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Tuberculosis is a leading cause of death in South Africa, with poor adherence undermining treatment success. Findings from recent research on the impact of mHealth (mobile health) interventions on tuberculosis treatment outcomes show promise, yet many interventions remain untested in African contexts. Rising smartphone ownership in South Africa enables more complex mHealth interventions, offering an opportunity to deploy behavioral tools within high-burden, resource-constrained settings. This pilot study evaluates the feasibility and effectiveness, among low-income patients at a South African clinic, of a WhatsApp (Meta)-based conversational mHealth platform designed to tackle specific behavioral barriers to adherence. Aims include the following: (1) evaluating coverage by studying the proportion of patients within the target group who own smartphones, (2) describing patterns of engagement with the platform and the role of mobile data scarcity as a barrier to use, and (3) producing evidence on the impact that a behavioral mHealth intervention can have on tuberculosis treatment success. Patients newly diagnosed with drug-susceptible pulmonary tuberculosis between August 2022 and October 2023 completed a screening survey. Those owning compatible mobile phones were invited to enroll. The platform provided reminders alongside behavioral support features. Coverage was studied by estimating smartphone ownership among screened patients and comparing characteristics between enrolled patients (n=42) and those receiving standard care (n=102) using standardized differences. Engagement was analyzed using local polynomial regressions for usage trends and logistic regressions to estimate the impact of mobile data top-ups. The marginal effect of enrollment on the probability of successfully completing tuberculosis treatment was studied using a t test and logistic regressions with and without covariates. A total of 34% (49/146) of screened participants owned a phone that could use WhatsApp. There were differences in characteristics by enrollment status. Further, 50% of patients engaged with the platform each day until the end of treatment. Overcoming an initial inability to send unprompted messages to inactive patients was associated with an immediate 13-percentage-point increase in aggregate engagement the following month. Mobile data scarcity hindered use-receiving mobile data top-ups within the previous week was associated with a 3.37-percentage-point increase (95% CI 0.0007 to 0.0666) in platform engagement. The estimated marginal effect of enrollment was a 17.6-percentage-point (95% CI 0.003 to 0.348) increase in treatment completion, becoming attenuated after adjusting for patient characteristics (12.8 percentage points, 95% CI -0.048 to 0.304). While phone ownership and mobile data constraints represent barriers to feasibility, findings suggest that smartphone-based mHealth interventions may aid successful treatment completion-alleviating health system burdens by automating care for less vulnerable patients. Engagement with the platform throughout tuberculosis treatment was high and stable, and enrolled users experienced a higher success rate. A randomized controlled trial is required for impact evaluation.

Rates of opioid use disorder (OUD) have increased among women over the past 2 decades. Medication treatment for opioid use disorder (MOUD) is effective but underused. Gender-specific treatments for women have been associated with improved substance use outcomes. However, these treatments have not specifically targeted women's engagement in MOUD, and the impact of existing gender-specific treatments is restricted by in-person delivery. The aim of this study was to develop a digital intervention to feasibly deliver gender-specific care that addresses the individualized needs of women with OUD to increase engagement in MOUD. A mixed methods, user-centered design approach was used to inform the development of a digital intervention. In phase 1, qualitative interviews were conducted with women with lived experience of OUD (n=20) and providers who treat women with OUD (n=8). Interviews were recorded, transcribed, and coded for themes. In addition, a larger sample of treatment providers (n=55) completed an online survey to further inform the content of the digital intervention. Phase 2 consisted of designing, beta-testing (n=5), and refining the intervention. The age of women with lived experience ranged from 21 to 59 (mean 38.5, SD 9.4) years; 63% (5/8) of providers interviewed were female participants. The qualitative interview data from women with lived experience and providers were grouped into 6 thematic categories: 3 treatment-related (1) barriers to treatment, (2) facilitators to successful recovery, and (3) important issues to address in treatment, and 3 technology-related (4) positives of using technology as part of treatment, (5) suggested technology features, and (6) barriers to using technology. Across the treatment-related categories, several themes touched on women-specific factors including family responsibilities, abusive partners, stigma, and motivation for treatment (eg, pregnancy). The technology-related categories provided information for designing the features of the intervention, as well as revealing barriers to technology use, which could be helpful in developing implementation strategies. Provider survey participants were primarily female participants (40/55, 73%), with a mean age of 42.5 (SD 12.5) years. Survey data provided additional information on barriers to treatment and suggested technology features. Based on these data and preliminary work, the Healthy Women intervention was created. Minor edits to content and visual design were made in the beta-testing phase. The final version includes a web-based component with 6 topic modules and a mobile component. Topics in the web-based component are presented through infographics, text, videos, and interactive questions. The mobile component includes daily motivational messages, skills practice activities (2/wk), weekly check-ins, and resources (always available). Important themes and suggested features from women with lived experience and providers were incorporated into a digital intervention for women with OUD. Data on feasibility, satisfaction, and engagement with the Healthy Women intervention are currently being collected in phase 3, a pilot randomized controlled trial.

SMS text message reminders have been used to promote many health behaviors, such as improving diet and physical activity, managing chronic health conditions, reminding patients about medical appointments, and supporting medication adherence across a range of health conditions. Despite their promise, developing effective reminders tailored to specific patient populations is resource-intensive. AI may facilitate item development, and online research panels may provide an efficient way to test message content with target users prior to implementing large-scale trials. This study aimed to (1) develop a library of antidepressant adherence-promoting SMS text messages that are perceived as helpful, (2) test whether an online panel approach can be used to evaluate them, and (3) identify message characteristics perceived as most helpful by patients with depression taking antidepressant medication. In total, 83 SMS text message reminders were developed based on barriers to adherence and behavior change technique pairings, with approximately half authored by the study team, and half generated by AI. Using an online panel, we recruited 181 American adults with depression currently prescribed an antidepressant medication. Each participant rated a subset of messages on how much they thought each would help them remember to take their medication. Associations between message characteristics and ratings were estimated using generalized linear models in Stata. Survey weights were used in analyses to align the sample with national antidepressant user demographics. The online panel was able to rapidly recruit a sample of participants, who provided 7520 item ratings in total. AI-generated messages were rated as significantly more helpful than those authored by humans (adjusted mean difference 0.24 on a 5-point scale, 95% CI 0.12-0.36; P<.001). Messages addressing delayed symptom benefit were preferred over other adherence barriers, and behavior change techniques emphasizing self-monitoring (P<.001), habit formation (P<.001), and natural consequences (P<.001) received significantly higher ratings than those using external influence or support. No difference was observed between motivational and informational message content. Online panels offer a rapid, scalable approach to evaluating SMS text message reminders for patients currently taking antidepressants. When provided with specific instructions and human-led examples, AI can efficiently generate message content perceived to be helpful in promoting medication adherence. Given that AI-generated content received higher ratings than human-authored messages, future work may consider using this tool to support rapid intervention development. In addition, identifying common barriers to adherence and applying behavior change techniques to address those barriers can inform targeted message development and support adherence. Taken together, these findings demonstrate the utility of combining low-cost methods such as online panel research with AI to accelerate the design and preliminary evaluation of digital health interventions.

Over the past half-century, medical research on cardiovascular disease (CVD) has achieved a great deal; however, medication adherence is unsatisfactory. Nearly 50% of patients do not follow prescriptions when taking medications, which limits the ability to maximize their therapeutic effects and results in adverse clinical outcomes and high healthcare costs. Furthermore, the effects of medication adherence interventions are disappointing, and tailored interventions have been proposed as an appropriate way to improve medication adherence. To rethink and reconstruct methods of improving medication adherence for CVD, the literature on tailored interventions for medication adherence focusing on CVD within the last 5 years is retrieved and reviewed. Focusing on identifying nonadherent patients, detecting barriers to medication adherence, delivering clinical interventions, and constructing theories, this article reviews the present state of tailored interventions for medication adherence in CVD and also rethinks the present difficulties and suggests avenues for future development.

Community college (CC) students face significant mental health concerns but are unlikely to receive treatment. Barriers to mental health service uptake among CC students have been delineated, but few studies have identified strategies to improve uptake. Text messaging has been used to address engagement barriers to mental health services among adolescents and adults, but little research has explored this strategy for CC students. The goal of this study was to partner with CC students to co-design and conduct pilot usability testing of a text messaging intervention to address barriers and increase uptake of a mental health screening and treatment program, called Screening and Treatment for Anxiety and Depression (STAND), offered to CC students. We conducted 2 parallel sets of 4 co-design focus groups with CC students who had varying levels of engagement with STAND. We used rapid qualitative analysis to extract key themes, create text message prototypes and refine them, and present updated prototypes to gather feedback across workshops. We also assessed six usability factors on a 5-point Likert scale: satisfaction, helpfulness, attractiveness, readability, comprehension, and likelihood of getting started with STAND after receiving texts. Key themes emerged about perceptions of texting, barriers to STAND, a basic framework for the text message intervention, feedback about the format of messages, and feedback about the content of messages. Students expressed positive regard for text messaging and general agreement on key barriers to STAND. Students codeveloped a framework for the intervention, including (1) delivering introductory texts to engage students in the text messages, (2) providing a personalized approach for students to select barriers most salient for them, and (3) delivering tailored content designed by students to address each barrier. Across workshops, several themes emerged with regard to how messages should be formatted and delivered, including the following: use short messages; use not too many messages; use relevant language; use images, memes, and short videos; and make messages \"human-like.\" Themes related to the content of messages included the following: reminders that you are not alone, knowledge that STAND has worked for other students, expressing understanding of student context and stressors, and providing an option to speak to a team member. Mean ratings on usability factors ranged from 3.88 (SD 0.64) to 4.25 (SD 0.46). This study describes a process for co-designing a text messaging mental health engagement intervention with CC students that is grounded in a human-centered design approach. Further research is needed to rigorously test this intervention and make iterative refinements to improve response and effectiveness.

The National Health Service 10-year health plan emphasizes an increasing shift toward digital health care delivery. However, there is limited research on how best to support, engage, and include individuals who are digitally excluded. As health care services become more digitally driven, evidence-based interventions are needed to address digital exclusion and ensure equitable access to care, particularly for people living with long-term conditions. This study aimed to evaluate the feasibility and acceptability of providing digital literacy training alongside a digital health intervention (DHI; Ex-Tab intervention), compared with providing a DHI alone. Kidney Beam, a DHI designed to promote physical activity and improve quality of life in people with chronic kidney disease (CKD), was used as an exemplar DHI. This mixed methods, single-site pilot randomized controlled trial recruited 40 adults with CKD who were digitally excluded. Digital exclusion was defined as lacking access to a Wi-Fi-enabled digital device or having a Digital Health Care Literacy Scale (DHLS) score of <7 (range 0-21). Participants were randomized 1:1 to receive either the Kidney Beam Ex-Tab intervention or Kidney Beam alone (control). The intervention group received a Wi-Fi-enabled iPad on loan with Kidney Beam preinstalled, digital literacy training, and ongoing support to access the 12-week Kidney Beam program (twice weekly live exercise and education sessions). The control group received sign-up instructions for Kidney Beam only. Feasibility outcomes were assessed against a priori progression criteria and included screening, recruitment, retention, adherence, safety, and acceptability. Secondary outcomes included the Kidney Disease Quality of Life Questionnaire, Chalder Fatigue Questionnaire, and Patient Health Questionnaire-4. Outcomes were measured at baseline and 12 weeks. Acceptability and user experience were explored through semistructured interviews with participants from both groups at 12 weeks (n=25). Between September 2023 and September 2024, a total of 169 individuals were screened and 40 were enrolled (median age 66.5 years; 20 male individuals; median DHLS score: 4). Twenty-one participants were randomized to the Kidney Beam Ex-Tab group and 19 to the Kidney Beam alone group. Of the 40 participants, 35 (88%) completed the 12-week follow-up (intervention: n=18; control: n=17). All prespecified feasibility criteria for recruitment, retention, adherence, and safety were met. Qualitative findings indicated that the tablet loan and digital literacy training were acceptable and highly valued, enhancing confidence, motivation, and DHI engagement. Providing loaned devices was particularly important for overcoming access barriers, especially for participants unable to afford their own device. Providing Wi-Fi-enabled devices and digital literacy training alongside a DHI was feasible and acceptable for people with lower digital literacy levels. The findings support progression to a future definitive multicenter trial or implementation study and offer transferable insights for the design of digital inclusion strategies for other long-term health conditions.

Medication adherence remains a significant unmet challenge for optimizing patient outcomes. Recent advances in the conceptualization, measurement, and support of medication adherence offer fresh opportunities to make a meaningful impact on adherence-related behavior and outcomes. These advances emphasize the multifaceted and dynamic nature of medication adherence, provide novel methods for monitoring medication adherence in clinical care, and articulate a set of multilevel strategies to more effectively improve and sustain medication adherence. Here, we offer recommendations for how clinicians can better engage with, and benefit from, these innovations to improve patient medication adherence and associated treatment outcomes.

Background Consuming a balanced diet and regular activity have health benefits. However, many adults have a difficult time adhering to diet and activity recommendations, especially in lifestyle interventions. Adherence to recommendations could be improved if common facilitators and barriers are accounted for in intervention design. The aim of this systematic review was to understand perceived barriers and facilitators to lifestyle (diet and/or activity) intervention guidelines. Methods This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Studies included relied on qualitative methods to explore the barriers and facilitators healthy adults ( ≥ 18 years) experienced in lifestyle interventions. Google Scholar, Cochrane Reviews, Medline, PubMed, and Web of Science were searched from January 2005 to October 2021. Main themes from each paper were thematically analyzed and reported as a barrier or facilitator to adherence at the individual, environment or intervention level using inductively derived themes. Study quality was assessed using the Critical Appraisal Skills Programme. Results Thirty-five papers were included. Of these, 46% were conducted in North America and the majority had more female participants (86% in mixed-sex studies, 26% females only). Similar themes emerged across all three levels as facilitators and barriers. At the individual level, attitudes, concern for health and physical changes. At the environmental level, social support, social accountability, changeable and unchangeable aspects of the community. Finally, delivery and design and content at the intervention level. An additional facilitator at the intervention level included fostering self-regulation through Behavior Change Taxonomies (BCT). Conclusions Lifestyle interventions that foster self-regulatory skills, opportunities for social engagement and personalization of goals may improve behaviour adherence. This can be achieved through inclusion of BCT, tapering off of intervention supports, identification of meaningful goals and anticipated barriers with participants.

Despite the high prevalence of type 2 diabetes mellitus in China, few patients are achieving adequate management targets. While digital behavior change interventions (DBCIs) are promising solutions, sustained long-term user engagement with these new technologies remains challenging. The objectives of this study were to (1) describe the long-term user engagement with the SMARTDiabetes app, (2) explore the associations between user engagement and trial effectiveness, and (3) identify main influencing factors of user engagement. A mixed methods process evaluation was conducted alongside the 2-year SMARTDiabetes trial to assess long-term user engagement with the DBCI, investigate its association with trial effectiveness, and explore its influencing factors. Quantitative data included clinical outcomes and app usage data; qualitative data included an expert review of the DBCI and semistructured interviews with key stakeholders. Findings were synthesized using Michie's conceptual framework for engagement with DBCIs. A total of 1038 participants were included in the quantitative analyses, and 12 in-depth interviews were conducted in June 2020. The mean proportion of monthly active users was 46.4% (SD 7.8%), with a gradual decline from 56.3% at the start (April 2018) to 42.2% at the end of trial (July 2019). The proportion of sustained active users was 32.9% (342/1038), with rural users showing a significantly higher rate than urban users (38.3% vs 27.3%; P<.001). We found a strong link between user engagement and the effectiveness in achieving primary health outcome (risk ratio 1.37, 95% CI 1.21-1,55; P<.001) and a clear dose-response relationship between the level of app interactions and degree of improvement in the health outcome. Key drivers of user engagement included 6 behavior change techniques (ie, reward, feedback, reminders, goal setting, self-monitoring, and social support features), 4 implementation facilitators (credibility features, professional support, guidance, and ease of use), and 5 contextual contributors (younger age, better education, greater smartphone literacy, closer patient-doctor relationship, and stronger primary health care facilities commitment). Long-term, sustained engagement with a mobile app intervention for type 2 diabetes mellitus self-management is achievable in the primary health care setting in China. Higher engagement is associated with better health outcomes. The influencing factors identified in the SMARTDiabetes study provide valuable insights for developing targeted strategies to enhance user engagement with DBCIs and improve overall program effectiveness.

Social support is necessary for patients with heart failure (HF) to take medication, which can lead to decreased hospitalization and mortality rates. However, the effect of patient health literacy on this relationship remains unclear. This study aimed to evaluate the mediating effect of health literacy on the relationship between social support and medication adherence among patients with HF. A cross-sectional correlational design was used between August and October 2024 for 249 patients with HF. Data were collected using patients’ sociodemographic and health status, the Arabic version of the General Medication Adherence Scale (GMAS), BRIEF Health Literacy Screening Tool, and Oslo Social Support Scale (OSSS-3). Hayes’ Process Macro program, version 4.2, Model 4, was used to assess the possible interaction effects. Statistical significance was set at p less than .05. There was a weak positive correlation between patients’ medication adherence and health literacy (r = .247, p  < .001) and social support (r = .204, p  < .001). In addition, there was a significant correlation between HL status and social support (r = .314, p  < .001). Factors that increased medication adherence included older age (B = 0.06, p  = .027), not smoking (B = 2.21, p  < .001), other chronic diseases (B = 1.23, p  = .005), higher health literacy (B = 0.30, p  = .002), and social support (B = 0.33, p  = .044). The model indicated an indirect positive effect of social support on medication adherence through health literacy (β = 0.064, p  = .007). Social support had a positive direct effect on health literacy (β = 0.314, p  < .001) and a positive effect of health literacy on medication adherence (β = 0.203, p  = .002). Social support had a significant positive direct effect on medication adherence (β = 0.140, p  = .031), with a total effect of β = 0.204, p  = .001. Health literacy showed a statistically significant indirect association in the mediation model. This study revealed that patients with higher health literacy are better equipped to manage complex treatment regimens and engage in self-care. This effect was further amplified by social support, which both directly and indirectly enhanced adherence.