PLOS digital health最新文献

{"title":"Feasibility and preliminary efficacy of an online mindful walking intervention among COVID-19 long haulers: A mixed methods study including daily diary surveys.","authors":"Abhishek Aggarwal, Shan Qiao, Chih-Hsiang Yang, Slone Taylor, Cheuk Chi Tam, Xiaoming Li","doi":"10.1371/journal.pdig.0000794","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000794","url":null,"abstract":"<p><p>COVID-19 long haulers face profound psychosocial stressors (e.g., depression, anxiety, PTSD) and physical health challenges (e.g., brain fog, fatigue). This study tests the feasibility and initial impact of a digitally delivered mindful-walking (MW) intervention for improving the physical and psychosocial wellbeing of COVID-19 long haulers. We recruited 23 participants via Facebook groups, between March and November 2021, for a 4-week online MW intervention (i.e., 2 mindfulness practice sessions per week), that was delivered entirely through the study Facebook group. The intervention was assessed using mixed methods. Quantitative data were collected through brief daily evening surveys (i.e., 28 days) over the 4-week intervention period, and measured affect, cognition, mindfulness, physical activity, and MW engagement. Qualitative data were extracted from the Facebook group's Paradata (i.e., participant feedback, engagement metrics, and all social media interactions). Multilevel modeling was employed for the statistical analysis and a pragmatic approach was used for the qualitative analysis. The participants reported a high feasibility score (mean=4.93/7, SD=1.88), which was comprised of perceived usefulness, satisfaction, and ease of use. Those who engaged in MW, on any given day, frequently reported better psychosocial moods with more positive affect (β=0.89, p<0.01), less negative affect (β=-0.83, p<0.01), higher perceived cognitive ability (β=0.52, p<0.05), and more physical activity (β=0.41, p<0.05). Additionally, participants who practiced MW more consistently during the study reported higher levels of momentary mindfulness (β=0.3 p<0.01). Participants expressed satisfaction with the intervention, reporting benefits such as better symptom management and an overall improvement in wellbeing. Despite the small sample size, the digital delivery of our MW intervention via Facebook showed high acceptability. Preliminary efficacy findings indicate improved mental wellbeing and physical activity among long haulers. Larger-scale RCTs are needed in the future to improve the robustness and applicability of findings.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000794"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the feasibility, adoption, cost-effectiveness, and sustainability of telemedicine interventions in managing COVID-19 within low-and-middle-income countries (LMICs): A systematic review.","authors":"Nonye M Okafor, Imani Thompson, Vandana Venkat, Courtney Robinson, Aishwarya Rao, Sumedha Kulkarni, Leah Frerichs, Khady Ndiaye, Deborah Adenikinju, Chukwuemeka Iloegbu, John Pateña, Hope Lappen, Dorice Vieira, Joyce Gyamfi, Emmanuel Peprah","doi":"10.1371/journal.pdig.0000771","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000771","url":null,"abstract":"<p><p>COVID-19 has tragically taken the lives of more than 6.5 million people globally, significantly challenging healthcare systems and service delivery, especially in low-and middle-income countries (LMICs). This systematic review aims to: (1) evaluate the feasibility of telemedicine interventions for COVID-19 management; (2) assess the adoption of telemedicine interventions during the COVID-19 pandemic; (3) examine the cost-effectiveness of telemedicine implementation efforts and (4) analyze the sustainability of telemedicine interventions for COVID-19 disease management within LMIC service settings. We reviewed studies from selected public health and health science databases, focusing on those conducted in countries classified as low and middle-income by the World Bank, using telemedicine for confirmed COVID-19 cases, and adhering to Proctor's framework for implementation outcomes. Of the 766 articles identified and 642 screened, only 3 met all inclusion criteria. These studies showed reduced reliance on antibiotics, prescription drugs, and emergency department referrals among telemedicine patients. Statistical parity was observed in the length of stay, diagnostic test ordering rates, and International Classification of Diseases (ICD)-10 diagnoses between telemedicine and in-person visits. Telemedicine interventions designed for post-COVID physical rehabilitation demonstrated safety, sustainability, and enhanced quality of life for patients without requiring specialized equipment, proving adaptable across contexts with appropriate technology. These interventions were also economically sustainable and cost-effective for healthcare systems as a whole. Proposed strategies to bridge implementation gaps include community-level assessments, strategic planning, multisectoral partnerships of local hospital administration and lawmakers, legal consultations, and healthcare informatics improvements. Increased investment in telemedicine research focusing on infectious disease management is crucial for the continued development and refinement of effective strategies tailored to resource-constrained regions.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000771"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telehealth or in-person HIV care? Qualitative study findings on decision-making from people with HIV and HIV care providers in South Carolina during the COVID-19 pandemic.","authors":"Valerie Yelverton, Salome-Joelle Gass, Daniel Amoatika, Christopher Cooke, Jan Ostermann, Nabil Natafgi, Nicole L Hair, Bankole Olatosi, Otis L Owens, Shan Qiao, Xiaoming Li, Caroline Derrick, Sharon Weissman, Helmut Albrecht","doi":"10.1371/journal.pdig.0000812","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000812","url":null,"abstract":"<p><p>The COVID-19 pandemic disrupted HIV care services across the United States. Telehealth was rapidly implemented to ensure HIV care continuity. Despite the evidence of unequal telehealth uptake among some people with HIV (PWH), the decision-making processes to determine who received telehealth or in-person care are under-researched. This study assessed which decision criteria and processes determined which HIV care visit type was used by PWH and HIV care providers during the COVID-19 pandemic. Qualitative in-depth interviews with 18 PWH and 10 HIV care providers from South Carolina assessed PWHs' and HIV care providers' decision-making criteria and processes for telehealth HIV care during the COVID-19 pandemic. Interviews were analyzed using thematic analysis. Most PWH (11 out of 18) and all providers had used telehealth for HIV care. To guide visit type decisions, interviewees reported decision-making criteria across four domains: patient-related criteria, clinical criteria, provider preference, and HIV care continuity. Patient-related criteria included patient preference, convenience, fear of COVID-19 exposure and stigma, and transportation barriers. Clinical criteria included the need for a physical exam, a person's care history and health status. While all identified decision criteria were important, we found a hierarchical structure: care continuity superseded other criteria. Some clinical criteria were reported as decision-relevant criteria by providers but not PWH. Most PWH reported that they were included or took the lead in the visit type decision process. Decision-making processes to determine PWHs' HIV care visit types considered criteria across multiple domains. The superseding criteria was to sustain HIV care continuity. To guide future telehealth use, shared decision-making is needed to weigh patient-related, provider-related, and clinical decision criteria and maintain care continuity, and to comprehensively include all relevant decision criteria.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000812"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based assessment of pulp involvement in primary molars using YOLO v8.","authors":"Aydin Sohrabi, Nazila Ameli, Masoud Mirimoghaddam, Yuli Berlin-Broner, Hollis Lai, Maryam Amin","doi":"10.1371/journal.pdig.0000816","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000816","url":null,"abstract":"<p><p>Dental caries is a major global public health problem, especially among young children. Rapid decay progression often necessitates pulp treatment, making accurate pulp condition assessment crucial. Despite advances in pulp management techniques, diagnostic methods for assessing pulp involvement have not significantly improved. This study aimed to develop a machine learning (ML) model to diagnose pulp involvement using radiographs of carious primary molars. Clinical charts and bitewing radiographs of 900 children treated from 2018-2022 at the University of Alberta dental clinic were reviewed, yielding a sample of 482 teeth. images were preprocessed, standardized, and labeled based on clinical diagnoses. Data were split into training, validation, and test sets, with data augmentation applied to classify 2 categories of outcomes. The YOLOv8m-cls model architecture included convolutional and classification layers, and performance was evaluated using top-1 and top-5 accuracy metrics. The YOLOv8m-cls model achieved a top-1 accuracy of 78.7% for upper primary molars and 87.8% for lower primary molars. Validation datasets showed higher accuracy for lower primary teeth. Performance on new test images demonstrated precision, recall, accuracy, and F1-scores, highlighting the model's effectiveness in diagnosing pulp involvement, with lower primary molars showing superior results. This study developed a promising CNN model for diagnosing pulp involvement in primary teeth using bitewing radiographs, showing promise for clinical application in pediatric dentistry. Future research should explore whole bitewing images, include clinical variables, and integrate heat maps to enhance the model. This tool could streamline clinical practice, improve informed consent, and assist in dental student training.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000816"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effect of software and hardware version on Apple Watch activity measurement: A secondary analysis of the COVFIT retrospective cohort study.","authors":"Shelby L Sturrock, Rahim Moineddin, Dionne Gesink, Sarah Woodruff, Daniel Fuller","doi":"10.1371/journal.pdig.0000727","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000727","url":null,"abstract":"<p><p>The objective of this study was to estimate the impact of software and hardware version on Apple Watch activity measurement using data from the COVFIT retrospective cohort study. We estimated the impact of software and hardware versions on activity measurement by comparing daily active calories and daily exercise minutes in the 7 days before and 7 days after upgrading from watchOS 5 to 6, 6 to 7, 7 to 8, 8 to 9 or between two hardware versions. For each transition, we fit mixed effect negative binomial regression models to estimate the effect of the upgrade on daily (a) exercise minutes and (b) active calories, overall and stratified by sex, with and without adjusting for weekday. We also calculated and plotted the mean person-level change in average activity levels between the two weeks. As a control, we repeated the entire analysis comparing activity data two weeks before vs. one week before each upgrade. 253 participants contributed data about at least one transition (software = 250, hardware = 74). Hardware upgrades were not associated with either outcome; however, some software upgrades were. Upgrading from watchOS 7 to 8 was associated with a large, statistically significant increase in daily exercise minutes (unadjusted rate ratio (RR) = 1.13, 95% CI: 1.06, 1.20). WatchOS 6 to 7 and 8 to 9 transitions were associated with statistically significant decreases in daily exercise minutes (6 to 7: unadjusted RR = 0.92, 95% CI: 0.86, 0.99; 8 to 9: unadjusted RR = 0.91, 95% CI: 0.86, 0.96) and active calories (6 to 7: RR = 0.96, 95% CI: 0.94, 0.99); 8 to 9: RR = 0.97, 95% CI: 0.94, 0.99). There was no significant change in either outcome during in the two-week control period for most transitions. Differences in software version over time or between people may confound physical activity analyses using Apple Watch data.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000727"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the diagnostic accuracy of an HIV self-test optimized by a digital app-based solution: Results from a secondary data analysis of a field trial in South Africa.","authors":"Ashlyn Beecroft, Aliasgar Esmail, Olivia Vaikla, Thomas Duchaine, Nora Engel, Chen Liang, Qihuang Zhang, Keertan Dheda, Nitika Pant Pai","doi":"10.1371/journal.pdig.0000791","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000791","url":null,"abstract":"<p><strong>Background: </strong>To reach UNAIDS 95-95-95 targets, digital HIV self-testing (HIVST) strategy aided by applications, platforms, and readers can engage young people and adults living with undetected HIV infection. Evidence on its acceptability, feasibility, impact exists, yet accuracy data are limited.</p><p><strong>Methods: </strong>A secondary data analysis of a quasi-RCT of digital HIVST in South Africa was performed. We hypothesized app-guided digital interpretation of oral self-test enhanced test accuracy. We compared accuracy between digital HIVST supervised vs. unsupervised (with/without healthcare worker). Self-test results were interpreted and uploaded by participants, compared using computer vision technology, against lab reference standard by trained healthcare professionals.</p><p><strong>Results: </strong>1513 digital HIVST participants reported pooled Sensitivity (Sn) = 95.52% (95% CI, 94.48%-96.56%); Specificity (Sp): 99.93% (95% CI, 99.79%-100.06%); Positive predictive value (PPV): 99.22% (95% CI, 98.78%-99.67%); Negative Predictive Value (NPV): 99.57% (95% CI, 99.24%-99.90%). 565 participants on supervised digital HIVST, reported a pooled Sn: 93.65% (95% CI, 91.64-95.66); Sp: 100.00% (95% CI, 100.00-100.00); PPV: 100.00% (95% CI, 100.00-100.00); NPV: 99.21% (95% CI, 98.48-99.94). 968 unsupervised digital HIVST participants, reported a pooled Sn: 97.18% (95% CI, 96.13-98.24); Sp: 99.89% (95% CI, 99.67-100.10); PPV: 98.57% (95% CI, 97.82-99.33); NPV: 99.77% (95% CI, 99.47-100.08). Non-digital HIVST vs. study digital HIVST data at 5% significance level - Sn: chi = 0.6495, p-value = 0.4203, Sp: chi = 0.3831, p-value = 0.5259. Supervised vs. unsupervised HIVST at 5% significance level - Sn: chi = 0.973, p-value = 0.3237, Sp: chi = 0.527, p-value = 0.4449.</p><p><strong>Conclusions: </strong>Digital HIVST improved interpretation of test results, increased accuracy and predictive value estimations (upper limit 98%-100%), removing subjectivity. Unsupervised digital HIVST users performed better than supervised. Digital HIVST results can potentially signal a rapid triage to therapy or prevention pathways, while awaiting lab confirmation. Findings have implications for scale up of digital HIVST initiatives in global settings.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000791"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ethical challenges and evolving strategies in the integration of artificial intelligence into clinical practice.","authors":"Ellison B Weiner, Irene Dankwa-Mullan, William A Nelson, Saeed Hassanpour","doi":"10.1371/journal.pdig.0000810","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000810","url":null,"abstract":"<p><p>Artificial intelligence (AI) has rapidly transformed various sectors, including healthcare, where it holds the potential to transform clinical practice and improve patient outcomes. However, its integration into medical settings brings significant ethical challenges that need careful consideration. This paper examines the current state of AI in healthcare, focusing on five critical ethical concerns: justice and fairness, transparency, patient consent and confidentiality, accountability, and patient-centered and equitable care. These concerns are particularly pressing as AI systems can perpetuate or even exacerbate existing biases, often resulting from non-representative datasets and opaque model development processes. The paper explores how bias, lack of transparency, and challenges in maintaining patient trust can undermine the effectiveness and fairness of AI applications in healthcare. In addition, we review existing frameworks for the regulation and deployment of AI, identifying gaps that limit the widespread adoption of these systems in a just and equitable manner. Our analysis provides recommendations to address these ethical challenges, emphasizing the need for fairness in algorithm design, transparency in model decision-making, and patient-centered approaches to consent and data privacy. By highlighting the importance of continuous ethical scrutiny and collaboration between AI developers, clinicians, and ethicists, we outline pathways for achieving more responsible and inclusive AI implementation in healthcare. These strategies, if adopted, could enhance both the clinical value of AI and the trustworthiness of AI systems among patients and healthcare professionals, ensuring that these technologies serve all populations equitably.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000810"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation and impact of mhealth in the management of diabetes mellitus in Africa: A systematic review and meta-analysis.","authors":"Franklin Okechukwu Dike, Jean Claude Mutabazi, Ezekiel Musa, Blessing Chinenye Ubani, Ahmed Sherif Isa, Chidiebele Malachy Ezeude, Henry Iheonye, Isah Idris Ainavi","doi":"10.1371/journal.pdig.0000776","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000776","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The World Health Organization (WHO) has proposed the concept of mobile health to support healthcare systems delivery worldwide. Mobile health (mHealth) involves using Information and Communication Technology (ICT) for health care provision or delivery services. In the context of Africa, a region that has witnessed a significant increase in mobile phone availability and usage in the last decade and a corresponding rise in the incidence and prevalence of diabetes mellitus, this study has global implications. We conducted a systematic review on the extent of mHealth implementation in managing diabetes mellitus in Africa. We estimated its impact on achieving desired glycemic targets, sustained control, and preventing complications in the past decade.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods and analysis: &lt;/strong&gt;The studies assessing the utilization of mHealth in managing patients with diabetes mellitus in Africa were considered based on the PICO method: Population, Intervention, Comparator, and Outcomes. MEDLINE, PubMed, SCOPUS, and the Pan African Clinical Trials Registry were searched. Two authors, independent of each other, screened titles and abstracts retrieved using the search strategy, retrieved the full-text articles, and assessed them for eligibility, extracting data after that. A third independent reviewer was brought in to resolve disagreements between the two authors by discussion. The revised Cochrane Collaboration Risk of Bias Tool was used to assess the quality of included studies. A narrative synthesis of extracted data was done due to the paucity of eligible studies, and the results were summarized in a meta-analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;None of the six included studies measured the mean FPG or percentage changes as primary outcomes. Five measured the percentage change in HbA1c from baseline to the end of the study. The percentage change in HbA1c from the baseline ranged from 3.6% to 20.53%, achieving significance in three studies. In the meta-analysis the overall WMD (95% CI) was 0.992 (0.48, 1.50). This, in combination with a high z score of 3.822, p &lt;0.001 suggests a statistically significant overall effect that is not likely due to chance. However, a considerable heterogeneity (I2 = 63.9%, p = 0.026) was present implying that the observed effect may not be generalizable to all the studies due to differences in study characteristics in this case most likely sample size and duration of study. None of the studies addressed the secondary outcomes of measuring the direct relationships between these mHealth interventions and the prevention or early detection of diabetes complications.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Overall, there was a statistically significant reduction in HbA1c levels among individuals living with type 2 diabetes in Africa following mHealth interventions. Few studies were included in the meta-analysis with significant heterogeneity. Therefore, we recommend more well-designed randomized ","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000776"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliability of online, remote neuropsychological assessment in people with and without subjective cognitive decline.","authors":"Katie A Peterson, Adrian Leddy, Michael Hornberger","doi":"10.1371/journal.pdig.0000682","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000682","url":null,"abstract":"<p><p>Online, remote neuropsychological assessment paradigms may offer a cost-effective alternative to in-person assessment for people who experience subjective cognitive decline (SCD). However, it is vital to establish the psychometric properties of such paradigms. The present study (i) evaluates test-retest reliability of remote, online neuropsychological tests from the NeurOn software platform in people with and without SCD (Non-SCD) recruited from the general population; and (ii) investigates potential group differences in baseline performance and longitudinal change. Ninety-nine participants (SCD N = 44, Non-SCD N = 55) completed seven tests from the NeurOn battery, covering visual and verbal memory, working memory, attention and psychomotor speed. Sixty-nine participants (SCD N = 34, Non-SCD N = 35) repeated the assessment six (+/- one) months later. SCD was classified using the Cognitive Change Index questionnaire. Test-retest reliability of the NeurOn test outcome measures ranged from poor to good, with the strongest evidence of reliability shown for the Sustained Attention to Response Test and Picture Recognition. The SCD group was significantly older than the Non-SCD group so group differences were investigated using analysis of covariance whilst controlling for the effect of age. SCD scored significantly better than Non-SCD for Digit Span Backwards (maximum sequence length) and Picture Recognition (recall of object position) at baseline. However, these were not significant when using the Bonferroni-adjusted alpha level. There were no differences between SCD and Non-SCD in longitudinal change. The results suggest online, remote neuropsychological assessment is a promising option for assessing and monitoring SCD, however more research is needed to determine the most suitable tests in terms of reliability and sensitivity to SCD.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000682"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigating digital frontiers in UAE healthcare: A qualitative exploration of healthcare professionals' and patients' experiences with AI and telemedicine.","authors":"Azza Alkaabi, Deena Elsori","doi":"10.1371/journal.pdig.0000586","DOIUrl":"https://doi.org/10.1371/journal.pdig.0000586","url":null,"abstract":"<p><p>The integration of artificial intelligence (AI) and telemedicine into healthcare has significantly advanced patient-centered care, enhancing accessibility, convenience, and patient-doctor relationships. However, different factors determine the extent to which such benefits are realized, especially in unique healthcare settings such as the United Arab Emirates (UAE). In this regard, this research explores healthcare professionals' and patients' perspectives to understand various factors that influence the adoption and use of AI in the UAE's healthcare sector. This research sought to understand the benefits, challenges, and enablers of successful adoption and utilization of AI and telemedicine in the UAE's healthcare setting. Through this objective, this research aims to contribute to the scanty knowledge on the integration of emerging technologies, such as AI, in different infrastructural and cultural contexts. The study employed a qualitative approach, through which eight healthcare professionals and seven patients (totaling 15 participants) were recruited from Dubai- and Abu Dhabi-based hospitals using the purposive sampling strategy. The participants' insights and views on the research topic were captured using semi-structured face-to-face interviews. These interviews were analyzed using the thematic analysis strategy. This study established that while AI and telemedicine are associated with various benefits, including enhancing the management of chronic illnesses, effective controlling of infectious diseases, saving patients and hospitals health-related costs and time, and enhancing convenience, they suffer from various drawbacks, including limited infrastructural and financial resources, significant gaps in skills, safety concerns, and the likelihood of misdiagnosis and misinformation. The study also observed that the successful integration of AI and telemedicine in the UAE healthcare sector necessitated incentivizing stakeholders to use this technology, full involvement and engagement of stakeholders across all stages of implementation, adequate training of the healthcare staff, and public engagement and awareness. This research demonstrates that integrating AI and telemedicine in the UAE healthcare sector necessitates addressing contextual infrastructural and cultural hindrances. The results highlight the need to address such limitations, adequately train healthcare professionals, and enhance data privacy. The study also lays a foundation for further research into contextual challenges hindering the effective adoption and implementation of AI and telemedicine in different healthcare settings in order to develop a generic, context-specific framework that will guide the adoption of such emerging technologies in the global healthcare industry.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 4","pages":"e0000586"},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}