BMC digital health最新文献

{"title":"Patient tracking and retention with Malawi's electronic medical records system in antiretroviral treatment clinics.","authors":"Sterner Msamila, Mbongeni Chizonda, Geoffrey Singini, Veena Sampathkumar, Misheck Luhanga, George Mtonga, Howard Kress, Thulani Maphosa","doi":"10.1186/s44247-026-00259-8","DOIUrl":"10.1186/s44247-026-00259-8","url":null,"abstract":"<p><strong>Background: </strong>Leveraging the widespread availability of the Electronic Medical Records System (EMRS) in Malawi, the Clinic Missed Appointment (CMA) reporting tool was introduced in April 2021 to support the identification and reintegration of antiretroviral treatment (ART) clients who miss scheduled clinic appointments, thereby enhancing patient care and retention. This study examined the impact of the CMA tool on patient retention.</p><p><strong>Methods: </strong>Using a before-after study design, we conducted trend analysis of nationally program ART data. EMRS data from October 2020 to June 2023 were analyzed using descriptive statistics to compare periods before and after the implementation of the CMA tool. Trends in patient retention were assessed, including treatment interruptions, clients alive on ART, and successful ART restarts. Additionally, these retention indicators were stratified by sex and age-group to examine differences in the proportions of clients interrupting treatment and returning to treatment.</p><p><strong>Results: </strong>From October 2020 to June 2023, quarterly cases of ART treatment interruptions decreased by 45%, while the number of clients alive on treatment increased by 11%. However, the rate of return to care following ART interruption declined by 70%. The proportion of clients interrupting ART was consistently higher among males (4.2%) than females (3.4%), while return-to-care rates after interruption did not observably differ significantly by sex. ART interruption and return-to-care rates also varied by age, with the highest interruption rates observed among children aged <1 year and the lowest among adults aged >50 years.</p><p><strong>Conclusions: </strong>Following implementation of the EMRS CMA reporting tool, there was a correlated observed decrease in ART interruption and improved retention in care. The system's capacity to quickly and correctly generate follow-up lists might have optimized time for client tracing. Sex- and Age-sensitive interventions may be important to enhance treatment adherence and retention.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"4 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13588544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seeing beyond positivity: computer vision approach to decoding BinaxNOW COVID-19 tests and forecasting negative results.","authors":"Morgan N Greenleaf, Richard Parsons, Colin Shea, Phuong-Vi Nguyen, Jesse J Waggoner, Anuradha Rao, Leda Bassit, Heather Bowers, Courtney Sabino, Raymond F Schinazi, Santiago Arconada, Robert G Mannino, Wilbur Lam","doi":"10.1186/s44247-026-00287-4","DOIUrl":"10.1186/s44247-026-00287-4","url":null,"abstract":"<p><strong>Background: </strong>The emergence of COVID-19 facilitated the widespread use, regulatory awareness, and societal familiarity of lateral flow assays (LFA) for self-diagnosis. The increased frequency in the use of LFA's as well as their increased use by the general population amplified some of the major drawbacks of these tests, namely, the reliance on user interpretation of the test result, the qualitative nature of the result itself, and the lower sensitivity and specificity compared to traditional polymerase chain reaction (PCR)-based diagnostic testing. Furthermore, the results of these tests and the interpretation of them by lay users were increasingly used as a public health tool by authorities, where recommendations were made on how members of the public should act in response to self-interpretation of test results. Our aims were to develop an objective image analysis algorithm that can (1) interpret the result of a popular COVID-19 LFA Rapid Antigen Test (RAT) and accurately estimate viral load, and (2) predict how long after a positive test a user will test negative on the RAT, indicating loss of infectiousness and the ability to be around others without fear of spreading infection.</p><p><strong>Results: </strong>Indeed, we found that we could estimate viral load to within a RMSE of 1.44 Cycle Threshold (C_T) of gold standard PCR testing, and that we can predict the result status of a user upon a follow up visit at least 5 days post-symptom onset with a sensitivity of 99%, a specificity of 73% and an accuracy of 94%. The analysis algorithm was finally embedded in a mobile application for ease of use.</p><p><strong>Conclusion: </strong>The development of an objective image analysis algorithm for estimating viral load combined with smartphone apps represents a significant improvement upon LFA RAT technologies being used by millions worldwide to diagnose a variety of epidemiologically significant diseases.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1186/s44247-026-00287-4.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"4 1","pages":"63"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13457443/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148714792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and implementation of \"<i>Mazboot Bunyad</i>\": a digital health intervention for the screening and management of undernutrition among children aged 6-59 months, at private provider clinics in urban slums of Karachi, Pakistan.","authors":"Shifa Salman Habib, Ammarah Ali, Muhammad Fazal Hussain Qureshi, Shehla Zaidi, Fasih Hansmukh, Wardah Ahmed, Tahira Hasham, Sajad Alam, Khalid Memon, Naveed Bhutto, Diwakar Mohan, Zahid Ali Memon","doi":"10.1186/s44247-026-00303-7","DOIUrl":"10.1186/s44247-026-00303-7","url":null,"abstract":"<p><strong>Background: </strong>Undernutrition remains a leading driver of child mortality and morbidity in low- and middle-income countries, yet surveillance and case management in Pakistan still rely largely on infrequent surveys and paper-based registers that cannot track nutritional status in real time. The private sector, where most Pakistani households seek care, has been largely excluded from nutrition programming. We describe the development and early implementation of Mazboot Bunyad, a digital nutrition registry embedded within an integrated nutrition-immunization programme at private provider clinics in high-risk, low-income settlements of Karachi.</p><p><strong>Methods: </strong>The Android application and web dashboard used in this implementation study were designed through a participatory process using the AHEAD framework, in consultation with provincial health authorities, immunization staff, and community nutrition worker. The system used QR-linked child records, an embedded digital decision-support system that classified children by mid-upper arm circumference and has automated follow-up reminders. The tool was deployed across 33 clinics, and routinely collected programme data, a preliminary analysis of data from 1 July to 31 December 2024 were retrospectively reviewed.</p><p><strong>Results: </strong>During the period of 6 months, the <i>Mazboot Bunyad</i> application was used to screen and enroll 8,406 children aged 6-59 months. Field teams used the embedded Digital Decision Support System (DDSS) to classify children aged 6-59 months in real-time. Of these, 71.4% were classified as normal, 22.3% as moderately acutely malnourished (MAM), and 6.2% as severely acutely malnourished (SAM). The largest share of enrollments was among children aged 13-24 months (40.5%). Male children represented a slightly larger share of total enrollments (52.2%), but SAM burden was higher among females (7.3%) compared to males (5.3%). Supervisory teams used the dashboard to identify defaulters, monitor stock availability, and follow case recovery timelines.</p><p><strong>Conclusions: </strong>Early implementation of <i>Mazboot Bunyad</i> highlighted opportunities for enhanced nutritional surveillance using real-time tracking, but also challenges such as supply chain gaps that could affect the overall implementation. These offer valuable lessons for scaling digital tools in real world settings across Pakistan and other LMICs.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1186/s44247-026-00303-7.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"4 1","pages":"72"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13638715/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can mHealth improve migrant wellness during public health emergencies? A community-engaged qualitative study during the COVID-19 pandemic.","authors":"Chad Abresch, Michelle Warren, Ellen Kerns, Alice Sato, Gleb Haynatzki, Jonathan Figliomeni, Fernando Sanchez, Gisela Marfileno, Lisvey Rivera, M Jana Broadhurst, Russell J McCulloh","doi":"10.1186/s44247-026-00253-0","DOIUrl":"10.1186/s44247-026-00253-0","url":null,"abstract":"<p><strong>Background: </strong>The COVID-19 pandemic exposed significant healthcare access disparities for migrant communities, with infection rates up to three times higher than the general population. While mobile health technology offers potential solutions for reaching vulnerable populations during public health emergencies, implementation barriers persist. This study evaluates how mobile health interventions can effectively serve migrant communities through analysis of a digital health program implemented in rural Nebraska.</p><p><strong>Results: </strong>Analysis of semi-structured interviews with migrant family members between February 2022 and June 2024 revealed three key elements driving program success: culturally congruent support through community navigators, immediate access to testing and results, and program adaptability to meet broader community needs. Community navigators proved essential, expanding beyond technical support to address social needs ranging from food insecurity to domestic issues. The combination of digital tools with human support enabled families to make timely decisions about work and school attendance while accessing crucial social services.</p><p><strong>Conclusions: </strong>Digital health interventions can effectively serve migrant communities when designed with cultural sensitivity and supported by community navigators. While public health systems should prioritize technological infrastructure for emergency response, success requires concurrent investment in culturally responsive human support systems. The integration of digital tools with adaptable community navigation provides a model for reaching vulnerable populations during future public health emergencies.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1186/s44247-026-00253-0.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"4 1","pages":"16"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12992342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147482509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benchmarking Generative AI Tools for Interpretation of the WHO TB Mutation Catalogue.","authors":"Miguel Moreno-Molina, Anita Suresh, Rebecca E Colman, Timothy C Rodwell","doi":"10.1186/s44247-025-00225-w","DOIUrl":"10.1186/s44247-025-00225-w","url":null,"abstract":"<p><p>The World Health Organization (WHO) 2023 Mutation Catalogue for <i>Mycobacterium tuberculosis</i> is a crucial knowledgebase and tool for clinical interpretation of mutations associated with drug-resistant TB. However, the document's complexity and size pose challenges for many users. This study evaluated the potential of generative artificial intelligence (AI) models to facilitate natural language user interaction with the catalogue. This was a benchmarking study, not a clinical usability trial. Four prominent AI models-Google Gemini 2.5 Pro, OpenAI ChatGPT 4.1, Perplexity AI, and DeepSeek R1-were assessed through general test questions, mutation search and retrieval tasks using both full catalogue queries and antibiotic-specific tables, and the application of additional grading rules to score novel mutations. Performance was measured based on accuracy, completeness, clarity, source citation, and the presence of hallucinations. Google Gemini 2.5 Pro consistently demonstrated superior performance in accuracy, completeness, and avoidance of hallucinations across most evaluations, especially in general queries and large dataset searches. DeepSeek R1 excelled in applying grading rules to novel mutations and showed high accuracy in focused datasets, but exhibited some hallucinations. ChatGPT 4.1 was strong in clarity but lacked proper citations, and Perplexity AI showed variable performance with a higher frequency of hallucinations. The findings highlight the potential of AI tools to enhance the accessibility of complex knowledgebases like the WHO Mutation Catalogue, while emphasizing the need for rigorous benchmarking. While no model is yet suitable for direct clinical use, the results suggest that with further development, models like Google Gemini 2.5 Pro could form the basis of a custom AI agent to assist users in navigating this critical resource, ultimately contributing to improved TB control efforts.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"4 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12952903/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147349800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An educational intervention for unpaid/family carers of patients with breathlessness in advanced disease: developing a web-based resource.","authors":"Morag Farquhar, Sylvia Barnes, Roberta Lovick, Julie Burkin, Sophie Howson, Ravi Mahadeva, David Gilligan, Ingrid Muller, Kate Greenwell, Chris Todd, Gail Ewing","doi":"10.1186/s44247-026-00309-1","DOIUrl":"https://doi.org/10.1186/s44247-026-00309-1","url":null,"abstract":"<p><strong>Background: </strong>Chronic refractory breathlessness is distressing, disabling, and common in advanced disease. Unpaid/family carers provide support for patients, but often lack knowledge and confidence, experiencing anxiety which can lead to crises. The Learning about Breathlessness programme (LaB) sought to address this. Working with carers and clinical experts, the LaB1 Study identified six topics carers of patients with breathlessness due to cancer or chronic obstructive pulmonary disease (COPD) want to learn about breathlessness, and how they want to learn. To accommodate carers' varied learning preferences a web-based educational intervention was proposed, with four delivery modes: self-accessed, or accessed via peer-led support groups, established clinician-led groups, or in clinician one-to-ones. The 2-stage LaB2 Study sought to co-develop the web-based resource, suitable for these delivery modes and mapped to carers' learning needs identified in LaB1.</p><p><strong>Method: </strong>Building on LaB1, website content was co-developed iteratively through qualitative interviews, focus groups and workshops with bereaved carers, current carers, and patients living with breathlessness due to cancer or COPD (n=24), and with a Carer Advisory Group and Study Advisory Group (included clinical experts) (Stage 1). User feedback on the prototype website was then collected from carers, patients and clinicians (n=16) using 'think-aloud' interviews enabling website refinement through an iterative process (Stage 2).</p><p><strong>Results: </strong>The co-developed web-based resource, \"Supporting Someone with Breathlessness\", covers the six topics carers wanted to learn about and is designed to meet cancer/COPD carers preferences in terms of ways of learning. As such it includes words, pictures, film clips of peer carers and clinical experts, links to other resources and downloadable leaflets. Carers, patients and clinicians confirmed content utility and acceptability and suggested enhancements which enabled refinement. User feedback suggested the utility of the four potential delivery modes.</p><p><strong>Conclusion: </strong>To the best of our knowledge, \"Supporting Someone with Breathlessness\" is the first website dedicated to meeting the needs of unpaid/family carers of people with breathlessness in advanced disease: https://supporting-breathlessness.org.uk/. The content and format of this nationally endorsed web-based resource were guided by an evidence base of carer educational need and learning preferences. Design features ensure content is accessible for those without digital access.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1186/s44247-026-00309-1.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"4 1","pages":"74"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13658331/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149186017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An iterative mindset approach as an adjunct to the national diabetes prevention program: a randomized trial assessing retention, engagement and weight loss.","authors":"Joshua W Leichter, Michael J Cannon, Yvonne Mensa-Wilmot, Zena W Belay, Anyssa S Garza, Abby M Schmalz, Keenan I Walch, Kyra Bobinet","doi":"10.1186/s44247-026-00247-y","DOIUrl":"10.1186/s44247-026-00247-y","url":null,"abstract":"<p><strong>Background: </strong>Retention and engagement continue to be a challenge for the National Diabetes Prevention Program lifestyle change program (LCP). This challenge is especially stark for persons living in medically-underserved, economically-disadvantaged communities. In the current work, we sought to investigate if a digital solution-an adjunct habit formation app (Fresh Tri^®) grounded in neuroscience theory around iteration (i.e., changing one's approach to a problem when encountering challenges)-could improve these metrics, as well as weight loss, in these populations.</p><p><strong>Methods: </strong>We conducted a randomized study using a three-level, nested hierarchical structure, with 364 participants (212 intervention; 152 control) across 33 sites from February 1, 2021-October 13, 2022. We examined retention, engagement (number of sessions attended) and ≥ 5% body weight loss for participants in the intervention condition (standard LCP curriculum plus the Fresh Tri iterative mindset app) compared to the control condition (standard LCP curriculum) and also to a nationally representative group (National DPP LCP data from the United States Centers for Disease Control and Prevention (CDC)).</p><p><strong>Results: </strong>Intervention participants reported higher retention than controls at 6 months (79.7% vs. 67.1%; OR = 2.06; 95% CI = 1.15-3.68; <i>P</i>=.01) and 12 months (78.3% vs. 53.1%; OR = 3.14; 95% CI = 1.11-8.88; <i>P</i>=.03). Engagement at 6 and 12 months was not statistically different. Compared to the National DPP LCP participants overall, both the intervention and control arms had higher retention (<i>P</i><.001) and engagement (intervention <i>P</i><.001; control <i>P</i>=.02) at 6 months. We found no differences in ≥ 5% body weight loss between intervention and control groups at 6 months (26% vs. 27%; OR = 0.99; 95% CI = 0.57-1.73; <i>P</i>=.97, <i>P</i>=.90), but a statistically significant higher proportion of those in the intervention arm having ≥ 5% weight loss after 12 months (41.3% vs. 30.6%, OR = 1.72; 95% CI = 1.01-2.92; <i>P</i>=.05).</p><p><strong>Conclusions: </strong>Overall, these results show promise for the applicability of a digital habit formation app, based on an iterative mindset, as an adjunct to the LCP for retention and weight loss.</p><p><strong>Trial registration: </strong>This clinical trial (ClinicalTrials.gov Identifier: NCT06656273) was retrospectively registered on October 18, 2024.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"4 1","pages":"13"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12935709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Providers' and pregnant women's perspectives on obstetric point-of-care ultrasound use in peri-urban Karachi, Pakistan: a qualitative study.","authors":"Laeba Hussain, Nida Salman Yazdani, Ayesha Khalid, Fariya Ahmed, Hamna Javed, Ishrat Fatima, Imran Nisar, Fyezah Jehan, Katelyn Rittenhouse, Bethany L Freeman, Jeffery Stringer, Zahra Hoodbhoy","doi":"10.1186/s44247-026-00295-4","DOIUrl":"10.1186/s44247-026-00295-4","url":null,"abstract":"<p><strong>Background: </strong>Ultrasound is essential for antenatal care (ANC), yet access remains limited in many low- and middle-income countries (LMICs) due to shortages of equipment and trained personnel. Point-of-care ultrasound (POCUS) offers a feasible solution for gestational dating, detection of high-risk conditions, and referral decision-making in these settings. Understanding the perspectives of both healthcare providers (HCPs) and pregnant women is important for successful integration of POCUS into routine antenatal care. This study aimed to explore the perceptions of obstetric POCUS use among HCPs and pregnant women at a peri-urban community in Karachi, Pakistan.</p><p><strong>Methods: </strong>A qualitative study was conducted at a peri-urban site in Karachi, Pakistan to explore the perceptions of obstetric POCUS among HCPs and pregnant women. Purposive sampling was employed and in-depth interviews (IDIs) were conducted with pregnant women and HCPs from an ongoing POCUS cohort study until thematic saturation was achieved, yielding a total of nine participants (six pregnant women and three HCPs). Interviews were audio recorded, transcribed, translated, and analyzed using a thematic analysis framework.</p><p><strong>Results: </strong>The five common themes identified were role of ultrasound, perceived utility of POCUS, limitations and areas of improvement, myths and misconceptions, and recommendations for future use. POCUS was perceived as a valuable and feasible tool for ANC due to its portability and ability to perform rapid assessment closer to communities. Women valued reduced travel times while HCPs highlighted its user-friendly design and short learning curve for basic obstetric assessment and referral decisions. However, concerns regarding technical difficulties and diagnostic limitations were also noted. Moreover, pregnant women and providers appraised POCUS from different vantage points: women's confidence was largely driven by the reassurance of seeing the fetus directly, while providers held a more cautious view of what the device could diagnose. Findings were consistent with key constructs of the Technology Acceptance Model (TAM), as both women and providers recognized POCUS as a practical and beneficial addition to antenatal care. Both groups supported expanding POCUS use in community-based antenatal care.</p><p><strong>Conclusions: </strong>Targeted interventions focusing on structured training and community education may support effective integration of POCUS into routine ANC and improve access to obstetric imaging in underserved communities, with the potential to improve maternal and neonatal outcomes.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1186/s44247-026-00295-4.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"4 1","pages":"64"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13493394/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148802319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Older adults' preferences for features of medication adherence technologies: a preference elicitation study.","authors":"Ghada Elba, Bincy Baby, Ryan H Griffin, Tejal Patel","doi":"10.1186/s44247-025-00222-z","DOIUrl":"10.1186/s44247-025-00222-z","url":null,"abstract":"<p><strong>Introduction: </strong>Older adults are at risk of medication non-adherence due to complex medication regimens and medication management challenges. Medication adherence technologies can help, but previous research demonstrates variability in usability and preferences of their features among older adults. Therefore, our objective is to examine older adults' preferences for medication adherence technology features and their trade-offs to guide the development of these technologies. This will facilitate serving older adults better by addressing their needs and preference.</p><p><strong>Methods: </strong>Guided by the Patient-Centered Benefit-Risk Framework, we conducted a questionnaire based preference elicitation study where older adults ranked 10 medication adherence technology features identified through qualitative interviews, then identified acceptable trade-offs. Recruitment of our sample was based on convenience sampling, and the inclusion criteria was older adults above 60 years and older and able to speak and read English. The ranking was evaluated by calculating the relative importance using relative importance index (RII) and the trade-offs were assessed using win rate analysis. Statistical significance was assessed using Kruskal Wallis analysis.</p><p><strong>Results: </strong>Thirty older adults were recruited, of which twenty-three (mean age 73 years, 47.8% males) participated. The 10 reported features were button size, screen size, device size, compartment division, setting time and alarm, alarm sound, user-friendly leaflet, battery operated, locking features, and number of steps to set up the device. Screen size was ranked highest with relative importance index (RII) of 0.75. Win-rate analysis of trade-offs revealed that a user-friendly leaflet was the most frequently selected feature with p value < 0.001 (Kruskal Wallis test).</p><p><strong>Conclusion: </strong>This study highlights the importance of understanding the preferences of older adults to guide selecting the medication adherence technology that better meet their needs, as well as developing tools supporting medication management and adherence.</p><p><strong>Clinical trial number: </strong>Not applicable.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1186/s44247-025-00222-z.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"3 1","pages":"86"},"PeriodicalIF":3.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12641034/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145607387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Healthy at Home for COPD: An Integrated Digital Monitoring, Treatment, and Pulmonary Rehabilitation Intervention.","authors":"Laurel O'Connor, Stephanie Behar, Seanan Tarrant, Pamela Stamegna, Caitlin Pretz, Biqi Wang, Brandon Savage, Thomas Scornavacca, Jeanne Shirshac, Tracey Wilkie, Michael Hyder, Adrian Zai, Shaun Toomey, Marie Mullen, Kimberly Fisher, Emil Tigas, Steven Wong, David D McManus, Eric Alper, Peter K Lindenauer, Eric Dickson, John P Broach, Vik Kheterpal, Apurv Soni","doi":"10.1186/s44247-024-00142-4","DOIUrl":"10.1186/s44247-024-00142-4","url":null,"abstract":"<p><strong>Background: </strong>Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality in the United States. Frequent exacerbations result in higher use of emergency services and hospitalizations, leading to poor patient outcomes and high costs. The objective of this study is to demonstrate the feasibility of a multimodal, community-based intervention in treating acute COPD exacerbations.</p><p><strong>Results: </strong>Over 18 months, 1,333 patients were approached and 100 (7.5%) were enrolled (mean age 66, 52% female). Ninety-six participants (96%) remained in the study for the full enrollment period. Fifty-five (55%) participated in tele-pulmonary-rehabilitation. Participants wore the smartwatch for a median of 114 days (IQR 30-210) and 18.9 hours/day (IQR16-20) resulting in a median of 1034 minutes/day (IQR 939-1133). The rate at which participants completed scheduled survey instruments ranged from 78-93%. Nearly all participants (85%) performed COPD ecological momentary assessment at least once with a median of 4.85 recordings during study participation. On average, a 2.48-point improvement (p=0.03) in COPD Assessment Test Score was observed from baseline to study completion. The adherence and symptom improvement metrics were not associated with baseline patient activation measures.</p><p><strong>Conclusions: </strong>A multimodal intervention combining preventative care, symptom and biometric monitoring, and MIH services was feasible in adults living with COPD. Participants demonstrated high protocol fidelity and engagement and reported improved quality of life.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12245176/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}