@Article{info:doi/10.2196/63017, author="Lempe, Notger Paul and Guinemer, Camille and F{\"u}rstenau, Daniel and Dressler, Corinna and Balzer, Felix and Schaaf, Thorsten", title="Health Care Social Robots in the Age of Generative AI: Protocol for a Scoping Review", journal="JMIR Res Protoc", year="2025", month="Apr", day="14", volume="14", pages="e63017", keywords="robotics", keywords="social robots", keywords="artificial intelligence", keywords="generative AI", keywords="human-robot interaction", keywords="health care sector", keywords="PRISMA", abstract="Background: Social robots (SR), sensorimotor machines designed to interact with humans, can help to respond to the increasing demands in the health care sector. To ensure the successful use of this technology, acceptance is paramount. Generative artificial intelligence (AI) is an emerging technology with the potential to enhance the functionality of SR and promote user acceptance by further improving human-robot interaction. Objective: We present a protocol for a scoping review of the literature on the implementation of generative AI in SR in the health care sector. The aim of this scoping review is to map out the intersection of SR and generative AI in the health care sector; to explore if generative AI is applied in SR in the health care sector; to outline which models of generative AI and SR are used for these implementations; and to explore whether user acceptance is reported as an outcome following these implementations. This scoping review supports future research by providing an overview of the state of connectedness of 2 emerging technologies and by mapping out research gaps. Methods: We follow the methodological framework developed by Arksey and O'Malley and the recommendations by the Joanna Briggs Institute. Our protocol was drafted using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews). We will conduct a systematic literature search of the online databases MEDLINE, Embase, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and IEEE Xplore, aiming to retrieve relevant data items via tabular data charting from references meeting specific inclusion criteria which are studies published from 2010 onwards, set in the health care sector, focusing on SR with physical bodies and implemented generative AI. There are no restrictions on study types. Results will be categorized, clustered, and summarized using tables, graphs, visual representations, and narratives. Results: After conducting a preliminary search and deduplication in the second quarter of 2024, we retrieved 3176 preliminary results. This scoping review will be supplemented with the next methodological steps, including retrieving the results in a reference management tool as well as screening titles, abstracts, and full text regarding specific inclusion criteria. The completion of these steps is scheduled for the second quarter of 2025. Limitations based on the heterogeneity of the included studies and the general breadth of a scoping review compared to a systematic review are to be expected. To reduce bias, we adopted a system of dual reviews and thorough documentation of the study selection. Conclusions: The conducted preliminary search implies that there are a sufficient number of heterogeneous references to complete this scoping review. To our knowledge, this is the first scoping review on generative AI in health care SR. International Registered Report Identifier (IRRID): PRR1-10.2196/63017 ", doi="10.2196/63017", url="https://www.researchprotocols.org/2025/1/e63017" } @Article{info:doi/10.2196/67840, author="Lu, Zhen and Dong, Binhua and Cai, Hongning and Tian, Tian and Wang, Junfeng and Fu, Leiwen and Wang, Bingyi and Zhang, Weijie and Lin, Shaomei and Tuo, Xunyuan and Wang, Juntao and Yang, Tianjie and Huang, Xinxin and Zheng, Zheng and Xue, Huifeng and Xu, Shuxia and Liu, Siyang and Sun, Pengming and Zou, Huachun", title="Identifying Data-Driven Clinical Subgroups for Cervical Cancer Prevention With Machine Learning: Population-Based, External, and Diagnostic Validation Study", journal="JMIR Public Health Surveill", year="2025", month="Mar", day="19", volume="11", pages="e67840", keywords="cervical cancer", keywords="human papillomavirus", keywords="screening", keywords="machine learning", keywords="cervical tumor", keywords="cancer", keywords="carcinoma", keywords="tumor", keywords="malignant", keywords="ML", keywords="phenomapping strategy", keywords="logistic regression", keywords="regression", keywords="population-based", keywords="validation study", keywords="cancer prevention", keywords="validity", keywords="usability", keywords="algorithm", keywords="surveillance", keywords="electronic health record", keywords="EHR", abstract="Background: Cervical cancer remains a major global health issue. Personalized, data-driven cervical cancer prevention (CCP) strategies tailored to phenotypic profiles may improve prevention and reduce disease burden. Objective: This study aimed to identify subgroups with differential cervical precancer or cancer risks using machine learning, validate subgroup predictions across datasets, and propose a computational phenomapping strategy to enhance global CCP efforts. Methods: We explored the data-driven CCP subgroups by applying unsupervised machine learning to a deeply phenotyped, population-based discovery cohort. We extracted CCP-specific risks of cervical intraepithelial neoplasia (CIN) and cervical cancer through weighted logistic regression analyses providing odds ratio (OR) estimates and 95\% CIs. We trained a supervised machine learning model and developed pathways to classify individuals before evaluating its diagnostic validity and usability on an external cohort. Results: This study included 551,934 women (median age, 49 years) in the discovery cohort and 47,130 women (median age, 37 years) in the external cohort. Phenotyping identified 5 CCP subgroups, with CCP4 showing the highest carcinoma prevalence. CCP2--4 had significantly higher risks of CIN2+ (CCP2: OR 2.07 [95\% CI: 2.03?2.12], CCP3: 3.88 [3.78?3.97], and CCP4: 4.47 [4.33?4.63]) and CIN3+ (CCP2: 2.10 [2.05?2.14], CCP3: 3.92 [3.82?4.02], and CCP4: 4.45 [4.31?4.61]) compared to CCP1 (P<.001), consistent with the direction of results observed in the external cohort. The proposed triple strategy was validated as clinically relevant, prioritizing high-risk subgroups (CCP3-4) for colposcopies and scaling human papillomavirus screening for CCP1-2. Conclusions: This study underscores the potential of leveraging machine learning algorithms and large-scale routine electronic health records to enhance CCP strategies. By identifying key determinants of CIN2+/CIN3+ risk and classifying 5 distinct subgroups, our study provides a robust, data-driven foundation for the proposed triple strategy. This approach prioritizes tailored prevention efforts for subgroups with varying risks, offering a novel and scalable tool to complement existing cervical cancer screening guidelines. Future work should focus on independent external and prospective validation to maximize the global impact of this strategy. ", doi="10.2196/67840", url="https://publichealth.jmir.org/2025/1/e67840" } @Article{info:doi/10.2196/67682, author="Baek, Gumhee and Cha, Chiyoung and Han, Jin-Hui", title="AI Chatbots for Psychological Health for Health Professionals: Scoping Review", journal="JMIR Hum Factors", year="2025", month="Mar", day="19", volume="12", pages="e67682", keywords="artificial intelligence", keywords="AI chatbot", keywords="psychological health", keywords="health professionals", keywords="burnout", keywords="scoping review", abstract="Background: Health professionals face significant psychological burdens including burnout, anxiety, and depression. These can negatively impact their well-being and patient care. Traditional psychological health interventions often encounter limitations such as a lack of accessibility and privacy. Artificial intelligence (AI) chatbots are being explored as potential solutions to these challenges, offering available and immediate support. Therefore, it is necessary to systematically evaluate the characteristics and effectiveness of AI chatbots designed specifically for health professionals. Objective: This scoping review aims to evaluate the existing literature on the use of AI chatbots for psychological health support among health professionals. Methods: Following Arksey and O'Malley's framework, a comprehensive literature search was conducted across eight databases, covering studies published before 2024, including backward and forward citation tracking and manual searching from the included studies. Studies were screened for relevance based on inclusion and exclusion criteria, among 2465 studies retrieved, 10 studies met the criteria for review. Results: Among the 10 studies, six chatbots were delivered via mobile platforms, and four via web-based platforms, all enabling one-on-one interactions. Natural language processing algorithms were used in six studies and cognitive behavioral therapy techniques were applied to psychological health in four studies. Usability was evaluated in six studies through participant feedback and engagement metrics. Improvements in anxiety, depression, and burnout were observed in four studies, although one reported an increase in depressive symptoms. Conclusions: AI chatbots show potential tools to support the psychological health of health professionals by offering personalized and accessible interventions. Nonetheless, further research is required to establish standardized protocols and validate the effectiveness of these interventions. Future studies should focus on refining chatbot designs and assessing their impact on diverse health professionals. ", doi="10.2196/67682", url="https://humanfactors.jmir.org/2025/1/e67682" } @Article{info:doi/10.2196/52972, author="Rosenfeld, Daniel and Brennan, Sean and Wallach, Andrew and Long, Theodore and Keeley, Chris and Kurien, Joseph Sarah", title="COVID-19 Testing Equity in New York City During the First 2 Years of the Pandemic: Demographic Analysis of Free Testing Data", journal="JMIR Public Health Surveill", year="2025", month="Mar", day="13", volume="11", pages="e52972", keywords="COVID-19 testing", keywords="health disparities", keywords="equity in testing", keywords="New York City", keywords="socioeconomic factors", keywords="testing accessibility", keywords="health care inequalities", keywords="demographic analysis", keywords="COVID-19 mortality", keywords="coronavirus", keywords="SARS-CoV-2", keywords="pandemic", keywords="equitable testing", keywords="cost", keywords="poor neighborhood", keywords="resources", abstract="Background: COVID-19 has caused over 46,000 deaths in New York City, with a disproportional impact on certain communities. As part of the COVID-19 response, the city has directly administered over 6 million COVID-19 tests (in addition to millions of indirectly administered tests not covered in this analysis) at no cost to individuals, resulting in nearly half a million positive results. Given that the prevalence of testing, throughout the pandemic, has tended to be higher in more affluent areas, these tests were targeted to areas with fewer resources. Objective: This study aimed to evaluate the impact of New York City's COVID-19 testing program; specifically, we aimed to review its ability to provide equitable testing in economically, geographically, and demographically diverse populations. Of note, in addition to the brick-and-mortar testing sites evaluated herein, this program conducted 2.1 million tests through mobile units to further address testing inequity. Methods: Testing data were collected from the in-house Microsoft SQL Server Management Studio 18 Clarity database, representing 6,347,533 total tests and 449,721 positive test results. These tests were conducted at 48 hospital system locations. Per capita testing rates by zip code tabulation area (ZCTA) and COVID-19 positivity rates by ZCTA were used as dependent variables in separate regressions. Median income, median age, the percentage of English-speaking individuals, and the percentage of people of color were used as independent demographic variables to analyze testing patterns across several intersecting identities. Negative binomial regressions were run in a Jupyter Notebook using Python. Results: Per capita testing inversely correlated with median income geographically. The overall pseudo r2 value was 0.1101 when comparing hospital system tests by ZCTA against the selected variables. The number of tests significantly increased as median income fell (SE 1.00000155; P<.001). No other variables correlated at a significant level with the number of tests (all P values were >.05). When considering positive test results by ZCTA, the number of positive test results also significantly increased as median income fell (SE 1.57e--6; P<.001) and as the percentage of female residents fell (SE 0.957; P=.001). The number of positive test results by ZCTA rose at a significant level alongside the percentage of English-only speakers (SE 0.271; P=.03). Conclusions: New York City's COVID-19 testing program was able to improve equity through the provision of no-cost testing, which focused on areas of the city that were disproportionately impacted by COVID-19 and had fewer resources. By detecting higher numbers of positive test results in resource-poor neighborhoods, New York City was able to deploy additional resources, such as those for contact tracing and isolation and quarantine support (eg, free food delivery and free hotel stays), early during the COVID-19 pandemic. Equitable deployment of testing is feasible and should be considered early in future epidemics or pandemics. ", doi="10.2196/52972", url="https://publichealth.jmir.org/2025/1/e52972" } @Article{info:doi/10.2196/59165, author="De la Torre, Katherine and Min, Sukhong and Lee, Hyobin and Kang, Daehee", title="The Application of Preventive Medicine in the Future Digital Health Era", journal="J Med Internet Res", year="2025", month="Feb", day="27", volume="27", pages="e59165", keywords="preventive medicine", keywords="personalized prevention", keywords="digital health technology", keywords="digital health", keywords="artificial intelligence", keywords="wearable devices", keywords="telemedicine", doi="10.2196/59165", url="https://www.jmir.org/2025/1/e59165", url="http://www.ncbi.nlm.nih.gov/pubmed/40053712" } @Article{info:doi/10.2196/66056, author="Wang, Jianli and Orpana, Heather and Carrington, Andr{\'e} and Kephart, George and Vasiliadis, Helen-Maria and Leikin, Benjamin", title="Development and Validation of Prediction Models for Perceived and Unmet Mental Health Needs in the Canadian General Population: Model-Based Synthetic Estimation Study", journal="JMIR Public Health Surveill", year="2025", month="Feb", day="19", volume="11", pages="e66056", keywords="population risk prediction", keywords="development", keywords="validation", keywords="perceived mental health need", keywords="unmet mental health need", abstract="Background: Research has shown that perceptions of a mental health need are closely associated with service demands and are an important dimension in needs assessment. Perceived and unmet mental health needs are important factors in the decision-making process regarding mental health services planning and resources allocation. However, few prediction tools are available to be used by policy and decision makers to forecast perceived and unmet mental health needs at the population level. Objective: We aim to develop prediction models to forecast perceived and unmet mental health needs at the provincial and health regional levels in Canada. Methods: Data from 2018, 2019, and 2020 Canadian Community Health Survey and Canadian Urban Environment were used (n=65,000 each year). Perceived and unmet mental health needs were measured by the Perceived Needs for Care Questionnaire. Using the 2018 dataset, we developed the prediction models through the application of regression synthetic estimation for the Atlantic, Central, and Western regions. The models were validated in the 2019 and 2020 datasets at the provincial level and in 10 randomly selected health regions by comparing the observed and predicted proportions of the outcomes. Results: In 2018, a total of 17.82\% of the participants reported perceived mental health need and 3.81\% reported unmet mental health need. The proportions were similar in 2019 (18.04\% and 3.91\%) and in 2020 (18.1\% and 3.92\%). Sex, age, self-reported mental health, physician diagnosed mood and anxiety disorders, self-reported life stress and life satisfaction were the predictors in the 3 regional models. The individual based models had good discriminative power with C statistics over 0.83 and good calibration. Applying the synthetic models in 2019 and 2020 data, the models had the best performance in Ontario, Quebec, and British Columbia; the absolute differences between observed and predicted proportions were less than 1\%. The absolute differences between the predicted and observed proportion of perceived mental health needs in Newfoundland and Labrador (?4.16\% in 2020) and Prince Edward Island (4.58\% in 2019) were larger than those in other provinces. When applying the models in the 10 selected health regions, the models calibrated well in the health regions in Ontario and in Quebec; the absolute differences in perceived mental health needs ranged from 0.23\% to 2.34\%. Conclusions: Predicting perceived and unmet mental health at the population level is feasible. There are common factors that contribute to perceived and unmet mental health needs across regions, at different magnitudes, due to different population characteristics. Therefore, predicting perceived and unmet mental health needs should be region specific. The performance of the models at the provincial and health regional levels may be affected by population size. ", doi="10.2196/66056", url="https://publichealth.jmir.org/2025/1/e66056" } @Article{info:doi/10.2196/69007, author="Sezgin, Emre and Kocaballi, Baki Ahmet", title="Era of Generalist Conversational Artificial Intelligence to Support Public Health Communications", journal="J Med Internet Res", year="2025", month="Jan", day="20", volume="27", pages="e69007", keywords="messaging apps", keywords="public health communication", keywords="language models", keywords="artificial intelligence", keywords="AI", keywords="generative AI", keywords="conversational AI", doi="10.2196/69007", url="https://www.jmir.org/2025/1/e69007" } @Article{info:doi/10.2196/64539, author="S{\'a}nchez-Gonz{\'a}lez, Luis Juan and S{\'a}nchez-Rodr{\'i}guez, Luis Juan and Gonz{\'a}lez-Sarmiento, Rogelio and Navarro-L{\'o}pez, V{\'i}ctor and Ju{\'a}rez-Vela, Ra{\'u}l and P{\'e}rez, Jes{\'u}s and Mart{\'i}n-Vallejo, Javier", title="Effect of Physical Exercise on Telomere Length: Umbrella Review and Meta-Analysis", journal="JMIR Aging", year="2025", month="Jan", day="10", volume="8", pages="e64539", keywords="aging", keywords="chromosome", keywords="exercise", keywords="meta-analysis", keywords="telomere", keywords="telomerase", keywords="genes", keywords="genome", keywords="DNA", abstract="Background: Telomere length (TL) is a marker of cellular health and aging. Physical exercise has been associated with longer telomeres and, therefore, healthier aging. However, results supporting such effects vary across studies. Our aim was to synthesize existing evidence on the effect of different modalities and durations of physical exercise on TL. Objective: The aim of this study was to explore the needs and expectations of individuals with physical disabilities and their interventionists for the use of a virtual reality physical activity platform in a community organization. Methods: We performed an umbrella review and meta-analysis. Data sources included PubMed, Embase, Web of Science, Cochrane Library, and Scopus. We selected systematic reviews and meta-analyses of randomized and nonrandomized controlled clinical trials evaluating the effect of physical exercise on TL. Results: Our literature search retrieved 12 eligible systematic reviews, 5 of which included meta-analyses. We identified 22 distinct primary studies to estimate the overall effect size of physical exercise on TL. The overall effect size was 0.28 (95\% CI 0.118-0.439), with a heterogeneity test value Q of 43.08 (P=.003) and I{\texttwosuperior} coefficient of 51\%. The number of weeks of intervention explained part of this heterogeneity (Q\_B=8.25; P=.004), with higher effect sizes found in studies with an intervention of less than 30 weeks. Exercise modality explained additional heterogeneity within this subgroup (Q\_B=10.28, P=.02). The effect sizes were small for aerobic exercise and endurance training, and moderate for high-intensity interval training. Conclusions: Our umbrella review and meta-analysis detected a small-moderate positive effect of physical exercise on TL, which seems to be influenced by the duration and type of physical exercise. High quality studies looking into the impact of standardized, evidence-based physical exercise programs on TL are still warranted. Trial Registration: PROSPERO CRD42024500736; https://www.crd.york.ac.uk/PROSPERO/display\_record.php?RecordID=500736 ", doi="10.2196/64539", url="https://aging.jmir.org/2025/1/e64539" } @Article{info:doi/10.2196/64995, author="Miller, I. Joshua and Hassell, L. Kathryn and Kellar-Guenther, Yvonne and Quesada, Stacey and West, Rhonda and Sontag, Marci", title="The Prevalence of Sickle Cell Disease in Colorado and Methodologies of the Colorado Sickle Cell Data Collection Program: Public Health Surveillance Study", journal="JMIR Public Health Surveill", year="2024", month="Dec", day="9", volume="10", pages="e64995", keywords="sickle cell disease", keywords="public health surveillance", keywords="prevalence", keywords="birth prevalence", keywords="Colorado", keywords="sickle cell", keywords="surveillance", keywords="SCD", keywords="USA", keywords="data collection", keywords="blood disorder", keywords="policy development", keywords="hematology", keywords="United States", abstract="Background: Sickle cell disease (SCD) is a genetic blood disorder that affects approximately 100,000 individuals in the United States, with the highest prevalence among Black or African American populations. While advances in care have improved survival, comprehensive state-level data on the prevalence of SCD remain limited, which hampers efforts to optimize health care services. To address this gap, the Colorado Sickle Cell Data Collection (CO-SCDC) program was established in 2021 as part of the Centers for Disease Control and Prevention's initiative to enhance surveillance and public health efforts for SCD. Objective: The objectives of this study were to describe the establishment of the CO-SCDC program and to provide updated estimates of the prevalence and birth prevalence of SCD in Colorado, including geographic dispersion. Additional objectives include evaluating the accuracy of case identification methods and leveraging surveillance activities to inform public health initiatives. Methods: Data were collected from Health Data Compass (a multi-institutional data warehouse) containing electronic health records from the University of Colorado Health and Children's Hospital Colorado for the years 2012?2020. Colorado newborn screening program data were included for confirmed SCD diagnoses from 2001 to 2020. Records were linked using the Colorado University Record Linkage tool and deidentified for analysis. Case definitions, adapted from the Centers for Disease Control and Prevention's Registry and Surveillance System for Hemoglobinopathies project, classified cases as possible, probable, or definite SCD. Clinical validation by hematologists was performed to ensure accuracy, and prevalence rates were calculated using 2020 US Census population estimates. Results: In 2019, 435 individuals were identified as living with SCD in Colorado, an increase of 16\%?40\% over previous estimates, with the majority (n=349, 80.2\%) identifying as Black or African American. The median age of individuals was 19 years. The prevalence of SCD was highest in urban counties, with concentrations in Arapahoe, Denver, and El Paso counties. Birth prevalence of SCD increased from 11.9 per 100,000 live births between 2010 and 2014 to 20.1 per 100,000 live births between 2015 and 2019 with 58.5\% (n=38) of cases being hemoglobin (Hb) SS or HbS$\beta$0 thalassemia subtypes. The study highlighted a 67\% (n=26) increase in SCD births over the decade, correlating with the growth of the Black or African American population in the state. Conclusions: The CO-SCDC program successfully established the capacity to perform SCD surveillance and, in doing so, identified baseline prevalence estimates for SCD in Colorado. The findings highlight geographic dispersion across Colorado counties, highlighting the need for equitable access to specialty care, particularly for rural populations. The combination of automated data linkage and clinical validation improved case identification accuracy. Future efforts will expand surveillance to include claims data to better capture health care use and address potential underreporting. These results will guide public health interventions aimed at improving care for individuals with SCD in Colorado. ", doi="10.2196/64995", url="https://publichealth.jmir.org/2024/1/e64995" } @Article{info:doi/10.2196/60140, author="Poncet, R{\'e}my and Gargominy, Olivier", title="In the Shadow of Medicine: The Glaring Absence of Occurrence Records of Human-Hosted Biodiversity", journal="Online J Public Health Inform", year="2024", month="Dec", day="9", volume="16", pages="e60140", keywords="human microbiome", keywords="bacterial occurrence data", keywords="public health", keywords="one health", keywords="biodiversity data gap", keywords="medical data integration", keywords="medical data", keywords="microbiome", keywords="bacterial", keywords="bacteria", keywords="biodiversity", keywords="disease prevention", keywords="pathogens", keywords="user-friendly", keywords="bacterial pathogens", doi="10.2196/60140", url="https://ojphi.jmir.org/2024/1/e60140" } @Article{info:doi/10.2196/59138, author="Kang, Ye Ji and Jung, Weon and Kim, Ji Hyun and An, Hyun Ji and Yoon, Hee and Kim, Taerim and Chang, Hansol and Hwang, Yeon Sung and Park, Eun Jong and Lee, Tak Gun and Cha, Chul Won and Heo, Sejin and Lee, Uk Se", title="Temporary Telemedicine Policy and Chronic Disease Management in South Korea: Retrospective Analysis Using National Claims Data", journal="JMIR Public Health Surveill", year="2024", month="Nov", day="20", volume="10", pages="e59138", keywords="telemedicine", keywords="public health", keywords="medication adherence", keywords="COVID-19", keywords="chronic diseases", abstract="Background: Since its introduction, telemedicine for patients with chronic diseases has been studied in various clinical settings. However, there is limited evidence of the effectiveness and medical safety of the nationwide adoption of telemedicine. Objective: This study aimed to analyze the effects of telemedicine on chronic diseases during the COVID-19 pandemic under a temporary telemedicine policy in South Korea using national claims data. Methods: Health insurance claims data were extracted over 2 years: 1 year before (from February 24, 2019, to February 23, 2020) and 1 year after the policy was implemented (from February 24, 2020, to February 23, 2021). We included all patients who used telemedicine at least once in the first year after the policy was implemented and compared them with a control group of patients who never used telemedicine. The comparison focused on health care use; the medication possession ratio (MPR); and admission rates to general wards (GWs), emergency departments (EDs), and intensive care units (ICUs) using difference-in-differences analysis. A total of 4 chronic diseases were targeted: hypertension, diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), and common mental disorders. Results: A total of 1,773,454 patients with hypertension; 795,869 patients with DM; 37,460 patients with COPD; and 167,084 patients with common mental disorders were analyzed in this study. Patients diagnosed with hypertension or DM showed increased MPRs without an increase in GW, ED, or ICU admission rates during the policy year. Moreover, patients in the DM group who did not use telemedicine had higher rates of ED, GW, and ICU admissions, and patients in the hypertension group had higher rates of GW or ICU admissions after 1 year of policy implementation. This trend was not evident in COPD and common mental disorders. Conclusions: The temporary telemedicine policy was effective in increasing medication adherence and reducing admission rates for patients with hypertension and DM; however, the efficacy of the policy was limited for patients with COPD and common mental disorders. Future studies are required to demonstrate the long-term effects of telemedicine policies with various outcome measures reflecting disease characteristics. ", doi="10.2196/59138", url="https://publichealth.jmir.org/2024/1/e59138" } @Article{info:doi/10.2196/53340, author="Bito, Seiji and Hayashi, Yachie and Fujita, Takanori and Takahashi, Ikuo and Arai, Hiromi and Yonemura, Shigeto", title="Survey of Citizens' Preferences for Combined Contact Tracing App Features During a Pandemic: Conjoint Analysis", journal="JMIR Public Health Surveill", year="2024", month="Nov", day="14", volume="10", pages="e53340", keywords="digital contact tracing apps", keywords="infectious disease", keywords="conjoint analysis", keywords="user attitudes", keywords="public preferences", keywords="citizen values", keywords="attitude to health", keywords="COVID-19", keywords="contact tracing", keywords="privacy", keywords="questionnaires", abstract="Background: During the COVID-19 pandemic, an increased need for novel solutions such as digital contact tracing apps to mitigate virus spread became apparent. These apps have the potential to enhance public health initiatives through timely contact tracing and infection rate reduction. However, public and academic scrutiny has emerged around the adoption and use of these apps due to privacy concerns. Objective: This study aims to investigate public attitudes and preferences for contact tracing apps, specifically in Japan, using conjoint analysis to examine what specifications the public values most in such apps. By offering a nuanced understanding of the values that citizens prioritize, this study can help balance public health benefits and data privacy standards when designing contact tracing apps and serve as reference data for discussions on legal development and social consensus formation in the future. Methods: A cross-sectional, web-based questionnaire survey was conducted to determine how various factors related to the development and integration of infectious disease apps affect the public's intention to use such apps. Individuals were recruited anonymously by a survey company. All respondents were asked to indicate their preferences for a combination of basic attributes and infectious disease app features for conjoint analysis. The respondents were randomly divided into 2 groups: one responded to a scenario where the government was assumed to be the entity dealing with infectious disease apps (ie, the government cluster), and the other responded to a scenario where a commercial company was assumed to be this entity (ie, the business cluster). Samples of 500 respondents from each randomly selected group were used as target data. Results: For the government cluster, the most important attribute in scenario A was distributor rights (42.557), followed by public benefits (29.458), personal health benefits (22.725), and profit sharing (5.260). For the business cluster, the most important attribute was distributor rights (45.870), followed by public benefits (32.896), personal health benefits (13.994), and profit sharing (7.240). Hence, personal health benefits tend to be more important in encouraging active app use than personal financial benefits. However, the factor that increased motivation for app use the most was the public health benefits of cutting infections by half. Further, concern about the use of personal data collected by the app for any secondary purpose was a negative incentive, which was more significant toward app use compared to the other 3 factors. Conclusions: The findings suggest that potential app users are positively motivated not only by personal health benefits but also by contributing to public health. Thus, a combined approach can be taken to increase app use. ", doi="10.2196/53340", url="https://publichealth.jmir.org/2024/1/e53340" } @Article{info:doi/10.2196/55160, author="France, Sonja and Dettori, Amy and Ekici, Seda and McKinley, Lilian and Patel, Sana and Jewell, Teresa and Crocker, E. Mary", title="Community Health Worker Videoconferencing Interventions for Disease Management and Health Promotion: Protocol for a Scoping Review", journal="JMIR Res Protoc", year="2024", month="Nov", day="7", volume="13", pages="e55160", keywords="community health worker", keywords="lay health worker", keywords="telehealth", keywords="videoconferencing", keywords="intervention", keywords="digital divide", keywords="disease management", keywords="health promotion", abstract="Background: Public health interventions delivered by community health workers (CHWs) have been proven effective in improving health outcomes across multiple fields, particularly in populations that are underserved by traditional health care systems. To date, little research is available about how CHW-led interventions could be successfully delivered virtually, despite many other health care services being offered via telehealth. Objective: This paper details a scoping review protocol that aims to assess the existing literature on CHW-led interventions using videoconferencing technology. Methods: The scoping review protocol was developed using the Joanna Briggs Institute's guidelines on conduct of scoping reviews. Included papers will describe a direct intervention to manage disease or improve health, delivered by CHWs via videoconferencing. Multiple literature databases and gray literature will be searched. Abstracts and then full texts will be reviewed to determine inclusion by 2 independent reviewers; conflicts at each stage will be resolved by a third reviewer. A data extraction tool will be used by reviewers to independently chart data from included studies; results will be reviewed for accuracy by a second reviewer. Included papers will be analyzed to identify the breadth of the available evidence, including barriers, facilitators, effectiveness, and best practices described in the literature. Data will be summarized in a narrative review. Results: This study commenced in April 2022, and the study protocol was finalized in November 2022. A preliminary search of the published literature (excluding gray literature) in July 2024 revealed 276 reports after removal of duplicates. The formal literature search will commence in August 2024, with results available by December 2024. We intend to publish results in the academic literature as well as creating a report accessible to nonacademic and community audiences. Conclusions: This review will illuminate the breadth of the evidence available on CHW videoconferencing interventions, with specific focus on strategies for implementation success and equity of access. and will be of great value to organizations that offer CHW services. International Registered Report Identifier (IRRID): DERR1-10.2196/55160 ", doi="10.2196/55160", url="https://www.researchprotocols.org/2024/1/e55160" } @Article{info:doi/10.2196/58085, author="Conderino, Sarah and Anthopolos, Rebecca and Albrecht, S. Sandra and Farley, M. Shannon and Divers, Jasmin and Titus, R. Andrea and Thorpe, E. Lorna", title="Addressing Information Biases Within Electronic Health Record Data to Improve the Examination of Epidemiologic Associations With Diabetes Prevalence Among Young Adults: Cross-Sectional Study", journal="JMIR Med Inform", year="2024", month="Oct", day="1", volume="12", pages="e58085", keywords="information bias", keywords="electronic health record", keywords="EHR", keywords="epidemiologic method", keywords="confounding factor", keywords="diabetes", keywords="epidemiology", keywords="young adult", keywords="cross-sectional study", keywords="risk factor", keywords="asthma", keywords="race", keywords="ethnicity", keywords="diabetic", keywords="diabetic adult", abstract="Background: Electronic health records (EHRs) are increasingly used for epidemiologic research to advance public health practice. However, key variables are susceptible to missing data or misclassification within EHRs, including demographic information or disease status, which could affect the estimation of disease prevalence or risk factor associations. Objective: In this paper, we applied methods from the literature on missing data and causal inference to assess whether we could mitigate information biases when estimating measures of association between potential risk factors and diabetes among a patient population of New York City young adults. Methods: We estimated the odds ratio (OR) for diabetes by race or ethnicity and asthma status using EHR data from NYU Langone Health. Methods from the missing data and causal inference literature were then applied to assess the ability to control for misclassification of health outcomes in the EHR data. We compared EHR-based associations with associations observed from 2 national health surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health and Nutrition Examination Survey, representing traditional public health surveillance systems. Results: Observed EHR-based associations between race or ethnicity and diabetes were comparable to health survey-based estimates, but the association between asthma and diabetes was significantly overestimated (OREHR 3.01, 95\% CI 2.86-3.18 vs ORBRFSS 1.23, 95\% CI 1.09-1.40). Missing data and causal inference methods reduced information biases in these estimates, yielding relative differences from traditional estimates below 50\% (ORMissingData 1.79, 95\% CI 1.67-1.92 and ORCausal 1.42, 95\% CI 1.34-1.51). Conclusions: Findings suggest that without bias adjustment, EHR analyses may yield biased measures of association, driven in part by subgroup differences in health care use. However, applying missing data or causal inference frameworks can help control for and, importantly, characterize residual information biases in these estimates. ", doi="10.2196/58085", url="https://medinform.jmir.org/2024/1/e58085" } @Article{info:doi/10.2196/59191, author="Delaney, Tessa and Jackson, K. Jacklyn and Brown, L. Alison and Lecathelinais, Christophe and Wolfenden, Luke and Hudson, Nayerra and Young, Sarah and Groombridge, Daniel and Pinfold, Jessica and Craven, David Paul and Redman, Sinead and Wiggers, John and Kingsland, Melanie and Hayes, Margaret and Sutherland, Rachel", title="Perceived Acceptability of Technology Modalities for the Provision of Universal Child and Family Health Nursing Support in the First 6-8 Months After Birth: Cross-Sectional Study", journal="JMIR Pediatr Parent", year="2024", month="Sep", day="24", volume="7", pages="e59191", keywords="maternal", keywords="postnatal", keywords="postpartum", keywords="acceptability", keywords="technology", keywords="digital health", keywords="first 2000 days", keywords="child health", keywords="experience", keywords="experiences", keywords="attitude", keywords="attitudes", keywords="opinion", keywords="perception", keywords="perceptions", keywords="perspective", keywords="perspectives", keywords="acceptance", keywords="cross sectional", keywords="survey", keywords="surveys", keywords="questionnaire", keywords="questionnaires", keywords="pediatric", keywords="pediatrics", keywords="infant", keywords="infants", keywords="infancy", keywords="baby", keywords="babies", keywords="neonate", keywords="neonates", keywords="neonatal", keywords="newborn", keywords="newborns", keywords="nurse", keywords="nurses", keywords="nursing", abstract="Background: Child and Family Health Nursing (CFHN) services provide universal care to families during the first 2000 days (conception: 5 years) to support optimal health and developmental outcomes of children in New South Wales, Australia. The use of technology represents a promising means to encourage family engagement with CFHN services and enable universal access to evidenced-based age and stage information. Currently, there is little evidence exploring the acceptability of various models of technology-based support provided during the first 2000 days, as well as the maternal characteristics that may influence this. Objective: This study aims to describe (1) the acceptability of technology-based models of CFHN support to families in the first 6 months, and (2) the association between the acceptability of technology-based support and maternal characteristics. Methods: A cross-sectional survey was undertaken between September and November 2021 with women who were 6-8 months post partum within the Hunter New England Local Health District of New South Wales, Australia. Survey questions collected information on maternal demographics and pregnancy characteristics, perceived stress, access to CFHN services, as well as preferences and acceptability of technology-based support. Descriptive statistics were used to describe the characteristics of the sample, the proportion of women accessing CFHN services, maternal acceptability of technology-based support from CFHN services, and the appropriateness of timing of support. Multivariable logistic regression models were conducted to assess the association between maternal characteristics and the acceptability of technology-based CFHN support. Results: A total of 365 women participated in the study, most were 25 to 34 years old (n=242, 68\%), had completed tertiary level education or higher (n=250, 71\%), and were employed or on maternity leave (n=280, 78\%). Almost all (n=305, 89\%) women reported accessing CFHN services in the first 6 months following their child's birth. The majority of women (n=282-315, 82\%-92\%) ``strongly agreed or agreed'' that receiving information from CFHN via technology would be acceptable, and most (n=308) women ``strongly agreed or agreed'' with being provided information on a variety of relevant health topics. Acceptability of receiving information via websites was significantly associated with maternal employment status (P=.01). The acceptability of receiving support via telephone and email was significantly associated with maternal education level (adjusted odds ratio 2.64, 95\% CI 1.07-6.51; P=.03 and adjusted odds ratio 2.90, 95\% CI 1.20-7.00; P=.02, respectively). Maternal age was also associated with the acceptability of email support (P=.04). Conclusions: Technology-based CFHN support is generally acceptable to mothers. Maternal characteristics, including employment status, education level, and age, were found to modify the acceptability of specific technology modalities. The findings of this research should be considered when designing technology-based solutions to providing universal age and stage child health and developmental support for families during the first 2000 days. ", doi="10.2196/59191", url="https://pediatrics.jmir.org/2024/1/e59191", url="http://www.ncbi.nlm.nih.gov/pubmed/39316424" } @Article{info:doi/10.2196/54861, author="Lin, Ting-Yu and Yen, Ming-Fang Amy and Chen, Li-Sheng Sam and Hsu, Chen-Yang and Lai, Chao-Chih and Luh, Dih-Ling and Yeh, Yen-Po and Chen, Hsiu-Hsi Tony", title="Kinetics of Viral Shedding for Outbreak Surveillance of Emerging Infectious Diseases: Modeling Approach to SARS-CoV-2 Alpha and Omicron Infection", journal="JMIR Public Health Surveill", year="2024", month="Sep", day="19", volume="10", pages="e54861", keywords="COVID-19", keywords="PCR testing", keywords="Ct values", keywords="viral load", keywords="kinetics of viral shedding", keywords="emerging infectious disease", keywords="SARS-CoV-2 variants", keywords="infection surveillance", abstract="Background: Previous studies have highlighted the importance of viral shedding using cycle threshold (Ct) values obtained via reverse transcription polymerase chain reaction to understand the epidemic trajectories of SARS-CoV-2 infections. However, it is rare to elucidate the transition kinetics of Ct values from the asymptomatic or presymptomatic phase to the symptomatic phase before recovery using individual repeated Ct values. Objective: This study proposes a novel Ct-enshrined compartment model to provide a series of quantitative measures for delineating the full trajectories of the dynamics of viral load from infection until recovery. Methods: This Ct-enshrined compartment model was constructed by leveraging Ct-classified states within and between presymptomatic and symptomatic compartments before recovery or death among people with infections. A series of recovery indices were developed to assess the net kinetic movement of Ct-up toward and Ct-down off recovery. The model was applied to (1) a small-scale community-acquired Alpha variant outbreak under the ``zero-COVID-19'' policy without vaccines in May 2021 and (2) a large-scale community-acquired Omicron variant outbreak with high booster vaccination rates following the lifting of the ``zero-COVID-19'' policy in April 2022 in Taiwan. The model used Bayesian Markov chain Monte Carlo methods with the Metropolis-Hastings algorithm for parameter estimation. Sensitivity analyses were conducted by varying Ct cutoff values to assess the robustness of the model. Results: The kinetic indicators revealed a marked difference in viral shedding dynamics between the Alpha and Omicron variants. The Alpha variant exhibited slower viral shedding and lower recovery rates, but the Omicron variant demonstrated swifter viral shedding and higher recovery rates. Specifically, the Alpha variant showed gradual Ct-up transitions and moderate recovery rates, yielding a presymptomatic recovery index slightly higher than 1 (1.10), whereas the Omicron variant had remarkable Ct-up transitions and significantly higher asymptomatic recovery rates, resulting in a presymptomatic recovery index much higher than 1 (152.5). Sensitivity analysis confirmed the robustness of the chosen Ct values of 18 and 25 across different recovery phases. Regarding the impact of vaccination, individuals without booster vaccination had a 19\% higher presymptomatic incidence rate compared to those with booster vaccination. Breakthrough infections in boosted individuals initially showed similar Ct-up transition rates but higher rates in later stages compared to nonboosted individuals. Overall, booster vaccination improved recovery rates, particularly during the symptomatic phase, although recovery rates for persistent asymptomatic infection were similar regardless of vaccination status once the Ct level exceeded 25. Conclusions: The study provides new insights into dynamic Ct transitions, with the notable finding that Ct-up transitions toward recovery outpaced Ct-down and symptom-surfacing transitions during the presymptomatic phase. The Ct-up against Ct-down transition varies with variants and vaccination status. The proposed Ct-enshrined compartment model is useful for the surveillance of emerging infectious diseases in the future to prevent community-acquired outbreaks. ", doi="10.2196/54861", url="https://publichealth.jmir.org/2024/1/e54861" } @Article{info:doi/10.2196/46485, author="Fonseca, Martina and MacKenna, Brian and Mehrkar, Amir and and Walters, E. Caroline and Hickman, George and Pearson, Jonathan and Fisher, Louis and Inglesby, Peter and Bacon, Seb and Davy, Simon and Hulme, William and Goldacre, Ben and Koffman, Ofra and Bakhai, Minal", title="The Use of Online Consultation Systems or Remote Consulting in England Characterized Through the Primary Care Health Records of 53 Million People in the OpenSAFELY Platform: Retrospective Cohort Study", journal="JMIR Public Health Surveill", year="2024", month="Sep", day="18", volume="10", pages="e46485", keywords="online consultation system", keywords="remote monitoring", keywords="triage", keywords="primary care research", keywords="health informatics", keywords="general practice", keywords="digital primary care", keywords="electronic health record coding", keywords="OpenSAFELY", keywords="trusted research environment", abstract="Background: The National Health Service (NHS) Long Term Plan, published in 2019, committed to ensuring that every patient in England has the right to digital-first primary care by 2023-2024. The COVID-19 pandemic and infection prevention and control measures accelerated work by the NHS to enable and stimulate the use of online consultation (OC) systems across all practices for improved access to primary care. Objective: We aimed to explore general practice coding activity associated with the use of OC systems in terms of trends, COVID-19 effect, variation, and quality. Methods: With the approval of NHS England, the OpenSAFELY platform was used to query and analyze the in situ electronic health records of suppliers The Phoenix Partnership (TPP) and Egton Medical Information Systems, covering >53 million patients in >6400 practices, mainly in 2019-2020. Systematized Medical Nomenclature for Medicine--Clinical Terminology (SNOMED-CT) codes relevant to OC systems and written OCs were identified including eConsultation. Events were described by volumes and population rates, practice coverage, and trends before and after the COVID-19 pandemic. Variation was characterized among practices, by sociodemographics, and by clinical history of long-term conditions. Results: Overall, 3,550,762 relevant coding events were found in practices using TPP, with the code eConsultation detected in 84.56\% (2157/2551) of practices. Activity related to digital forms of interaction increased rapidly from March 2020, the onset of the pandemic; namely, in the second half of 2020, >9 monthly eConsultation coding events per 1000 registered population were registered compared to <1 a year prior. However, we found large variations among regions and practices: December 2020 saw the median practice have 0.9 coded instances per 1000 population compared to at least 36 for the highest decile of practices. On sociodemographics, the TPP cohort with OC instances, when compared (univariate analysis) to the cohort with general practitioner consultations, was more predominantly female (661,235/1,087,919, 60.78\% vs 9,172,833/17,166,765, 53.43\%), aged 18 to 40 years (349,162/1,080,589, 32.31\% vs 4,295,711/17,000,942, 25.27\%), White (730,389/1,087,919, 67.14\% vs 10,887,858/17,166,765, 63.42\%), and less deprived (167,889/1,068,887, 15.71\% vs 3,376,403/16,867,074, 20.02\%). Looking at the eConsultation code through multivariate analysis, it was more commonly recorded among patients with a history of asthma (adjusted odds ratio [aOR] 1.131, 95\% CI 1.124-1.137), depression (aOR 1.144, 95\% CI 1.138-1.151), or atrial fibrillation (aOR 1.119, 95\% CI 1.099-1.139) when compared to other patients with general practitioner consultations, adjusted for long-term conditions, age, and gender. Conclusions: We successfully queried general practice coding activity relevant to the use of OC systems, showing increased adoption and key areas of variation during the pandemic at both sociodemographic and clinical levels. The work can be expanded to support monitoring of coding quality and underlying activity. This study suggests that large-scale impact evaluation studies can be implemented within the OpenSAFELY platform, namely looking at patient outcomes. ", doi="10.2196/46485", url="https://publichealth.jmir.org/2024/1/e46485", url="http://www.ncbi.nlm.nih.gov/pubmed/39292500" } @Article{info:doi/10.2196/54269, author="Jahnel, Tina and Pan, Chen-Chia and Pedros Barnils, N{\'u}ria and Muellmann, Saskia and Freye, Merle and Dassow, Hans-Henrik and Lange, Oliver and Reinschluessel, V. Anke and Rogowski, Wolf and Gerhardus, Ansgar", title="Developing and Evaluating Digital Public Health Interventions Using the Digital Public Health Framework DigiPHrame: A Framework Development Study", journal="J Med Internet Res", year="2024", month="Sep", day="12", volume="26", pages="e54269", keywords="digital public health", keywords="DiPH", keywords="digital health", keywords="public health", keywords="framework", keywords="development", keywords="evaluation", keywords="guidance", keywords="program evaluation", keywords="telemedicine", keywords="intervention", keywords="technological advancement", keywords="opportunity", keywords="technology", keywords="implementation", keywords="digital public health framework", keywords="DigiPHrame", keywords="scoping review", keywords="COVID-19", keywords="contact-tracing app", keywords="contact tracing", abstract="Background: Digital public health (DiPH) interventions may help us tackle substantial public health challenges and reach historically underserved populations, in addition to presenting valuable opportunities to improve and complement existing services. However, DiPH interventions are often triggered through technological advancements and opportunities rather than public health needs. To develop and evaluate interventions designed to serve public health needs, a comprehensive framework is needed that systematically covers all aspects with relevance for public health. This includes considering the complexity of the technology, the context in which the technology is supposed to operate, its implementation, and its effects on public health, including ethical, legal, and social aspects. Objective: We aimed to develop such a DiPH framework with a comprehensive list of core principles to be considered throughout the development and evaluation process of any DiPH intervention. Methods: The resulting digital public health framework (DigiPHrame) was based on a scoping review of existing digital health and public health frameworks. After extracting all assessment criteria from these frameworks, we clustered the criteria. During a series of multidisciplinary meetings with experts from the Leibniz ScienceCampus Digital Public Health, we restructured each domain to represent the complexity of DiPH. In this paper, we used a COVID-19 contact--tracing app as a use case to illustrate how DigiPHrame may be applied to assess DiPH interventions. Results: The current version of DigiPHrame consists of 182 questions nested under 12 domains. Domain 1 describes the current status of health needs and existing interventions; domains 2 and 3, the DiPH technology under assessment and aspects related to human-computer interaction, respectively; domains 4 and 5, structural and process aspects, respectively; and domains 6-12, contextual conditions and the outcomes of the DiPH intervention from broad perspectives. In the CWA use case, a number of questions relevant during its development but also important for assessors once the CWA was available were highlighted. Conclusions: DigiPHrame is a comprehensive framework for the development and assessment of digital technologies designed for public health purposes. It is a living framework and will, therefore, be updated regularly and as new public health needs and technological advancements emerge. ", doi="10.2196/54269", url="https://www.jmir.org/2024/1/e54269" } @Article{info:doi/10.2196/54750, author="Sanjak, S. Jaleal and McAuley, M. Erin and Raybern, Justin and Pinkham, Richard and Tarnowski, Jacob and Miko, Nicole and Rasmussen, Bridgette and Manalo, J. Christian and Goodson, Michael and Stamps, Blake and Necciai, Bryan and Sozhamannan, Shanmuga and Maier, J. Ezekiel", title="Wastewater Surveillance Pilot at US Military Installations: Cost Model Analysis", journal="JMIR Public Health Surveill", year="2024", month="Sep", day="6", volume="10", pages="e54750", keywords="wastewater surveillance", keywords="cost analysis", keywords="military health", keywords="public health", keywords="sanitation", keywords="sanitary", keywords="water", keywords="wastewater", keywords="surveillance", keywords="environment", keywords="environmental", keywords="cost", keywords="costs", keywords="economic", keywords="economics", keywords="finance", keywords="financial", keywords="pathogen", keywords="pathogens", keywords="biosurveillance", abstract="Background: The COVID-19 pandemic highlighted the need for pathogen surveillance systems to augment both early warning and outbreak monitoring/control efforts. Community wastewater samples provide a rapid and accurate source of environmental surveillance data to complement direct patient sampling. Due to its global presence and critical missions, the US military is a leader in global pandemic preparedness efforts. Clinical testing for COVID-19 on US Air Force (USAF) bases (AFBs) was effective but costly with respect to direct monetary costs and indirect costs due to lost time. To remain operating at peak capacity, such bases sought a more passive surveillance option and piloted wastewater surveillance (WWS) at 17 AFBs to demonstrate feasibility, safety, utility, and cost-effectiveness from May 2021 to January 2022. Objective: We model the costs of a wastewater program for pathogens of public health concern within the specific context of US military installations using assumptions based on the results of the USAF and Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense pilot program. The objective was to determine the cost of deploying WWS to all AFBs relative to clinical swab testing surveillance regimes. Methods: A WWS cost projection model was built based on subject matter expert input and actual costs incurred during the WWS pilot program at USAF AFBs. Several SARS-CoV-2 circulation scenarios were considered, and the costs of both WWS and clinical swab testing were projected. Analysis was conducted to determine the break-even point and how a reduction in swab testing could unlock funds to enable WWS to occur in parallel. Results: Our model confirmed that WWS is complementary and highly cost-effective when compared to existing alternative forms of biosurveillance. We found that the cost of WWS was between US \$10.5-\$18.5 million less expensive annually in direct costs as compared to clinical swab testing surveillance. When the indirect cost of lost work was incorporated, including lost work associated with required clinical swab testing, we estimated that over two-thirds of clinical swab testing could be maintained with no additional costs upon implementation of WWS. Conclusions: Our results support the adoption of WWS across US military installations as part of a more comprehensive and early warning system that will enable adaptive monitoring during disease outbreaks in a more cost-effective manner than swab testing alone. ", doi="10.2196/54750", url="https://publichealth.jmir.org/2024/1/e54750" } @Article{info:doi/10.2196/52759, author="Baillet, Ma{\"e}lle and Wathelet, Marielle and Lamer, Antoine and Fr{\'e}vent, Camille and Fovet, Thomas and D'Hondt, Fabien and Notredame, Charles-Edouard and Vaiva, Guillaume and G{\'e}nin, Michael", title="Association Between COVID-19 and Self-Harm: Nationwide Retrospective Ecological Spatiotemporal Study in Metropolitan France", journal="JMIR Public Health Surveill", year="2024", month="Aug", day="27", volume="10", pages="e52759", keywords="self-harm", keywords="COVID-19", keywords="spatiotemporal analysis", keywords="ecological regression", keywords="data reuse", abstract="Background: The COVID-19 pandemic has not been associated with increases in suicidal behavior at the national, regional, or county level. However, previous studies were not conducted on a finer scale or adjusted for ecological factors. Objective: Our objective was to assess the fine-scale spatiotemporal association between self-harm and COVID-19 hospitalizations, while considering ecological factors. Methods: Using the French national hospital discharge database, we extracted data on hospitalizations for self-harm of patients older than 10 years (from 2019 to 2021) or for COVID-19 (from 2020 to 2021) in metropolitan France. We first calculated monthly standardized incidence ratios (SIRs) for COVID-19 between March 2020 and December 2021, using a Besag, York, and Molli{\'e} spatiotemporal model. Next, we entered the SIRs into an ecological regression in order to test the association between hospital admissions for self-harm and those for COVID-19. Lastly, we adjusted for ecological variables with time lags of 0 to 6 months. Results: Compared with a smoothed SIR of ?1, smoothed SIRs from 1 to 3, from 3 to 4, and greater than 4 for COVID-19 hospital admissions were associated with a subsequent increase in hospital admissions for self-harm, with a time lag of 2 to 4 months, 4 months, and 6 months, respectively. Conclusions: A high SIR for hospital admissions for COVID-19 was a risk factor for hospital admission for self-harm some months after the epidemic peaks. This finding emphasizes the importance of monitoring and seeking to prevent suicide attempts outside the epidemic peak periods. ", doi="10.2196/52759", url="https://publichealth.jmir.org/2024/1/e52759" } @Article{info:doi/10.2196/47416, author="Kost, Joseph Gerald and Eng, Muyngim and Zadran, Amanullah", title="Geospatial Point-of-Care Testing Strategies for COVID-19 Resilience in Resource-Poor Settings: Rural Cambodia Field Study", journal="JMIR Public Health Surveill", year="2024", month="Aug", day="27", volume="10", pages="e47416", keywords="Cambodia", keywords="COVID-19", keywords="diagnostic portals", keywords="mobile-testing van and clinic", keywords="molecular diagnostics", keywords="point-of-care testing", keywords="POCT", keywords="public health resilience", keywords="rapid antigen test", keywords="RAgT", keywords="SARS-CoV-2", keywords="Solano and Yolo counties", keywords="California", abstract="Background: Point-of-care testing (POCT) generates intrinsically fast, inherently spatial, and immediately actionable results. Lessons learned in rural Cambodia and California create a framework for planning and mobilizing POCT with telehealth interventions. Timely diagnosis can help communities assess the spread of highly infectious diseases, mitigate outbreaks, and manage risks. Objective: The aims of this study were to identify the need for POCT in Cambodian border provinces during peak COVID-19 outbreaks and to quantify geospatial gaps in access to diagnostics during community lockdowns. Methods: Data sources comprised focus groups, interactive learners, webinar participants, online contacts, academic experts, public health experts, and officials who determined diagnostic needs and priorities in rural Cambodia during peak COVID-19 outbreaks. We analyzed geographic distances and transit times to testing in border provinces and assessed a high-risk province, Banteay Meanchey, where people crossed borders daily leading to disease spread. We strategized access to rapid antigen testing and molecular diagnostics in the aforementioned province and applied mobile-testing experience among the impacted population. Results: COVID-19 outbreaks were difficult to manage in rural and isolated areas where diagnostics were insufficient to meet needs. The median transit time from border provinces (n=17) to testing sites was 73 (range 1-494) minutes, and in the high-risk Banteay Meanchey Province (n=9 districts), this transit time was 90 (range 10-150) minutes. Within border provinces, maximum versus minimum distances and access times for testing differed significantly (P<.001). Pareto plots revealed geospatial gaps in access to testing for people who are not centrally located. At the time of epidemic peaks in Southeast Asia, mathematical analyses showed that only one available rapid antigen test met the World Health Organization requirement of sensitivity >80\%. We observed that in rural Solano and Yolo counties, California, vending machines and public libraries dispensing free COVID-19 test kits 24-7 improved public access to diagnostics. Mobile-testing vans equipped with COVID-19 antigen, reverse transcription polymerase chain reaction, and multiplex influenza A/B testing proved useful for differential diagnosis, public awareness, travel certifications, and telehealth treatment. Conclusions: Rural diagnostic portals implemented in California demonstrated a feasible public health strategy for Cambodia. Automated dispensers and mobile POCT can respond to COVID-19 case surges and enhance preparedness. Point-of-need planning can enhance resilience and assure spatial justice. Public health assets should include higher-quality, lower-cost, readily accessible, and user-friendly POCT, such as self-testing for diagnosis, home molecular tests, distributed border detection for surveillance, and mobile diagnostics vans for quick telehealth treatment. High-risk settings will benefit from the synthesis of geospatially optimized POCT, automated 24-7 test access, and timely diagnosis of asymptomatic and symptomatic patients at points of need now, during new outbreaks, and in future pandemics. ", doi="10.2196/47416", url="https://publichealth.jmir.org/2024/1/e47416", url="http://www.ncbi.nlm.nih.gov/pubmed/39190459" } @Article{info:doi/10.2196/55705, author="Trettin, Bettina and Skj{\o}th, Maria Mette and Munk, Trier Nadja and Vestergaard, Tine and Nielsen, Charlotte", title="Shifting Grounds---Facilitating Self-Care in Testing for Sexually Transmitted Infections Through the Use of Self-Test Technology: Qualitative Study", journal="J Particip Med", year="2024", month="Aug", day="14", volume="16", pages="e55705", keywords="chlamydia", keywords="sexually transmitted diseases", keywords="participatory design", keywords="self-test", keywords="qualitative", keywords="Chlamydia trachomatis", keywords="lymphogranuloma venereum", keywords="participatory", keywords="STD", keywords="STDs", keywords="sexually transmitted", keywords="sexually transmitted illness", keywords="sexually transmitted illnesses", keywords="STI", keywords="STIs", keywords="participation", keywords="self-testing", keywords="screening", keywords="health screening", keywords="asymptomatic screening", keywords="testing uptake", abstract="Background: Chlamydia remains prevalent worldwide and is considered a global public health problem. However, testing rates among young sexually active people remain low. Effective clinical management relies on screening asymptomatic patients. However, attending face-to-face consultations of testing for sexually transmitted infections is associated with stigmatization and anxiety. Self-testing technology (STT) allows patients to test themselves for chlamydia and gonorrhea without the presence of health care professionals. This may result in wider access to testing and increase testing uptake. Therefore, the sexual health clinic at Odense University Hospital has designed and developed a technology that allows patients to get tested at the clinic through self-collected sampling without a face-to-face consultation. Objective: This study aimed to (1) pilot-test STT used in clinical practice and (2) investigate the experiences of patients who have completed a self-test for chlamydia and gonorrhea. Methods: The study was conducted as a qualitative study inspired by the methodology of participatory design. Ethnographic methods were applied in the feasibility study and the data analyzed were inspired by the action research spiral in iterative processes using steps, such as plan, act, observe, and reflect. The qualitative evaluation study used semistructured interviews and data were analyzed using a qualitative 3-level analytical model. Results: The findings from the feasibility study, such as lack of signposting and adequate information, led to the final modifications of the self-test technology and made it possible to implement it in clinical practice. The qualitative evaluation study found that self-testing was seen as more appealing than testing at a face-to-face consultation because it was an easy solution that both saved time and allowed for the freedom to plan the visit independently. Security was experienced when the instructions balanced between being detail-oriented while also being simple and illustrative. The anonymity and discretion contributed to preserving privacy and removed the fear of an awkward conversation or being judged by health care professionals thus leading to the reduction of intrusive feelings. Conclusions: Accessible health care services are crucial in preventing and reducing the impact of sexually transmitted infections and STT may have the potential to increase testing uptake as it takes into account some of the barriers that exist. The pilot test and evaluation have resulted in a fully functioning implementation of STT in clinical practice. ", doi="10.2196/55705", url="https://jopm.jmir.org/2024/1/e55705" } @Article{info:doi/10.2196/54556, author="Sriharan, Abi and Sekercioglu, Nigar and Mitchell, Cheryl and Senkaiahliyan, Senthujan and Hertelendy, Attila and Porter, Tracy and Banaszak-Holl, Jane", title="Leadership for AI Transformation in Health Care Organization: Scoping Review", journal="J Med Internet Res", year="2024", month="Aug", day="14", volume="26", pages="e54556", keywords="AI implementation", keywords="innovation", keywords="health care", keywords="leadership", keywords="AI", keywords="artificial intelligence", keywords="management", keywords="organization", keywords="health care organization", keywords="strategy", abstract="Background: The leaders of health care organizations are grappling with rising expenses and surging demands for health services. In response, they are increasingly embracing artificial intelligence (AI) technologies to improve patient care delivery, alleviate operational burdens, and efficiently improve health care safety and quality. Objective: In this paper, we map the current literature and synthesize insights on the role of leadership in driving AI transformation within health care organizations. Methods: We conducted a comprehensive search across several databases, including MEDLINE (via Ovid), PsycINFO (via Ovid), CINAHL (via EBSCO), Business Source Premier (via EBSCO), and Canadian Business \& Current Affairs (via ProQuest), spanning articles published from 2015 to June 2023 discussing AI transformation within the health care sector. Specifically, we focused on empirical studies with a particular emphasis on leadership. We used an inductive, thematic analysis approach to qualitatively map the evidence. The findings were reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines. Results: A comprehensive review of 2813 unique abstracts led to the retrieval of 97 full-text articles, with 22 included for detailed assessment. Our literature mapping reveals that successful AI integration within healthcare organizations requires leadership engagement across technological, strategic, operational, and organizational domains. Leaders must demonstrate a blend of technical expertise, adaptive strategies, and strong interpersonal skills to navigate the dynamic healthcare landscape shaped by complex regulatory, technological, and organizational factors. Conclusions: In conclusion, leading AI transformation in healthcare requires a multidimensional approach, with leadership across technological, strategic, operational, and organizational domains. Organizations should implement a comprehensive leadership development strategy, including targeted training and cross-functional collaboration, to equip leaders with the skills needed for AI integration. Additionally, when upskilling or recruiting AI talent, priority should be given to individuals with a strong mix of technical expertise, adaptive capacity, and interpersonal acumen, enabling them to navigate the unique complexities of the healthcare environment. ", doi="10.2196/54556", url="https://www.jmir.org/2024/1/e54556", url="http://www.ncbi.nlm.nih.gov/pubmed/39009038" } @Article{info:doi/10.2196/55657, author="Yuan, Yingchao and Liu, Chang and Guo, Moning and Xin, Zhong and Chen, Guanjie and Yang, Yue and Zheng, Jianpeng and Zang, Bai and Yang, Jinkui", title="Exploring Cancer Incidence Trends by Age and Sex Among 14.14 Million Individuals in China From 2007 to 2021: Population-Based Study", journal="JMIR Public Health Surveill", year="2024", month="Aug", day="7", volume="10", pages="e55657", keywords="cancer", keywords="incidence", keywords="trend", keywords="sex-based", keywords="women", abstract="Background: Sex is a crucial factor in the development, progression, and treatment of cancer, making it vital to examine cancer incidence trends by sex for effective prevention strategies. Objective: This study aimed to assess the incidence of cancer in China between 2007 and 2021, with a focus on sex-based trends. Methods: A population-based cancer registry comprising 14.14 million individuals was maintained between 2007 and 2021 by the Beijing Municipal Health Big Data and Policy Research Center. The age-standardized rates (ASRs) of cancers were calculated using the Segi population. The average annual percentage of change (AAPC) was evaluated using the joinpoint regression model, while the Bayesian age-period-cohort model was used to predict cancer incidence in the next 10 years. Results: From 2007 to 2021, the study included 651,342 incident patients with cancer, of whom 51.2\% (n=333,577) were women. The incidence indicated by the ASR for all cancers combined was 200.8 per 100,000 for women and 184.4 per 100,000 for men. The increase in incidence indicated by AAPC for all malignancies combined significantly increased in women between 2007 and 2021 (AAPC=3.1\%; P<.001), whereas it remained constant in men (AAPC=0.3\%; P=.30). Although the overall incidence of all cancers indicated by AAPC increased in young men (AAPC=3.2\%; P=.01), the greatest increase was observed among young women (AAPC=6.1\%; P<.001). The incidence rate ratio for cancer in women increased among subsequent younger generations compared with patients born in the 1962-1966 cohort. The ASR in women will increase 1.6-fold over the next 10 years, with women having twice the incidence rate of men by 2031. Conclusions: The rising incidence of cancer among women in China has become a growing concern, emphasizing the need for increased efforts in cancer prevention and early screening, especially among young women. ", doi="10.2196/55657", url="https://publichealth.jmir.org/2024/1/e55657" } @Article{info:doi/10.2196/52536, author="Yuan, Lei and Jiang, Qinqin and Liu, Yuqing and Liu, Yijun and Du, Maolin and Sun, Jinhai and Li, Meina", title="Decomposition Analysis of Depressive Symptom Differences Among Older Adults With Hypertension Between Urban and Rural Areas: Cross-Sectional Study", journal="JMIR Public Health Surveill", year="2024", month="Aug", day="1", volume="10", pages="e52536", keywords="depression", keywords="older", keywords="hypertension", keywords="Fairlie decomposition", keywords="China", keywords="older adult", keywords="elderly", abstract="Background: Hypertension is the most prevalent chronic disease among China's older population, which comprises a growing proportion of the overall demographic. Older individuals with chronic diseases have a higher risk of developing depressive symptoms than their healthy counterparts, as evidenced in China's older population, where patients with hypertension exhibit varying rates of depression depending on residing in urban or rural areas. Objective: This study aimed to investigate factors influencing and contributing to the disparities in depressive symptoms among older urban and rural patients with hypertension in China. Methods: We used a cross-sectional study design and derived data from the 8th Chinese Longitudinal Health Longevity Survey of 2018. The Fairlie model was applied to analyze the factors contributing to disparities in depressive symptoms between urban and rural older populations with hypertension. Results: The sample size for this study was 5210, and 12.8\% (n=669) of participants exhibited depressive symptoms. The proportions of depressive symptoms in rural and urban areas were 14.1\% (n=468) and 10.7\% (n=201), respectively. In rural areas, years of education (1-6 years: odds ratio [OR] 0.68, 95\% CI 1.10-1.21; ?7 years: OR 0.47, 95\% CI 0.24-0.94), alcohol consumption (yes: OR 0.52, 95\% CI 0.29-0.93), exercise (yes: OR 0.78, 95\% CI 0.56-1.08), and sleep duration (6.0-7.9 hours: OR 0.29, 95\% CI 0.17-0.52; 8.0-9.9 hours: OR 0.24, 95\% CI 0.13-0.43; ?10.0 hours: OR 0.22, 95\% CI 0.11-0.41) were protective factors against depressive symptoms in older adults with hypertension, while gender (female: OR 1.94, 95\% CI 1.33-2.81), self-reported income status (poor: OR 3.07, 95\% CI 2.16-4.37), and activities of daily living (ADL) dysfunction (mild: OR 1.69, 95\% CI 1.11-2.58; severe: OR 3.03, 95\% CI 1.46-6.32) were risk factors. In urban areas, age (90-99 years: OR 0.37, 95\% CI 0.16-0.81; ?100 years: OR 0.19, 95\% CI 0.06-0.66), exercise (yes: OR 0.33, 95\% CI 0.22-0.51), and sleep duration (6.0-7.9 hours: OR 0.27, 95\% CI 0.10-0.71; 8.0-9.9 hours: OR 0.16, 95\% CI 0.06-0.44; ?10.0 hours: OR 0.18, 95\% CI 0.06-0.57) were protective factors, while years of education (1-6 years: OR 1.91, 95\% CI 1.05-3.49), self-reported income status (poor: OR 2.94, 95\% CI 1.43-6.08), and ADL dysfunction (mild: OR 2.38, 95\% CI 1.39-4.06; severe: OR 3.26, 95\% CI 1.21-8.76) were risk factors. The Fairlie model revealed that 91.61\% of differences in depressive symptoms could be explained by covariates, including years of education (contribution 63.1\%), self-reported income status (contribution 13.2\%), exercise (contribution 45.7\%), sleep duration (contribution 20.8\%), ADL dysfunction (contribution ?9.6\%), and comorbidities (contribution ?22.9\%). Conclusions: Older patients with hypertension in rural areas had more depressive symptoms than their counterparts residing in urban areas, which could be explained by years of education, self-reported income status, exercise, sleep duration, ADL dysfunction, and comorbidities. Factors influencing depressive symptoms had similarities regarding exercise, sleep duration, self-reported income status, and ADL dysfunction as well as differences regarding age, gender, years of education, and alcohol consumption. ", doi="10.2196/52536", url="https://publichealth.jmir.org/2024/1/e52536" } @Article{info:doi/10.2196/50355, author="Han Sr, Wei and Li 2nd, Yuanting and Chen 3rd, Changgen and Huang, Danni and Wang, Junchao and Li, Xiang and Ji, Zhongliang and Li, Qin and Li, Zhuang", title="5G Key Technologies for Helicopter Aviation Medical Rescue", journal="J Med Internet Res", year="2024", month="Aug", day="1", volume="26", pages="e50355", keywords="low airspace", keywords="helicopters", keywords="medical aid", keywords="5G technology", keywords="aeronautical engineering", doi="10.2196/50355", url="https://www.jmir.org/2024/1/e50355" } @Article{info:doi/10.2196/52019, author="Shi, Yulin and Wang, Baohua and Zhao, Jian and Wang, Chunping and Li, Ning and Chen, Min and Wan, Xia", title="Summary Measure of Health-Related Quality of Life and Its Related Factors Based on the Chinese Version of the Core Healthy Days Measures: Cross-Sectional Study", journal="JMIR Public Health Surveill", year="2024", month="Jul", day="31", volume="10", pages="e52019", keywords="health-related quality of life", keywords="Healthy Days", keywords="summary measure", keywords="health status indicators", keywords="exploratory factor analyses", keywords="confirmatory factor analyses", abstract="Background: The core Healthy Days measures were used to track the population-level health status in the China Chronic Disease and Risk Factor Surveillance; however, they were not easily combined to create a summary of the overall health-related quality of life (HRQOL), limiting this indicator's use. Objective: This study aims to develop a summary score based on the Chinese version of the core Healthy Days measures (HRQOL-5) and apply it to estimate HRQOL and its determinants in a Chinese population. Methods: From November 2018 to May 2019, a multistage stratified cluster survey was conducted to examine population health status and behavioral risk factors among the resident population older than 15 years in Weifang City, Shandong Province, China. Both exploratory factor analyses and confirmatory factor analyses were performed to reveal the underlying latent construct of HRQOL-5 and then to quantify the overall HRQOL by calculating its summary score. Tobit regression models were finally carried out to identify the influencing factors of the summary score. Results: A total of 26,269 participants (male: n=13,571, 51.7\%; mean age 55.9, SD 14.9 years) were included in this study. A total of 71\% (n=18,663) of respondents reported that they had excellent or very good general health. One summary factor was extracted to capture overall HRQOL using exploratory factor analysis. The confirmatory factor analysis further confirmed this one-factor model (Tucker-Lewis index, comparative fit index, and goodness-of-fit index >0.90; root mean square error of approximation 0.02). Multivariate Tobit regression analysis showed that age ($\beta$=--0.06), educational attainments (primary school: $\beta$=0.72; junior middle school: $\beta$=1.46; senior middle school or more: $\beta$=2.58), average income (?{\textyen}30,000 [US \$4200]: $\beta$=0.69), physical activity ($\beta$=0.75), alcohol use ($\beta$=0.46), self-reported disease ($\beta$=?6.36), and self-reported injury ($\beta$=--5.00) were the major influencing factors on the summary score of the HRQOL-5. Conclusions: This study constructs a summary score from the HRQOL-5, providing a comprehensive representation of population-level HRQOL. Differences in summary scores of different subpopulations may help set priorities for health planning in China to improve population HRQOL. ", doi="10.2196/52019", url="https://publichealth.jmir.org/2024/1/e52019" } @Article{info:doi/10.2196/49205, author="Knauss, Samuel and Andriamiadana, Gracia and Leitheiser, Roxane and Rampanjato, Zavaniarivo and B{\"a}rnighausen, Till and Emmrich, Valentin Julius", title="Effect of the COVID-19 Lockdown on Mobile Payments for Maternal Health: Regression Discontinuity Analysis", journal="JMIR Public Health Surveill", year="2024", month="Jul", day="30", volume="10", pages="e49205", keywords="digital health", keywords="behavioral surveillance", keywords="digital health wallet", keywords="mobile money", keywords="COVID-19", keywords="health financing", keywords="public health", keywords="sub-Saharan Africa", abstract="Background: The COVID-19 pandemic resulted in the unprecedented popularity of digital financial services for contactless payments and government cash transfer programs to mitigate the economic effects of the pandemic. The effect of the pandemic on the use of digital financial services for health in low- and middle-income countries, however, is poorly understood. Objective: This study aimed to assess the effect of the first COVID-19 lockdown on the use of a mobile maternal health wallet, with a particular focus on delineating the age-dependent differential effects, and draw conclusions on the effect of lockdown measures on the use of digital health services. Methods: We analyzed 819,840 person-days of health wallet use data from 3416 women who used health care at 25 public sector primary care facilities and 4 hospitals in Antananarivo, Madagascar, between January 1 and August 27, 2020. We collected data on savings, payments, and voucher use at the point of care. To estimate the effects of the first COVID-19 lockdown in Madagascar, we used regression discontinuity analysis around the starting day of the first COVID-19 lockdown on March 23, 2020. We determined the bandwidth using a data-driven method for unbiased bandwidth selection and used modified Poisson regression for binary variables to estimate risk ratios as lockdown effect sizes. Results: We recorded 3719 saving events, 1572 payment events, and 3144 use events of electronic vouchers. The first COVID-19 lockdown in Madagascar reduced mobile money savings by 58.5\% (P<.001), payments by 45.8\% (P<.001), and voucher use by 49.6\% (P<.001). Voucher use recovered to the extrapolated prelockdown counterfactual after 214 days, while savings and payments did not cross the extrapolated prelockdown counterfactual. The recovery duration after the lockdown differed by age group. Women aged >30 years recovered substantially faster, returning to prelockdown rates after 34, 226, and 77 days for savings, payments, and voucher use, respectively. Younger women aged <25 years did not return to baseline values. The results remained robust in sensitivity analyses using {\textpm}20 days of the optimal bandwidth. Conclusions: The COVID-19 lockdown greatly reduced the use of mobile money in the health sector, affecting savings, payments, and voucher use. Savings were the most significantly reduced, implying that the lockdown affected women's expectations of future health care use. Declines in payments and voucher use indicated decreased actual health care use caused by the lockdown. These effects are crucial since many maternal and child health care services cannot be delayed, as the potential benefits will be lost or diminished. To mitigate the adverse impacts of lockdowns on maternal health service use, digital health services could be leveraged to provide access to telemedicine and enhance user communication with clear information on available health care access options and adherence to safety protocols. ", doi="10.2196/49205", url="https://publichealth.jmir.org/2024/1/e49205", url="http://www.ncbi.nlm.nih.gov/pubmed/39078698" } @Article{info:doi/10.2196/54064, author="Bhawra, Jasmin and Elsahli, Nadine and Patel, Jamin", title="Applying Digital Technology to Understand Human Experiences of Climate Change Impacts on Food Security and Mental Health: Scoping Review", journal="JMIR Public Health Surveill", year="2024", month="Jul", day="23", volume="10", pages="e54064", keywords="climate change", keywords="digital health", keywords="ecoanxiety", keywords="environmental hazards", keywords="food security", keywords="mental health", keywords="scoping review", keywords="smartphone apps", keywords="digital apps", keywords="mobile health", keywords="mobile phone", abstract="Background: The global impact of climate change ranges from intense heatwaves to extreme weather events that endanger entire ecosystems and people's way of life. Adverse climate change events place undue stress on food and health systems, with consequences for human food security and mental health status. Ubiquitous digital devices, such as smartphones, have the potential to manage existing and emerging climate-related crises, given their ability to enable rapid response, instant communication, and knowledge sharing. Objective: This scoping review aimed to identify digital apps being used to capture or address climate change impacts on food security and mental health to inform the development of a digital citizen science initiative. Methods: A scoping review was conducted using 3 peer-reviewed databases (PubMed, IEEE Xplore, and Web of Science) and manual gray literature searches of relevant organizational (ie, governmental and nonprofit) websites to identify articles and reports published between January 2012 and July 2023. Three separate searches were conducted in each database to identify digital apps focused on climate change and (1) food security, (2) mental health, and (3) food security and mental health. Two reviewers conducted initial screening, with a third reviewer resolving any discrepancies. Articles focused on climate change impacts on wildlife or agriculture (ie, not human food security) were excluded. Full-text screening was conducted for shortlisted articles, and a final data abstraction table was generated, summarizing key app features, contextual factors, and participant involvement. Results: From the 656 records screened, 14 digital apps met the inclusion criteria. The food security apps (n=7, 50\%) aimed to capture traditional knowledge to preserve food systems, conduct food security assessments, and aid users in decreasing food insecurity risk. The mental health apps (n=7, 50\%) assessed climate change--related stress and provided users with coping strategies following adverse weather events. No digital apps examined the intersection of climate change, food security, and mental health. Key app features included user-to-user communication (n=5, 36\%), knowledge databases (n=5, 36\%), data collection and analysis (n=3, 21\%), gamification (n=1, 7\%), and educational resources (n=2, 14\%) to address climate change impacts on food security or mental health. In total, 3 approaches to participant involvement were used across studies, including contributory (n=1, 7\%), collaborative (n=1, 7\%), and cocreative (n=1, 7\%) approaches, to ensure the relevance and use of digital apps. Conclusions: Most digital apps identified provided a service to citizens to either prevent adverse climate change--related health impacts or manage these effects following an acute event or a natural disaster. The capacity of ubiquitous digital tools to enable near real-time communication, the involvement of various stakeholder groups, and their ability to share relevant educational resources in a timely manner are important for developing tailored climate change adaptation and mitigation strategies across jurisdictions. ", doi="10.2196/54064", url="https://publichealth.jmir.org/2024/1/e54064" } @Article{info:doi/10.2196/48259, author="Gu, Wenjun and Wang, Jinhua and Zhang, Yunqi and Liang, Shaolin and Ai, Zisheng and Li, Jiyu", title="Evolution of Digital Health and Exploration of Patented Technologies (2017-2021): Bibliometric Analysis", journal="Interact J Med Res", year="2024", month="Jul", day="11", volume="13", pages="e48259", keywords="technology trends", keywords="digital health", keywords="patent", keywords="bibliometric analysis", keywords="CiteSpace5.1R8", abstract="Background: The significant impact of digital health emerged prominently during the COVID-19 pandemic. Despite this, there is a paucity of bibliometric analyses focusing on technologies within the field of digital health patents. Patents offer a wealth of insights into technologies, commercial prospects, and competitive landscapes, often undisclosed in other publications. Given the rapid evolution of the digital health industry, safeguarding algorithms, software, and advanced surgical devices through patent systems is imperative. The patent system simultaneously acts as a valuable repository of technological knowledge, accessible to researchers. This accessibility facilitates the enhancement of existing technologies and the advancement of medical equipment, ultimately contributing to public health improvement and meeting public demands. Objective: The primary objective of this study is to gain a more profound understanding of technology hotspots and development trends within the field of digital health. Methods: Using a bibliometric analysis methodology, we assessed the global technological output reflected in patents on digital health published between 2017 and 2021. Using Citespace5.1R8 and Excel 2016, we conducted bibliometric visualization and comparative analyses of key metrics, including national contributions, institutional affiliations, inventor profiles, and technology topics. Results: A total of 15,763 digital health patents were identified as published between 2017 and 2021. The China National Intellectual Property Administration secured the top position with 7253 published patents, whereas Koninklijke Philips emerged as the leading institution with 329 patents. Notably, Assaf Govari emerged as the most prolific inventor. Technology hot spots encompassed categories such as ``Medical Equipment and Information Systems,'' ``Image Analysis,'' and ``Electrical Diagnosis,'' classified by Derwent Manual Code. A patent related to the technique of receiving and transmitting data through microchips garnered the highest citation, attributed to the patentee Covidien LP. Conclusions: The trajectory of digital health patents has been growing since 2017, primarily propelled by China, the United States, and Japan. Applications in health interventions and enhancements in surgical devices represent the predominant scenarios for digital health technology. Algorithms emerged as the pivotal technologies protected by patents, whereas techniques related to data transfer, storage, and exchange in the digital health domain are anticipated to be focal points in forthcoming basic research. ", doi="10.2196/48259", url="https://www.i-jmr.org/2024/1/e48259" } @Article{info:doi/10.2196/49127, author="Fraser, F. Hamish S. and Mugisha, Michael and Bacher, Ian and Ngenzi, Lune Joseph and Seebregts, Christopher and Umubyeyi, Aline and Condo, Jeanine", title="Factors Influencing Data Quality in Electronic Health Record Systems in 50 Health Facilities in Rwanda and the Role of Clinical Alerts: Cross-Sectional Observational Study", journal="JMIR Public Health Surveill", year="2024", month="Jul", day="3", volume="10", pages="e49127", keywords="data quality", keywords="electronic health record", keywords="EHR", keywords="electronic medical record", keywords="EMR", keywords="HIV", keywords="Rwanda", abstract="Background: Electronic health records (EHRs) play an increasingly important role in delivering HIV care in low- and middle-income countries. The data collected are used for direct clinical care, quality improvement, program monitoring, public health interventions, and research. Despite widespread EHR use for HIV care in African countries, challenges remain, especially in collecting high-quality data. Objective: We aimed to assess data completeness, accuracy, and timeliness compared to paper-based records, and factors influencing data quality in a large-scale EHR deployment in Rwanda. Methods: We randomly selected 50 health facilities (HFs) using OpenMRS, an EHR system that supports HIV care in Rwanda, and performed a data quality evaluation. All HFs were part of a larger randomized controlled trial, with 25 HFs receiving an enhanced EHR with clinical decision support systems. Trained data collectors visited the 50 HFs to collect 28 variables from the paper charts and the EHR system using the Open Data Kit app. We measured data completeness, timeliness, and the degree of matching of the data in paper and EHR records, and calculated concordance scores. Factors potentially affecting data quality were drawn from a previous survey of users in the 50 HFs. Results: We randomly selected 3467 patient records, reviewing both paper and EHR copies (194,152 total data items). Data completeness was >85\% threshold for all data elements except viral load (VL) results, second-line, and third-line drug regimens. Matching scores for data values were close to or >85\% threshold, except for dates, particularly for drug pickups and VL. The mean data concordance was 10.2 (SD 1.28) for 15 (68\%) variables. HF and user factors (eg, years of EHR use, technology experience, EHR availability and uptime, and intervention status) were tested for correlation with data quality measures. EHR system availability and uptime was positively correlated with concordance, whereas users' experience with technology was negatively correlated with concordance. The alerts for missing VL results implemented at 11 intervention HFs showed clear evidence of improving timeliness and completeness of initially low matching of VL results in the EHRs and paper records (11.9\%-26.7\%; P<.001). Similar effects were seen on the completeness of the recording of medication pickups (18.7\%-32.6\%; P<.001). Conclusions: The EHR records in the 50 HFs generally had high levels of completeness except for VL results. Matching results were close to or >85\% threshold for nondate variables. Higher EHR stability and uptime, and alerts for entering VL both strongly improved data quality. Most data were considered fit for purpose, but more regular data quality assessments, training, and technical improvements in EHR forms, data reports, and alerts are recommended. The application of quality improvement techniques described in this study should benefit a wide range of HFs and data uses for clinical care, public health, and disease surveillance. ", doi="10.2196/49127", url="https://publichealth.jmir.org/2024/1/e49127" } @Article{info:doi/10.2196/52773, author="Wang, JianLi and Kharrat, Zadeh Fatemeh Gholi and Gari{\'e}py, Genevi{\`e}ve and Gagn{\'e}, Christian and Pelletier, Jean-Fran{\c{c}}ois and Massamba, Kubuta Victoria and L{\'e}vesque, Pascale and Mohammed, Mada and Lesage, Alain", title="Predicting the Population Risk of Suicide Using Routinely Collected Health Administrative Data in Quebec, Canada: Model-Based Synthetic Estimation Study", journal="JMIR Public Health Surveill", year="2024", month="Jun", day="28", volume="10", pages="e52773", keywords="population risk prediction", keywords="case-control", keywords="development", keywords="validation", keywords="health administrative data", keywords="suicide", keywords="depression", keywords="anxiety", keywords="Quebec", keywords="Canada", keywords="mental health", keywords="suicide prevention", keywords="prevention", keywords="adolescent", keywords="adolescents", keywords="teen", keywords="teens", keywords="teenager", keywords="teenagers", keywords="male", keywords="female", abstract="Background: Suicide is a significant public health issue. Many risk prediction tools have been developed to estimate an individual's risk of suicide. Risk prediction models can go beyond individual risk assessment; one important application of risk prediction models is population health planning. Suicide is a result of the interaction among the risk and protective factors at the individual, health care system, and community levels. Thus, policy and decision makers can play an important role in suicide prevention. However, few prediction models for the population risk of suicide have been developed. Objective: This study aims to develop and validate prediction models for the population risk of suicide using health administrative data, considering individual-, health system--, and community-level predictors. Methods: We used a case-control study design to develop sex-specific risk prediction models for suicide, using the health administrative data in Quebec, Canada. The training data included all suicide cases (n=8899) that occurred from January 1, 2002, to December 31, 2010. The control group was a 1\% random sample of living individuals in each year between January 1, 2002, and December 31, 2010 (n=645,590). Logistic regression was used to develop the prediction models based on individual-, health care system--, and community-level predictors. The developed model was converted into synthetic estimation models, which concerted the individual-level predictors into community-level predictors. The synthetic estimation models were directly applied to the validation data from January 1, 2011, to December 31, 2019. We assessed the performance of the synthetic estimation models with four indicators: the agreement between predicted and observed proportions of suicide, mean average error, root mean square error, and the proportion of correctly identified high-risk regions. Results: The sex-specific models based on individual data had good discrimination (male model: C=0.79; female model: C=0.85) and calibration (Brier score for male model 0.01; Brier score for female model 0.005). With the regression-based synthetic models applied in the validation data, the absolute differences between the synthetic risk estimates and observed suicide risk ranged from 0\% to 0.001\%. The root mean square errors were under 0.2. The synthetic estimation model for males correctly predicted 4 of 5 high-risk regions in 8 years, and the model for females correctly predicted 4 of 5 high-risk regions in 5 years. Conclusions: Using linked health administrative databases, this study demonstrated the feasibility and the validity of developing prediction models for the population risk of suicide, incorporating individual-, health system--, and community-level variables. Synthetic estimation models built on routinely collected health administrative data can accurately predict the population risk of suicide. This effort can be enhanced by timely access to other critical information at the population level. ", doi="10.2196/52773", url="https://publichealth.jmir.org/2024/1/e52773" } @Article{info:doi/10.2196/58565, author="Denis, Fabrice and Le Goff, Florian and Desbois, Madhu and Gepner, Agnes and Feliciano, Guillaume and Silber, Denise and Zeitoun, Jean-David and Assuied, Peretz Guedalia", title="Early Detection of 5 Neurodevelopmental Disorders of Children and Prevention of Postnatal Depression With a Mobile Health App: Observational Cross-Sectional Study", journal="JMIR Public Health Surveill", year="2024", month="Jun", day="18", volume="10", pages="e58565", keywords="mobile phone", keywords="pediatric", keywords="infant", keywords="baby", keywords="neonate", keywords="newborn", keywords="toddler", keywords="child", keywords="early detection", keywords="app", keywords="application", keywords="screening", keywords="algorithm", keywords="NDD", keywords="neurodevelopmental disorder", keywords="autism", keywords="ASD", keywords="autism spectrum disorder", keywords="attention deficit/hyperactivity disorder", keywords="ADHD", keywords="attention deficit", keywords="PND", keywords="postnatal depression", keywords="mHealth", keywords="mobile health", keywords="real-world study", keywords="smartphone", keywords="dyspraxia", keywords="delayed", keywords="language", keywords="dyslexia", keywords="incidence", keywords="prevalence", abstract="Background: Delay in the diagnosis of neurodevelopmental disorders (NDDs) in toddlers and postnatal depression (PND) is a major public health issue. In both cases, early intervention is crucial but too rarely implemented in practice. Objective: Our goal was to determine if a dedicated mobile app can improve screening of 5 NDDs (autism spectrum disorder [ASD], language delay, dyspraxia, dyslexia, and attention-deficit/hyperactivity disorder [ADHD]) and reduce PND incidence. Methods: We performed an observational, cross-sectional, data-based study in a population of young parents in France with at least 1 child aged <10 years at the time of inclusion and regularly using Malo, an ``all-in-one'' multidomain digital health record electronic patient-reported outcome (PRO) app for smartphones. We included the first 50,000 users matching the criteria and agreeing to participate between May 1, 2022, and February 8, 2024. Parents received periodic questionnaires assessing skills in neurodevelopment domains via the app. Mothers accessed a support program to prevent PND and were requested to answer regular PND questionnaires. When any PROs matched predefined criteria, an in-app recommendation was sent to book an appointment with a family physician or pediatrician. The main outcomes were the median age of the infant at the time of notification for possible NDD and the incidence of PND detection after childbirth. One secondary outcome was the relevance of the NDD notification by consultation as assessed by health professionals. Results: Among 55,618 children median age 4 months (IQR 9), 439 (0.8\%) had at least 1 disorder for which consultation was critically necessary. The median ages of notification for probable ASD, language delay, dyspraxia, dyslexia, and ADHD were 32.5 (IQR 12.8), 16 (IQR 13), 36 (IQR 22.5), 80 (IQR 5), and 61 (IQR 15.5) months, respectively. The rate of probable ADHD, ASD, dyslexia, language delay, and dyspraxia in the population of children of the age included between the detection limits of each alert was 1.48\%, 0.21\%, 1.52\%, 0.91\%, and 0.37\%, respectively. Sensitivity of alert notifications for suspected NDDs as assessed by the physicians was 78.6\% and specificity was 98.2\%. Among 8243 mothers who completed a PND questionnaire, highly probable PND was detected in 938 (11.4\%), corresponding to a reduction of --31\% versus our previous study without a support program. Suspected PND was detected a median 96 days (IQR 86) after childbirth. Among 130 users who filled in the satisfaction survey, 99.2\% (129/130) found the app easy to use and 70\% (91/130) reported that the app improved follow-up of their child. The app was rated 4.8/5 on Apple's App Store. Conclusions: Algorithm-based early alerts suggesting NDDs were highly specific with good sensitivity as assessed by real-life practitioners. Early detection of 5 NDDs and PNDs was efficient and led to a possible 31\% reduction in PND incidence. Trial Registration: ClinicalTrials.gov NCT06301087; https://www.clinicaltrials.gov/study/NCT06301087 ", doi="10.2196/58565", url="https://publichealth.jmir.org/2024/1/e58565", url="http://www.ncbi.nlm.nih.gov/pubmed/38888952" } @Article{info:doi/10.2196/48605, author="Shen, Hongxia and van der Kleij, Rianne and van der Boog, M. Paul J. and Chavannes, H. Niels", title="Developing a Tailored eHealth Self-Management Intervention for Patients With Chronic Kidney Disease in China: Intervention Mapping Approach", journal="JMIR Form Res", year="2024", month="Jun", day="13", volume="8", pages="e48605", keywords="eHealth", keywords="self-management", keywords="intervention mapping", keywords="chronic kidney disease", keywords="intervention development", keywords="mobile phone", abstract="Background: Chronic kidney disease (CKD) is a major public health concern. Adequate self-management skills are vital to reduce CKD burden, optimize patient health outcomes, and control health care expenditures. Using eHealth to support CKD self-management has the potential to promote healthy behaviors and improve health outcomes of patients with CKD. However, knowledge of the implementation of such interventions in general, and in China specifically, is still limited. Objective: This study aims to develop a tailored eHealth self-management intervention for patients with CKD in China based on the Dutch Medical Dashboard (MD) eHealth self-management intervention. Methods: We used an intervention mapping approach. In phase 1, a systematic review and 2 qualitative studies were conducted to examine the needs, beliefs, and perceptions of patients with CKD and health care professionals regarding CKD self-management and eHealth interventions. Afterward, key factors gathered from the aforementioned studies were categorized following the 5 domains of the Consolidated Framework for Implementation Research (CFIR). In phase 2, we specified program outcomes, performance objectives, determinants, theory-based methods, and practical strategies. Knowledge obtained from previous results was combined to complement core components of the MD self-management intervention and adapt them for Chinese patients with CKD. Additionally, the CFIR--Expert Recommendations for Implementing Change Matching Tool was pragmatically used to generate a list of potential implementation strategies to address the key factors influencing the implementation of eHealth CKD self-management interventions, and implementation strategies were discussed and finalized with the intervention monitoring group. Results: An overview of the CFIR domains showed the essential factors influencing the implementation of eHealth CKD self-management interventions in Chinese settings, including ``knowledge and beliefs'' in the domain ``individual characteristics,'' ``quality and advantage of eHealth intervention'' in the domain ``intervention characteristics,'' ``compatibility'' in the domain ``inner setting,'' and ``cultural context'' in the domain ``outer setting.'' To ensure the effectiveness of the Dutch MD--based self-management intervention, we did not change the core self-management intervention components of MD that underlie its effectiveness, such as self-monitoring. We identified surface-level cultural adaptations involving customizing intervention content, messages, and approaches to the observable cultural characteristics of the local population to enhance the intervention's appeal, receptivity, and feasibility, such as providing video or voice call options to support interactions with health care professionals. Furthermore, the adapted modules such as Knowledge Center and My Self-Monitoring were developed in a mobile health app. Conclusions: Our study resulted in the delivery of a culturally tailored, standardized eHealth self-management intervention for patients with CKD in China that has the potential to optimize patients' self-management skills and improve health status and quality of life. Moreover, our study's research approach and results can inform future research on the tailoring and translation of evidence-based, eHealth self-management interventions to various contexts. Trial Registration: ClinicalTrials.gov NCT04212923; https://classic.clinicaltrials.gov/ct2/show/NCT04212923 ", doi="10.2196/48605", url="https://formative.jmir.org/2024/1/e48605", url="http://www.ncbi.nlm.nih.gov/pubmed/38869943" } @Article{info:doi/10.2196/51585, author="Gauld, Christophe and Hartley, Sarah and Micoulaud-Franchi, Jean-Arthur and Royant-Parola, Sylvie", title="Sleep Health Analysis Through Sleep Symptoms in 35,808 Individuals Across Age and Sex Differences: Comparative Symptom Network Study", journal="JMIR Public Health Surveill", year="2024", month="Jun", day="11", volume="10", pages="e51585", keywords="symptom", keywords="epidemiology", keywords="age", keywords="sex", keywords="diagnosis", keywords="network approach", keywords="sleep", keywords="sleep health", abstract="Background: Sleep health is a multidimensional construct that includes objective and subjective parameters and is influenced by individual sleep-related behaviors and sleep disorders. Symptom network analysis allows modeling of the interactions between variables, enabling both the visualization of relationships between different factors and the identification of the strength of those relationships. Given the known influence of sex and age on sleep health, network analysis can help explore sets of mutually interacting symptoms relative to these demographic variables. Objective: This study aimed to study the centrality of symptoms and compare age and sex differences regarding sleep health using a symptom network approach in a large French population that feels concerned about their sleep. Methods: Data were extracted from a questionnaire provided by the R{\'e}seau Morph{\'e}e health network. A network analysis was conducted on 39 clinical variables related to sleep disorders and sleep health. After network estimation, statistical analyses consisted of calculating inferences of centrality, robustness (ie, testifying to a sufficient effect size), predictability, and network comparison. Sleep clinical variable centralities within the networks were analyzed by both sex and age using 4 age groups (18-30, 31-45, 46-55, and >55 years), and local symptom-by-symptom correlations determined. Results: Data of 35,808 participants were obtained. The mean age was 42.7 (SD 15.7) years, and 24,964 (69.7\%) were women. Overall, there were no significant differences in the structure of the symptom networks between sexes or age groups. The most central symptoms across all groups were nonrestorative sleep and excessive daytime sleepiness. In the youngest group, additional central symptoms were chronic circadian misalignment and chronic sleep deprivation (related to sleep behaviors), particularly among women. In the oldest group, leg sensory discomfort and breath abnormality complaint were among the top 4 central symptoms. Symptoms of sleep disorders thus became more central with age than sleep behaviors. The high predictability of central nodes in one of the networks underlined its importance in influencing other nodes. Conclusions: The absence of structural difference between networks is an important finding, given the known differences in sleep between sexes and across age groups. These similarities suggest comparable interactions between clinical sleep variables across sexes and age groups and highlight the implication of common sleep and wake neural circuits and circadian rhythms in understanding sleep health. More precisely, nonrestorative sleep and excessive daytime sleepiness are central symptoms in all groups. The behavioral component is particularly central in young people and women. Sleep-related respiratory and motor symptoms are prominent in older people. These results underscore the importance of comprehensive sleep promotion and screening strategies tailored to sex and age to impact sleep health. ", doi="10.2196/51585", url="https://publichealth.jmir.org/2024/1/e51585", url="http://www.ncbi.nlm.nih.gov/pubmed/38861716" } @Article{info:doi/10.2196/52182, author="Lee, Jun Jae and Lee, Hee Kyung", title="Optimal Systolic Blood Pressure for the Prevention of All-Cause and Cardiovascular Disease Mortality in Older Adults With Hypertension: Nationwide Population-Based Cohort Study", journal="JMIR Public Health Surveill", year="2024", month="Jun", day="11", volume="10", pages="e52182", keywords="aged", keywords="blood pressure", keywords="cardiovascular diseases", keywords="hypertension", keywords="mortality", keywords="older adults", keywords="geriatric", keywords="elderly", keywords="cardiovascular", keywords="Korea", keywords="Korean", keywords="insurance", keywords="cohort study", keywords="systolic", keywords="risk", keywords="aging", keywords="health outcome", abstract="Background: Target systolic blood pressure (SBP) levels for older adults with hypertension vary across countries, leading to challenges in determining the appropriate SBP level. Objective: This study aims to identify the optimal SBP level for minimizing all-cause and cardiovascular disease (CVD) mortality in older Korean adults with hypertension. Methods: This retrospective cohort study used data from the National Health Insurance Service database. We included older adults aged 65 years or older who were newly diagnosed with hypertension and underwent a National Health Insurance Service health checkup in 2003-2004. We excluded patients who had a history of hypertension or CVD, were not prescribed medication for hypertension, had missing blood pressure or any other covariate values, and had fewer than 2 health checkups during the follow-up period until 2020. We categorized the average SBP levels into 6 categories in 10 mm Hg increments, from <120 mm Hg to ?160 mm Hg; 130-139 mm Hg was the reference range. Cox proportional hazards models were used to examine the relationship between SBP and all-cause and CVD mortalities, and subgroup analysis was conducted by age group (65-74 years and 75 years or older). Results: A total of 68,901 older adults newly diagnosed with hypertension were included in this study. During the follow-up period, 32,588 (47.3\%) participants had all-cause mortality and 4273 (6.2\%) had CVD mortality. Compared to older adults with SBP within the range of 130-139 mm Hg, individuals who fell into the other SBP categories, excluding those with SBP 120-129 mm Hg, showed significantly higher all-cause and CVD mortality. Subgroup analysis showed that older adults aged 65-74 years had higher all-cause and CVD mortality rates according to SBP categories than those aged 75 years or older. Conclusions: The SBP levels within the range of 120-139 mm Hg were associated with the lowest all-cause and CVD mortality rates among older Korean adults with hypertension. It is recommended to reduce SBP to <140 mm Hg, with 120 mm Hg as the minimum value for SBP, for older Korean adults with hypertension. Additionally, stricter SBP management is required for adults aged 65-74 years. ", doi="10.2196/52182", url="https://publichealth.jmir.org/2024/1/e52182", url="http://www.ncbi.nlm.nih.gov/pubmed/38861307" } @Article{info:doi/10.2196/48043, author="Chen, Wenxiu and Zhang, Bin and Wang, Chen and An, Wei and Guruge, Kumudumali Shashika and Chui, Ho-kwong and Yang, Min", title="A Metric of Societal Burden Based on Virus Succession to Determine Economic Losses and Health Benefits of China's Lockdown Policies: Model Development and Validation", journal="JMIR Public Health Surveill", year="2024", month="Jun", day="7", volume="10", pages="e48043", keywords="SARS-CoV-2", keywords="lockdown", keywords="virus succession", keywords="benefit", keywords="loss", keywords="fatality rate", keywords="pandemic", keywords="blanket lockdown", keywords="partial lockdown", abstract="Background: The COVID-19 pandemic had a profound impact on the global health system and economic structure. Although the implementation of lockdown measures achieved notable success in curbing the spread of the pandemic, it concurrently incurred substantial socioeconomic costs. Objective: The objective of this study was to delineate an equilibrium between the economic losses and health benefits of lockdown measures, with the aim of identifying the optimal boundary conditions for implementing these measures at various pandemic phases. Methods: This study used a model to estimate the half-lives of the observed case fatality rates of different strains. It was based on global infection and death data collected by the World Health Organization and strain sequence time series data provided by Nextstrain. The connection between the health benefits and economic losses brought by lockdown measures was established through the calculation of disability-adjusted life years. Taking China's city lockdowns as an example, this study determined the cost-benefit boundary of various lockdown measures during the evolution of COVID-19. Results: The study reveals a direct proportionality between economic losses due to lockdowns and the observed case fatality rates of virus strains, a relationship that holds true irrespective of population size or per capita economic output. As SARS-CoV-2 strains evolve and population immunity shifts, there has been a notable decrease in the observed case fatality rate over time, exhibiting a half-life of roughly 8 months. This decline in fatality rates may offset the health benefits of maintaining unchanged lockdown measures, given that the resultant economic losses might exceed the health benefits. Conclusions: The initial enforcement of lockdown in Wuhan led to significant health benefits. However, with the decline in the observed case fatality rate of the virus strains, the economic losses increasingly outweighed the health benefits. Consequently, it is essential to consistently refine and enhance lockdown strategies in accordance with the evolving fatality and infection rates of different virus strains, thereby optimizing outcomes in anticipation of future pandemics. ", doi="10.2196/48043", url="https://publichealth.jmir.org/2024/1/e48043", url="http://www.ncbi.nlm.nih.gov/pubmed/38848555" } @Article{info:doi/10.2196/56593, author="He, Yan and Tang, Ying and Hua, Qun and Li, Xin and Ge, You and Liu, Yangyang and Tang, Rong and Tian, Ye and Li, Wei", title="Exploring Dynamic Changes in HIV-1 Molecular Transmission Networks and Key Influencing Factors: Cross-Sectional Study", journal="JMIR Public Health Surveill", year="2024", month="May", day="29", volume="10", pages="e56593", keywords="HIV", keywords="dynamic", keywords="molecular transmission network", keywords="influence factors", keywords="HIV-1", keywords="molecular network", keywords="real-time analysis", keywords="transmission", keywords="Nanjing", keywords="infection", keywords="gene distance", keywords="heterosexual", keywords="homosexual", keywords="dynamic alteration", keywords="dynamic alterations", keywords="risk factor", abstract="Background: The HIV-1 molecular network is an innovative tool, using gene sequences to understand transmission attributes and complementing social and sexual network studies. While previous research focused on static network characteristics, recent studies' emphasis on dynamic features enhances our understanding of real-time changes, offering insights for targeted interventions and efficient allocation of public health resources. Objective: This study aims to identify the dynamic changes occurring in HIV-1 molecular transmission networks and analyze the primary influencing factors driving the dynamics of HIV-1 molecular networks. Methods: We analyzed and compared the dynamic changes in the molecular network over a specific time period between the baseline and observed end point. The primary factors influencing the dynamic changes in the HIV-1 molecular network were identified through univariate analysis and multivariate analysis. Results: A total of 955 HIV-1 polymerase fragments were successfully amplified from 1013 specimens; CRF01\_AE and CRF07\_BC were the predominant subtypes, accounting for 40.8\% (n=390) and 33.6\% (n=321) of the specimens, respectively. Through the analysis and comparison of the basic and terminal molecular networks, it was discovered that 144 sequences constituted static molecular networks, and 487 sequences contributed to the formation of dynamic molecular networks. The findings of the multivariate analysis indicated that the factors occupation as a student, floating population, Han ethnicity, engagement in occasional or multiple sexual partnerships, participation in anal sex, and being single were independent risk factors for the dynamic changes observed in the HIV-1 molecular network, and the odds ratio (OR; 95\% CIs) values were 2.63 (1.54-4.47), 1.83 (1.17-2.84), 2.91 (1.09-7.79), 1.75 (1.06-2.90), 4.12 (2.48-6.87), 5.58 (2.43-12.80), and 2.10 (1.25-3.54), respectively. Heterosexuality and homosexuality seem to exhibit protective effects when compared to bisexuality, with OR values of 0.12 (95\% CI 0.05-0.32) and 0.26 (95\% CI 0.11-0.64), respectively. Additionally, the National Eight-Item score and sex education experience were also identified as protective factors against dynamic changes in the HIV-1 molecular network, with OR values of 0.12 (95\% CI 0.05-0.32) and 0.26 (95\% CI 0.11-0.64), respectively. Conclusions: The HIV-1 molecular network analysis showed 144 sequences in static networks and 487 in dynamic networks. Multivariate analysis revealed that occupation as a student, floating population, Han ethnicity, and risky sexual behavior were independent risk factors for dynamic changes, while heterosexuality and homosexuality were protective compared to bisexuality. A higher National Eight-Item score and sex education experience were also protective factors. The identification of HIV dynamic molecular networks has provided valuable insights into the characteristics of individuals undergoing dynamic alterations. These findings contribute to a better understanding of HIV-1 transmission dynamics and could inform targeted prevention strategies. ", doi="10.2196/56593", url="https://publichealth.jmir.org/2024/1/e56593", url="http://www.ncbi.nlm.nih.gov/pubmed/38810253" } @Article{info:doi/10.2196/50088, author="Maugeri, Andrea and Barchitta, Martina and Basile, Guido and Agodi, Antonella", title="Public and Research Interest in Telemedicine From 2017 to 2022: Infodemiology Study of Google Trends Data and Bibliometric Analysis of Scientific Literature", journal="J Med Internet Res", year="2024", month="May", day="16", volume="26", pages="e50088", keywords="telemedicine", keywords="eHealth", keywords="digital medicine", keywords="COVID-19", keywords="Google Trends", keywords="bibliometric", keywords="Google", keywords="data spanning", keywords="accessibility", keywords="cost reduction", keywords="cost", keywords="noncommunicable disease", keywords="mobile health", keywords="awareness", keywords="policy decision", abstract="Background: Telemedicine offers a multitude of potential advantages, such as enhanced health care accessibility, cost reduction, and improved patient outcomes. The significance of telemedicine has been underscored by the COVID-19 pandemic, as it plays a crucial role in maintaining uninterrupted care while minimizing the risk of viral exposure. However, the adoption and implementation of telemedicine have been relatively sluggish in certain areas. Assessing the level of interest in telemedicine can provide valuable insights into areas that require enhancement. Objective: The aim of this study is to provide a comprehensive analysis of the level of public and research interest in telemedicine from 2017 to 2022 and also consider any potential impact of the COVID-19 pandemic. Methods: Google Trends data were retrieved using the search topics ``telemedicine'' or ``e-health'' to assess public interest, geographic distribution, and trends through a joinpoint regression analysis. Bibliographic data from Scopus were used to chart publications referencing the terms ``telemedicine'' or ``eHealth'' (in the title, abstract, and keywords) in terms of scientific production, key countries, and prominent keywords, as well as collaboration and co-occurrence networks. Results: Worldwide, telemedicine generated higher mean public interest (relative search volume=26.3\%) compared to eHealth (relative search volume=17.6\%). Interest in telemedicine remained stable until January 2020, experienced a sudden surge (monthly percent change=95.7\%) peaking in April 2020, followed by a decline (monthly percent change=--22.7\%) until August 2020, and then returned to stability. A similar trend was noted in the public interest regarding eHealth. Chile, Australia, Canada, and the United States had the greatest public interest in telemedicine. In these countries, moderate to strong correlations were evident between Google Trends and COVID-19 data (ie, new cases, new deaths, and hospitalized patients). Examining 19,539 original medical articles in the Scopus database unveiled a substantial rise in telemedicine-related publications, showing a total increase of 201.5\% from 2017 to 2022 and an average annual growth rate of 24.7\%. The most significant surge occurred between 2019 and 2020. Notably, the majority of the publications originated from a single country, with 20.8\% involving international coauthorships. As the most productive country, the United States led a cluster that included Canada and Australia as well. European, Asian, and Latin American countries made up the remaining 3 clusters. The co-occurrence network categorized prevalent keywords into 2 clusters, the first cluster primarily focused on applying eHealth, mobile health (mHealth), or digital health to noncommunicable or chronic diseases; the second cluster was centered around the application of telemedicine and telehealth within the context of the COVID-19 pandemic. Conclusions: Our analysis of search and bibliographic data over time and across regions allows us to gauge the interest in this topic, offer evidence regarding potential applications, and pinpoint areas for additional research and awareness-raising initiatives. ", doi="10.2196/50088", url="https://www.jmir.org/2024/1/e50088", url="http://www.ncbi.nlm.nih.gov/pubmed/38753427" } @Article{info:doi/10.2196/55211, author="Haghayegh, Shahab and Gao, Chenlu and Sugg, Elizabeth and Zheng, Xi and Yang, Hui-Wen and Saxena, Richa and Rutter, K. Martin and Weedon, Michael and Ibanez, Agustin and Bennett, A. David and Li, Peng and Gao, Lei and Hu, Kun", title="Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study", journal="JMIR Public Health Surveill", year="2024", month="May", day="7", volume="10", pages="e55211", keywords="circadian rhythm", keywords="dementia", keywords="actigraphy", keywords="cognitive decline", keywords="RAR", keywords="rest-activity rhythms", keywords="cognitive impairment", abstract="Background: The relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults. Objective: We leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults. Methods: We analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease. Results: During the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95\% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95\% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95\% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95\% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95\% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95\% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged <70 and >70 years, and in non--shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase. Conclusions: Based on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults. ", doi="10.2196/55211", url="https://publichealth.jmir.org/2024/1/e55211", url="http://www.ncbi.nlm.nih.gov/pubmed/38713911" } @Article{info:doi/10.2196/46687, author="Lau, Y. Kitty and Kang, Jian and Park, Minah and Leung, Gabriel and Wu, T. Joseph and Leung, Kathy", title="Estimating the Epidemic Size of Superspreading Coronavirus Outbreaks in Real Time: Quantitative Study", journal="JMIR Public Health Surveill", year="2024", month="Feb", day="12", volume="10", pages="e46687", keywords="coronavirus", keywords="superspreading event", keywords="SSE", keywords="epidemic size", keywords="severe acute respiratory syndrome", keywords="SARS", keywords="Middle East respiratory syndrome", keywords="MERS", keywords="coronavirus disease 2019", keywords="COVID-19", abstract="Background: Novel coronaviruses have emerged and caused major epidemics and pandemics in the past 2 decades, including SARS-CoV-1, MERS-CoV, and SARS-CoV-2, which led to the current COVID-19 pandemic. These coronaviruses are marked by their potential to produce disproportionally large transmission clusters from superspreading events (SSEs). As prompt action is crucial to contain and mitigate SSEs, real-time epidemic size estimation could characterize the transmission heterogeneity and inform timely implementation of control measures. Objective: This study aimed to estimate the epidemic size of SSEs to inform effective surveillance and rapid mitigation responses. Methods: We developed a statistical framework based on back-calculation to estimate the epidemic size of ongoing coronavirus SSEs. We first validated the framework in simulated scenarios with the epidemiological characteristics of SARS, MERS, and COVID-19 SSEs. As case studies, we retrospectively applied the framework to the Amoy Gardens SARS outbreak in Hong Kong in 2003, a series of nosocomial MERS outbreaks in South Korea in 2015, and 2 COVID-19 outbreaks originating from restaurants in Hong Kong in 2020. Results: The accuracy and precision of the estimation of epidemic size of SSEs improved with longer observation time; larger SSE size; and more accurate prior information about the epidemiological characteristics, such as the distribution of the incubation period and the distribution of the onset-to-confirmation delay. By retrospectively applying the framework, we found that the 95\% credible interval of the estimates contained the true epidemic size after 37\% of cases were reported in the Amoy Garden SARS SSE in Hong Kong, 41\% to 62\% of cases were observed in the 3 nosocomial MERS SSEs in South Korea, and 76\% to 86\% of cases were confirmed in the 2 COVID-19 SSEs in Hong Kong. Conclusions: Our framework can be readily integrated into coronavirus surveillance systems to enhance situation awareness of ongoing SSEs. ", doi="10.2196/46687", url="https://publichealth.jmir.org/2024/1/e46687", url="http://www.ncbi.nlm.nih.gov/pubmed/38345850" } @Article{info:doi/10.2196/48107, author="Zhu, Dandan and Huang, Jing and Hu, Bei and Cao, Donglin and Chen, Dingqiang and Song, Xinqiang and Chen, Jialing and Zhou, Hao and Cen, Aiqun and Hou, Tieying", title="Trial of the Pluslife SARS-CoV-2 Nucleic Acid Rapid Test Kit: Prospective Cohort Study", journal="JMIR Public Health Surveill", year="2023", month="Nov", day="14", volume="9", pages="e48107", keywords="SARS-CoV-2", keywords="COVID-19", keywords="RHAM", keywords="RNase hybridization-assisted amplification", keywords="field trial", keywords="diagnosis", keywords="screening", keywords="rapid test", keywords="cohort study", keywords="detection", keywords="recruitment", keywords="infection", keywords="Pluslife", abstract="Background: In response to the SARS-CoV-2 epidemic, a convenient, rapid, and sensitive diagnostic method for detecting COVID-19 is crucial for patient control and timely treatment. Objective: This study aimed to validate the detection of SARS-CoV-2 with the Pluslife SARS-CoV-2 rapid test kit developed based on a novel thermostatic amplification technique called RNase hybridization-assisted amplification. Methods: From November 25 to December 8, 2022, patients with suspected or confirmed COVID-19, close contacts, and health care workers at high risk of exposure were recruited from 3 hospitals and 1 university. Respiratory specimens were collected for testing with the Pluslife SARS-CoV-2 rapid test kit and compared with reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and a commercial antigen assay kit. Samples from 1447 cases were obtained from 3 ``ready-to-test'' scenarios in which samples were collected on site and tested immediately, and samples from 503 cases were obtained from a ``freeze-thaw test'' scenario in which samples were collected, frozen, and thawed for testing. Results: Pluslife SARS-CoV-2 rapid testing of samples from the ``ready-to-test'' scenario was found to be accurate (overall sensitivity and specificity of 98.3\% and 99.3\%, respectively) and diagnostically useful (positive and negative likelihood ratios of 145.45 and 0.02, respectively). Pluslife SARS-CoV-2 rapid testing of samples from the ``freeze-thaw test'' scenario was also found to be accurate (overall sensitivity and specificity of 71.2\% and 98.6\%, respectively) and diagnostically useful (positive and negative likelihood ratios of 51.01 and 0.67, respectively). Our findings demonstrated that the time efficiency and accuracy of the results in a ``ready-to-test'' scenario were better. The time required from sample preparation to the seeing the result of the Pluslife SARS-CoV-2 rapid test was 10 to 38 minutes, which was substantially shorter than that of RT-qPCR (at least 90 minutes). In addition, the diagnostic efficacy of the Pluslife SARS-CoV-2 rapid test was better than that of a commercial antigen assay kit. Conclusions: The developed RNase hybridization-assisted amplification assay provided rapid, sensitive, and convenient detection of SARS-CoV-2 infection and may be useful for enhanced detection of COVID-19 in homes, high-risk industries, and hospitals. ", doi="10.2196/48107", url="https://publichealth.jmir.org/2023/1/e48107", url="http://www.ncbi.nlm.nih.gov/pubmed/37962934" } @Article{info:doi/10.2196/41999, author="Qiu, Hang and Wang, Liya and Zhou, Li and Wang, Xiaodong", title="Comorbidity Patterns in Patients Newly Diagnosed With Colorectal Cancer: Network-Based Study", journal="JMIR Public Health Surveill", year="2023", month="Sep", day="5", volume="9", pages="e41999", keywords="colorectal cancer", keywords="comorbidity patterns", keywords="prevalence", keywords="health status disparities", keywords="network analysis", keywords="routinely collected health data", abstract="Background: Patients with colorectal cancer (CRC) often present with multiple comorbidities, and many of these can affect treatment and survival. However, previous comorbidity studies primarily focused on diseases in commonly used comorbidity indices. The comorbid status of CRC patients with respect to the entire spectrum of chronic diseases has not yet been investigated. Objective: This study aimed to systematically analyze all chronic diagnoses and diseases co-occurring, using a network-based approach and large-scale administrative health data, and provide a complete picture of the comorbidity pattern in patients newly diagnosed with CRC from southwest China. Methods: In this retrospective observational study, the hospital discharge records of 678 hospitals from 2015 to 2020 in Sichuan Province, China were used to identify new CRC cases in 2020 and their history of diseases. We examined all chronic diagnoses using ICD-10 (International Classification of Diseases, 10th Revision) codes at 3 digits and focused on chronic diseases with >1\% prevalence in at least one subgroup (1-sided test, P<.025), which resulted in a total of 66 chronic diseases. Phenotypic comorbidity networks were constructed across all CRC patients and different subgroups by sex, age (18-59, 60-69, 70-79, and ?80 years), area (urban and rural), and cancer site (colon and rectum), with comorbidity as a node and linkages representing significant correlations between multiple comorbidities. Results: A total of 29,610 new CRC cases occurred in Sichuan, China in 2020. The mean patient age at diagnosis was 65.6 (SD 12.9) years, and 75.5\% (22,369/29,610) had at least one comorbidity. The most prevalent comorbidities were hypertension (8581/29,610, 29.0\%; 95\% CI 28.5\%-29.5\%), hyperplasia of the prostate (3816/17,426, 21.9\%; 95\% CI 21.3\%-22.5\%), and chronic obstructive pulmonary disease (COPD; 4199/29,610, 14.2\%; 95\% CI 13.8\%-14.6\%). The prevalence of single comorbidities was different in each subgroup in most cases. Comorbidities were closely associated, with disorders of lipoprotein metabolism and hyperplasia of the prostate mediating correlations between other comorbidities. Males and females shared 58.3\% (141/242) of disease pairs, whereas male-female disparities occurred primarily in diseases coexisting with COPD, cerebrovascular diseases, atherosclerosis, heart failure, or renal failure among males and with osteoporosis or gonarthrosis among females. Urban patients generally had more comorbidities with higher prevalence and more complex disease coexistence relationships, whereas rural patients were more likely to have co-existing severe diseases, such as heart failure comorbid with the sequelae of cerebrovascular disease or COPD. Conclusions: Male-female and urban-rural disparities in the prevalence of single comorbidities and their complex coexistence relationships in new CRC cases were not due to simple coincidence. The results reflect clinical practice in CRC patients and emphasize the importance of measuring comorbidity patterns in terms of individual and coexisting diseases in order to better understand comorbidity patterns. ", doi="10.2196/41999", url="https://publichealth.jmir.org/2023/1/e41999", url="http://www.ncbi.nlm.nih.gov/pubmed/37669093" } @Article{info:doi/10.2196/46264, author="Choi, Ju-Young and Ha, Sang-Won and Jeong, Da-Eun and Lee, Jaeho and Kim, Donghoon and Min, Jin-Young and Min, Kyoung-Bok", title="Association Between the Loss of Gait Harmony and Cognitive Impairment: Cross-Sectional Study", journal="JMIR Public Health Surveill", year="2023", month="Jul", day="10", volume="9", pages="e46264", keywords="cognitive function", keywords="gait phase", keywords="physical performance", keywords="dementia", keywords="older adult", keywords="aging", keywords="asymmetric", keywords="balance", keywords="gait analysis", keywords="cognition", keywords="cognitive impairment", keywords="gait", keywords="gait pattern", abstract="Background: Functional limitations and disabilities have been associated with a decrease in cognitive function due to increasing age. Gait performance and cognitive function have been associated with gait variability in executive function, the phase domain in memory, and gait abnormalities in cognitive decline. Objective: Our study aimed to investigate whether gait harmony was associated with cognitive function in the older adult population. Moreover, we aimed to investigate whether gait harmony was associated with cognitive function and explore each cognitive function in a specific harmonic state. Methods: The study population included 510 adults aged ?60 years who visited the Department of Neurology at the Veterans Health Service Medical Center, Seoul, South Korea. Gait data were collected using a 3D motion capture device with a wireless inertial measurement unit system. For cognitive function assessments, we used the Seoul Neuropsychological Screening Battery-Core test, which evaluates the level of cognitive function or impairment in 5 cognitive domains. Results: In general, the association between the Seoul Neuropsychological Screening Battery-Core tests and the stance-to-swing ratio in the >1.63 ratio group yielded lower $\beta$ coefficients than those in the 1.50-1.63 ratio group. After adjustment for confounders, the odds ratio (OR) for the Digit Symbol Coding test (adjusted OR 0.42, 95\% CI 0.20-0.88) and the Korean version of the Color Word Stroop Test: 60 seconds (adjusted OR 0.51, 95\% CI 0.29-0.89) for frontal and executive function were significantly lower for the >1.63 ratio group than the reference group. Conclusions: Our findings suggest that the gait phase ratio is a valuable indicator of walking deficits and may also be associated with cognitive impairment in older adults. ", doi="10.2196/46264", url="https://publichealth.jmir.org/2023/1/e46264", url="http://www.ncbi.nlm.nih.gov/pubmed/37428538" } @Article{info:doi/10.2196/42963, author="Fernandes, Blossom and Neelakantan, Lakshmi and Shah, Himani and Sumant, Sushmita and Collins, Y. Pamela and Velloza, Jennifer and Bampton, Emily and Ranganathan, Swetha and Sibisi, Refiloe and Bashir, Toiba and Bowes, Joshua and David, Larisa Esther and Kaur, Harsimar and Malik, Umairah and Shannon, Issy and Gurumayum, Suvlaxmi and Burn, Anne-Marie and Sieberts, K. Solveig and and Fazel, Mina", title="Evidencing the Impact of Web-Based Coproduction With Youth on Mental Health Research: Qualitative Findings From the MindKind Study", journal="JMIR Public Health Surveill", year="2023", month="Jun", day="19", volume="9", pages="e42963", keywords="web-based youth coproduction", keywords="mental health", keywords="public involvement", keywords="young people", keywords="advisory groups", abstract="Background: Public involvement in research is a growing phenomenon as well as a condition of research funding, and it is often referred to as coproduction. Coproduction involves stakeholder contributions at every stage of research, but different processes exist. However, the impact of coproduction on research is not well understood. Web-based young people's advisory groups (YPAGs) were established as part of the MindKind study at 3 sites (India, South Africa, and the United Kingdom) to coproduce the wider research study. Each group site, led by a professional youth advisor, conducted all youth coproduction activities collaboratively with other research staff. Objective: This study aimed to evaluate the impact of youth coproduction in the MindKind study. Methods: To measure the impact of web-based youth coproduction on all stakeholders, the following methods were used: analysis of project documents, capturing the views of stakeholders using the Most Significant Change technique, and impact frameworks to assess the impact of youth coproduction on specific stakeholder outcomes. Data were analyzed in collaboration with researchers, advisors, and YPAG members to explore the impact of youth coproduction on research. Results: The impact was recorded on 5 levels. First, at the paradigmatic level, a novel method of conducting research allowed for a widely diverse group of YPAG representations, influencing study priorities, conceptualization, and design. Second, at the infrastructural level, the YPAG and youth advisors meaningfully contributed to the dissemination of materials; infrastructural constraints of undertaking coproduction were also identified. Third, at the organizational level, coproduction necessitated implementing new communication practices, such as a web-based shared platform. This meant that materials were easily accessible to the whole team and communication streams remained consistent. Fourth, at the group level, authentic relationships developed between the YPAG members, advisors, and the rest of the team, facilitated by regular web-based contact. Finally, at the individual level, participants reported enhanced insights into mental well-being and appreciation for the opportunity to engage in research. Conclusions: This study revealed several factors that shape the creation of web-based coproduction, with clear positive outcomes for advisors, YPAG members, researchers, and other project staff. However, several challenges of coproduced research were also encountered in multiple contexts and amid pressing timelines. For systematic reporting of the impact of youth coproduction, we propose that monitoring, evaluation, and learning systems be designed and implemented early. ", doi="10.2196/42963", url="https://publichealth.jmir.org/2023/1/e42963", url="http://www.ncbi.nlm.nih.gov/pubmed/37335609" } @Article{info:doi/10.2196/41369, author="Mudaranthakam, Pal Dinesh and Pepper, Sam and Fortney, Tanner and Alsup, Alexander and Woodward, Jennifer and Sykes, Kevin and Calhoun, Elizabeth", title="The Effects of COVID-19 Pandemic Policy on Social Needs Across the State of Kansas and Western Missouri: Paired Survey Response Testing", journal="JMIR Public Health Surveill", year="2023", month="Apr", day="25", volume="9", pages="e41369", keywords="social determinants of health", keywords="COVID-19", keywords="food assistance program", keywords="public health", keywords="quality of life", keywords="well-being", keywords="health disparity", keywords="health inequity", keywords="health policy", keywords="Kansas", keywords="social work", keywords="socioeconomic", abstract="Background: Studying patients' social needs is critical to the understanding of health conditions and disparities, and to inform strategies for improving health outcomes. Studies have shown that people of color, low-income families, and those with lower educational attainment experience greater hardships related to social needs. The COVID-19 pandemic represents an event that severely impacted people's social needs. This pandemic was declared by the World Health Organization on March 11, 2020, and contributed to food and housing insecurity, while highlighting weaknesses in the health care system surrounding access to care. To combat these issues, legislators implemented unique policies and procedures to help alleviate worsening social needs throughout the pandemic, which had not previously been exerted to this degree. We believe that improvements related to COVID-19 legislature and policy have positively impacted people's social needs in Kansas and Missouri, United States. In particular, Wyandotte County is of interest as it suffers greatly from issues related to social needs that many of these COVID-19--related policies aimed to improve. Objective: The research objective of this study was to evaluate the change in social needs before and after the COVID-19 pandemic declaration based on responses to a survey from The University of Kansas Health System (TUKHS). We further aimed to compare the social needs of respondents from Wyandotte County from those of respondents in other counties in the Kansas City metropolitan area. Methods: Social needs survey data from 2016 to 2022 were collected from a 12-question patient-administered survey distributed by TUKHS during a patient visit. This provided a longitudinal data set with 248,582 observations, which was narrowed down into a paired-response data set for 50,441 individuals who had provided at least one response before and after March 11, 2020. These data were then bucketed by county into Cass (Missouri), Clay (Missouri), Jackson (Missouri), Johnson (Kansas), Leavenworth (Kansas), Platte (Missouri), Wyandotte (Kansas), and Other counties, creating groupings with at least 1000 responses in each category. A pre-post composite score was calculated for each individual by adding their coded responses (yes=1, no=0) across the 12 questions. The Stuart-Maxwell marginal homogeneity test was used to compare the pre and post composite scores across all counties. Additionally, McNemar tests were performed to compare responses before and after March 11, 2020, for each of the 12 questions across all counties. Finally, McNemar tests were performed for questions 1, 7, 8, 9, and 10 for each of the bucketed counties. Significance was assessed at P<.05 for all tests. Results: The Stuart-Maxwell test for marginal homogeneity was significant (P<.001), indicating that respondents were overall less likely to identify an unmet social need after the COVID-19 pandemic. McNemar tests for individual questions indicated that after the COVID-19 pandemic, respondents across all counties were less likely to identify unmet social needs related to food availability (odds ratio [OR]=0.4073, P<.001), home utilities (OR=0.4538, P<.001), housing (OR=0.7143, P<.001), safety among cohabitants (OR=0.6148, P<.001), safety in their residential location (OR=0.6172, P<.001), child care (OR=0.7410, P<0.01), health care access (OR=0.3895, P<.001), medication adherence (OR=0.5449, P<.001), health care adherence (OR=0.6378, P<.001), and health care literacy (0.8729, P=.02), and were also less likely to request help with these unmet needs (OR=0.7368, P<.001) compared with prepandemic responses. Responses from individual counties were consistent with the overall results for the most part. Notably, no individual county demonstrated a significant reduction in social needs relating to a lack of companionship. Conclusions: Post-COVID-19 responses showed improvement across almost all social needs--related questions, indicating that the federal policy response possibly had a positive impact on social needs across the populations of Kansas and western Missouri. Some counties were impacted more than others and positive outcomes were not limited to urban counties. The availability of resources, safety net services, access to health care, and educational opportunities could play a role in this change. Future research should focus on improving survey response rates from rural counties to increase their sample size, and to evaluate other explanatory variables such as food pantry access, educational status, employment opportunities, and access to community resources. Government policies should be an area of focused research as they may affect the social needs and health of the individuals considered in this analysis. ", doi="10.2196/41369", url="https://publichealth.jmir.org/2023/1/e41369", url="http://www.ncbi.nlm.nih.gov/pubmed/36977199" } @Article{info:doi/10.2196/40814, author="Hirst, Yasemin and Stoffel, T. Sandro and Brewer, R. Hannah and Timotijevic, Lada and Raats, M. Monique and Flanagan, M. James", title="Understanding Public Attitudes and Willingness to Share Commercial Data for Health Research: Survey Study in the United Kingdom", journal="JMIR Public Health Surveill", year="2023", month="Mar", day="23", volume="9", pages="e40814", keywords="commercial data", keywords="data sharing", keywords="participant recruitment", keywords="loyalty cards", keywords="sociodemographic factors", keywords="data donation", keywords="data", keywords="health", keywords="public", keywords="acceptability", keywords="digital", keywords="mobile phone", abstract="Background: Health research using commercial data is increasing. The evidence on public acceptability and sociodemographic characteristics of individuals willing to share commercial data for health research is scarce. Objective: This survey study investigates the willingness to share commercial data for health research in the United Kingdom with 3 different organizations (government, private, and academic institutions), 5 different data types (internet, shopping, wearable devices, smartphones, and social media), and 10 different invitation methods to recruit participants for research studies with a focus on sociodemographic characteristics and psychological predictors. Methods: We conducted a web-based survey using quota sampling based on age distribution in the United Kingdom in July 2020 (N=1534). Chi-squared tests tested differences by sociodemographic characteristics, and adjusted ordered logistic regressions tested associations with trust, perceived importance of privacy, worry about data misuse and perceived risks, and perceived benefits of data sharing. The results are shown as percentages, adjusted odds ratios, and 95\% CIs. Results: Overall, 61.1\% (937/1534) of participants were willing to share their data with the government and 61\% (936/1534) of participants were willing to share their data with academic research institutions compared with 43.1\% (661/1534) who were willing to share their data with private organizations. The willingness to share varied between specific types of data---51.8\% (794/1534) for loyalty cards, 35.2\% (540/1534) for internet search history, 32\% (491/1534) for smartphone data, 31.8\% (488/1534) for wearable device data, and 30.4\% (467/1534) for social media data. Increasing age was consistently and negatively associated with all the outcomes. Trust was positively associated with willingness to share commercial data, whereas worry about data misuse and the perceived importance of privacy were negatively associated with willingness to share commercial data. The perceived risk of sharing data was positively associated with willingness to share when the participants considered all the specific data types but not with the organizations. The participants favored postal research invitations over digital research invitations. Conclusions: This UK-based survey study shows that willingness to share commercial data for health research varies; however, researchers should focus on effectively communicating their data practices to minimize concerns about data misuse and improve public trust in data science. The results of this study can be further used as a guide to consider methods to improve recruitment strategies in health-related research and to improve response rates and participant retention. ", doi="10.2196/40814", url="https://publichealth.jmir.org/2023/1/e40814", url="http://www.ncbi.nlm.nih.gov/pubmed/36951929" } @Article{info:doi/10.2196/43772, author="Tang, Weiming and Xie, Yewei and Xiong, Mingzhou and Wu, Dan and Ong, J. Jason and Wi, Elvira Teodora and Yang, Bin and Tucker, D. Joseph and Wang, Cheng", title="A Pay-It-Forward Approach to Improve Chlamydia and Gonorrhea Testing Uptake Among Female Sex Workers in China: Venue-Based Superiority Cluster Randomized Controlled Trial", journal="JMIR Public Health Surveill", year="2023", month="Mar", day="2", volume="9", pages="e43772", keywords="pay-it-forward", keywords="chlamydia", keywords="gonorrhea", keywords="testing", keywords="female sex workers", keywords="women", keywords="China", keywords="cost", keywords="stigma", keywords="prevention", keywords="community", keywords="HIV", keywords="care", keywords="STD", keywords="implementation", keywords="research", abstract="Background: Regular chlamydia and gonorrhea testing are essential for key populations, such as female sex workers (FSWs). However, testing cost, stigma, and lack of access prevent FSWs in low- and middle-income countries from receiving chlamydia and gonorrhea testing. A social innovation to address these problems is ``pay it forward,'' where an individual receives a gift (free testing) and then asks whether they would like to give a gift to another person in the community. Objective: This cluster randomized controlled trial examined the effectiveness and cost of the pay-it-forward strategy in increasing access to chlamydia and gonorrhea testing among FSWs in China. Methods: This trial integrated a pay-it-forward approach into a community-based HIV outreach service. FSWs (aged 18 years or older) were invited by an outreach team from 4 Chinese cities (clusters) to receive free HIV testing. The 4 clusters were randomized into 2 study arms in a 1:1 ratio: a pay-it-forward arm (offered chlamydia and gonorrhea testing as a gift) and a standard-of-care arm (out-of-pocket cost for testing: US \$11). The primary outcome was chlamydia and gonorrhea test uptake, as ascertained by administrative records. We conducted an economic evaluation using a microcosting approach from a health provider perspective, reporting our results in US dollars (at 2021 exchange rates). Results: Overall, 480 FSWs were recruited from 4 cities (120 per city). Most FSWs were aged ?30 years (313/480, 65.2\%), were married (283/480, 59\%), had an annual income