Journal of Medical Internet Research最新文献

{"title":"Electronic Health Interventions and Cervical Cancer Screening: Systematic Review and Meta-Analysis.","authors":"Xiaoxia Liu, Lianzhen Ning, Wenqi Fan, Chanyi Jia, Lina Ge","doi":"10.2196/58066","DOIUrl":"10.2196/58066","url":null,"abstract":"<p><strong>Background: </strong>Cervical cancer is a significant cause of mortality in women. Although screening has reduced cervical cancer mortality, screening rates remain suboptimal. Electronic health interventions emerge as promising strategies to effectively tackle this issue.</p><p><strong>Objective: </strong>This systematic review and meta-analysis aimed to determine the effectiveness of electronic health interventions in cervical cancer screening.</p><p><strong>Methods: </strong>On December 29, 2023, we performed an extensive search for randomized controlled trials evaluating electronic health interventions to promote cervical cancer screening in adults. The search covered multiple databases, including MEDLINE, the Cochrane Central Registry of Controlled Trials, Embase, PsycINFO, PubMed, Scopus, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature. These studies examined the effectiveness of electronic health interventions on cervical cancer screening. Studies published between 2013 and 2022 were included. Two independent reviewers evaluated the titles, abstracts, and full-text publications, also assessing the risk of bias using the Cochrane Risk of Bias 2 tool. Subgroup analysis was conducted based on subjects, intervention type, and economic level. The Mantel-Haenszel method was used within a random-effects model to pool the relative risk of participation in cervical cancer screening.</p><p><strong>Results: </strong>A screening of 713 records identified 14 articles (15 studies) with 23,102 participants, which were included in the final analysis. The intervention strategies used in these studies included short messaging services (4/14), multimode interventions (4/14), phone calls (2/14), web videos (3/14), and internet-based booking (1/14). The results indicated that electronic health interventions were more effective than control interventions for improving cervical cancer screening rates (relative risk [RR] 1.464, 95% CI 1.285-1.667; P<.001; I<sup>2</sup>=84%), cervical cancer screening (intention-to-treat) (RR 1.382, 95% CI 1.214-1.574; P<.001; I<sup>2</sup>=82%), and cervical cancer screening (per-protocol; RR 1.565, 95% CI 1.381-1.772; P<.001; I<sup>2</sup>=74%). Subgroup analysis revealed that phone calls (RR 1.82, 95% CI 1.40-2.38), multimode (RR 1.62, 95% CI 1.26-2.08), SMS (RR 1.41, 95% CI 1.14-1.73), and video- and internet-based booking (RR 1.25, 95% CI 1.03-1.51) interventions were superior to usual care. In addition, electronic health interventions did not show a statistically significant improvement in cervical cancer screening rates among women with HPV (RR 1.17, 95% CI 0.95-1.45). Electronic health interventions had a greater impact on improving cervical cancer screening rates among women in low- and middle-income areas (RR 1.51, 95% CI 1.27-1.79). There were no indications of small study effects or publication bias.</p><p><strong>Conclusions: </strong>Electronic health interventions are recom","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e58066"},"PeriodicalIF":8.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142558058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Role of the Generative Pretrained Transformer (GPT) in Alzheimer's Disease Management: Comparative Study of Neurologist- and Artificial Intelligence-Generated Responses.","authors":"Jiaqi Zeng, Xiaoyi Zou, Shirong Li, Yao Tang, Sisi Teng, Huanhuan Li, Changyu Wang, Yuxuan Wu, Luyao Zhang, Yunheng Zhong, Jialin Liu, Siru Liu","doi":"10.2196/51095","DOIUrl":"10.2196/51095","url":null,"abstract":"<p><strong>Background: </strong>Alzheimer's disease (AD) is a progressive neurodegenerative disorder posing challenges to patients, caregivers, and society. Accessible and accurate information is crucial for effective AD management.</p><p><strong>Objective: </strong>This study aimed to evaluate the accuracy, comprehensibility, clarity, and usefulness of the Generative Pretrained Transformer's (GPT) answers concerning the management and caregiving of patients with AD.</p><p><strong>Methods: </strong>In total, 14 questions related to the prevention, treatment, and care of AD were identified and posed to GPT-3.5 and GPT-4 in Chinese and English, respectively, and 4 respondent neurologists were asked to answer them. We generated 8 sets of responses (total 112) and randomly coded them in answer sheets. Next, 5 evaluator neurologists and 5 family members of patients were asked to rate the 112 responses using separate 5-point Likert scales. We evaluated the quality of the responses using a set of 8 questions rated on a 5-point Likert scale. To gauge comprehensibility and participant satisfaction, we included 3 questions dedicated to each aspect within the same set of 8 questions.</p><p><strong>Results: </strong>As of April 10, 2023, the 5 evaluator neurologists and 5 family members of patients with AD rated the 112 responses: GPT-3.5: n=28, 25%, responses; GPT-4: n=28, 25%, responses; respondent neurologists: 56 (50%) responses. The top 5 (4.5%) responses rated by evaluator neurologists had 4 (80%) GPT (GPT-3.5+GPT-4) responses and 1 (20%) respondent neurologist's response. For the top 5 (4.5%) responses rated by patients' family members, all but the third response were GPT responses. Based on the evaluation by neurologists, the neurologist-generated responses achieved a mean score of 3.9 (SD 0.7), while the GPT-generated responses scored significantly higher (mean 4.4, SD 0.6; P<.001). Language and model analyses revealed no significant differences in response quality between the GPT-3.5 and GPT-4 models (GPT-3.5: mean 4.3, SD 0.7; GPT-4: mean 4.4, SD 0.5; P=.51). However, English responses outperformed Chinese responses in terms of comprehensibility (Chinese responses: mean 4.1, SD 0.7; English responses: mean 4.6, SD 0.5; P=.005) and participant satisfaction (Chinese responses: mean 4.2, SD 0.8; English responses: mean 4.5, SD 0.5; P=.04). According to the evaluator neurologists' review, Chinese responses had a mean score of 4.4 (SD 0.6), whereas English responses had a mean score of 4.5 (SD 0.5; P=.002). As for the family members of patients with AD, no significant differences were observed between GPT and neurologists, GPT-3.5 and GPT-4, or Chinese and English responses.</p><p><strong>Conclusions: </strong>GPT can provide patient education materials on AD for patients, their families and caregivers, nurses, and neurologists. This capability can contribute to the effective health care management of patients with AD, leading to enhanced patient outco","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e51095"},"PeriodicalIF":8.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565080/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142558056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Do Scholars Conceptualize and Conduct Health and Digital Health Literacy Research? Survey of Federally Funded Scholars.","authors":"Mayank Sakhuja, Brooks Yelton, Simone Kavarana, Lauren Schaurer, Jancham Rachel Rumthao, Samuel Noblet, Michelle A Arent, Mark M Macauda, Lorie Donelle, Daniela B Friedman","doi":"10.2196/57040","DOIUrl":"10.2196/57040","url":null,"abstract":"<p><strong>Background: </strong>The concept of health literacy (HL) is constantly evolving, and social determinants of health (SDoH) have been receiving considerable attention in public health scholarship. Since a 1-size-fits-all approach for HL fails to account for multiple contextual factors and as a result poses challenges in improving literacy levels, there is a need to develop a deeper understanding of the current state of HL and digital health literacy (DHL) research.</p><p><strong>Objective: </strong>This study examined scholars' conceptualization and scope of work focused on HL and DHL.</p><p><strong>Methods: </strong>Using a search string, investigators (N=2042) focusing on HL, DHL, or both were identified from the grantee websites of the National Institutes of Health RePORTER (RePORT Expenditures and Results) and the Canadian Institutes of Health Research. The investigators were emailed a survey via Qualtrics. Survey questions examined the focus of work; whether the investigators studied HL/DHL in combination with other SDoH; the frameworks, definitions, and approaches used; and research settings. We analyzed survey data using SPSS Statistics version 28 and descriptive analysis, including frequencies and percentages, was conducted. Chi-square tests were performed to explore the association between the focus of work, settings, and age groups included in the investigators' research.</p><p><strong>Results: </strong>A total of 193 (9.5%) of 2042 investigators responded to the online survey. Most investigators (76/153, 49.7%) were from public health, 83/193 (43%) reported their research focused on HL alone, 46/193 (23.8%) mentioned DHL, and 64/193 (33.2%) mentioned both. The majority (133/153, 86.9%) studied HL/DHL in combination with other SDoH, 106/135 (78.5%) conducted HL/DHL work in a community setting, and 100/156 (64.1%) reported not using any specific definition to guide their work. Digital tools (89/135, 65.9%), plain-language materials (82/135, 60.7%), and visual guides (56/135, 41.5%) were the top 3 approaches used. Most worked with adults (131/139, 94.2%) and all races and ethnicities (47/121, 38.8%).</p><p><strong>Conclusions: </strong>HL and DHL research largely considered SDoH. Multiple HL tools and approaches were used that support the examination and improvement of literacy and communication surrounding health care issues.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e57040"},"PeriodicalIF":8.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142558060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Speech Analysis for Risk Detection of Depression, Anxiety, Insomnia, and Fatigue: Algorithm Development and Validation Study.","authors":"Rachid Riad, Martin Denais, Marc de Gennes, Adrien Lesage, Vincent Oustric, Xuan Nga Cao, Stéphane Mouchabac, Alexis Bourla","doi":"10.2196/58572","DOIUrl":"10.2196/58572","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;While speech analysis holds promise for mental health assessment, research often focuses on single symptoms, despite symptom co-occurrences and interactions. In addition, predictive models in mental health do not properly assess the limitations of speech-based systems, such as uncertainty, or fairness for a safe clinical deployment.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We investigated the predictive potential of mobile-collected speech data for detecting and estimating depression, anxiety, fatigue, and insomnia, focusing on other factors than mere accuracy, in the general population.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We included 865 healthy adults and recorded their answers regarding their perceived mental and sleep states. We asked how they felt and if they had slept well lately. Clinically validated questionnaires measuring depression, anxiety, insomnia, and fatigue severity were also used. We developed a novel speech and machine learning pipeline involving voice activity detection, feature extraction, and model training. We automatically modeled speech with pretrained deep learning models that were pretrained on a large, open, and free database, and we selected the best one on the validation set. Based on the best speech modeling approach, clinical threshold detection, individual score prediction, model uncertainty estimation, and performance fairness across demographics (age, sex, and education) were evaluated. We used a train-validation-test split for all evaluations: to develop our models, select the best ones, and assess the generalizability of held-out data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The best model was Whisper M with a max pooling and oversampling method. Our methods achieved good detection performance for all symptoms, depression (Patient Health Questionnaire-9: area under the curve [AUC]=0.76; F&lt;sub&gt;1&lt;/sub&gt;-score=0.49 and Beck Depression Inventory: AUC=0.78; F&lt;sub&gt;1&lt;/sub&gt;-score=0.65), anxiety (Generalized Anxiety Disorder 7-item scale: AUC=0.77; F&lt;sub&gt;1&lt;/sub&gt;-score=0.50), insomnia (Athens Insomnia Scale: AUC=0.73; F&lt;sub&gt;1&lt;/sub&gt;-score=0.62), and fatigue (Multidimensional Fatigue Inventory total score: AUC=0.68; F&lt;sub&gt;1&lt;/sub&gt;-score=0.88). The system performed well when it needed to abstain from making predictions, as demonstrated by low abstention rates in depression detection with the Beck Depression Inventory and fatigue, with risk-coverage AUCs below 0.4. Individual symptom scores were accurately predicted (correlations were all significant with Pearson strengths between 0.31 and 0.49). Fairness analysis revealed that models were consistent for sex (average disparity ratio [DR] 0.86, SD 0.13), to a lesser extent for education level (average DR 0.47, SD 0.30), and worse for age groups (average DR 0.33, SD 0.30).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study demonstrates the potential of speech-based systems for multifaceted mental health assessment in the general population, not only for detecting clini","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":" ","pages":"e58572"},"PeriodicalIF":8.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565087/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142348277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lessons From 3 Longitudinal Sensor-Based Human Behavior Assessment Field Studies and an Approach to Support Stakeholder Management: Content Analysis.","authors":"Johanna Kallio, Atte Kinnula, Satu-Marja Mäkelä, Sari Järvinen, Pauli Räsänen, Simo Hosio, Miguel Bordallo López","doi":"10.2196/50461","DOIUrl":"10.2196/50461","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Pervasive technologies are used to investigate various phenomena outside the laboratory setting, providing valuable insights into real-world human behavior and interaction with the environment. However, conducting longitudinal field trials in natural settings remains challenging due to factors such as low recruitment success and high dropout rates due to participation burden or data quality issues with wireless sensing in changing environments.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study gathers insights and lessons from 3 real-world longitudinal field studies assessing human behavior and derives factors that impacted their research success. We aim to categorize challenges, observe how they were managed, and offer recommendations for designing and conducting studies involving human participants and pervasive technology in natural settings.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We developed a qualitative coding framework to categorize and address the unique challenges encountered in real-life studies related to influential factor identification, stakeholder management, data harvesting and management, and analysis and interpretation. We applied inductive reasoning to identify issues and related mitigation actions in 3 separate field studies carried out between 2018 and 2022. These 3 field studies relied on gathering annotated sensor data. The topics involved stress and environmental assessment in an office and a school, collecting self-reports and wrist device and environmental sensor data from 27 participants for 3.5 to 7 months; work activity recognition at a construction site, collecting observations and wearable sensor data from 15 participants for 3 months; and stress recognition in location-independent knowledge work, collecting self-reports and computer use data from 57 participants for 2 to 5 months. Our key extension for the coding framework used a stakeholder identification method to identify the type and role of the involved stakeholder groups, evaluating the nature and degree of their involvement and influence on the field trial success.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Our analysis identifies 17 key lessons related to planning, implementing, and managing a longitudinal, sensor-based field study on human behavior. The findings highlight the importance of recognizing different stakeholder groups, including those not directly involved but whose areas of responsibility are impacted by the study and therefore have the power to influence it. In general, customizing communication strategies to engage stakeholders on their terms and addressing their concerns and expectations is essential, while planning for dropouts, offering incentives for participants, conducting field tests to identify problems, and using tools for quality assurance are relevant for successful outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our findings suggest that field trial implementation should include additional effort to clarify the expectatio","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e50461"},"PeriodicalIF":8.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565077/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142558061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of King's Theory of Goal Attainment in Blood Glucose Management for Newly Diagnosed Patients With Type 2 Diabetes: Randomized Controlled Trial.","authors":"Man Yan, Yingchun Yu, Shuping Li, Peiling Zhang, Jiaxiang Yu","doi":"10.2196/59142","DOIUrl":"10.2196/59142","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Diabetes poses a significant public health challenge in China and globally, with the number of patients expected to reach 592 million by 2035, notably in Asia. In China alone, an estimated 140 million individuals are living with diabetes, and a significant portion is nonadherent to medications, underscoring the urgency of effective management strategies. Recognizing the necessity of early and comprehensive management for newly diagnosed patients with type 2 diabetes, this study leverages an online teach-back method and \"Internet + Nursing\" platform based on King's Theory of Goal Attainment. The approach aims to enhance glycemic control and reduce fear and misconceptions about the disease, addressing both the educational and emotional needs of the patients.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The primary aim of this study was to assess the effectiveness of King's Goal Attainment Theory in the management of newly diagnosed patients with type 2 diabetes. This research sought to develop a collaborative model for blood glucose management, integrating the expertise and roles of physicians, nurses, and patients. The model is designed to enhance the synergy in health care provision, ensuring a comprehensive approach to diabetes management.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In this study conducted at Changzhou Traditional Chinese Medicine Hospital between January 2022 and February 2023, eligible patients were randomized into a control group or an online feedback group. The control group received standard care, while the online feedback group participated in a King's Theory of Goal Attainment-based online teach-back program, enhanced by \"Internet + Nursing\" strategies. This included an interactive platform for goal planning, video content sharing, comprehension assessment, misconception correction, and patient-driven recaps of disease information. Health monitoring was facilitated through the \"Internet + Nursing\" platform. The study focused on comparing changes in glucose metabolism and emotional disorder symptoms between the groups to evaluate the intervention's effectiveness.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Following a 24-week intervention, we observed significant differences in key metrics between the online feedback group and the control group, each comprising 60 participants. The online feedback group demonstrated significant reductions in fasting plasma glucose, 2-hour postprandial glucose, and hemoglobin A&lt;sub&gt;1c&lt;/sub&gt; (P&lt;.05). Additionally, there was a notable decrease in hypoglycemia-related anxiety and alexithymia within this group. Conversely, the control group maintained relatively higher values for these metrics at the same time point (P&lt;.05). These findings underscore the efficacy of online feedback in managing glycemic control and reducing psychological distress associated with hypoglycemia.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The online teaching-back method, guided by King's Theory of Goal Attainment, effectively","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e59142"},"PeriodicalIF":5.8,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565083/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142558057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing Medical Intelligence-Leveraging Fast Healthcare Interoperability Resources to Improve Clinical Management: Retrospective Cohort and Clinical Implementation Study.","authors":"Alexander Brehmer, Christopher Martin Sauer, Jayson Salazar Rodríguez, Kelsey Herrmann, Moon Kim, Julius Keyl, Fin Hendrik Bahnsen, Benedikt Frank, Martin Köhrmann, Tienush Rassaf, Amir-Abbas Mahabadi, Boris Hadaschik, Christopher Darr, Ken Herrmann, Susanne Tan, Jan Buer, Thorsten Brenner, Hans Christian Reinhardt, Felix Nensa, Michael Gertz, Jan Egger, Jens Kleesiek","doi":"10.2196/55148","DOIUrl":"10.2196/55148","url":null,"abstract":"<p><strong>Background: </strong>FHIR (Fast Healthcare Interoperability Resources) has been proposed to enable health data interoperability. So far, its applicability has been demonstrated for selected research projects with limited data.</p><p><strong>Objective: </strong>This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for clinical decision-making.</p><p><strong>Methods: </strong>A Python package for the use of multimodal FHIR data (FHIRPACK [FHIR Python Analysis Conversion Kit]) was developed and pioneered in 5 real-world clinical use cases, that is, myocardial infarction, stroke, diabetes, sepsis, and prostate cancer. Patients were identified based on the ICD-10 (International Classification of Diseases, Tenth Revision) codes, and outcomes were derived from laboratory tests, prescriptions, procedures, and diagnostic reports. Results were provided as browser-based dashboards.</p><p><strong>Results: </strong>For 2022, a total of 1,302,988 patient encounters were analyzed. (1) Myocardial infarction: in 72.7% (261/359) of cases, medication regimens fulfilled guideline recommendations. (2) Stroke: out of 1277 patients, 165 received thrombolysis and 108 thrombectomy. (3) Diabetes: in 443,866 serum glucose and 16,180 glycated hemoglobin A_1c measurements from 35,494 unique patients, the prevalence of dysglycemic findings was 39% (13,887/35,494). Among those with dysglycemia, diagnosis was coded in 44.2% (6138/13,887) of the patients. (4) Sepsis: In 1803 patients, Staphylococcus epidermidis was the primarily isolated pathogen (773/2672, 28.9%) and piperacillin and tazobactam was the primarily prescribed antibiotic (593/1593, 37.2%). (5) PC: out of 54, three patients who received radical prostatectomy were identified as cases with prostate-specific antigen persistence or biochemical recurrence.</p><p><strong>Conclusions: </strong>Leveraging FHIR data through large-scale analytics can enhance health care quality and improve patient outcomes across 5 clinical specialties. We identified (1) patients with sepsis requiring less broad antibiotic therapy, (2) patients with myocardial infarction who could benefit from statin and antiplatelet therapy, (3) patients who had a stroke with longer than recommended times to intervention, (4) patients with hyperglycemia who could benefit from specialist referral, and (5) patients with PC with early increases in cancer markers.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":" ","pages":"e55148"},"PeriodicalIF":8.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565078/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experiences With mHealth Use Among Patient-Caregiver Dyads With Chronic Heart Failure: Qualitative Study.","authors":"Xiaorong Jin, Yimei Zhang, Min Zhou, Xiong Zhang, Qian Mei, Yangjuan Bai, Wei Wei, Fang Ma","doi":"10.2196/57115","DOIUrl":"10.2196/57115","url":null,"abstract":"<p><strong>Background: </strong>Chronic heart failure has become a serious threat to the health of the global population, and self-management is key to treating chronic heart failure. The emergence of mobile health (mHealth) provides new ideas for the self-management of chronic heart failure in which the informal caregiver plays an important role. Current research has mainly studied the experiences with using mHealth among patients with chronic heart failure from the perspective of individual patients, and there is a lack of research from the dichotomous perspective.</p><p><strong>Objective: </strong>The aim of this study was to explore the experiences with mHealth use among patients with chronic heart failure and their informal caregivers from a dichotomous perspective.</p><p><strong>Methods: </strong>This descriptive phenomenological study from a post-positivist perspective used a dyadic interview method, and face-to-face semistructured interviews were conducted with patients with chronic heart failure and their informal caregivers. Data were collected and managed using NVivo 12 software, and data analysis used thematic analysis to identify and interpret participants' experiences and perspectives. The thematic analysis included familiarizing ourselves with the data, generating initial codes, searching for themes, reviewing themes, defining and naming themes, and producing the report.</p><p><strong>Results: </strong>A total of 14 dyads of patients with chronic heart failure and their informal caregivers (13 men and 15 women) participated in this study, including 3 couples and 11 parent-child pairs. We constructed 4 key themes and their subthemes related to the experiences with mHealth use: (1) opposing experiences with mHealth as human interaction or trauma (great experience with mHealth use; trauma), (2) supplement instead of replacement (it is useful but better as a reference; offline is unavoidable sometimes), (3) both agreement and disagreement over who should be the adopter of mHealth (achieving consensus regarding who should adopt mHealth; conflict occurs when considering patients as the adopter of mHealth), (4) for better mHealth (applying mHealth with caution; suggestions for improved mHealth).</p><p><strong>Conclusions: </strong>This study reported that the experiences with mHealth use among patients with chronic heart failure and their informal caregivers were mixed, and it highlighted the human touch of mHealth and the importance of network security. These results featured mHealth as a complement to offline hospitals rather than a replacement. In the context of modern or changing Chinese culture, we encourage patients to use mHealth by themselves and their informal caregivers to provide help when necessary. In addition, we need to use mHealth carefully, and future mHealth designs should focus more on ease of use and be oriented more toward older adults.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e57115"},"PeriodicalIF":8.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565088/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142558059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of Telecare Conversations on Lifestyle Management and Their Relation to Health Care Utilization for Patients with Heart Failure: Mixed Methods Study.","authors":"Mojisola Erdt, Sakinah Binte Yusof, Liquan Chai, Siti Umairah Md Salleh, Zhengyuan Liu, Halimah Binte Sarim, Geok Choo Lim, Hazel Lim, Nur Farah Ain Suhaimi, Lin Yulong, Yang Guo, Angela Ng, Sharon Ong, Bryan Peide Choo, Sheldon Lee, Huang Weiliang, Hong Choon Oh, Maria Klara Wolters, Nancy F Chen, Pavitra Krishnaswamy","doi":"10.2196/46983","DOIUrl":"10.2196/46983","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Telehealth interventions where providers offer support and coaching to patients with chronic conditions such as heart failure (HF) and type 2 diabetes mellitus (T2DM) are effective in improving health outcomes. However, the understanding of the content and structure of these interactions and how they relate to health care utilization remains incomplete.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to characterize the content and structure of telecare conversations on lifestyle management for patients with HF and investigate how these conversations relate to health care utilization.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We leveraged real-world data from 50 patients with HF enrolled in a postdischarge telehealth program, with the primary intervention comprising a series of telephone calls from nurse telecarers over a 12-month period. For the full cohort, we transcribed 729 English-language calls and annotated conversation topics. For a subcohort (25 patients with both HF and T2DM), we annotated lifestyle management content with fine-grained dialogue acts describing typical conversational structures. For each patient, we identified calls with unusually high ratios of utterances on lifestyle management as lifestyle-focused calls. We further extracted structured data for inpatient admissions from 6 months before to 6 months after the intervention period. First, to understand conversational structures and content of lifestyle-focused calls, we compared the number of utterances, dialogue acts, and symptom attributes in lifestyle-focused calls to those in calls containing but not focused on lifestyle management. Second, to understand the perspectives of nurse telecarers on these calls, we conducted an expert evaluation where 2 nurse telecarers judged levels of concern and follow-up actions for lifestyle-focused and other calls (not focused on lifestyle management content). Finally, we assessed how the number of lifestyle-focused calls relates to the number of admissions, and to the average length of stay per admission.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In comparative analyses, lifestyle-focused calls had significantly fewer utterances (P=.01) and more dialogue acts (P&lt;sub&gt;adj&lt;/sub&gt;=.005) than calls containing but not focused on lifestyle management. Lifestyle-focused calls did not contain deeper discussions on clinical symptoms. These findings indicate that lifestyle-focused calls entail short, intense discussions with greater emphasis on understanding patient experience and coaching than on clinical content. In the expert evaluation, nurse telecarers identified 24.2% (29/120) of calls assessed as concerning enough for follow-up. For these 29 calls, nurse telecarers were more attuned to concerns about symptoms and vitals (19/29, 65.5%) than lifestyle management concerns (4/29, 13.8%). The number of lifestyle-focused calls a patient had was modestly (but not significantly) associated with a lower average length of stay for in","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e46983"},"PeriodicalIF":8.3,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11561433/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142545947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Different Types of Social Media Use on the Mental Health of UK Adults: Longitudinal Observational Study.","authors":"Yue Yu, Jennifer Dykxhoorn, Ruth Plackett","doi":"10.2196/56950","DOIUrl":"10.2196/56950","url":null,"abstract":"<p><strong>Background: </strong>Previous studies have explored the association between social media use and mental health among adolescents. However, few studies using nationally representative longitudinal data have explored this relationship for adults and how the effect might change depending on how people use social media.</p><p><strong>Objective: </strong>This study investigated the longitudinal relationship between the frequency of viewing and posting on social media and mental health problems among UK adults.</p><p><strong>Methods: </strong>This study included 15,836 adults (aged 16 years and older) who participated in Understanding Society, a UK longitudinal survey. Social media use was measured with questions about the frequency of viewing social media and posting on social media in Understanding Society Wave 11 (2019-2021). We explored viewing and posting separately, as well as a combined exposure: (1) high viewing, high posting; (2) high viewing, low posting; (3) low viewing, high posting; and (4) low viewing, low posting. Mental health problems were measured in Wave 12 (2020-2022) using the General Health Questionnaire (GHQ-12), a validated scale for identifying symptoms of common mental health problems, where higher scores indicated more mental health problems (0 to 36). Unadjusted and adjusted linear regression models were estimated for viewing social media and posting on social media, adjusting for the baseline GHQ score, gender, age, ethnicity, employment, and education. We found no evidence for effect modification by gender and age so overall associations were reported.</p><p><strong>Results: </strong>In our adjusted models, we found no evidence of an association between the frequency of viewing social media and mental health problems in the following year. We found that adults who posted daily on social media had more mental health problems than those who never posted on social media, corresponding to a 0.35-point increase in GHQ score (β=0.35, 95% CI 0.01-0.68; P=.04). When we considered both social media behaviors, we found that those who frequently viewed and posted on social media scored 0.31 points higher on the GHQ score (β=0.31, 95% CI 0.04-0.58; P=.03) in the following year compared to those who rarely viewed or posted on social media.</p><p><strong>Conclusions: </strong>We found that a high frequency of posting on social media was associated with increased mental health problems a year later. However, we did not find evidence of a similar association based on the frequency of viewing social media content. This provides evidence that some types of active social media use (ie, posting) have a stronger link to mental health outcomes than some types of passive social media use (viewing). These results highlighted that the relationship between social media use and mental health is complex, and more research is needed to understand the mechanisms underlying these patterns to inform targeted interventions and policies.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e56950"},"PeriodicalIF":5.8,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11561428/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142545958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}