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OBJECTIVE: To investigate the feasibility of pre- and post-encounter patient-reported outcome (PRO) measure collection within an outpatient integrative health and medicine (IHM) clinic and to characterize factors associated with successful completion. METHODS: We conducted a retrospective review of 27,464 outpatient IHM encounters including 9,520 chiropractic; 8,237 acupuncture; 5,847 massage; 2,345 IHM consultation; and 1,515 osteopathic manipulation treatment encounters at four clinics offering IHM over 18 months. Patients were asked to complete paper questionnaires rating pain, anxiety, and stress from 0-10 immediately pre- and post-encounter. Generalized linear mixed effect regression models were used to examine the relationship between demographic, clinical, and operational covariates and completing (1) pre-encounter and (2) paired (i.e., pre and post) PROs. RESULTS: Patients (N = 5587, mean age 49 years, 74% white, 77% female) generally presented for musculoskeletal conditions (81.7%), with a chief complaint of pain (55.1%). 21,852 (79.6%) encounters were among patients who completed pre-encounter PROs; 11,709/21,852 (53.6%) completed subsequent post-encounter PROs. Odds of PRO completion were more impacted by provider, operational, and clinical-level factors than patient factors. Covariates associated with increased odds of pre-encounter PRO completion included being female, having additional IHM encounters, and having a pain or anxiety complaint. Covariates associated with increased odds of paired PRO completion included being aged 31-40 vs. 51-60 years and having additional IHM encounters. CONCLUSION: Implementing a paper-based PRO collection system in outpatient IHM is feasible; however, collecting post-encounter PROs was challenging. Future endeavors should leverage the electronic health record and patient portals to optimize PRO collection and engage patients and clinical providers.

Preprints, versions of scientific manuscripts that precede peer review, are growing in popularity. They offer an opportunity to democratize and accelerate research, as they have no publication costs or a lengthy peer review process. Preprints are often later published in peer-reviewed venues, but these publications and the original preprints are frequently not linked in any way. To this end, we developed a tool, PreprintMatch, to find matches between preprints and their corresponding published papers, if they exist. This tool outperforms existing techniques to match preprints and papers, both on matching performance and speed. PreprintMatch was applied to search for matches between preprints (from bioRxiv and medRxiv), and PubMed. The preliminary nature of preprints offers a unique perspective into scientific projects at a relatively early stage, and with better matching between preprint and paper, we explored questions related to research inequity. We found that preprints from low income countries are published as peer-reviewed papers at a lower rate than high income countries (39.6% and 61.1%, respectively), and our data is consistent with previous work that cite a lack of resources, lack of stability, and policy choices to explain this discrepancy. Preprints from low income countries were also found to be published quicker (178 vs 203 days) and with less title, abstract, and author similarity to the published version compared to high income countries. Low income countries add more authors from the preprint to the published version than high income countries (0.42 authors vs 0.32, respectively), a practice that is significantly more frequent in China compared to similar countries. Finally, we find that some publishers publish work with authors from lower income countries more frequently than others.

Citations play an important role in researchers careers as a key factor in evaluation of scientific impact. Many anecdotes advice authors to exploit this fact and cite prospective reviewers to try obtaining a more positive evaluation for their submission. In this work, we investigate if such a citation bias actually exists: Does the citation of a reviewers own work in a submission cause them to be positively biased towards the submission? In conjunction with the review process of two flagship conferences in machine learning and algorithmic economics, we execute an observational study to test for citation bias in peer review. In our analysis, we carefully account for various confounding factors such as paper quality and reviewer expertise, and apply different modeling techniques to alleviate concerns regarding the model mismatch. Overall, our analysis involves 1,314 papers and 1,717 reviewers and detects citation bias in both venues we consider. In terms of the effect size, by citing a reviewers work, a submission has a non-trivial chance of getting a higher score from the reviewer: an expected increase in the score is approximately 0.23 on a 5-point Likert item. For reference, a one-point increase of a score by a single reviewer improves the position of a submission by 11% on average.

Medical natural language processing (NLP) systems are a key enabling technology for transforming Big Data from clinical report repositories to information used to support disease models and validate intervention methods. However, current medical NLP systems fall considerably short when faced with the task of logically interpreting clinical text. In this paper, we describe a framework inspired by mechanisms of human cognition in an attempt to jump the NLP performance curve. The design centers on a hierarchical semantic compositional model (HSCM), which provides an internal substrate for guiding the interpretation process. The paper describes insights from four key cognitive aspects: semantic memory, semantic composition, semantic activation, and hierarchical predictive coding. We discuss the design of a generative semantic model and an associated semantic parser used to transform a free-text sentence into a logical representation of its meaning. The paper discusses supportive and antagonistic arguments for the key features of the architecture as a long-term foundational framework.

Quantifying the colors of objects is useful in a wide range of applications, including medical diagnosis, agricultural monitoring, and food safety. Accurate colorimetric measurement of objects is a laborious process normally performed through a color matching test in the laboratory. A promising alternative is to use digital images for colorimetric measurement, due to their portability and ease of use. However, image-based measurements suffer from errors caused by the non-linear image formation process and unpredictable environmental lighting. Solutions to this problem often perform relative color correction among multiple images through discrete color reference boards, which may yield biased results due to the lack of continuous observation. In this paper, we propose a smartphone-based solution, that couples a designated color reference board with a novel color correction algorithm, to achieve accurate and absolute color measurements. Our color reference board contains multiple color stripes with continuous color sampling at the sides. A novel correction algorithm is proposed to utilize a first-order spatial varying regression model to perform the color correction, which leverages both the absolute color magnitude and scale to maximize the correction accuracy. The proposed algorithm is implemented as a "human-in-the-loop" smartphone application, where users are guided by an augmented reality scheme with a marker tracking module to take images at an angle that minimizes the impact of non-Lambertian reflectance. Our experimental results show that our colorimetric measurement is device independent and can reduce up to 90% color variance for images collected under different lighting conditions. In the application of reading pH values from test papers, we show that our system performs 200% better than human reading. The designed color reference board, the correction algorithm, and our augmented reality guiding approach form an integrated system as a novel solution to measure color with increased accuracy. This technique has the flexibility to improve color reading performance in systems beyond existing applications, evidenced by both qualitative and quantitative experiments on example applications such as pH-test reading.

The Anticoagulation Length of Therapy and Risk of New Adverse Events In Venous Thromboembolism (ALTERNATIVE) study was designed to compare the benefits and harms of different treatment options for extended treatment of venous thromboembolism (VTE). In this paper, we describe the study cohort, survey data collection, and preliminary results. We identified 39,605 adult patients (age ≥ 18 years) from two large integrated health care delivery systems who were diagnosed with incident VTE and received initial anticoagulation therapy of 3 months or longer. A subset of the cohort (12,737) was invited to participate in a survey. Surveys were completed in English, Spanish or Mandarin via a mailed questionnaire, an online secure web link, or telephone. The survey domains included demographics, personal medical history, anticoagulant treatment history, anticoagulant treatment satisfaction, health-related quality of life and health literacy. A total of 5,017 patients participated in the survey for an overall response rate of 39.4%. The mean (SD) age of the survey respondents was 63.0 (14.5) years and self-reported race was 76.0% White/European, 11.1% Black/African American, and 3.8% Asian/Pacific Islander and 14.0% reported Hispanic ethnicity. Sixty percent of respondents completed the web survey, while 29.0% completed the mail-in paper survey, and 11.0% completed the survey via telephone. The ALTERNATIVE Study will address knowledge gaps by comparing several treatment alternatives for the extended management of VTE so that this information could be used by patients and clinicians to make more informed, patient-centered treatment choices.

The question of whether it is appropriate to attribute authorship to deceased individuals of original studies in the biomedical literature is contentious. Authorship guidelines utilized by journals do not provide a clear consensus framework that is binding on those in the field. To guide and inform the implementation of authorship frameworks it would be useful to understand the extent of the practice in the scientific literature, but studies that have systematically quantified the prevalence of this phenomenon in the biomedical literature have not been performed to date. To address this issue, we quantified the prevalence of publications by deceased authors in the biomedical literature from the period 1990-2020. We screened 2,601,457 peer-reviewed papers from the full text Europe PubMed Central database. We applied natural language processing, stringent filtering and manual curation to identify a final set of 1,439 deceased authors. We then determined these authors published a total of 38,907 papers over their careers with 5,477 published after death. The number of deceased publications has been growing rapidly, a 146-fold increase since the year 2000. This rate of increase was still significant when accounting for the growing total number of publications and pool of authors. We found that more than 50% of deceased author papers were first submitted after the death of the author and that over 60% of these papers failed to acknowledge the deceased authors status. Most deceased authors published less than 10 papers after death but a small pool of 30 authors published significantly more. A pool of 266 authors published more than 90% of their total publications after death. Our analysis indicates that the attribution of deceased authorship in the literature is not an occasional occurrence but a burgeoning trend. A consensus framework to address authorship by deceased scientists is warranted.

Inconsistent use of terminology among diverse stakeholders hinders effective communication in micronutrient programs, especially large-scale food fortification (LSFF) which involves stakeholders from different sectors. To align the terminology use, the Micronutrient Data Innovation Alliance (DInA) of the Micronutrient Forum (MNF) created a lexicon of terms related to LSFF and other micronutrient programs. The purpose of this lexicon is to establish a central repository of consensus definitions of key terms to facilitate communication among diverse stakeholders involved in micronutrient programs including public and private sectors, donor agencies, food industries, academic institutions, etc. This paper describes the methodology of lexicon development. Important terms related to micronutrient programs were compiled from multiple sources, including United Nations agencies, program implementation and technical support agencies, relevant websites, and scientific literature. The selection of terms was guided by key micronutrient interventions (fortification, supplementation, dietary diversification) and the program cycle (assessment, planning, implementation, monitoring and evaluation). Definitions of terms were identified from these references and checked for consistency across different sources. For terms with multiple definitions, a modified Delphi method was applied to harmonize the definitions. The first draft lexicon (n = 113 terms) was reviewed by six experts from the University of California, Davis (UCD) and MNF, and second draft (n = 115 terms) was shared with 24 global micronutrient experts for feedback. Fifty-four terms were found to have multiple definitions. Of which, minor modification was made for 12-terms with nominal difference and remaining 42-terms were shared with over 140 micronutrient-experts disseminated via an online survey through newsletters and emails to solicit experts opinions on the most appropriate definition or a modified one. Nineteen legal terms and 83 micronutrient terms (n = 102 terms) were subsequently added. Overall, 39 experts from diverse areas of expertise (LSFF, micronutrient program planning and implementation, surveys and research, policy development, food industry regulations, food safety, and public health nutrition) participated in the online survey. The terms with >75% agreement among experts were considered as final, while the remaining were reviewed again by experts from UCD and MNF until consensus was reached on harmonized definitions. The current lexicon is available online at the DInA-website. and contains 217 terms and will be maintained as a living document. The lexicon will facilitate the ability of key stakeholders of micronutrient programs to evaluate and compare program performance in order to make informed decisions on how to ensure future progress in reducing micronutrient deficiencies.

The COVID-19 pandemic has negatively impacted the mental health and wellbeing of post-secondary students. Resilience has been found to serve as a protective factor against mental distress among students during the pandemic. Despite the plethora of research that exists on post-secondary students during this crisis, most studies exploring students health and resilience are quantitative and lack diversity. To date, the lived experiences of health-related quality of life (HRQOL) and resilience among graduate students representing diversity in age, gender, ethnicity, parental status, university, degree, and faculty during the COVID-19 pandemic remain unknown. As a part of a larger study, the purpose of this qualitative paper was to understand the lived experiences of resilience and HRQOL among a diverse sample of graduate students approximately 18 months into the COVID-19 pandemic in Ontario, Canada. A total of 14 students participated in semi-structured interviews exploring HRQOL domains, factors that supported/undermined participants resilience, challenges/barriers to being resilient, and participants inner strength. Thematic analysis revealed 5 themes: (1) cultural influences on resilience; (2) the role of privilege/power in shaping resilience; (3) how life stage and past experiences support resilience; (4) how the COVID-19 pandemic has undermined the resilience of equity-deserving groups; and (5) the role of disability/chronic pain. This work presents a unique dichotomy between how the COVID-19 pandemic has disrupted the lives of some graduate students, while simultaneously creating opportunities for others to thrive. Findings from this work underscore the importance of creating inclusive and accessible educational spaces to support graduate students resilience and HRQOL currently, and in times of crisis.

The rapid advances in Generative AI tools have produced both excitement and worry about how AI will impact academic writing. However, little is known about what norms are emerging around AI use in manuscript preparation or how these norms might be enforced. We address both gaps in the literature by conducting a survey of 271 academics about whether it is necessary to report ChatGPT use in manuscript preparation and by running GPT-modified abstracts from 2,716 published papers through a leading AI detection software to see if these detectors can detect different AI uses in manuscript preparation. We find that most academics do not think that using ChatGPT to fix grammar needs to be reported, but detection software did not always draw this distinction, as abstracts for which GPT was used to fix grammar were often flagged as having a high chance of being written by AI. We also find disagreements among academics on whether more substantial use of ChatGPT to rewrite text needs to be reported, and these differences were related to perceptions of ethics, academic role, and English language background. Finally, we found little difference in their perceptions about reporting ChatGPT and research assistant help, but significant differences in reporting perceptions between these sources of assistance and paid proofreading and other AI assistant tools (Grammarly and Word). Our results suggest that there might be challenges in getting authors to report AI use in manuscript preparation because (i) there is not uniform agreement about what uses of AI should be reported and (ii) journals might have trouble enforcing nuanced reporting requirements using AI detection tools.

ObjectiveThe Mexican government has pursued multiple initiatives to improve healthcare coverage and financial protection. Yet, out-of-pocket health spending and use of private sector providers in Mexico remains high. In this paper, we sought to describe the characteristics of public and private healthcare users, describe recent visit quality across provider types, and to assess whether perceiving the public healthcare sector as poor quality is associated with private health sector use.Methods and findingsWe analyzed the cross-sectional People's Voice Survey conducted from December 2022 to January 2023. We used Chi-square tests to compare contextual, individual, and need-for-care factors and ratings of most recent visits between users of public (social security and other public providers) and private sector providers (stand-alone private providers and providers adjacent to pharmacies). We used a multivariable Poisson regression model to assess associations between low ratings of public healthcare sources and the use of private care. Among the 811 respondents with a healthcare visit in the past year, 31.2% used private sources. Private healthcare users were more educated and had higher incomes than public healthcare users. Quality of most recent visit was rated more highly in private providers (70.2% rating the visit as excellent or very good for stand-alone private providers and 54.3% for pharmacy-adjacent doctors) compared to social security (41.6%) and other public providers (46.6%). Those who perceived public health institutions as low quality had a higher probability of seeking private healthcare.ConclusionUsers rated public care visits poorly relative to private care; at the population level, perceptions of poor quality care may drive private care use and hence out-of-pocket costs. Improving public healthcare quality is necessary to ensure universal health coverage.

Authoring of help content within educational technologies is labor intensive, requiring many iterations of content creation, refining, and proofreading. In this paper, we conduct an efficacy evaluation of ChatGPT-generated help using a 3 x 4 study design (N = 274) to compare the learning gains of ChatGPT to human tutor-authored help across four mathematics problem subject areas. Participants are randomly assigned to one of three hint conditions (control, human tutor, or ChatGPT) paired with one of four randomly assigned subject areas (Elementary Algebra, Intermediate Algebra, College Algebra, or Statistics). We find that only the ChatGPT condition produces statistically significant learning gains compared to a no-help control, with no statistically significant differences in gains or time-on-task observed between learners receiving ChatGPT vs human tutor help. Notably, ChatGPT-generated help failed quality checks on 32% of problems. This was, however, reducible to nearly 0% for algebra problems and 13% for statistics problems after applying self-consistency, a hallucination mitigation technique for Large Language Models.

Dynamic functional connectivity investigates how the interactions among brain regions vary over the course of an fMRI experiment. Such transitions between different individual connectivity states can be modulated by changes in underlying physiological mechanisms that drive functional network dynamics, e.g., changes in attention or cognitive effort. In this paper, we develop a multi-subject Bayesian framework where the estimation of dynamic functional networks is informed by time-varying exogenous physiological covariates that are simultaneously recorded in each subject during the fMRI experiment. More specifically, we consider a dynamic Gaussian graphical model approach where a non-homogeneous hidden Markov model is employed to classify the fMRI time series into latent neurological states. We assume the state-transition probabilities to vary over time and across subjects as a function of the underlying covariates, allowing for the estimation of recurrent connectivity patterns and the sharing of networks among the subjects. We further assume sparsity in the network structures via shrinkage priors, and achieve edge selection in the estimated graph structures by introducing a multi-comparison procedure for shrinkage-based inferences with Bayesian false discovery rate control. We evaluate the performances of our method vs alternative approaches on synthetic data. We apply our modeling framework on a resting-state experiment where fMRI data have been collected concurrently with pupillometry measurements, as a proxy of cognitive processing, and assess the heterogeneity of the effects of changes in pupil dilation on the subjects propensity to change connectivity states. The heterogeneity of state occupancy across subjects provides an understanding of the relationship between increased pupil dilation and transitions toward different cognitive states.

BACKGROUND: 1.8 million Veterans are estimated to need legal services, such as for housing eviction prevention, discharge upgrades, and state and federal Veterans benefits. While having ones legal needs met is known to improve ones health and its social determinants, many Veterans legal needs remain unmet. Public Law 116-315 enacted in 2021 authorizes VA to fund legal services for Veterans (LSV) by awarding grants to legal service providers including nonprofit organizations and law schools legal assistance programs. This congressionally mandated LSV initiative will award grants to about 75 competitively selected entities providing legal services. This paper describes the protocol for evaluating the initiative. The evaluation will fulfill congressional reporting requirements, and inform continued implementation and sustainment of LSV over time. METHODS: Our protocol calls for a prospective, mixed-methods observational study with a repeated measures design, aligning to the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) and Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) frameworks. In 2023, competitively selected legal services-providing organizations will be awarded grants to implement LSV. The primary outcome will be the number of Veterans served by LSV in the 12 months after the awarding of the grant. The evaluation has three Aims. Aim 1 will focus on measuring primary and secondary LSV implementation outcomes aligned to RE-AIM. Aim 2 will apply the mixed quantitative-qualitative Matrixed Multiple Case Study method to identify patterns in implementation barriers, enablers, and other i-PARIHS-aligned factors that relate to observed outcomes. Aim 3 involves a mixed-methods economic evaluation to understand the costs and benefits of LSV implementation. DISCUSSION: The LSV initiative is a new program that VA is implementing to help Veterans who need legal assistance. To optimize ongoing and future implementation of this program, it is important to rigorously evaluate LSVs outcomes, barriers and enablers, and costs and benefits. We have outlined the protocol for such an evaluation, which will lead to recommending strategies and resource allocation for VAs LSV implementation.

ObjectivesSurveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children.MethodsThis cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations.ResultsWe developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses.ConclusionsThe combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.

BACKGROUND: The gut-brain axis involves bidirectional communication between the gut-microbiota and central nervous system. This study aimed to investigate whether probiotics and/or prebiotics, known as Microbiome-targeted Therapies (MTTs), improve cognition and prevent postoperative cognitive dysfunction (POCD). METHODS: Relevant animal and human studies were identified using a systematic database search (PubMed, EMBASE, Cochrane Library, and Web of Science), focusing on the effects of MTTs on inflammation, perioperative and non-perioperative cognitive impairment. Screening and data extraction were conducted by two independent reviewers. The Risk of bias was assessed using the SYRCLEs risk of bias tool for animal studies. The revised Cochrane risk of bias tool (RoB 2) was used for human studies. RESULTS: A total of 24 articles were selected; 16 of these involved animal studies, and 8 described studies in humans. In these papers, the use of MTTs consistently resulted in decreased inflammation in perioperative and non-perioperative settings. Out of 16 animal studies, 5 studies (2 associated with delirium and 3 studies related to POCD) were conducted in a perioperative setting. MTTs improved perioperative cognitive behavior and reduced inflammation in all 5 animal studies. Eleven animal studies were conducted in a non-perioperative setting. In all of these studies, MTTs showed improvement in learning and memory function. MTTs showed a positive effect on levels of pro-inflammatory cytokines and biomarkers related to cognitive function. Among the 8 human studies, only one study examined the effects of perioperative MTTs on cognitive function. This study showed a reduced incidence of POCD along with improved cognitive function. Of the remaining 7 studies, 6 suggested that MTTs improved behavioral test results and cognition in non-perioperative environments. One study failed to show any significant differences in memory, biomarkers of inflammation, or oxidative factors. CONCLUSION: In the studies we examined, most showed that MTTs decrease inflammation by down-regulating inflammatory cytokines and oxidative stress in both perioperative and non-perioperative settings. In general, MTTs also seem to have a positive effect on cognition through neural, immune, endocrine, and metabolic pathways. However, these effects have not yet resulted in a consensus regarding preventative strategies or treatments. Based on these current research results, MTTs could be a potential new preventative strategy for cognitive impairment after surgery.

The spread of misinformation and conspiracies has been an ongoing issue since the early stages of the internet era, resulting in the emergence of the field of infodemiology (i.e., information epidemiology), which investigates the transmission of health-related information. Due to the high volume of online misinformation in recent years, there is a need to continue advancing methodologies in order to effectively identify narratives and themes. While machine learning models can be used to detect misinformation and conspiracies, these models are limited in their generalizability to other datasets and misinformation phenomenon, and are often unable to detect implicit meanings in text that require contextual knowledge. To rapidly detect evolving conspiracist narratives within high volume online discourse while identifying nuanced themes requiring the comprehension of subtext, this study describes a hybrid methodology that combines natural language processing (i.e., topic modeling and sentiment analysis) with qualitative content coding approaches to characterize conspiracy discourse related to 5G wireless technology and COVID-19 on Twitter (currently known as X). Discourse that focused on correcting 5G conspiracies was also analyzed for comparison. Sentiment analysis shows that conspiracy-related discourse was more likely to use language that was analytic, combative, past-oriented, referenced social status, and expressed negative emotions. Corrections discourse was more likely to use words reflecting cognitive processes, prosocial relations, health-related consequences, and future-oriented language. Inductive coding characterized conspiracist narratives related to global elites, anti-vax sentiment, medical authorities, religious figures, and false correlations between technology advancements and disease outbreaks. Further, the corrections discourse did not address many of the narratives prevalent in conspiracy conversations. This paper aims to further bridge the gap between computational and qualitative methodologies by demonstrating how both approaches can be used in tandem to emphasize the positive aspects of each methodology while minimizing their respective drawbacks.

INTRODUCTION: Latinos are the fastest growing aging population in the U.S. However, there has been limited attention to conceptualizing successful aging among Latinos, especially those residing in rural communities. Latinos are the largest racial or ethnic group residing in rural underserved communities and rural Latinos experience significant structural barriers to access the conditions they need to age well. The goal of this study is to make unique contributions to the successful aging literature by describing what successful aging means for middle-aged Latinas residing in a rural community. METHODS: This qualitative paper used inductive thematic content analysis to examine definitions of successful aging among Latina women (n = 40) residing in an underserved agricultural community and entering mid-life (mean = 49 years old; age range 40-64). RESULTS: With regards to definitions of successful aging, four themes emerged: 1) Having good health; 2) maintaining an active lifestyle; 3) the wellbeing of ones children; and 4) being independent. DISCUSSION: Participants definitions of successful aging aligned to some extent with existing frameworks, specifically related to health and independence. However, middle-aged Latina participants unique definitions of successful aging also diverged from existing frameworks, especially around the wellbeing of their children and the importance of work as a way of maintaining an active lifestyle. More research is needed to understand the unique social context and circumstances of middle-aged Latinos residing in rural communities and how they influence their aging journeys. This can provide important information for the development of culturally sensitive services, interventions, and policies to help Latinos age well.

Non-polyadenylated RNA includes a large subset of crucial regulators of RNA expression and constitutes a substantial portion of the transcriptome, playing essential roles in gene regulation. For example, enhancer RNAs are long non-coding RNAs that perform enhancer-like functions, are bi-directionally transcribed, and usually lack polyA tails. This paper presents a novel method, selSeq, that selectively removes mRNA and pre-mRNA from samples enabling the selective sequencing of crucial regulatory elements, including non-polyadenylated RNAs such as long non-coding RNA, enhancer RNA, and non-canonical mRNA.

Many animals take advantage of the shaded, humid, and protected environments in subcortical spaces, i.e., thin spaces under the loosened bark of dead trees. Permanent inhabitants of subcortical spaces often show specialized morphologies, such as a miniaturized or dorsoventrally flattened body. However, the evolutionary consequences of these specialized morphologies on behavioral, ecological, and life-history traits have been little studied. We studied the mating biology and anatomy of Platylabia major (usually placed in the family Anisolabididae), which is an obligate inhabitant of subcortical spaces with a paper-like flattened body, and compared them with those of two thicker, spongiphorid earwigs, Nesogaster amoenus and Paralabellula curvicauda. Mating trials in various settings showed that Pl. major requires thin spaces sandwiched by two planes to accomplish genital coupling and insemination. In contrast, the thicker species, although also frequently found in subcortical spaces, could mate on a single horizontal plane due to the ability of the male to twist its abdomen through approximately 180°. Examination by micro-computed tomography and a reagent-based clearing technique revealed no substantive differences in the configuration of mid-abdominal musculature between the species. The dorsal and lateral muscles of Pl. major, which are almost parallel to the antero-posterior body axis for accommodation within the thin abdomen, seemed incapable of producing the power to twist the abdomen. The abdominal musculature conforms to a simple pattern in both male and female earwigs, which is repeated in each of the pregenital segments. We conclude that small differences in the range of motion of each abdominal segment can result in large differences in possible mating postures and positions. Surgical experiments also demonstrated that both right and left penises of Pl. major are competent and used for insemination with no lateral bias, as in most other earwigs with twin penises studied to date.

Despite extensive debate on the effects of COVID-19 mitigation measures in school settings, little evidence exists on trends in school childrens mental health over the course of the COVID-19 pandemic. The objective of this paper was to identify factors affecting parent reports of school childrens mental health during COVID-19 Omicron variant outbreak in a cohort of high-risk, socially vulnerable children attending public elementary schools. We analyzed four waves of cross-sectional, online-administered surveys completed by parents of children attending public elementary schools in San Diego between November 2021 and March of 2022. Children (n = 684) ranged in age from 2-17 years. We used multilevel linear mixed effects models to assess determinants of parent-reported child mental health status. The outcome was child mental health, as reported by the parent. Parents consistently rated their childrens mental health as very good, though parents who experienced recent COVID-related challenges and who had older children reported lower levels of mental health in their children. Childrens mental health was generally considered to be very good, as judged by their parents during a period of constant in-school masking and the Omicron variant outbreak. Structural support mechanisms aimed at mitigating COVID-related challenges for adults may offer benefit to childrens mental health.

The ongoing COVID-19 pandemic produced far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community's COVID-19 response lead to the emergence of new research at the remarkable rate of more than 250 papers published per day. This posed a challenge for the scientific community as traditional methods of engagement with the literature were strained by the volume of new research being produced. Meanwhile, the urgency of response lead to an increasingly prominent role for preprint servers and a diffusion of relevant research through many channels simultaneously. These factors created a need for new tools to change the way scientific literature is organized and found by researchers. With this challenge in mind, we present an overview of COVIDScholar https://covidscholar.org, an automated knowledge portal which utilizes natural language processing (NLP) that was built to meet these urgent needs. The search interface for this corpus of more than 260,000 research articles, patents, and clinical trials served more than 33,000 users at an average of 2,000 monthly active users and a peak of more than 8,600 weekly active users in the summer of 2020. Additionally, we include an analysis of trends in COVID-19 research over the course of the pandemic with a particular focus on the first 10 months, which represents a unique period of rapid worldwide shift in scientific attention.

BackgroundAdvance care planning (ACP) is influenced by several factors (e.g., patient's readiness to engage, clinician's skills, and the cultural environment). Availability of reliable and valid self-reported measures of the ACP domains is crucial, including cross-cultural equivalence.AimTo culturally adapt into Italian the 19-item Quality of Communication (QOC) and the 4-item ACP Engagement (4-item ACP-E) questionnaires.MethodsWe translated and culturally adapted the two questionnaires and produced a significant other (SO) version of the QOC (QOC-SO). Each questionnaire was field tested via cognitive interviews with users: nine patients (QOC, 4-item ACP-E) and three SOs (QOC-SO) enrolled at three palliative care services.ResultsWe made minor changes to 5/19 QOC items, to improve clarity and internal consistency; we changed the response option 'didn't do' into 'not applicable'. Finally, we slightly revised the QOC to adapt it to the paper/electronic format. QOC debriefing revealed that the section on end of life was emotionally challenging for both patients and SOs. We simplified the 4-item ACP-E layout, added a sentence in the introduction, and revised the wording of one item, to improve coherence with the Italian ACP legislation. ACP-E debriefing did not reveal any major issue.ConclusionsResults were satisfactory in terms of semantic, conceptual and normative equivalence of both questionnaires. Acceptability was satisfactory for the 4-item ACP-E, while findings of the QOC cognitive debriefing informed a major amendment of a pilot trial protocol on ACP in multiple sclerosis (ConCure-SM): use of the interviewer version only, in an adaptive form. Psychometric testing of both questionnaires on a large, independent sample will follow.

Although a tremendous amount of modern interaction is electronic, our understanding of everyday digital communications-including what they look like and how their properties vary by medium and relationship type-is still growing. In this paper, we examine digital exchange in two of its simplest forms: email and SMS. Specifically, our data consist of 2,004 messages provided by a diverse sample of college students, supplemented by in-depth interviews with their authors. These data were collected in 2010-a time when both mediums were widespread but devoid of most of their modern complexity. Based on these data, we make two contributions: First, we develop an empirically grounded typology of the basic properties of text-based digital communication; second, we document the distribution of these properties across five common relationship types. Respectively, these findings provide a starting point to understanding the substance of digital exchange in all its many forms and an empirical benchmark for comparison.

This collection provides a contemporary excerpt of Cities as complex systems. The contributions have been submitted between April and October 2020. We briefly discuss example papers addressing the themes urban scaling, urban mobility, flows in cities, spatial analysis, information technology and cities, and cities in time. After motivating the intersection of cities and complexity, we provide an introduction and additional thoughts on urban scaling.

Given increased prevalence of direct-to-consumer (DTC) genetic health tests in recent years, this paper delves into discourses among researchers at professional genomics conferences and lay DTC genetic test users on popular discussion website Reddit to understand the contested value of genetic knowledge and its direct implications for health management. Harnessing ethnographic observations at five conferences and a text -analysis of 52 Reddit threads, we find both experts and lay patient-consumers navigate their own versions of "productive uncertainty." Experts develop genetic technologies to legitimize unsettled genomics as medical knowledge and mobilize resources and products, while lay patient-consumers turn to Internet forums to gain clarity on knowledge gaps that help better manage their genetic risk states. By showing how the uncertain nature of genomics serves as a productive force placing both parties within a mutually cooperative cycle, we argue that experts and patient-consumers co-produce a form of relational medicalization that concretizes "risk" itself as a disease state.

Nurse, Midwives and Allied Health Professionals (AHPs), along with other health and social care colleagues are the backbone of healthcare services. They have played a key role in responding to the increased demands on healthcare during the COVID-19 pandemic. This paper compares cross-sectional data on quality of working life, wellbeing, coping and burnout of nurses, midwives and AHPs in the United Kingdom (UK) at two time points during the COVID-19 pandemic. An anonymous online repeated cross-sectional survey was conducted at two timepoints, Phase 1 (7th May 2020-3rd July 2020); Phase 2 (17th November 2020-1st February 2021). The survey consisted of the Short Warwick-Edinburgh Mental Wellbeing Scale, the Work-Related Quality of Life Scale, and the Copenhagen Burnout Inventory (Phase 2 only) to measure wellbeing, quality of working life and burnout. The Brief COPE scale and Strategies for Coping with Work and Family Stressors scale assessed coping strategies. Descriptive statistics and multiple linear regressions examined the effects of coping strategies and demographic and work-related variables on wellbeing and quality of working life. A total of 1839 nurses, midwives and AHPs responded to the first or second survey, with a final sample of 1410 respondents -586 from Phase 1; 824 from Phase 2, (422 nurses, 192 midwives and 796 AHPs). Wellbeing and quality of working life scores were significantly lower in the Phase 2 sample compared to respondents in Phase 1 (p

Little is known about longitudinal patterns of welfare program participation among single mothers after they transition from employment to unemployment. To better understand how utilization patterns of these welfare programs may change during the 12 months after a job loss, we used the 2008 Survey of Income and Program Participation to examine the patterns of participation in Medicaid, the Supplemental Nutrition Assistance Program, Temporary Assistance for Needy Families, and unemployment insurance among 342 single mothers who transitioned from employment to unemployment during the Great Recession. Using sequence analysis and cluster analysis, this paper identified four distinct patterns of program participation: (a) constantly receiving in-kind benefits; (b) primarily but not solely receiving food stamps; (c) inconsistent unemployment insurance or Medicaid-based benefits; and (d) limited or no benefits. Almost two-fifths of our sample of single mothers received inconsistent, limited, or no benefits. Results of the multinomial regression revealed that race, work disability, poverty, homeownership, and region of residence were significant factors that influenced whether study subjects participated in or had access to social safety net programs. Our findings illustrate the heterogeneity in patterns of multiple program participation among single mothers transitioning from employment to unemployment. Better understanding these varied patterns may inform decisions that increase the accessibility of US social safety net programs for single mothers during periods of personal economic hardship.

Porcine reproductive and respiratory syndrome (PRRS) is an extremely contagious disease that causes great damage to the U.S. pork industry. PRRS is not subject to official control in the U.S., but most producers adopt control strategies, including vaccination. However, the PRRS virus mutates frequently, facilitating its ability to infect even vaccinated animals. In this paper we analyze how increased vaccination on sow farms reduces PRRS losses and when vaccination is profitable. We develop a SIR model to simulate the spread of an outbreak between and within swine farms located in a region of Minnesota. Then, we estimate economic losses due to PRRS and calculate the benefits of vaccination. We find that increased vaccination of sow farms increases the private profitability of vaccination, and also transmits positive externalities to farms that do not vaccinate. Although vaccination reduces industry losses, a low to moderate vaccine efficacy implies that large PRRS losses remain, even on vaccinated farms. Our approach provides useful insight into the dynamics of an endemic animal disease and the benefits of different vaccination regimens.

BackgroundPersons with submicroscopic malaria infection are a major reservoir of gametocytes that sustain malaria transmission in sub-Saharan Africa. Despite recent decreases in the national malaria burden in Kenya due to vector control interventions, malaria transmission continues to be high in western regions of the country bordering Lake Victoria. The objective of this study was to advance knowledge of the topographical, demographic and behavioral risk factors associated with submicroscopic malaria infection in the Lake Victoria basin in Kisumu County.MethodsCross-sectional community surveys for malaria infection were undertaken in three eco-epidemiologically distinct zones in Nyakach sub-County, Kisumu. Adjacent regions were topologically characterized as lakeshore, hillside and highland plateau. Surveys were conducted during the 2019 and 2020 wet and dry seasons. Finger prick blood smears and dry blood spots (DBS) on filter paper were collected from 1,777 healthy volunteers for microscopic inspection and real time-PCR (RT-PCR) diagnosis of Plasmodium infection. Persons who were PCR positive but blood smear negative were considered to harbor submicroscopic infections. Topographical, demographic and behavioral risk factors were correlated with community prevalence of submicroscopic infections.ResultsOut of a total of 1,777 blood samples collected, 14.2% (253/1,777) were diagnosed as submicroscopic infections. Blood smear microscopy and RT-PCR, respectively, detected 3.7% (66/1,777) and 18% (319/1,777) infections. Blood smears results were exclusively positive for P. falciparum, whereas RT-PCR also detected P. malariae and P. ovale mono- and co-infections. Submicroscopic infection prevalence was associated with topographical variation (χ2 = 39.344, df = 2, p

This paper introduces a series of high resolution (100-meter) population grids for eight different sociodemographic variables across the state of California using data from the 2020 census. These layers constitute the 'CA-POP' dataset, and were produced using dasymetric mapping methods to downscale census block populations using fine-scale residential tax parcel boundaries and Microsoft's remotely-sensed building footprint layer as ancillary datasets. In comparison to a number of existing gridded population products, CA-POP shows good concordance and offers a number of benefits, including more recent data vintage, higher resolution, more accurate building footprint data, and in some cases more sophisticated but parsimonious and transparent dasymetric mapping methodologies. A general accuracy assessment of the CA-POP dasymetric mapping methodology was conducted by producing a population grid that was constrained by population observations within block groups instead of blocks, enabling a comparison of this grid's population apportionment to block-level census values, yielding a median absolute relative error of approximately 30% for block group-to-block apportionment. However, the final CA-POP grids are constrained by higher-resolution census block-level observations, likely making them even more accurate than these block group-constrained grids over a given region, but for which error assessments of population disaggregation is not possible due to the absence of observational data at the sub-block scale. The CA-POP grids are freely available as GeoTIFF rasters online at github.com/njdepsky/CA-POP, for total population, Hispanic/Latinx population of any race, and non-Hispanic populations for the following groups: American Indian/Alaska Native, Asian, Black/African-American, Native Hawaiian and other Pacific Islander, White, other race or multiracial (two or more races) and residents under 18 years old (i.e. minors).

The increasing concern about the degradation of water-dependent ecosystems calls for considering ecosystems benefits in water management decision-making. Sustainable water management requires adequate economic and biophysical information on water systems supporting both human activities and natural ecosystems. This information is essential for assessing the impact on social welfare of water allocation options. This paper evaluates various alternative water management policies by including the spatial and sectoral interrelationships between the economic and environmental uses of water. A hydroeconomic model is developed to analyze water management policies for adaptation to reduced water availability in the Ebro Basin of Spain. The originality in our contribution is the integration of environmental benefits across the basin, by using endemic biophysical information that relates stream flows and ecosystem status in the Ebro Basin. The results show the enhancement of social welfare that can be achieved by protecting environmental flows, and the tradeoffs between economic and environmental benefits under alternative adaptation strategies. The introduction of water markets is a policy that maximizes the private benefits of economic activities, but disregards environmental benefits. The results show that the current institutional policy where stakeholders cooperate inside the water authority, provides lower private benefits but higher environmental benefits compared to those obtained under water markets, especially under severe droughts. However, the water authority is not allocating enough environmental flows to optimize social welfare. This study informs strategies for protection of environmental flows in the Ebro Basin, which is a compelling decision under the imminent climate change impacts on water availability in coming decades.

BackgroundThe reopening of college and university campuses was seen as presenting a high risk for transmission of COVID-19. Thus, these institutions faced with a new public health challenge never heretofore faced on this scale. To magnify the problem, they needed to rapidly develop and implement re-opening plans in an environment filled with uncertainty and for a population that was significantly less likely to observe COVID-19 mitigation behaviors. In response, within three weeks of opening, as part of its COVID-19 public health strategy, a West Coast university created and trained a public health workforce comprised of 282 undergraduates tasked with encouraging compliance with COVID-19 mitigating healthy behaviors.Main objectivesThis paper describes the use and outcomes of a practicum framework to quickly create a university-based public health workforce. It addresses two questions: (1) Using a practicum framework, what are important considerations in designing and building a public health workforce for a university campus? and (2) What are the benefits to the workforce in terms of public health education and professional growth?MethodsProgram administrative data were used to describe the workforce and their learning outcomes.ResultsThe majority of students indicated that through the practicum, they learned new skills/developed new attitudes (71.7%) and became aware of their own strengths and opportunities for professional growth (73.7%). The types of new skills and attitudes learned included communication (49.2%), conflict management (20.4%), time management (7.5%), and open-mindedness/less judgmental attitude (14.6%). In terms of public health, they gained an understanding of infectious disease prevention (40.9%) that is multi-disciplinary (20.5%), and involves a community effort (36.8%).ConclusionsThese findings demonstrate an effective way of rapidly addressing public health concerns that allowed for on the job training and opportunities for young adults to learn and grow. The practicum framework allowed the expeditious development of a public health workforce that ensured a fit between student interests and the role. This led to high retention with the majority of students continuing into the winter quarter. Only 5% of students reported not being satisfied with their position. None of the students contracted job-related COVID-19. The role gave students a sense of purpose during the pandemic's uncertain times that helped to protect them from the negative effects of stress. The practicum structure and support fostered a safe environment in which students were able to feel part of the larger community while gaining valuable work experience and skills and serve their community.