BACKGROUND: Low physical activity among older adults is related to adverse health outcomes such as depression and loneliness, poor physical function and increased risk of falls. This study was designed to increase physical activity through a digital, group-based, physical activity and music intervention and to examine its effectiveness on social, mental and physical health outcomes.
METHODS: Participants were 34 older adults (65 years +) recruited across four care homes in Scotland to a pilot study. Surveys were administered at baseline and post-intervention, comprising measures of fear of falling, depression and anxiety, loneliness, sleep satisfaction and quality of life. A battery of physical function tests and saliva sampling for cortisol and dehydroepiandrosterone hormone analysis were also conducted at each time point. Additionally, process evaluation measures (recruitment, intervention fidelity, attendance, retention rates and safety) were monitored. The intervention comprised 12 weeks of three prescribed digital sessions per week: movement and music (n = 2) and music-only (n = 1), delivered by an activity coordinator in the care home. Post-intervention interviews with staff and participants were conducted to gain qualitative data on the acceptability of the intervention.
RESULTS: An average of 88% of prescribed sessions were delivered. Pre- to post-intervention intention-to-treat analysis across all participants revealed significant improvements in anxiety, salivary DHEA, fear of falling and loneliness. There were no significant improvements in health-related quality of life, perceived stress, sleep satisfaction or physical function tests, including handgrip strength. Qualitative analysis highlighted benefits of and barriers to the programme.
CONCLUSIONS: The digital movement and music intervention was deemed acceptable and delivered with moderate fidelity, justifying progression to a full-scale trial. Although a proper control group would have yielded more confident causal relationships, preliminary psychosocial and biological effects were evident from this trial. To show significant improvements in physical function, it is likely that a bigger sample size providing sufficient power to detect significant changes, greater adherence, longer intervention and/or higher exercise volume may be necessary.
BACKGROUND: The trial is registered at ClinicalTrials.gov, number NCT05601102 on 01/11/2022.

UNASSIGNED: Physical inactivity is associated with health risks, contributing to various diseases and all-cause mortality. Despite recommendations for regular physical activity (PA), many adults remain inactive, influenced by socioeconomic and environmental factors. Digital interventions, particularly web-based PA programs, offer promising possibilities to promote PA across populations. These programs vary in their effectiveness, reflecting differences in design, user engagement, and behavior change techniques employed.
UNASSIGNED: This study evaluates the effectiveness of the 12-week multimodal web-based TKFitnessCoach. The PA online program is part of the TK-HealthCoach. This study investigates the program\'s impact on self-reported PA levels, goal attainment, healthrelated quality of life, body weight, and eating behavior, comparing an interactive personalized web-based intervention and non-interactive web-based health information.
UNASSIGNED: In a randomized controlled trial (RCT), participants were allocated to either the intervention group (IG), receiving access to the interactive TK-FitnessCoach, or the control group (CG) that was provided a static website with evidence-based information on PA. The study targeted a German-speaking adult population interested in improving health behavior. Data was assessed at T0 (beginning of the study), T1 (postintervention), T2, 6 months, and T3, 12 months follow-ups, focusing on self-reported PA at T3 and on various secondary outcomes.
UNASSIGNED: We achieved equally distributed sociodemographics in both the IG and the CG with a mean age of 42.8 (IG), resp. 43.1 years (CG), and female participants of 76.1 % (IG), resp. 74.7 % (CG). PA at baseline was 277.9 min/week in the IG and 273.3 min/week in the CG. Both, the IG (n = 1153 in the Intention-to-treat (ITT) dataset) and CG (n = 1177 in the ITT dataset) exhibited significant increases in PA over time (IG(T3-T0) = 72.92 min/week; CG(T3-T0) = 74.12 min/week).However, the study did not find significant differences in the effectiveness of the interactive TK-FitnessCoach compared to the non-interactive control in terms of improving PA and related health outcomes. The intensity of using the TK-FitnessCoach was not associated with PA.
UNASSIGNED: Both programs were effective in promoting PA among adults, with no significant differences observed between the two RCT groups. This highlights the potential of digital interventions in addressing physical inactivity, suggesting that the effectiveness of such programs may not solely depend on their interactivity but also on the quality and relevance of the information provided. Further research is needed to explore optimization strategies for such interventions, especially for persons with low PA, including user engagement, behavior change techniques, and the integration of objective PA tracking methods.
UNASSIGNED: German Clinical Trials Register DRKS00020249; https://drks.de/search/en/trial/DRKS00020249.

BACKGROUND: Despite being the primary setting for HIV prevention among men who have sex with men (MSM) since the start of the epidemic, community-based organizations (CBOs) struggle to reach this historically stigmatized and largely hidden population with face-to-face interventions. HIV researchers have readily turned to the internet to deliver critical HIV education to this group, with evidence of high effectiveness and acceptability across studies. However, implementation outside of research contexts has been limited and not well studied. We aimed to assess HIV CBOs\' readiness to adopt digital health interventions and identify contextual factors that may contribute to differing levels of readiness.
METHODS: We recruited 22 CBOs across the US through a pragmatic request-for-proposals process to deliver Keep It Up! (KIU!), an evidence-based eHealth HIV prevention program. We used mixed methods to examine CBO readiness to adopt digital health interventions (RADHI). Before implementation, CBO staff completed a 5-item RADHI scale (scored 0-4) that demonstrated concurrent and predictive validity. We interviewed CBO staff using semi-structured questions guided by the Consolidated Framework for Implementation Research and compared RADHI score groups on determinants identified from the interviews.
RESULTS: Eighty-five staff (range = 1-10 per CBO) completed the RADHI. On average, CBOs reported moderate-to-great readiness (2.74) to adopt KIU!. High RADHI CBOs thought KIU! was a top priority and an innovative program complementary to their existing approaches for their clients. Low RADHI CBOs expressed concerns that KIU! could be a cultural mismatch for their clients, was lower priority than existing programs and services, relied on clients\' own motivation, and might not be suitable for clients with disabilities. Value, appeal, and limitations did not differ by RADHI group.
CONCLUSIONS: While HIV CBOs are excited for the opportunities and advantages of digital interventions, additional pre-implementation and implementation support may be needed to increase perceived value and usability for different client populations. Addressing these limitations is critical to effective digital prevention interventions for HIV and other domains such as mental health, chronic disease management, and transitions in care. Future research can utilize our novel, validated measure of CBOs\' readiness to adopt digital health interventions.
BACKGROUND: NCT03896776, clinicaltrials.gov, 1 April 2019.

BACKGROUND: Advanced cancer significantly impacts patients\' and family caregivers\' quality of life. When patients and caregivers are supported concurrently as a dyad, the well-being of each person is optimized. Family, Outlook, Communication, Uncertainty, Symptom management (FOCUS) is a dyadic, psychoeducational intervention developed in the United States, shown to improve the well-being and quality of life of patients with advanced cancer and their primary caregivers. Originally, a nurse-delivered in-person intervention, FOCUS has been adapted into a self-administered web-based intervention for European delivery.
OBJECTIVE: The aims of this study are to (1) adapt FOCUS to the Australian context (FOCUSau); (2) evaluate the effectiveness of FOCUSau in improving the emotional well-being and self-efficacy of patients with advanced cancer and their primary caregiver relative to usual care control group; (3) compare health care use between the intervention and control groups; and (4) assess the acceptability, feasibility, and scalability of FOCUSau in order to inform future maintainable implementation of the intervention within the Australian health care system.
METHODS: FOCUS will be adapted prior to trial commencement, using an iterative stakeholder feedback process to create FOCUSau. To examine the efficacy and cost-effectiveness of FOCUSau and assess its acceptability, feasibility, and scalability, we will undertake a hybrid type 1 implementation study consisting of a phase 3 (clinical effectiveness) trial along with an observational implementation study. Participants will include patients with cancer who are older than 18 years, able to access the internet, and able to identify a primary support person or caregiver who can also be approached for participation. The sample size consists of 173 dyads in each arm (ie, 346 dyads in total). Patient-caregiver dyad data will be collected at 3 time points-baseline (T0) completed prerandomization; first follow-up (T1; N=346) at 12 weeks post baseline; and second follow-up (T2) at 24 weeks post baseline.
RESULTS: The study was funded in March 2022. Recruitment commenced in July 2024.
CONCLUSIONS: If shown to be effective, this intervention will improve the well-being of patients with advanced cancer and their family caregivers, regardless of their location or current level of health care support.
BACKGROUND: ClinicalTrials.gov NCT06082128; https://clinicaltrials.gov/study/NCT06082128.
UNASSIGNED: PRR1-10.2196/55252.

BACKGROUND: Cardiometabolic diseases (CMDs) are a group of interrelated conditions, including heart failure and diabetes, that increase the risk of cardiovascular and metabolic complications. The rising number of Australians with CMDs has necessitated new strategies for those managing these conditions, such as digital health interventions. The effectiveness of digital health interventions in supporting people with CMDs is dependent on the extent to which users engage with the tools. Augmenting digital health interventions with conversational agents, technologies that interact with people using natural language, may enhance engagement because of their human-like attributes. To date, no systematic review has compiled evidence on how design features influence the engagement of conversational agent-enabled interventions supporting people with CMDs. This review seeks to address this gap, thereby guiding developers in creating more engaging and effective tools for CMD management.
OBJECTIVE: The aim of this systematic review is to synthesize evidence pertaining to conversational agent-enabled intervention design features and their impacts on the engagement of people managing CMD.
METHODS: The review is conducted in accordance with the Cochrane Handbook for Systematic Reviews of Interventions and reported in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Searches will be conducted in the Ovid (Medline), Web of Science, and Scopus databases, which will be run again prior to manuscript submission. Inclusion criteria will consist of primary research studies reporting on conversational agent-enabled interventions, including measures of engagement, in adults with CMD. Data extraction will seek to capture the perspectives of people with CMD on the use of conversational agent-enabled interventions. Joanna Briggs Institute critical appraisal tools will be used to evaluate the overall quality of evidence collected.
RESULTS: This review was initiated in May 2023 and was registered with the International Prospective Register of Systematic Reviews (PROSPERO) in June 2023, prior to title and abstract screening. Full-text screening of articles was completed in July 2023 and data extraction began August 2023. Final searches were conducted in April 2024 prior to finalizing the review and the manuscript was submitted for peer review in July 2024.
CONCLUSIONS: This review will synthesize diverse observations pertaining to conversational agent-enabled intervention design features and their impacts on engagement among people with CMDs. These observations can be used to guide the development of more engaging conversational agent-enabled interventions, thereby increasing the likelihood of regular intervention use and improved CMD health outcomes. Additionally, this review will identify gaps in the literature in terms of how engagement is reported, thereby highlighting areas for future exploration and supporting researchers in advancing the understanding of conversational agent-enabled interventions.
BACKGROUND: PROSPERO CRD42023431579; https://tinyurl.com/55cxkm26.
UNASSIGNED: DERR1-10.2196/52973.

BACKGROUND: Limited guidance exists for analyzing participant engagement in provider-guided digital health interventions (DHIs). System usage is commonly assessed, with acknowledged limitations in measuring socio-affective and cognitive aspects of engagement. Nurse WRITE, an 8-week web-based nurse-guided DHI for managing symptoms among women with recurrent ovarian cancer, offers an opportunity to develop a framework for assessing multidimensional engagement.
OBJECTIVE: This study aims to develop a conceptual and analytic framework to measure socio-affective, cognitive, and behavioral engagement with provider-guided DHIs. We then illustrate the framework\'s ability to describe and categorize engagement using Nurse WRITE as an example.
METHODS: A sample of 68 participants from Nurse WRITE who posted on the message boards were included. We adapted a prior framework for conceptualizing and operationalizing engagement across 3 dimensions and finalized a set of 6 distinct measures. Using patients\' posts, we created 2 socio-affective engagement measures-total count of socio-affective engagement classes (eg, sharing personal experience) and total word count-and 2 cognitive engagement measures-total count of cognitive engagement classes (eg, asking information-seeking questions) and average question completion percentage. Additionally, we devised behavioral engagement measures using website data-the total count of symptom care plans and plan reviews. k-Means clustering categorized the participants into distinct groups based on levels of engagement across 3 dimensions. Descriptive statistics and narratives were used to describe engagement in 3 dimensions.
RESULTS: On average, participants displayed socio-affective engagement 34.7 times, writing 14,851 words. They showed cognitive engagement 19.4 times, with an average of 78.3% completion of nurses\' inquiries. Participants also submitted an average of 1.6 symptom care plans and 0.7 plan reviews. Participants were clustered into high (n=13), moderate (n=17), and low engagers (n=38) based on the 6 measures. High engagers wrote a median of 36,956 (IQR 26,199-46,265) words. They demonstrated socio-affective engagement approximately 81 times and cognitive engagement around 46 times, approximately 6 times that of the low engagers and twice that of the moderate engagers. High engagers had a median of 91.7% (IQR 82.2%-93.7%) completion of the nurses\' queries, whereas moderate engagers had 86.4% (IQR 80%-96.4%), and low engagers had 68.3% (IQR 60.1%-79.6%). High engagers completed a median of 3 symptom care plans and 2 reviews, while moderate engagers completed 2 plans and 1 review. Low engagers completed a median of 1 plan with no reviews.
CONCLUSIONS: This study developed and reported an engagement framework to guide behavioral intervention scientists in understanding and analyzing participants\' engagement with provider-guided DHIs. Significant variations in engagement levels across 3 dimensions highlight the importance of measuring engagement with provider-guided DHIs in socio-affective, cognitive, and behavioral dimensions. Future studies should validate the framework with other DHIs, explore the influence of patient and provider factors on engagement, and investigate how engagement influences intervention efficacy.

Background and Objectives: Chronic Obstructive Pulmonary Disease (COPD) is the third most common cause of death globally. Pulmonary rehabilitation (PR) programmes are important to reduce COPD symptoms and improve the quality of life of people with COPD. Digital health interventions have recently been adopted in PR programmes, which allow people with COPD to participate in such programmes with low barriers. The aim of this study is to review and discuss the reported effects of digital health interventions on PR outcomes in people with COPD. Materials and Methods: To achieve the study goals, a systematic literature search was conducted using PubMed (MEDLINE), CINAHL, AMED, SPORTDiscus and the Physiotherapy Evidence Database. Randomised clinical trials (RCTs) were included if they met specified criteria. Two reviewers independently checked titles, abstracts, and performed full-text screening and data extraction. The quality assessment and risk of bias were performed in accordance with the PEDRO scale and Cochrane Risk of Bias tool 2, respectively. Results: Thirteen RCTs were included in this systematic review with 1525 participants with COPD. This systematic review showed the potential positive effect of digital health PR on the exercise capacity-measured by 6- and 12-min walking tests, pulmonary function, dyspnoea and health-related quality of life. There was no evidence for advantages of digital health PR in the improvement of anxiety, depression, and self-efficacy. Conclusions: Digital health PR is more effective than traditional PR in improving the pulmonary and physical outcomes for people with COPD, but there was no difference between the two PR programmes in improving the psychosocial outcomes. The certainty of the findings of this review is affected by the small number of included studies.

BACKGROUND: Digital health is being used as an accelerator to improve the traditional healthcare system, aiding countries in achieving their sustainable development goals. Burkina Faso aims to harmonize its digital health interventions to guide its digital health strategy for the coming years. The current assessment represents upstream work to steer the development of this strategic plan.
METHODS: This was a quantitative, descriptive study conducted between September 2022 and April 2023. It involved a two-part survey: a self-administered questionnaire distributed to healthcare information managers in facilities, and direct interviews conducted with software developers. This was complemented by a documentary review of the country\'s strategic and standards documents on digital transformation.
RESULTS: Burkina Faso possesses a relatively comprehensive collection of governance documents pertaining to digital transformation. The study identified a total of 35 digital health interventions. Analysis showed that 89% of funding originated from technical and financial partners as well as the private sector. While the use of open-source technologies for the development of the applications, software, or platforms used to implement these digital health interventions is well established (77%), there remains a deficiency in the integration of data from different platforms. Furthermore, the classification of digital health interventions revealed an uneven distribution between the different elements across domains: the health system, the classification of digital health interventions (DHI), and the subsystems of the National Health Information System (NHIS). Most digital health intervention projects are still in the pilot phase (66%), with isolated electronic patient record initiatives remaining incomplete. Within the public sector, these records typically take the form of electronic registers or isolated specialty records in a hospital. Within the private sector, tool implementation varies based on expressed needs. Challenges persist in adhering to interoperability norms and standards during tool design, with minimal utilization of the data generated by the implemented tools.
CONCLUSIONS: This study provides an insightful overview of the digital health environment in Burkina Faso and highlights significant challenges regarding intervention strategies. The findings serve as a foundational resource for developing the digital health strategic plan. By addressing the identified shortcomings, this plan will provide a framework for guiding future digital health initiatives effectively.

BACKGROUND: Digital diabetes prevention programs (dDPPs) are effective \"digital prescriptions\" but have high attrition rates and program noncompletion. To address this, we developed a personalized automatic messaging system (PAMS) that leverages SMS text messaging and data integration into clinical workflows to increase dDPP engagement via enhanced patient-provider communication. Preliminary data showed positive results. However, further investigation is needed to determine how to optimize the tailoring of support technology such as PAMS based on a user\'s preferences to boost their dDPP engagement.
OBJECTIVE: This study evaluates leveraging machine learning (ML) to develop digital engagement phenotypes of dDPP users and assess ML\'s accuracy in predicting engagement with dDPP activities. This research will be used in a PAMS optimization process to improve PAMS personalization by incorporating engagement prediction and digital phenotyping. This study aims (1) to prove the feasibility of using dDPP user-collected data to build an ML model that predicts engagement and contributes to identifying digital engagement phenotypes, (2) to describe methods for developing ML models with dDPP data sets and present preliminary results, and (3) to present preliminary data on user profiling based on ML model outputs.
METHODS: Using the gradient-boosted forest model, we predicted engagement in 4 dDPP individual activities (physical activity, lessons, social activity, and weigh-ins) and general activity (engagement in any activity) based on previous short- and long-term activity in the app. The area under the receiver operating characteristic curve, the area under the precision-recall curve, and the Brier score metrics determined the performance of the model. Shapley values reflected the feature importance of the models and determined what variables informed user profiling through latent profile analysis.
RESULTS: We developed 2 models using weekly and daily DPP data sets (328,821 and 704,242 records, respectively), which yielded predictive accuracies above 90%. Although both models were highly accurate, the daily model better fitted our research plan because it predicted daily changes in individual activities, which was crucial for creating the \"digital phenotypes.\" To better understand the variables contributing to the model predictor, we calculated the Shapley values for both models to identify the features with the highest contribution to model fit; engagement with any activity in the dDPP in the last 7 days had the most predictive power. We profiled users with latent profile analysis after 2 weeks of engagement (Bayesian information criterion=-3222.46) with the dDPP and identified 6 profiles of users, including those with high engagement, minimal engagement, and attrition.
CONCLUSIONS: Preliminary results demonstrate that applying ML methods with predicting power is an acceptable mechanism to tailor and optimize messaging interventions to support patient engagement and adherence to digital prescriptions. The results enable future optimization of our existing messaging platform and expansion of this methodology to other clinical domains.
BACKGROUND: ClinicalTrials.gov NCT04773834; https://www.clinicaltrials.gov/ct2/show/NCT04773834.
UNASSIGNED: RR2-10.2196/26750.

BACKGROUND: Digital health interventions (DHIs) have the potential to enable public end users, such as citizens and patients, to manage and improve their health. Although the number of available DHIs is increasing, examples of successfully established DHIs in public health systems are limited. To counteract the nonuse of DHIs, they should be comprehensively evaluated while integrating end users. Unfortunately, there is a wide variability and heterogeneity according to the approaches of evaluation, which creates a methodological challenge.
OBJECTIVE: This scoping review aims to provide an overview of the current established processes for evaluating DHIs, including methods, indicators, and end-user involvement. The review is not limited to a specific medical field or type of DHI but offers a holistic overview.
METHODS: This scoping review was conducted following the JBI methodology for scoping reviews based on the framework by Arksey & O\'Malley and complies with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Three scientific databases (PubMed, Scopus, and Science Direct) were searched in April 2023. English and German studies between 2008 and 2023 were considered when evaluating DHIs that explicitly address public end users. The process of study selection was carried out by several researchers to avoid reviewer bias.
RESULTS: The search strategy identified 9618 publications, of which 160 were included. Among these included articles, 200 evaluations were derived and analyzed. The results showed that there is neither a consensus on the methods to evaluate DHIs nor a commonly agreed definition or usage of the evaluated indicators, which results in a broad variety of evaluation practices. This aligns with observations of the existing literature. It was found that there is a lack of references to existing frameworks for the evaluation of DHIs. The majority of the included studies referred to user-centered approaches and involved end users in the evaluation process. As assistance for people developing and evaluating DHIs and as a basis for thinking about appropriate ways to evaluate DHIs, a results matrix was created where the findings were combined per DHI cluster. Additionally, general recommendations for the evaluators of DHIs were formulated.
CONCLUSIONS: The findings of this scoping review offer a holistic overview of the variety and heterogeneity according to the approaches of evaluation of DHIs for public end users. Evaluators of these DHIs should be encouraged to reference established frameworks or measurements for justification. This would ease the transferability of the results among similar evaluation studies within the digital health sector, thereby enhancing the coherence and comparability of research in this area.