Background: Thyroid disease (TD) is a prominent endocrine disorder that raises global health concerns; however, its comorbidity patterns remain unclear.
Objective: This study aims to apply a network-based method to comprehensively analyze the comorbidity patterns of TD using large-scale real-world health data.
Methods: In this retrospective observational study, we extracted the comorbidities of adult patients with TD from both private and public data sets. All comorbidities were identified using ICD-10 (International Classification of Diseases, 10th Revision) codes at the 3-digit level, and those with a prevalence greater than 2% were analyzed. Patients were categorized into several subgroups based on sex, age, and disease type. A phenotypic comorbidity network (PCN) was constructed, where comorbidities served as nodes and their significant correlations were represented as edges, encompassing all patients with TD and various subgroups. The associations and differences in comorbidities within the PCN of each subgroup were analyzed and compared. The PageRank algorithm was used to identify key comorbidities.
Results: The final cohorts included 18,311 and 50,242 patients with TD in the private and public data sets, respectively. Patients with TD demonstrated complex comorbidity patterns, with coexistence relationships differing by sex, age, and type of TD. The number of comorbidities increased with age. The most prevalent TDs were nontoxic goiter, hypothyroidism, hyperthyroidism, and thyroid cancer, while hypertension, diabetes, and lipoprotein metabolism disorders had the highest prevalence and PageRank values among comorbidities. Males and patients with benign TD exhibited a greater number of comorbidities, increased disease diversity, and stronger comorbidity associations compared with females and patients with thyroid cancer.
Conclusions: Patients with TD exhibited complex comorbidity patterns, particularly with cardiocerebrovascular diseases and diabetes. The associations among comorbidities varied across different TD subgroups. This study aims to enhance the understanding of comorbidity patterns in patients with TD and improve the integrated management of these individuals.
{"title":"Analyzing Comorbidity Patterns in Patients With Thyroid Disease Using Large-Scale Electronic Medical Records: Network-Based Retrospective Observational Study.","authors":"Yanqun Huang, Siyuan Chen, Yongfeng Wang, Xiaohong Ou, Huanhuan Yan, Xin Gan, Zhixiao Wei","doi":"10.2196/54891","DOIUrl":"10.2196/54891","url":null,"abstract":"<p><strong>Background: </strong>Thyroid disease (TD) is a prominent endocrine disorder that raises global health concerns; however, its comorbidity patterns remain unclear.</p><p><strong>Objective: </strong>This study aims to apply a network-based method to comprehensively analyze the comorbidity patterns of TD using large-scale real-world health data.</p><p><strong>Methods: </strong>In this retrospective observational study, we extracted the comorbidities of adult patients with TD from both private and public data sets. All comorbidities were identified using ICD-10 (International Classification of Diseases, 10th Revision) codes at the 3-digit level, and those with a prevalence greater than 2% were analyzed. Patients were categorized into several subgroups based on sex, age, and disease type. A phenotypic comorbidity network (PCN) was constructed, where comorbidities served as nodes and their significant correlations were represented as edges, encompassing all patients with TD and various subgroups. The associations and differences in comorbidities within the PCN of each subgroup were analyzed and compared. The PageRank algorithm was used to identify key comorbidities.</p><p><strong>Results: </strong>The final cohorts included 18,311 and 50,242 patients with TD in the private and public data sets, respectively. Patients with TD demonstrated complex comorbidity patterns, with coexistence relationships differing by sex, age, and type of TD. The number of comorbidities increased with age. The most prevalent TDs were nontoxic goiter, hypothyroidism, hyperthyroidism, and thyroid cancer, while hypertension, diabetes, and lipoprotein metabolism disorders had the highest prevalence and PageRank values among comorbidities. Males and patients with benign TD exhibited a greater number of comorbidities, increased disease diversity, and stronger comorbidity associations compared with females and patients with thyroid cancer.</p><p><strong>Conclusions: </strong>Patients with TD exhibited complex comorbidity patterns, particularly with cardiocerebrovascular diseases and diabetes. The associations among comorbidities varied across different TD subgroups. This study aims to enhance the understanding of comorbidity patterns in patients with TD and improve the integrated management of these individuals.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e54891"},"PeriodicalIF":1.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11487213/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher Gundler, Karl Gottfried, Alexander Johannes Wiederhold, Maximilian Ataian, Marcus Wurlitzer, Jan Erik Gewehr, Frank Ückert
Background: Clinical routine data derived from university hospitals hold immense value for health-related research on large cohorts. However, using secondary data for hypothesis testing necessitates adherence to scientific, legal (such as the General Data Protection Regulation, federal and state protection legislations), technical, and administrative requirements. This process is intricate, time-consuming, and susceptible to errors.
Objective: This study aims to develop a platform that enables clinicians to use current real-world data for testing research and evaluate advantages and limitations at a large university medical center (542,944 patients in 2022).
Methods: We identified requirements from clinical practitioners, conceptualized and implemented a platform based on the existing components, and assessed its applicability in clinical reality quantitatively and qualitatively.
Results: The proposed platform was established at the University Medical Center Hamburg-Eppendorf and made 639 forms encompassing 10,629 data elements accessible to all resident scientists and clinicians. Every day, the number of patients rises, and parts of their electronic health records are made accessible through the platform. Qualitatively, we were able to conduct a retrospective analysis of Parkinson disease over 777 patients, where we provide additional evidence for a significantly higher proportion of action tremors in patients with rest tremors (340/777, 43.8%) compared with those without rest tremors (255/777, 32.8%), as determined by a chi-square test (P<.001). Quantitatively, our findings demonstrate increased user engagement within the last 90 days, underscoring clinicians' increasing adoption of the platform in their regular research activities. Notably, the platform facilitated the retrieval of clinical data from 600,000 patients, emphasizing its substantial added value.
Conclusions: This study demonstrates the feasibility of simplifying the use of clinical data to enhance exploration and sustainability in scientific research. The proposed platform emerges as a potential technological and legal framework for other medical centers, providing them with the means to unlock untapped potential within their routine data.
{"title":"Unlocking the Potential of Secondary Data for Public Health Research: Retrospective Study With a Novel Clinical Platform.","authors":"Christopher Gundler, Karl Gottfried, Alexander Johannes Wiederhold, Maximilian Ataian, Marcus Wurlitzer, Jan Erik Gewehr, Frank Ückert","doi":"10.2196/51563","DOIUrl":"10.2196/51563","url":null,"abstract":"<p><strong>Background: </strong>Clinical routine data derived from university hospitals hold immense value for health-related research on large cohorts. However, using secondary data for hypothesis testing necessitates adherence to scientific, legal (such as the General Data Protection Regulation, federal and state protection legislations), technical, and administrative requirements. This process is intricate, time-consuming, and susceptible to errors.</p><p><strong>Objective: </strong>This study aims to develop a platform that enables clinicians to use current real-world data for testing research and evaluate advantages and limitations at a large university medical center (542,944 patients in 2022).</p><p><strong>Methods: </strong>We identified requirements from clinical practitioners, conceptualized and implemented a platform based on the existing components, and assessed its applicability in clinical reality quantitatively and qualitatively.</p><p><strong>Results: </strong>The proposed platform was established at the University Medical Center Hamburg-Eppendorf and made 639 forms encompassing 10,629 data elements accessible to all resident scientists and clinicians. Every day, the number of patients rises, and parts of their electronic health records are made accessible through the platform. Qualitatively, we were able to conduct a retrospective analysis of Parkinson disease over 777 patients, where we provide additional evidence for a significantly higher proportion of action tremors in patients with rest tremors (340/777, 43.8%) compared with those without rest tremors (255/777, 32.8%), as determined by a chi-square test (P<.001). Quantitatively, our findings demonstrate increased user engagement within the last 90 days, underscoring clinicians' increasing adoption of the platform in their regular research activities. Notably, the platform facilitated the retrieval of clinical data from 600,000 patients, emphasizing its substantial added value.</p><p><strong>Conclusions: </strong>This study demonstrates the feasibility of simplifying the use of clinical data to enhance exploration and sustainability in scientific research. The proposed platform emerges as a potential technological and legal framework for other medical centers, providing them with the means to unlock untapped potential within their routine data.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e51563"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11480676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher Robert Timothy Hillyar, Natalie Bishop, Anjan Nibber, Frances Jean Bell-Davies, Juling Ong
Background: Plagiocephaly is defined as an asymmetrical distortion of the skull, resulting in an oblique trapezoid or parallelogram head shape. Deformational plagiocephaly (DP) is caused by forces acting on one side of the back of the head, distorting normal skull symmetry.
Objective: The aims of this systematic review and meta-analysis were to critically assess the evidence for nonobstetric risk factors for DP and to make evidence-based recommendations for reducing the prevalence of DP.
Methods: The selection criterion was studies reporting risk factors for DP. Case reviews, case series, expert opinions, and systematic reviews were excluded. PubMed and Web of Science were searched from August 21, 2010, to August 21, 2022. Publication bias was assessed using funnel plots. Meta-analyses were presented using forest plots.
Results: A total of 19 studies (cohort studies: n=13, 68%; case-control studies: n=5, 26%; and cross-sectional studies: n=1, 5%) with a total of 14,808 participants were included. Of the 43 investigated potential nonobstetric factors, 16 (37%) were associated with DP. Of these 16 factors, 12 (75%) had odds ratios (ORs) with 95% CIs not crossing 1: insufficient vitamin D intake (OR 7.15, 95% CI 3.77-13.54), head position preference (OR 4.75, 95% CI 3.36-6.73), bottle-only feeding (OR 4.65, 95% CI 2.70-8.00), reduced tummy time (OR 3.51, 95% CI 1.71-7.21), sleeping position (OR 3.12, 95% CI 2.21-4.39), fewer motor milestones reached by the age of 6 months (OR 2.56, 95% CI 1.66-3.96), obesity (OR 2.45, 95% CI 1.02-5.90), maternal education level (OR 1.66, 95% CI 1.17-2.37), male sex (OR 1.51, 95% CI 1.07-2.12), formula feeding (OR 1.51, 95% CI 1.00-2.27), head circumference (OR 1.22, 95% CI 1.06-1.40), and mechanical ventilation (OR 1.10, 95% CI 1.00-1.14). No evidence of publication bias was detected.
Conclusions: This study provides a comprehensive assessment of the nonobstetric factors associated with DP and presents 11 evidence-based recommendations for reducing its prevalence. The primary limitation is that only publication bias was assessed.
背景:头颅畸形(Plagiocephaly)是指头颅的不对称变形,导致头部呈斜梯形或平行四边形。变形性头颅畸形(DP)是由作用于一侧后脑勺的力造成的,扭曲了正常的头颅对称性:本系统综述和荟萃分析的目的是严格评估导致畸形头畸形的非产科风险因素的证据,并为降低畸形头畸形的患病率提出循证建议:方法:选择标准是报告 DP 风险因素的研究。排除了病例回顾、系列病例、专家意见和系统回顾。检索了 2010 年 8 月 21 日至 2022 年 8 月 21 日期间的 PubMed 和 Web of Science。采用漏斗图评估发表偏倚。采用森林图进行元分析:共纳入 19 项研究(队列研究:n=13,占 68%;病例对照研究:n=5,占 26%;横断面研究:n=1,占 5%),共有 14 808 名参与者。在 43 项被调查的潜在非产科因素中,16 项(37%)与 DP 相关。在这 16 个因素中,12 个因素(75%)的几率比(ORs)与 95% CIs 不超过 1:维生素 D 摄入不足(OR 7.15,95% CI 3.77-13.54)、头位偏好(OR 4.75,95% CI 3.36-6.73)、只用奶瓶喂养(OR 4.65,95% CI 2.70-8.00)、腹部时间减少(OR 3.51,95% CI 1.71-7.21)、睡姿(OR 3.12,95% CI 2.21-4.39)、运动里程数减少(OR 3.15,95% CI 3.77-13.54)。37)、男性(OR 1.51,95% CI 1.07-2.12)、配方喂养(OR 1.51,95% CI 1.00-2.27)、头围(OR 1.22,95% CI 1.06-1.40)和机械通气(OR 1.10,95% CI 1.00-1.14)。未发现发表偏倚的证据:本研究对与DP相关的非产科因素进行了全面评估,并提出了11项循证建议以降低其发生率。主要局限性在于仅评估了发表偏倚:PERCORCO CRD42020204979; https://www.crd.york.ac.uk/prospero/display_record.php?id=crd42020204979。
{"title":"Assessing the Evidence for Nonobstetric Risk Factors for Deformational Plagiocephaly: Systematic Review and Meta-Analysis.","authors":"Christopher Robert Timothy Hillyar, Natalie Bishop, Anjan Nibber, Frances Jean Bell-Davies, Juling Ong","doi":"10.2196/55695","DOIUrl":"10.2196/55695","url":null,"abstract":"<p><strong>Background: </strong>Plagiocephaly is defined as an asymmetrical distortion of the skull, resulting in an oblique trapezoid or parallelogram head shape. Deformational plagiocephaly (DP) is caused by forces acting on one side of the back of the head, distorting normal skull symmetry.</p><p><strong>Objective: </strong>The aims of this systematic review and meta-analysis were to critically assess the evidence for nonobstetric risk factors for DP and to make evidence-based recommendations for reducing the prevalence of DP.</p><p><strong>Methods: </strong>The selection criterion was studies reporting risk factors for DP. Case reviews, case series, expert opinions, and systematic reviews were excluded. PubMed and Web of Science were searched from August 21, 2010, to August 21, 2022. Publication bias was assessed using funnel plots. Meta-analyses were presented using forest plots.</p><p><strong>Results: </strong>A total of 19 studies (cohort studies: n=13, 68%; case-control studies: n=5, 26%; and cross-sectional studies: n=1, 5%) with a total of 14,808 participants were included. Of the 43 investigated potential nonobstetric factors, 16 (37%) were associated with DP. Of these 16 factors, 12 (75%) had odds ratios (ORs) with 95% CIs not crossing 1: insufficient vitamin D intake (OR 7.15, 95% CI 3.77-13.54), head position preference (OR 4.75, 95% CI 3.36-6.73), bottle-only feeding (OR 4.65, 95% CI 2.70-8.00), reduced tummy time (OR 3.51, 95% CI 1.71-7.21), sleeping position (OR 3.12, 95% CI 2.21-4.39), fewer motor milestones reached by the age of 6 months (OR 2.56, 95% CI 1.66-3.96), obesity (OR 2.45, 95% CI 1.02-5.90), maternal education level (OR 1.66, 95% CI 1.17-2.37), male sex (OR 1.51, 95% CI 1.07-2.12), formula feeding (OR 1.51, 95% CI 1.00-2.27), head circumference (OR 1.22, 95% CI 1.06-1.40), and mechanical ventilation (OR 1.10, 95% CI 1.00-1.14). No evidence of publication bias was detected.</p><p><strong>Conclusions: </strong>This study provides a comprehensive assessment of the nonobstetric factors associated with DP and presents 11 evidence-based recommendations for reducing its prevalence. The primary limitation is that only publication bias was assessed.</p><p><strong>Trial registration: </strong>PROSPERO CRD42020204979; https://www.crd.york.ac.uk/prospero/display_record.php? ID=CRD42020204979.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e55695"},"PeriodicalIF":1.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11447428/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142300566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Raff, Kurtis Stewart, Michelle Christie Yang, Jessie Shang, Sonya Cressman, Roger Tam, Jessica Wong, Martin C Tammemägi, Kendall Ho
<p><strong>Background: </strong>Prehospital telemedicine triage systems combined with machine learning (ML) methods have the potential to improve triage accuracy and safely redirect low-acuity patients from attending the emergency department. However, research in prehospital settings is limited but needed; emergency department overcrowding and adverse patient outcomes are increasingly common.</p><p><strong>Objective: </strong>In this scoping review, we sought to characterize the existing methods for ML-enhanced telemedicine emergency triage. In order to support future research, we aimed to delineate what data sources, predictors, labels, ML models, and performance metrics were used, and in which telemedicine triage systems these methods were applied.</p><p><strong>Methods: </strong>A scoping review was conducted, querying multiple databases (MEDLINE, PubMed, Scopus, and IEEE Xplore) through February 24, 2023, to identify potential ML-enhanced methods, and for those eligible, relevant study characteristics were extracted, including prehospital triage setting, types of predictors, ground truth labeling method, ML models used, and performance metrics. Inclusion criteria were restricted to the triage of emergency telemedicine services using ML methods on an undifferentiated (disease nonspecific) population. Only primary research studies in English were considered. Furthermore, only those studies using data collected remotely (as opposed to derived from physical assessments) were included. In order to limit bias, we exclusively included articles identified through our predefined search criteria and had 3 researchers (DR, JS, and KS) independently screen the resulting studies. We conducted a narrative synthesis of findings to establish a knowledge base in this domain and identify potential gaps to be addressed in forthcoming ML-enhanced methods.</p><p><strong>Results: </strong>A total of 165 unique records were screened for eligibility and 15 were included in the review. Most studies applied ML methods during emergency medical dispatch (7/15, 47%) or used chatbot applications (5/15, 33%). Patient demographics and health status variables were the most common predictors, with a notable absence of social variables. Frequently used ML models included support vector machines and tree-based methods. ML-enhanced models typically outperformed conventional triage algorithms, and we found a wide range of methods used to establish ground truth labels.</p><p><strong>Conclusions: </strong>This scoping review observed heterogeneity in dataset size, predictors, clinical setting (triage process), and reported performance metrics. Standard structured predictors, including age, sex, and comorbidities, across articles suggest the importance of these inputs; however, there was a notable absence of other potentially useful data, including medications, social variables, and health system exposure. Ground truth labeling practices should be reported in a standard fashion as t
背景:院前远程医疗分诊系统与机器学习(ML)方法相结合,有可能提高分诊的准确性,并安全地将低危重病人转到急诊科就诊。然而,针对院前环境的研究虽然有限,但却亟待开展;急诊科人满为患、患者病情恶化的现象日益普遍:在这篇范围综述中,我们试图描述现有的 ML 增强型远程医疗急诊分诊方法的特点。为了支持未来的研究,我们旨在界定使用了哪些数据源、预测因子、标签、ML 模型和性能指标,以及这些方法应用于哪些远程医疗分诊系统:在 2023 年 2 月 24 日之前,我们对多个数据库(MEDLINE、PubMed、Scopus 和 IEEE Xplore)进行了范围审查,以确定潜在的 ML 增强方法,并提取符合条件的相关研究特征,包括院前分诊设置、预测因子类型、基本真实标记方法、使用的 ML 模型和性能指标。纳入标准仅限于使用 ML 方法对未分化(非特异性疾病)人群进行紧急远程医疗服务分流。只考虑英语的初级研究。此外,只有使用远程收集的数据(而不是通过身体评估得出的数据)的研究才被纳入。为了减少偏差,我们只收录通过预定义搜索标准确定的文章,并由 3 位研究人员(DR、JS 和 KS)独立筛选所得研究。我们对研究结果进行了叙述性综合,以建立该领域的知识库,并确定即将推出的 ML 增强方法可能存在的不足:结果:共筛选出 165 条符合条件的记录,其中 15 条被纳入综述。大多数研究在紧急医疗派遣过程中应用了人工智能方法(7/15,47%)或使用了聊天机器人应用(5/15,33%)。患者人口统计学和健康状况变量是最常见的预测因素,而社会变量则明显缺乏。常用的 ML 模型包括支持向量机和基于树的方法。ML 增强模型的表现通常优于传统的分诊算法,我们发现用于建立基本真实标签的方法多种多样:本次范围界定审查在数据集规模、预测因素、临床环境(分诊流程)和报告的性能指标方面发现了异质性。不同文章中的标准结构化预测因子(包括年龄、性别和合并症)表明了这些输入数据的重要性;然而,其他可能有用的数据(包括药物、社会变量和医疗系统接触)却明显缺乏。由于模型的真实性能取决于这些标签,因此应以标准方式报告基本真实标签做法。本综述要求今后的工作形成一个标准化的框架,从而支持在经 ML 增强的院前分诊系统中进行一致的报告和性能比较。
{"title":"Improving Triage Accuracy in Prehospital Emergency Telemedicine: Scoping Review of Machine Learning-Enhanced Approaches.","authors":"Daniel Raff, Kurtis Stewart, Michelle Christie Yang, Jessie Shang, Sonya Cressman, Roger Tam, Jessica Wong, Martin C Tammemägi, Kendall Ho","doi":"10.2196/56729","DOIUrl":"10.2196/56729","url":null,"abstract":"<p><strong>Background: </strong>Prehospital telemedicine triage systems combined with machine learning (ML) methods have the potential to improve triage accuracy and safely redirect low-acuity patients from attending the emergency department. However, research in prehospital settings is limited but needed; emergency department overcrowding and adverse patient outcomes are increasingly common.</p><p><strong>Objective: </strong>In this scoping review, we sought to characterize the existing methods for ML-enhanced telemedicine emergency triage. In order to support future research, we aimed to delineate what data sources, predictors, labels, ML models, and performance metrics were used, and in which telemedicine triage systems these methods were applied.</p><p><strong>Methods: </strong>A scoping review was conducted, querying multiple databases (MEDLINE, PubMed, Scopus, and IEEE Xplore) through February 24, 2023, to identify potential ML-enhanced methods, and for those eligible, relevant study characteristics were extracted, including prehospital triage setting, types of predictors, ground truth labeling method, ML models used, and performance metrics. Inclusion criteria were restricted to the triage of emergency telemedicine services using ML methods on an undifferentiated (disease nonspecific) population. Only primary research studies in English were considered. Furthermore, only those studies using data collected remotely (as opposed to derived from physical assessments) were included. In order to limit bias, we exclusively included articles identified through our predefined search criteria and had 3 researchers (DR, JS, and KS) independently screen the resulting studies. We conducted a narrative synthesis of findings to establish a knowledge base in this domain and identify potential gaps to be addressed in forthcoming ML-enhanced methods.</p><p><strong>Results: </strong>A total of 165 unique records were screened for eligibility and 15 were included in the review. Most studies applied ML methods during emergency medical dispatch (7/15, 47%) or used chatbot applications (5/15, 33%). Patient demographics and health status variables were the most common predictors, with a notable absence of social variables. Frequently used ML models included support vector machines and tree-based methods. ML-enhanced models typically outperformed conventional triage algorithms, and we found a wide range of methods used to establish ground truth labels.</p><p><strong>Conclusions: </strong>This scoping review observed heterogeneity in dataset size, predictors, clinical setting (triage process), and reported performance metrics. Standard structured predictors, including age, sex, and comorbidities, across articles suggest the importance of these inputs; however, there was a notable absence of other potentially useful data, including medications, social variables, and health system exposure. Ground truth labeling practices should be reported in a standard fashion as t","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e56729"},"PeriodicalIF":1.9,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11429666/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142300578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lucy Chikwetu, Parker Vakili, Andrew Takais, Rabih Younes
Background: Diet-related diseases, such as type 2 diabetes, require strict dietary management to slow down disease progression and call for innovative management strategies. Conventional diet monitoring places a significant memory burden on patients, who may not accurately remember details of their meals and thus frequently falls short in preventing disease progression. Recent advances in sensor and computational technologies have sparked interest in developing eating detection platforms.
Objective: This review investigates central hemodynamic and thermoregulatory responses as potential biomarkers for eating detection.
Methods: We searched peer-reviewed literature indexed in PubMed, Web of Science, and Scopus on June 20, 2022, with no date limits. We also conducted manual searches in the same databases until April 21, 2024. We included English-language papers demonstrating the impact of eating on central hemodynamics and thermoregulation in healthy individuals. To evaluate the overall study quality and assess the risk of bias, we designed a customized tool inspired by the Cochrane assessment framework. This tool has 4 categories: high, medium, low, and very low. A total of 2 independent reviewers conducted title and abstract screening, full-text review, and study quality and risk of bias analysis. In instances of disagreement between the 2 reviewers, a third reviewer served as an adjudicator.
Results: Our search retrieved 11,450 studies, and 25 met our inclusion criteria. Among the 25 included studies, 32% (8/25) were classified as high quality, 52% (13/25) as medium quality, and 16% (4/25) as low quality. Furthermore, we found no evidence of publication bias in any of the included studies. A consistent postprandial increase in heart rate, cardiac output, and stroke volume was observed in at least 95% (heart rate: 19/19, cardiac output: 18/19, stroke volume: 11/11) of the studies that investigated these variables' responses to eating. Specifically, cardiac output increased by 9%-100%, stroke volume by 18%-41%, and heart rate by 6%-21% across these studies. These changes were statistically significant (P<.05). In contrast, the 8 studies that investigated postprandial thermoregulatory effects displayed grossly inconsistent results, showing wide variations in response with no clear patterns of change, indicating a high degree of variability among these studies.
Conclusions: Our findings demonstrate that central hemodynamic responses, particularly heart rate, hold promise for wearable-based eating detection, as cardiac output and stroke volume cannot be measured by any currently available noninvasive medical or consumer-grade wearables.
{"title":"Central Hemodynamic and Thermoregulatory Responses to Food Intake as Potential Biomarkers for Eating Detection: Systematic Review.","authors":"Lucy Chikwetu, Parker Vakili, Andrew Takais, Rabih Younes","doi":"10.2196/52167","DOIUrl":"10.2196/52167","url":null,"abstract":"<p><strong>Background: </strong>Diet-related diseases, such as type 2 diabetes, require strict dietary management to slow down disease progression and call for innovative management strategies. Conventional diet monitoring places a significant memory burden on patients, who may not accurately remember details of their meals and thus frequently falls short in preventing disease progression. Recent advances in sensor and computational technologies have sparked interest in developing eating detection platforms.</p><p><strong>Objective: </strong>This review investigates central hemodynamic and thermoregulatory responses as potential biomarkers for eating detection.</p><p><strong>Methods: </strong>We searched peer-reviewed literature indexed in PubMed, Web of Science, and Scopus on June 20, 2022, with no date limits. We also conducted manual searches in the same databases until April 21, 2024. We included English-language papers demonstrating the impact of eating on central hemodynamics and thermoregulation in healthy individuals. To evaluate the overall study quality and assess the risk of bias, we designed a customized tool inspired by the Cochrane assessment framework. This tool has 4 categories: high, medium, low, and very low. A total of 2 independent reviewers conducted title and abstract screening, full-text review, and study quality and risk of bias analysis. In instances of disagreement between the 2 reviewers, a third reviewer served as an adjudicator.</p><p><strong>Results: </strong>Our search retrieved 11,450 studies, and 25 met our inclusion criteria. Among the 25 included studies, 32% (8/25) were classified as high quality, 52% (13/25) as medium quality, and 16% (4/25) as low quality. Furthermore, we found no evidence of publication bias in any of the included studies. A consistent postprandial increase in heart rate, cardiac output, and stroke volume was observed in at least 95% (heart rate: 19/19, cardiac output: 18/19, stroke volume: 11/11) of the studies that investigated these variables' responses to eating. Specifically, cardiac output increased by 9%-100%, stroke volume by 18%-41%, and heart rate by 6%-21% across these studies. These changes were statistically significant (P<.05). In contrast, the 8 studies that investigated postprandial thermoregulatory effects displayed grossly inconsistent results, showing wide variations in response with no clear patterns of change, indicating a high degree of variability among these studies.</p><p><strong>Conclusions: </strong>Our findings demonstrate that central hemodynamic responses, particularly heart rate, hold promise for wearable-based eating detection, as cardiac output and stroke volume cannot be measured by any currently available noninvasive medical or consumer-grade wearables.</p><p><strong>Trial registration: </strong>PROSPERO CRD42022360600; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=360600.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e52167"},"PeriodicalIF":1.9,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11422732/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142300577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paola Kammrath Betancor, Daniel Böhringer, Philip Maier, Thabo Lapp, Thomas Reinhard
Background: Anterior chamber-associated immune deviation (ACAID) is an active immunotolerance mechanism, which is induced by placing antigen into the anterior eye chamber as long as a major surgical trauma is avoided. For this reason, ACAID may be a major contributor to the favorable immunologic outcomes in Descemet membrane endothelial keratoplasty (DMEK). Rodent models have demonstrated the importance of a functional spleen for the development of an ACAID.
Objective: This study aimed to investigate whether splenectomy leads to increased rejection rates after DMEK in humans.
Methods: A retrospective evaluation was conducted on the course following DMEK at the Eye Center, Medical Center, University of Freiburg, for patients with a self-reported history of splenectomy compared to patients without this condition. Potential study patients were contacted by mail. A questionnaire to self-report splenectomy and the time thereof was sent out. The medical records of all consenting patients at the Eye Center were reviewed for graft survival and immune reactions.
Results: We asked 1818 patients after DMEK to report their history of splenectomy. A total of 1340 patients responded and were included in the study. Of these 1340 patients, 16 (1.2%) reported a history of splenectomy (ie, 26 DMEKs, with 10 patients being transplanted in both eyes and 6 patients being transplanted in 1 eye; median age at surgery 73.7, range 66.7-76.1 y). The remaining patients (1324 patients, ie, 1941 eyes) served as controls, with 1941 DMEKs (median age at surgery 71.5, range 64.1-77.2 y). Five (19%) out of the 26 eyes from the splenectomy group required a second transplant due to dislocation (n=2.8%), failure (n=2.8%), and rejection (n=1.4%). Kaplan-Meier analysis revealed no relevant difference compared with controls.
Conclusions: Our results suggest that splenectomy has no major effect on the outcome following DMEK. Subsequent, ACAID may not be the main reason for the favorable immunological outcomes in DMEK, or the camero-splenic axis may be subordinate in humans. However, we only included 16 patients who underwent splenectomy, so it might be possible that we missed a minor effect.
{"title":"Splenectomy as a Risk Factor for Graft Rejection Following Endothelial Transplantation: Retrospective Study.","authors":"Paola Kammrath Betancor, Daniel Böhringer, Philip Maier, Thabo Lapp, Thomas Reinhard","doi":"10.2196/50106","DOIUrl":"10.2196/50106","url":null,"abstract":"<p><strong>Background: </strong>Anterior chamber-associated immune deviation (ACAID) is an active immunotolerance mechanism, which is induced by placing antigen into the anterior eye chamber as long as a major surgical trauma is avoided. For this reason, ACAID may be a major contributor to the favorable immunologic outcomes in Descemet membrane endothelial keratoplasty (DMEK). Rodent models have demonstrated the importance of a functional spleen for the development of an ACAID.</p><p><strong>Objective: </strong>This study aimed to investigate whether splenectomy leads to increased rejection rates after DMEK in humans.</p><p><strong>Methods: </strong>A retrospective evaluation was conducted on the course following DMEK at the Eye Center, Medical Center, University of Freiburg, for patients with a self-reported history of splenectomy compared to patients without this condition. Potential study patients were contacted by mail. A questionnaire to self-report splenectomy and the time thereof was sent out. The medical records of all consenting patients at the Eye Center were reviewed for graft survival and immune reactions.</p><p><strong>Results: </strong>We asked 1818 patients after DMEK to report their history of splenectomy. A total of 1340 patients responded and were included in the study. Of these 1340 patients, 16 (1.2%) reported a history of splenectomy (ie, 26 DMEKs, with 10 patients being transplanted in both eyes and 6 patients being transplanted in 1 eye; median age at surgery 73.7, range 66.7-76.1 y). The remaining patients (1324 patients, ie, 1941 eyes) served as controls, with 1941 DMEKs (median age at surgery 71.5, range 64.1-77.2 y). Five (19%) out of the 26 eyes from the splenectomy group required a second transplant due to dislocation (n=2.8%), failure (n=2.8%), and rejection (n=1.4%). Kaplan-Meier analysis revealed no relevant difference compared with controls.</p><p><strong>Conclusions: </strong>Our results suggest that splenectomy has no major effect on the outcome following DMEK. Subsequent, ACAID may not be the main reason for the favorable immunological outcomes in DMEK, or the camero-splenic axis may be subordinate in humans. However, we only included 16 patients who underwent splenectomy, so it might be possible that we missed a minor effect.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e50106"},"PeriodicalIF":1.9,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11422749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142300579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michael J Luke, Sansanee Craig, Suzinne Pak-Gorstein, Marlíse Arellano, Jessica Zhang, S Margaret Wright, John Chuo, Philip V Scribano
Telehealth presents both the potential to improve access to care and to widen the digital divide contributing to health care disparities and obliging health care systems to standardize approaches to measure and display telehealth disparities. Based on a literature review and the operational experience of clinicians, informaticists, and researchers in the Supporting Pediatric Research on Outcomes and Utilization of Telehealth (SPROUT)-Clinical and Translational Science Awards (CTSA) Network, we outline a strategic framework for health systems to develop and optimally use a telehealth equity dashboard through a 3-phased approach of (1) defining data sources and key equity-related metrics of interest; (2) designing a dynamic and user-friendly dashboard; and (3) deploying the dashboard to maximize engagement among clinical staff, investigators, and administrators.
{"title":"Narrowing the Digital Divide: Framework for Creating Telehealth Equity Dashboards.","authors":"Michael J Luke, Sansanee Craig, Suzinne Pak-Gorstein, Marlíse Arellano, Jessica Zhang, S Margaret Wright, John Chuo, Philip V Scribano","doi":"10.2196/57435","DOIUrl":"10.2196/57435","url":null,"abstract":"<p><p>Telehealth presents both the potential to improve access to care and to widen the digital divide contributing to health care disparities and obliging health care systems to standardize approaches to measure and display telehealth disparities. Based on a literature review and the operational experience of clinicians, informaticists, and researchers in the Supporting Pediatric Research on Outcomes and Utilization of Telehealth (SPROUT)-Clinical and Translational Science Awards (CTSA) Network, we outline a strategic framework for health systems to develop and optimally use a telehealth equity dashboard through a 3-phased approach of (1) defining data sources and key equity-related metrics of interest; (2) designing a dynamic and user-friendly dashboard; and (3) deploying the dashboard to maximize engagement among clinical staff, investigators, and administrators.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e57435"},"PeriodicalIF":1.9,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11411219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142134410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hanlin Feng, Karin Kurata, Jianfei Cao, Kageyama Itsuki, Makoto Niwa, Atsushi Aoyama, Kota Kodama
<p><strong>Background: </strong>Advancements in technology have overcome geographical barriers, making telemedicine, which offers remote emergency services, healthcare, and medication guidance, increasingly popular. COVID-19 restrictions amplified its global importance by bridging distances.</p><p><strong>Objective: </strong>This study aimed to analyze Chinese and global literature data, present new global telemedicine research trends, and clarify the development potential, collaborations, and deficiencies in China's telemedicine research.</p><p><strong>Methods: </strong>We conducted bibliometrics and network analyses on relevant documents from the Web of Science database from 2001 to 2022. Data collection was completed on October 30, 2023. Considering COVID-19's impact, 2020 was used as a baseline, dividing the data into 2 periods: 2001-2019 and 2020-2022. The development potential was determined based on publication trends. An international coauthorship network analysis identified collaboration statuses and potential. Co-occurrence analysis was conducted for China and the world.</p><p><strong>Results: </strong>We identified 25,333 telemedicine-related research papers published between 2001 and 2022, with a substantial increase during the COVID-19 period (2020-2022), particularly in China (1.93-fold increase), moving its global publication rank from tenth to sixth. The United States, the United Kingdom, and Australia contributed 62.96% of the literature, far ahead of China's 3.90%. Globally, telemedicine research increased significantly post-2020. Between 2001 and 2019, the United States and Australia were central in coauthor networks; post-2020, the United States remained the largest node. Network hubs included the United States, the United Kingdom, Australia, and Canada. Keyword co-occurrence analysis revealed 5 global clusters from 2001 to 2019 (system technology, health care applications, mobile health, mental health, and electronic health) and 2020 to 2022 (COVID-19, children's mental health, artificial intelligence, digital health, and rehabilitation of middle-aged and older adults). In China, the research trends aligned with global patterns, with rapid growth post-2020. From 2001 to 2019, China cooperated closely with Indonesia, India, Japan, Taiwan, and South Korea. From 2020 to 2022, cooperation expanded to Japan, Singapore, Malaysia, and South Korea, as well as Saudi Arabia, Egypt, South Africa, Ghana, Lebanon, and other African and Middle Eastern countries. Chinese keyword co-occurrence analysis showed focus areas in system technology, health care applications, mobile health, big data analysis, and electronic health (2001-2019) and COVID-19, artificial intelligence, digital health, and mental health (2020-2022). Although psychology research increased, studies on children's mental health and middle-aged and older adults' rehabilitation were limited.</p><p><strong>Conclusions: </strong>We identified the latest trends in telemedicine res
{"title":"Telemedicine Research Trends in 2001-2022 and Research Cooperation Between China and Other Countries Before and After the COVID-19 Pandemic: Bibliometric Analysis.","authors":"Hanlin Feng, Karin Kurata, Jianfei Cao, Kageyama Itsuki, Makoto Niwa, Atsushi Aoyama, Kota Kodama","doi":"10.2196/40801","DOIUrl":"10.2196/40801","url":null,"abstract":"<p><strong>Background: </strong>Advancements in technology have overcome geographical barriers, making telemedicine, which offers remote emergency services, healthcare, and medication guidance, increasingly popular. COVID-19 restrictions amplified its global importance by bridging distances.</p><p><strong>Objective: </strong>This study aimed to analyze Chinese and global literature data, present new global telemedicine research trends, and clarify the development potential, collaborations, and deficiencies in China's telemedicine research.</p><p><strong>Methods: </strong>We conducted bibliometrics and network analyses on relevant documents from the Web of Science database from 2001 to 2022. Data collection was completed on October 30, 2023. Considering COVID-19's impact, 2020 was used as a baseline, dividing the data into 2 periods: 2001-2019 and 2020-2022. The development potential was determined based on publication trends. An international coauthorship network analysis identified collaboration statuses and potential. Co-occurrence analysis was conducted for China and the world.</p><p><strong>Results: </strong>We identified 25,333 telemedicine-related research papers published between 2001 and 2022, with a substantial increase during the COVID-19 period (2020-2022), particularly in China (1.93-fold increase), moving its global publication rank from tenth to sixth. The United States, the United Kingdom, and Australia contributed 62.96% of the literature, far ahead of China's 3.90%. Globally, telemedicine research increased significantly post-2020. Between 2001 and 2019, the United States and Australia were central in coauthor networks; post-2020, the United States remained the largest node. Network hubs included the United States, the United Kingdom, Australia, and Canada. Keyword co-occurrence analysis revealed 5 global clusters from 2001 to 2019 (system technology, health care applications, mobile health, mental health, and electronic health) and 2020 to 2022 (COVID-19, children's mental health, artificial intelligence, digital health, and rehabilitation of middle-aged and older adults). In China, the research trends aligned with global patterns, with rapid growth post-2020. From 2001 to 2019, China cooperated closely with Indonesia, India, Japan, Taiwan, and South Korea. From 2020 to 2022, cooperation expanded to Japan, Singapore, Malaysia, and South Korea, as well as Saudi Arabia, Egypt, South Africa, Ghana, Lebanon, and other African and Middle Eastern countries. Chinese keyword co-occurrence analysis showed focus areas in system technology, health care applications, mobile health, big data analysis, and electronic health (2001-2019) and COVID-19, artificial intelligence, digital health, and mental health (2020-2022). Although psychology research increased, studies on children's mental health and middle-aged and older adults' rehabilitation were limited.</p><p><strong>Conclusions: </strong>We identified the latest trends in telemedicine res","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e40801"},"PeriodicalIF":1.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11399753/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142114659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christine Ou, Kathryn Corby, Kelsey Booth, Hui-Hui Ou
Background: The declaration of the COVID-19 pandemic led to public health restrictions that impacted the lives of people across the globe. Parents were particularly burdened with balancing multiple responsibilities, such as working from home while caring for and educating their children. Alcohol use among parents is an area that warrants further exploration.
Objective: This study aimed to investigate patterns of parental alcohol consumption during the COVID-19 pandemic, focusing on relative changes in the frequency and quantity of alcohol use compared to prepandemic use, nonparent adult samples, or both.
Methods: A scoping review informed by the methodology of Arksey and O'Malley explored patterns of parental alcohol consumption during the COVID-19 pandemic. Searches were conducted in CINAHL, Ovid MEDLINE, PsycINFO, and Web of Science. Search terms were created using the Joanna Briggs Institute framework of Population, Concept, and Context, with the population being parents and the concept being alcohol consumption during the COVID-19 pandemic.
Results: The database search yielded 3568 articles, which were screened for eligibility. Of the 3568 articles, 40 (1.12%) met the inclusion criteria and were included in the scoping review. Findings indicated the following: (1) having children at home was a factor associated with parental patterns of alcohol use; (2) mixed findings regarding gender-related patterns of alcohol consumption; and (3) linkages between parental patterns of alcohol use and mental health symptoms of stress, depression, and anxiety.
Conclusions: This scoping review revealed heterogeneous patterns in parental alcohol use across sociocultural contexts during the COVID-19 pandemic. Given the known harms of alcohol use, it is worthwhile for clinicians to assess parental drinking patterns and initiate conversations regarding moderation in alcohol use.
{"title":"Parental Patterns of Alcohol Consumption During the COVID-19 Pandemic: Scoping Review.","authors":"Christine Ou, Kathryn Corby, Kelsey Booth, Hui-Hui Ou","doi":"10.2196/48339","DOIUrl":"10.2196/48339","url":null,"abstract":"<p><strong>Background: </strong>The declaration of the COVID-19 pandemic led to public health restrictions that impacted the lives of people across the globe. Parents were particularly burdened with balancing multiple responsibilities, such as working from home while caring for and educating their children. Alcohol use among parents is an area that warrants further exploration.</p><p><strong>Objective: </strong>This study aimed to investigate patterns of parental alcohol consumption during the COVID-19 pandemic, focusing on relative changes in the frequency and quantity of alcohol use compared to prepandemic use, nonparent adult samples, or both.</p><p><strong>Methods: </strong>A scoping review informed by the methodology of Arksey and O'Malley explored patterns of parental alcohol consumption during the COVID-19 pandemic. Searches were conducted in CINAHL, Ovid MEDLINE, PsycINFO, and Web of Science. Search terms were created using the Joanna Briggs Institute framework of Population, Concept, and Context, with the population being parents and the concept being alcohol consumption during the COVID-19 pandemic.</p><p><strong>Results: </strong>The database search yielded 3568 articles, which were screened for eligibility. Of the 3568 articles, 40 (1.12%) met the inclusion criteria and were included in the scoping review. Findings indicated the following: (1) having children at home was a factor associated with parental patterns of alcohol use; (2) mixed findings regarding gender-related patterns of alcohol consumption; and (3) linkages between parental patterns of alcohol use and mental health symptoms of stress, depression, and anxiety.</p><p><strong>Conclusions: </strong>This scoping review revealed heterogeneous patterns in parental alcohol use across sociocultural contexts during the COVID-19 pandemic. Given the known harms of alcohol use, it is worthwhile for clinicians to assess parental drinking patterns and initiate conversations regarding moderation in alcohol use.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e48339"},"PeriodicalIF":1.9,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384174/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142074535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stephanie T Lanza, Courtney Whetzel, Sandesh Bhandari
Background: There is evidence that anxiety and stress increased among college students during the COVID-19 pandemic. However, less is known about daily experiences of affect, worry, substance use behaviors, experiences of pleasure, concern over food security, experiences of bias or discrimination, feelings of belongingness, and other indicators of well-being and how they vary across days in this population.
Objective: This study surveyed a wide range of indicators of health and well-being in daily life over 21 days with a sample of college students in a large university system in the United States during the pandemic. The overall variance in each daily measure was partitioned to reflect the proportion due to (1) between-person differences versus (2) within-person, day-to-day variability. This is important because measures that vary primarily due to between-person differences may be more amenable to interventions that target particular students, whereas measures that vary more due to day-to-day variability may be more amenable to interventions that target day-level contextual factors.
Methods: A sample of 2068 young adult college students (aged 18-24, mean 19.8, SD 1.3 years; 66.6% women) completed a baseline survey; 97.3% (n=2012) then completed up to 21 consecutive daily surveys that assessed a comprehensive set of daily markers of health, behavior, and well-being. The daily diary study produced a total of 33,722 person-days.
Results: Among all person-days, a minority were substance use days (eg, 14.5% of days involved alcohol use, 5.6% vaping, and 5.5% cannabis). Experiences of pleasure were reported on most (73.5%) days. Between-person differences explained more than 50% of the variance in numerous indicators of health and well-being, including daily vaping, cannabis use, other illicit substance use, experiences of bias or discrimination, positive affect, negative affect, worry, food insecurity, and feelings of belonging at the university. In contrast, within-person differences explained more than 50% of the variance in daily alcohol use, cigarette use, stress, experiences of pleasure, where the student slept last night, and physical activity.
Conclusions: College student health and well-being are multifaceted, with some aspects likely driven by person-level characteristics and experiences and other aspects by more dynamic, contextual risk factors that occur in daily life. These findings implicate services and interventions that should target individual students versus those that should target days on which students are at high risk for poor experiences or behaviors.
{"title":"Health and Well-Being Among College Students in the United States During the COVID-19 Pandemic: Daily Diary Study.","authors":"Stephanie T Lanza, Courtney Whetzel, Sandesh Bhandari","doi":"10.2196/45689","DOIUrl":"10.2196/45689","url":null,"abstract":"<p><strong>Background: </strong>There is evidence that anxiety and stress increased among college students during the COVID-19 pandemic. However, less is known about daily experiences of affect, worry, substance use behaviors, experiences of pleasure, concern over food security, experiences of bias or discrimination, feelings of belongingness, and other indicators of well-being and how they vary across days in this population.</p><p><strong>Objective: </strong>This study surveyed a wide range of indicators of health and well-being in daily life over 21 days with a sample of college students in a large university system in the United States during the pandemic. The overall variance in each daily measure was partitioned to reflect the proportion due to (1) between-person differences versus (2) within-person, day-to-day variability. This is important because measures that vary primarily due to between-person differences may be more amenable to interventions that target particular students, whereas measures that vary more due to day-to-day variability may be more amenable to interventions that target day-level contextual factors.</p><p><strong>Methods: </strong>A sample of 2068 young adult college students (aged 18-24, mean 19.8, SD 1.3 years; 66.6% women) completed a baseline survey; 97.3% (n=2012) then completed up to 21 consecutive daily surveys that assessed a comprehensive set of daily markers of health, behavior, and well-being. The daily diary study produced a total of 33,722 person-days.</p><p><strong>Results: </strong>Among all person-days, a minority were substance use days (eg, 14.5% of days involved alcohol use, 5.6% vaping, and 5.5% cannabis). Experiences of pleasure were reported on most (73.5%) days. Between-person differences explained more than 50% of the variance in numerous indicators of health and well-being, including daily vaping, cannabis use, other illicit substance use, experiences of bias or discrimination, positive affect, negative affect, worry, food insecurity, and feelings of belonging at the university. In contrast, within-person differences explained more than 50% of the variance in daily alcohol use, cigarette use, stress, experiences of pleasure, where the student slept last night, and physical activity.</p><p><strong>Conclusions: </strong>College student health and well-being are multifaceted, with some aspects likely driven by person-level characteristics and experiences and other aspects by more dynamic, contextual risk factors that occur in daily life. These findings implicate services and interventions that should target individual students versus those that should target days on which students are at high risk for poor experiences or behaviors.</p>","PeriodicalId":51757,"journal":{"name":"Interactive Journal of Medical Research","volume":"13 ","pages":"e45689"},"PeriodicalIF":1.9,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11380054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}