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BackgroundPhysical inactivity and a poor diet are modifiable behaviors that contribute to obesity. Obesity is a well-recognized risk factor for chronic diseases, including diabetes. Mobile health (mHealth) apps can play an important adjuvant role in preventing and treating chronic diseases and promoting positive health behavior change among people with obesity, and eHealth literacy skills have the potential to impact mHealth app use. ObjectiveThe purpose of this study was to explore the associations between the 2 dimensions, access and application, of eHealth literacy skills and mHealth app use among US adults (≥18 years of age) with obesity (BMI ≥30 kg/m2). MethodsData were obtained from February to June 2020 using the Health Information National Trends Survey 5. A total of 1079 respondents met the inclusion criteria of adults with obesity and owners of smartphones. Individual associations between mHealth app use and sociodemographic variables were explored using weighted chi-square and 2-tailed t tests. A multivariable weighted logistic regression model was fitted, and adjusted odds ratios (ORs) of using mHealth apps with corresponding 95% CIs were reported across multiple sociodemographic variables. An Ising model-weighted network visualization was produced. A receiver operating characteristic curve was calculated, and the area under the curve was reported with the corresponding Delong 95% CI. ResultsA majority of respondents were female (550/923, 59.6%) or non-Hispanic White (543/923, 58.8%). Individuals in households earning less than US $50,000 comprised 41.4% (382/923) of the sample. All sociodemographic variables were found to be univariately significant at the 5% level, except employment and region. Results from the multivariable weighted logistic regression model showed that the adjusted odds of using an mHealth app are 3.13 (95% CI 1.69-5.80) and 2.99 (95% CI 1.67-5.37) times higher among those with an access eHealth literacy skill of using an electronic device to look for health or medical information for themselves and an application eHealth literacy skill of using electronic communications with a doctor or doctor’s office, respectively. Several sociodemographic variables were found to be significant, such as education, where adjusted ORs comparing subgroups to the lowest educational attainment were substantial (ORs ≥7.77). The network visualization demonstrated that all eHealth literacy skills and the mHealth app use variable were positively associated to varying degrees. ConclusionsThis work provides an initial understanding of mHealth app use and eHealth literacy skills among people with obesity, identifying people with obesity subpopulations who are at risk of a digital health divide. Future studies should identify equitable solutions for people with obesity (as well as other groups) and their use of mHealth apps.

BackgroundSome latest estimates show that approximately 95% of Americans own a smartphone with numerous functions such as SMS text messaging, the ability to take high-resolution pictures, and mobile software apps. Mobile health apps focusing on vaccination and immunization have proliferated in the digital health information technology market. Mobile health apps have the potential to positively affect vaccination coverage. However, their general functionality, user and disease coverage, and exchange of information have not been comprehensively studied or evaluated computationally. ObjectiveThe primary aim of this study is to develop a computational method to explore the descriptive, usability, information exchange, and privacy features of vaccination apps, which can inform vaccination app design. Furthermore, we sought to identify potential limitations and drawbacks in the apps’ design, readability, and information exchange abilities. MethodsA comprehensive codebook was developed to conduct a content analysis on vaccination apps’ descriptive, usability, information exchange, and privacy features. The search and selection process for vaccination-related apps was conducted from March to May 2019. We identified a total of 211 apps across both platforms, with iOS and Android representing 62.1% (131/211) and 37.9% (80/211) of the apps, respectively. Of the 211 apps, 119 (56.4%) were included in the final study analysis, with 42 features evaluated according to the developed codebook. The apps selected were a mix of apps used in the United States and internationally. Principal component analysis was used to reduce the dimensionality of the data. Furthermore, cluster analysis was used with unsupervised machine learning to determine patterns within the data to group the apps based on preselected features. ResultsThe results indicated that readability and information exchange were highly correlated features based on principal component analysis. Of the 119 apps, 53 (44.5%) were iOS apps, 55 (46.2%) were for the Android operating system, and 11 (9.2%) could be found on both platforms. Cluster 1 of the k-means analysis contained 22.7% (27/119) of the apps; these were shown to have the highest percentage of features represented among the selected features. ConclusionsWe conclude that our computational method was able to identify important features of vaccination apps correlating with end user experience and categorize those apps through cluster analysis. Collaborating with clinical health providers and public health officials during design and development can improve the overall functionality of the apps.

This scoping review explores the potential of electronic health records (EHR)-based studies to characterize long COVID. We screened all peer-reviewed publications in the English language from PubMed/MEDLINE, Scopus, and Web of Science databases until 14 September 2023, to identify the studies that defined or characterized long COVID based on data sources that utilized EHR in the United States, regardless of study design. We identified only 17 articles meeting the inclusion criteria. Respiratory conditions were consistently significant in all studies, followed by poor well-being features (n = 14, 82%) and cardiovascular conditions (n = 12, 71%). Some articles (n = 7, 41%) used a long COVID-specific marker to define the study population, relying mainly on ICD-10 codes and clinical visits for post-COVID-19 conditions. Among studies exploring plausible long COVID (n = 10, 59%), the most common methods were RT-PCR and antigen tests. The time delay for EHR data extraction post-test varied, ranging from four weeks to more than three months; however, most studies considering plausible long COVID used a waiting period of 28 to 31 days. Our findings suggest a limited utilization of EHR-derived data sources in defining long COVID, with only 59% of these studies incorporating a validation step. [ABSTRACT FROM AUTHOR]

The Paper Chase model is a synchronous collaborative approach to manuscript development. Through a structured and team-based design, authors participate in a "marathon" of writing, editing, revising, and submitting their publications within a specified period. This active-learning approach is considered a high-impact practice by engaging students in research dissemination through a collaborative project. This study sought to evaluate the feasibility and acceptability of a virtual Paper Chase exercise. We conducted the Paper Chase with six teams led by multidisciplinary faculty (with 24 undergraduate students and four graduate students). All participants were given pre-and post-surveys, with both open- and closed-ended questions. Results indicated that the process increased cooperative and problem-solving components of group work attitudes, increased participants' confidence in writing skills, increased understanding of research processes and that participants appreciated putting their skills immediately into practice. Participants identified strengths as well as opportunities for improvement in online modules and facilitation. The process was effective in that half of the manuscripts were submitted to peer-reviewed outlets within 90 days of the event. The positive evidence for learning in the virtual Paper Chase model supports future applications and may strengthen the involvement of students in research dissemination. Additional research may expand upon the findings by assessing group work dynamics, quality of final products, and conducting the process in a hybrid model. [ABSTRACT FROM AUTHOR]

A 12-year-old girl admitted to a hospital with fever, vomiting, and loss of consciousness died from meningococcal encephalitis. This is a severe infection of the brain caused by a bacteria called Neisseria meningitidis. This devastating disease is one reason why the meningococcal vaccine was developed.

As competition for teaching positions continues to increase, educators have learned a valuable lesson from corporate America -- professional portfolios can be the deciding factor in obtaining employment, especially for the beginning teacher. An effective portfolio provides the means for applicants to display their very best work and document special talents, abilities, and accomplishments while demonstrating their enthusiasm and commitment to the teaching profession. This article provides preservice and inservice teacher the information needed to create a compelling professional portfolio. Portfolio contents are discussed using a checklist of suggested items and strategies for collecting and organizing portfolio contents are included., As competition for teaching positions continues to increase, educators have learned a valuable lesson from corporate America -- professional portfolios can be the deciding factor in obtaining employment, especially for [...]

Wukovits, John. One Square Mile of Hell: The Battle for Tarawa. New York: New American Library, 2006. 320pp. $15 One Square Mile of Hell relates the story of the November [...]