESULTS: The SS app outperformed the control on the primary outcomes, but not on secondary outcomes. Also both conditions evidenced significant change over time from pre to post, with gains sustained at follow-up. External medication and supports during the trial did not differ by condition. CONCLUSION: This first RCT on a SS mobile app had positive results for reduction in substance use and trauma symptoms compared to a control app. This is noteworthy as mental health mobile apps, in general, evidence few positive outcomes. Our substance use finding is also notable as psychosocial interventions in PTSD/SUD populations find it harder to achieve reduction in SUD than trauma symptoms. Our control app may have represented too strong a comparison and weakened our ability to find results on secondary outcomes by condition.

PURPOSE AND APPROACH: Women in recovery describe stigma, negative treatment, and limited support as barriers to achieving their health and parenting goals. Mobile health technologies carefully tailored to support the unique needs of recovery communities can provide less burdensome alternatives to in-person services for women transitioning out of substance use treatment. An iterative design process integrated women's interests into the structure, content, and interaction flow of a mobile health (mHealth) app. SETTING AND PARTICIPANTS: Participants included women in recovery from opioid, alcohol, and polysubstance use disorders in a comprehensive housing program in urban Arizona. METHODS: Five focus groups with 3-7 participants each (n = 27 total) informed creation of the mHealth app. Informed by theoretical models of usability and person-centered design, development involved an iterative series of focus groups in which we asked women to comment on interest in using each feature. This provided a qualitative priority framework for feature development. We then modified the app and repeated the process to gauge consensus and continually refine our prototype. RESULTS: Women were interested in access to resources, such as housing, counseling, and parenting advice in settings known to treat women in recovery with respect. They also asked for positive messages, chatting with peers, and access to expert answers. They were less interested in points-based learning modules and "scored" activities, leading us to develop a "daily challenges" concept that builds good habits, but does not feel like "classwork". Women's recommendations shaped an mHealth app tailored to maximize utility, access, and safety for this at-risk population. CONCLUSION: Integration of user-centered design with applied ethnographic techniques guided the development of a custom-tailored mHealth app responsive to lived experiences and needs of women in recovery. Future research should evaluate the potential for user-centered apps to increase self-efficacy, perceived social support, and to reduce risk of relapse.

BACKGROUND: Conversational agents (CAs) are increasingly used as a promising tool for scalable, accessible, and personalized self-management support of people with a chronic disease. Studies of CAs for self-management of chronic disease operate within a multidisciplinary domain: self-management originates from (behavioral) psychology and CAs stem from intervention technology, while diseases are typically studied within the biomedical context. To ensure their effectiveness, structured evaluations and descriptions of the interventions, integrating biomedical, behavioral, and technological perspectives, are essential. OBJECTIVE: We aimed to examine the design and evaluation of CAs for self-management support of chronic diseases, focusing on their characteristics, integration of behavioral change techniques, and evaluation methods. The findings will guide future research and inform intervention design. METHODS: We conducted a systematic search in the PubMed and Embase databases to identify studies that investigated CAs for chronic disease self-management, published from January 1, 2018, to April 15, 2024. Full-text journal articles, published in English, studying the efficacy or effectiveness of a CA in the context of self-management for chronic diseases in adults were included. Data extraction was guided by conceptual frameworks to ensure comprehensive reporting of intervention and methodologies: the behavioral intervention technology model and the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and Online Telehealth) checklist. Risk of bias was assessed using the Risk of Bias 2 tool and the Risk of Bias in Non-randomized Studies-of Interventions (ROBINS-I) tool (version 2). RESULTS: In total, 25 studies were included, primarily focusing on text-based, rule-based CAs delivered via a mobile apps. The chronic diseases predominantly targeted were diabetes and cancer. Commonly identified clusters of behavior change techniques were "shaping knowledge," "feedback and monitoring," "natural consequences," and "associations." However, reporting of behavior change techniques and their delivery was lacking, and intervention descriptions were limited. Studies were mostly in the early phase, with a great variety in intervention descriptions, study methods, and outcome measures. CONCLUSIONS: Advancing the field of CA-based interventions requires transparent intervention descriptions, rigorous methodologies, consistent use of validated scales, standardized taxonomy, and reporting aligned with standardized frameworks. Enhanced integration of artificial intelligence-driven personalization and a focus on implementation in health care settings are critical for future research.

BACKGROUND: Although mobile health apps integrated with Internet of Things-enabled devices are increasingly used to satisfy the growing needs for home-based older adult care resulting from rapid population aging, their effectiveness is constrained by 3 key challenges: a focus on specific functions rather than on holistic and integrated support, absence of a solid theoretical framework for development, and a lack of personalized, real-time feedback to address diverse care needs. To overcome these limitations, we developed a knowledge-based clinical decision support system using mobile health technology-an intelligent and integrated older adults care model (SMART system). OBJECTIVE: This study aims to systematically outline the development process and outcomes of a knowledge base and trigger rules for the SMART system. METHODS: Our study adopted a user-centered approach guided by the nursing process and intervention mapping (IM) framework. We first identified older adult care needs through semistructured, in-depth interviews. Guided by the nursing process and informed by guidance from the World Health Organization's Integrated Care for Older People and World Health Organization International Classification of Functioning, Disability, and Health, along with the North American Nursing Diagnosis Association-I nursing diagnosis, we then determined care problems along with their underlying causes and risk factors and diagnostic criteria. Building on these findings, we applied the first 3 steps of the intervention mapping framework to formulate corresponding long-term and short-term care objectives, select appropriate evidence-based interventions, and match practical implementation approaches, which were grounded in rigorous evidence derived from systematic literature reviews, clinical guidelines, and expert insights. We also developed a set of trigger rules to link abnormalities in older adults with corresponding care problems and interventions in the SMART knowledge base. RESULTS: The semistructured in-depth interviews identified 5 types of care needs-daily life care, health care, external support, social participation, and self-development-which formed the foundation of the SMART knowledge base. Based on this, we identified 138 care problems, each with associated causes and risk factors and diagnostic criteria. The objective matrix comprised 138 long-term and 195 short-term care objectives. Guided by 15 expert-defined selection criteria, we then selected 450 evidence-based interventions, each paired with at least 1 feasible and practical implementation approach. Additionally, we developed diagnostic rules to match the assessment data with relevant care problems and their causes and risk factors and intervention trigger rules to formulate personalized interventions based on individual characteristics, ensuring tailored care aligned with specific care objectives. CONCLUSIONS: This study outlines the development process and outcomes of the SMART knowledge base and trigger rules. The study methodology offers theoretical support for developing knowledge bases and trigger rules of similar clinical decision support systems for home-based older adult care.

Providing human support for users of behavioral health technology can help facilitate the necessary engagement and clinical integration of digital tools in mental health care. A team conducted digital navigator training that taught participants how to promote patrons' digital literacy, evaluate and recommend health apps, and interpret smartphone data. The authors trained 80 participants from 21 organizations, demonstrating this training's feasibility, acceptability, and need. Case studies explore the implementation of this training curriculum. As technology's potential in mental health care expands, training can empower digital navigators to ensure that the use of digital tools is informed, equitable, and clinically relevant.

BACKGROUND: Type 1 diabetes (T1D) management requires following a complex and constant regimen relying on child or caregiver behaviors, skills, and knowledge. Psychological factors such as diabetes distress (DD), depression, and burnout are pertinent considerations in the treatment of pediatric T1D. Approximately 40% of youth and 61% of caregivers experience DD. Implementation of DD screening as part of clinical best practice is recommended and may facilitate treatment referral, perhaps leading to improved health or well-being for youth with T1D and their caregivers. By building on existing institutional infrastructure when available, screening via digital health platforms (applications, or "apps") may allow for timely screening of, and response to, DD. OBJECTIVE: This work details the creation, implementation, and refinement of a process to screen for DD in youth and their caregivers in the context of routine T1D care using a digital health platform. METHODS: DD screening was implemented in an outpatient endocrinology clinic over 1 year as part of a larger screen-to-treat trial for children aged 8-12.99 years and their caregivers. Validated measures were sent via digital health platform to be completed prior to the clinic visit. Results were initially reviewed manually, but a digital best practice alert (BPA) was later built to notify staff of elevated scores. Families experiencing DD received resources sent via the digital health platform. For this secondary analysis, child demographics and glycated hemoglobin A1c (HbA1c) were collected. RESULTS: During the screening period, absolute completion rates were 36.78% and 38.83%, with adjusted screening rates at 52.02% and 54.48%, for children and caregivers, respectively. A total of 21 children (mean HbA1c 8.04%, SD 1.39%) and 26 caregivers (child mean HbA1c 8.04%, SD 1.72%) reported elevated DD. Prior to BPA development, resources were sent to all but 1 family. After BPA implementation, all families were sent resources. CONCLUSIONS: Early findings indicate that DD education, screening, and response can be integrated via digital platforms in a freestanding outpatient endocrinology clinic, thereby facilitating timely treatment referral and provision of resources for those identified with distress. Notably, in the observed 1-year screening period, screening rates were low, and barriers to implementation were identified. While some implementation challenges were iteratively addressed, there is a need for future quality improvement initiatives to improve screening rates and the identification of, or response to, DD in our pediatric patients and their families.

Optimizing the overall health of individuals prior to pregnancy can improve both pregnancy and lifelong health outcomes. Despite extremely high financial expenditure on birth in the United States, maternal and infant mortality rates continue to rise. Moreover, significant racial and ethnic disparities persist in perinatal health outcomes. Preconception care, or health care provided before or between pregnancies, has the capacity to meet these challenges. Preconception care can be integrated into every health care visit, including visits with primary care, reproductive health, and mental health care clinicians. Increasing awareness among clinicians of the benefits of preconception care and equipping them with innovative strategies to implement this care into practice, the number of people receiving optimal care could be increased. Recent innovations in preconception care include group care, health applications (apps), reminders in electronic health records, social marketing campaigns, social media movements, community-based partnerships, health care policy and access, and improving public and clinician education on preconception health topics. Ultimately, improving preconception health is best done in partnership between the consumer and clinician. Midwives, whose care is person-centered and partnership-focused, are well positioned to champion the innovation and implementation of equitable preconception care. The purpose of this State of the Science review, therefore, is to synthesize the literature on recent evidence-based innovations that may be used to improve preconception health and counseling.

The fast developmental pace and widespread use of mobile technology and the internet mean that smartphone-based m-health (mobile health) applications (apps) have huge potential to further expand the reach of and access to drug-related health services towards a common goal of ensuring a healthier Europe. However, m-health for drug users and for health professionals in the field of drugs is still in its infancy and poorly documented at European Union (EU) level. The aim of this scoping study was therefore to carry out a first exploration of available smartphone applications in the drugs field within a European and global context. It explored the range of m-health applications available to users and professionals seeking information, support and advice in a wide range of EU languages. The systematic search of drug-related smartphone applications identified a total of 67 applications across the three main app stores. The identified m-health applications apply various technologies ranging from simple text-based content display to more advanced interactive functions such as video transmission, geo-tagging functions and automated personalised feedback. Based on the main objectives, content and target end-users of the 67 identified apps, three main groups of drug-related m-health applications emerged: apps that aim to disseminate drug-related information and advice, apps that provide interventions and support for drug users and apps for capacity building among health professionals. Most m-health apps address risk behaviour associated with drugs in general or drug use in specific settings (e.g. nightlife settings). Some drug-specific apps are available for more commonly used drugs such as cannabis and cocaine. A number of challenges for users, app developers and policymakers were identified in this scoping study. The lack of scientific evaluations of drug-related m-health interventions is concerning considering the increasing interest in and availability of such apps. Additionally, the lack of quality control of the content of these apps available to EU citizens, with no age limits, remains to be addressed. Global differences in therapeutic approaches used in the identified apps were apparent, especially between the United States and Europe, and this raises questions about the cross-cultural relevance of m-health applications. At the same time, the impact of the new EU General Data Protection Regulation may be of particular relevance in a context of fast global development of drug-related m-health apps available to EU citizens.

BACKGROUND: Supervised consumption sites (SCS) are an evidence-based intervention proven effective for preventing drug overdose deaths. Obstacles to accessing SCS include stigma, limited hours of operation, concerns about policing, and limited geographic availability. Mobile overdose response services (MORS) are novel technologies that provide virtual supervised consumption to help reduce the risk of fatal overdoses, especially for those who use alone. MORS can take various forms, such as phone-based hotlines and mobile apps. The aim of this article is to assess the perceptions of MORS among healthcare and harm reduction staff to determine if they would be comfortable educating clients about these services. METHODS: Twenty-two healthcare and harm reduction staff were recruited from Canada using convenience, snowball, and purposive sampling techniques to complete semistructured interviews. Inductive thematic analysis informed by grounded theory was used to identify main themes and subthemes. RESULTS: Four themes were identified: (1) increasing MORS awareness among healthcare providers was seen as useful; (2) MORS might lessen the burden of drug overdoses on the healthcare system but could also increase ambulance callouts; (3) MORS would benefit from certain improvements such as providing harm reduction resources and other supports; and (4) MORS are viewed as supplements for harm reduction, but SCS were preferred. CONCLUSIONS: This research provides valuable perspectives from healthcare and harm reduction workers to understand their perception of MORS and identifies key areas of potential improvement. Practical initiatives to improve MORS implementation outcomes exist.

BACKGROUND: Delivering prescription digital therapeutics (ie, evidence-based interventions designed to treat, manage, or prevent disorders via websites or smartphone apps) in primary care could increase patient access to substance use disorder (SUD) treatments. However, the optimal approach to implementing prescription digital therapeutics in primary care remains unknown. OBJECTIVE: This pilot study is a precursor to a larger trial designed to test whether implementation strategies (practice facilitation [PF] and health coaching [HC]) improve the delivery of prescription digital therapeutics for SUDs in primary care. This mixed methods study describes outcomes among patients in the 2 pilot clinics and presents qualitative findings on implementation. METHODS: From February 10 to August 6, 2021, a total of 3 mental health specialists embedded in 2 primary care practices of the same integrated health system were tasked with offering app-based prescription digital therapeutics to patients with SUD. In the first half of the pilot, implementation activities included training and supportive tools. PF (at 1 clinic) and HC (at 2 clinics) were added in the second half. All study analyses relied on secondary data, including electronic health records and digital therapeutic vendor data. Primary outcomes were the proportion of patients reached by the prescription digital therapeutics and fidelity related to ideal use. We used qualitative methods to assess the adherence to planned activities and the barriers and facilitators to implementing prescription digital therapeutics. RESULTS: Of all 18 patients prescribed the apps, 10 (56%) downloaded the app and activated their prescription, and 8 (44%) completed at least 1 module of content. Patients who activated the app completed 1 module per week on average. Ideal use (fidelity) was defined as completing 4 modules per week and having a monthly SUD-related visit; 1 (6%) patient met these criteria for 10 weeks (of the 12-week prescription period). A total of 5 (28%) patients had prescriptions while HC was available, 2 (11%) were successfully contacted, and both declined coaching. Clinicians reported competing clinical priorities, technical challenges, and logistically complex workflows in part because the apps required a prescription. Some pilot activities were impacted by staff turnover that coincided with the COVID-19 pandemic. The facilitators to implementation were high engagement and the perception that the apps could meet patient needs. CONCLUSIONS: The pilot study encountered the barriers to implementing prescription digital therapeutics in a real-world primary care setting, especially staffing shortages, turnover, and competing priorities for clinic teams. The larger randomized trial will clarify the extent to which PF and HC improve the implementation of digital therapeutics. TRIAL REGISTRATION: ClinicalTrials.gov NCT04907045; https://clinicaltrials.gov/study/NCT04907045.

Professionalism in any field requires keeping pace with change, and nowhere is it more true than medicine. Knowledge flow has changed dramatically since today's accreditation standards were developed, and change continues more rapidly than ever. It's time for a fresh look at how best to achieve care in this altered environment, where valid knowledge may come from the patient as well as from clinician resources: a sociological change driven by technological change. The power structure of the clinical relationship is inevitably altered as constraints on patient knowledge are loosened by the internet, apps, and devices, undermining a paradigm of patients as uninformed recipients of care based on a one-way flow of wisdom from providers. Case after case is presented showing that patients today have generated undeniable value, violating the expectations and assumed best practices of the old model. To understand this sociological (yet scientific) change, this article reviews the role of paradigms in the history of sciences as described in Thomas Kuhn's landmark book The Structure of Scientific Revolutions and describes how these anomalous patient stories force the conclusion that the traditional paradigm of patients is no longer supportable and a new paradigm is needed. This in turn means our standards of professionalism and appropriate care must be updated, lest we fail to achieve best possible care in our increasingly overburdened system. Our new standard must be to teach clinicians to recognize, welcome, and work with empowered "e-patients" in the new model of participatory medicine.

BACKGROUND: Health professionals' training is a key element to address unhealthy alcohol use in Primary Care (PC). Education about alcohol use can be effective in improving PC provider's knowledge and skills addressing alcohol-related problems. The aim of the study was to evaluate the training of health professionals to address unhealthy alcohol use in PC. METHODS: An observational, descriptive, cross-sectional, multicenter study was performed. LOCATION: PC centres of the Spanish National Health System (SNHS). PARTICIPANTS: Family physicians, residents and nurses completed an online questionnaire that inquired about their training (none, basic, medium or advanced), knowledge and preventive practices aimed at reducing unhealthy alcohol use. The study population was recruited via random sampling, stratified by the regions of the SNHS's PC centre, and by email invitation to members of two Spanish scientific societies of Family Medicine. RESULTS: A total of 1760 professionals participated in the study. Sixty-seven percent (95% CI: 67.5-71.8) reported not having received specific training to address unhealthy alcohol use, 30% (95% CI: 27.4-31.7) reported having received basic training, and 3% (95% CI: 2.3-4.0) medium/advanced training. The training received was greater in younger providers (p < 0.001) who participated in the PAPPS (Preventive Activities and Health Promotion Programme) (p < 0.001). Higher percentages of providers with intermediate or advanced training reported performing screening for unhealthy alcohol use (p < 0.001), clinical assessment of alcohol consumption (p < 0.001), counselling of patients to reduce their alcohol intake (p < 0.001) or to abstain, in the cases of pregnant women and drivers (p < 0.001). CONCLUSION: Our study reveals a low level of training among Spanish PC providers to address unhealthy alcohol use. A higher percentage of screening, clinical assessment and counselling interventions aimed at reducing unhealthy alcohol use was reported by health professionals with an intermediate or advanced level of training.