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Effective administration of a firm depends largely on the quality and commitment of the board of directors, who are expected to control the activities of the firm based on ethical and professional standards to ensure that corporate affairs are in line with corporate objectives. This study examines the mediating effect of earnings quality on the relationship between corporate board attributes and the value of listed insurance companies in Nigeria. The study utilized secondary sources of data collected from annual reports of the sampled companies for the periods 2009 to 2018. The population of the study comprises of all twenty seven (27) insurance companies listed on the Nigerian stock exchange, out of which fifteen (15) were selected as study sample. Data generated were examined by means of descriptive statistics to provide summary statistics for the variables and subsequently, correlation analysis was carried out using Pearson correlation technique for the correlation between the dependent, independent variables and the mediating variable. Path analysis using Structural Equation Modeling was used; also Monte Carlo’s test was employed to determine the significant of the indirect effect. It was found that board size, board meetings and women directorship significantly affect firm value. It also reveals that board size and board independence significantly affects earnings quality of listed insurance companies in Nigeria. Furthermore, the study finds that earnings quality does not significantly mediates the relationship between board size, board independence, women director, board meeting and firm value. However, it is mediating partially. This indicates that board attributes through the quality of the reported earnings a higher firm value will be achieved. Hence the study concludes that the direct association between boards attributes mechanisms and firm value is more crucial than their indirect association mediated by the earnings quality. Thus, the study recommends that investors should pay more attention to companies with high number of directors, as provided in the NAICOM code of corporate governance. Also, in order to have proper checking by independent directors, NAICOM should also ensure a strict adherence to the provision of the code to improve the quality of earnings and enhance the value of the listed insurance companies in Nigeria.

OBJECTIVE To examine the proposition that identical summary statistics (mean and/or SD) in different randomized controlled trials (RCT) or clinical cohorts can be explained by common or homogeneous source populations. STUDY DESIGN We estimated the probability of identical summary data in studies with high proportions of identical summary statistics, in simulations, and in control datasets. RESULTS The probability of both an identical mean and an identical SD for a variable in separate RCT is low (

Background Ecological processes such as seedling establishment, biotic interactions, and mortality can leave footprints on species spatial structure that can be detectable through spatial point-pattern analysis (SPPA). Being widely used in plant ecology, SPPA is increasingly carried out to describe biotic interactions and interpret pattern-process relationships. However, some aspects are still subjected to a non-negligible debate such as required sample size (in terms of the number of points and plot area), the link between the low number of points and frequently observed random (or independent) patterns, and relating patterns to processes. In this paper, an overview of SPPA is given based on rich and updated literature providing guidance for ecologists (especially beginners) on summary statistics, uni-/bi-/multivariate analysis, unmarked/marked analysis, types of marks, etc. Some ambiguities in SPPA are also discussed. Results SPPA has a long history in plant ecology and is based on a large set of summary statistics aiming to describe species spatial patterns. Several mechanisms known to be responsible for species spatial patterns are actually investigated in different biomes and for different species. Natural processes, plant environmental conditions, and human intervention are interrelated and are key drivers of plant spatial distribution. In spite of being not recommended, small sample sizes are more common in SPPA. In some areas, periodic forest inventories and permanent plots are scarce although they are key tools for spatial data availability and plant dynamic monitoring. Conclusion The spatial position of plants is an interesting source of information that helps to make hypotheses about processes responsible for plant spatial structures. Despite the continuous progress of SPPA, some ambiguities require further clarifications.

What does it mean for a private enterprise in China to be embedded in a family? Our purpose here is twofold: (1) use social network analysis to describe what it means for a firm to be embedded in a family, (2) reveal from the application a new kind of firm, not family, yet akin to family. Armed with data on a large probability sample of private enterprises — a third of which meet ownership and employment criteria of being family businesses — we uncover a category of “hybrid family firms” that look modern in the style of firms that exclude family, but operate socially in ways similar to family firms. Our conclusion from summary statistics on the sample is that there are no differences in average performance level or network advantage for the three categories of businesses: family firms, hybrid family firms, and family-excluded firms. The fact that CEOs of family firms and hybrid family firms more often turn to family as key business contacts is a fact about network composition that raises no question about network mechanisms. Whether the CEO turns to more or fewer family contacts, government help is more likely with stronger political connections, and business success and survival are more likely with a large, open network. That said, the look-modern, act-traditional hybrid family firms stand alone in prospering with a CEO embedded in a closed business network. Recognition of hybrid family firms adds to the literature’s illustrations of social network analysis used to distinguish types of businesses and business people, and extends the population of organizations within which governance and strategy are likely to be better understood when viewed through a family logic.

Study ObjectivesTo evaluate the level of shared genetic components between attention-deficit/hyperactivity disorder (ADHD) and sleep phenotype, common pathways between them and a possible causal relationship between traits.MethodsWe used summary statistics of the largest genome-wide association studies available for ADHD and sleep-related phenotypes including insomnia, napping, daytime dozing, snoring, ease getting up, daytime sleepiness, sleep duration and chronotype. We estimated the genomic correlation between ADHD and sleep-related traits using cross-trait LD-score regression and investigated potential common mechanisms using gene-based cross-trait metanalyses and functional enrichment analyses. The causal effect between the sleep related traits and ADHD was estimated with two sample Mendelian randomization (TSMR), using the Inverse Variance Weighted method as the main estimator.ResultsPositive genomic correlation between insomnia, daytime napping, daytime dozing, snoring, daytime sleepiness, short and long sleep duration, and ADHD were observed. Insomnia, sleep duration, daytime sleepiness, and snoring shared genes with ADHD, which were involved in neurobiological functions and regulatory signaling pathways. The TSMR approach supported a causal effect of insomnia, daytime napping, and short sleep duration on ADHD, and of ADHD on long sleep duration and chronotype.ConclusionOur findings suggest that the comorbidity between sleep phenotypes and ADHD may be mediated by common genetic factors with an important role on neuronal signaling pathways. In addition, it may also exist a causal effect of sleep disturbances and short sleep duration on ADHD, reinforcing the role of these sleep phenotypes as predictors or early markers of ADHD.Statement of SignificanceOur findings suggest that the comorbidity between sleep phenotypes and ADHD may be linked to common genetic factors with an important role on neuronal signaling pathways. They also show that a causal effect of sleep disturbances and short sleep duration on ADHD may exist, reinforcing the role of these sleep phenotypes as ADHD early markers, being able to predict the disorder. This study adds important information about the relationship between sleep, circadian rhythm, and ADHD since it raises new questions about the complexity of the phenomenon involving them and may also provide new treatment insights in this research field.

BACKGROUND: Transgender and gender-diverse individuals are particularly vulnerable to healthcare discrimination and related health sequelae. OBJECTIVE: To demonstrate diversity in demographics and explore variance in needs at the time of intake among patients seeking care at a large, urban gender health program. DESIGN: We present summary statistics of patient demographics, medical histories, and gender-affirming care needs stratified by gender identity and sexual orientation. PARTICIPANTS: We reviewed all intake interviews with individuals seeking care in our gender health program from 2017 to 2020. MAIN MEASURES: Clients reported all the types of care in which they were interested at the time of intake as their “reason for call” (i.e., establish primary care, hormone management, surgical services, fertility services, behavioral health, or other health concerns). KEY RESULTS: Of 836 patients analyzed, 350 identified as trans women, 263 as trans men, and 223 as non-binary. The most prevalent sexual identity was straight among trans women (34%) and trans men (38%), whereas most (69%) non-binary individuals identified as pansexual or queer; only 3% of non-binary individuals identified as straight. Over half of patients reported primary care, hormone management, or surgical services as the primary reason for contacting our program. Straight, transgender women were more likely to report surgical services as their primary reason for contacting our program, whereas gay transgender men were more likely to report primary care as their reason. CONCLUSIONS: Individuals contacting our gender health program to establish care were diverse in sexual orientation and gender-affirming care needs. Care needs varied with both gender identity and sexual orientation, but primary care, hormone management, and surgical services were high priorities across groups. Providers of gender-affirming care should inquire about sexual orientation and detailed treatment priorities, as trans and gender-diverse populations are not uniform in their treatment needs or goals. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-021-06791-9.

Background: Much of Sub-Saharan Africa meets the rising rates of musculoskeletal injury with traditional bone setting, especially given limitations in access to allopathic orthopaedic care. Concern for the safety of bone setter practices as well as recognition of their advantages have spurred research to understand the impact of these healers on public health. Objectives: Our study investigates the role of bone setting in Tanzania through patient utilization and perspectives. Methods: We surveyed 212 patients at the outpatient orthopaedic clinic at Kilimanjaro Christian Medical Centre (KCMC) in Moshi, Tanzania. Surveys were either self-administered or physician-administered. Summary statistics were calculated using XLSTAT. Open responses were analyzed using a deductive framework method. Results: Of all surveys, 6.3% (n=13) reported utilizing traditional bone setting for their injury prior to presenting to KCMC. Of the self-administered surveys, 13.6% (n=6) reported utilizing bone setting compared to 4.3% (n=7) of the physician-ad- ministered surveys (p=0.050). Negative perceptions of bone setting were more common than positive perceptions and the main reason patients did not utilize bone setting was concern for competency (35.8%, n=67). Conclusion: Our study found lower bone setting utilization than expected considering the reliance of Tanzanians on tradi- tional care reported in the literature. This suggests patients utilizing traditional care for musculoskeletal injury are not seeking allopathic care; therefore, collaboration with bone setters could expand allopathic access to these patients. Patients were less likely to report bone setter utilization to a physician revealing the stigma of seeking traditional care, which may present an obstacle for collaboration. Keywords: Bone setting; traditional medicine; traditional practitioners; orthopaedics; trauma.

Objective Describe the early impact of the COVID-19 pandemic on general surgery residency training nationwide. Design A 31-question electronic survey was distributed to general surgery program directors. Qualitative data underwent iterative coding analysis. Quantitative data were evaluated with summary statistics and bivariate analyses. Participants Eighty-four residency programs (33.6% response rate) with representation across US geographic regions, program affiliations, and sizes. Results Widespread changes were observed in the surgical training environment. One hundred percent of programs reduced the number of residents on rounds and 95.2% reduced the size of their in-hospital resident workforce; on average, daytime staffing decreased by nearly half. With telehealth clinics (90.5%) and remote inpatient consults (26.2%), both clinical care and resident didactics (86.9%) were increasingly virtual, with similar impact across all program demographics. Conversely, availability of some wellness initiatives was significantly higher among university programs than independent programs, including childcare (51.2% vs 6.7%), housing (41.9% vs 13.3%), and virtual mental health services (83.7% vs 53.3%). Conclusions Changes in clinical care delivery dramatically reduced in face-to-face learning opportunities for surgical trainees during the COVID-19 pandemic. While this effect had equal impact across all program types, sizes, and geographies, the same cannot be said for wellness initiatives. Though all programs initiated some strategies to protect resident health, the disparity between university programs and independent programs may be cause for action.

From the invention of Perkin’s Mauve in 1856, to publication of the first edition of theColour Indexin 1924, more than 1200 synthetic organic colourants were introduced. Some achieved commercial success, while others were rarely used for reasons such as high cost, low fastness, and toxicity. This turbulent period of innovation was largely driven by demand of the textile industry; however, synthetic colourants were subsequently adopted in many other applications. An understanding of the most common materials and their properties is therefore important to the study of heritage collections and their preservation. The risk of light damage during exhibition of objects is often a concern due to the fugitive nature of many synthetic colourants.To provide a foundation for focused research on synthetic dye identification and lightfastness, work was carried out to identify the most prominent of these colourants used in North America up to the year 1924 when the first edition of theColour Indexwas published. Information was compiled and analysed from several sources including multiple editions of theColour Index, and government documents related to the manufacture and trade of synthetic dyes that provide data from 1914 onwards. Cross-referencing between the information sources provided a summary of parameters for each colourant including the date of introduction, number of manufacturers, lightfastness, and quantity produced or imported in the United States.A document published in 1916 by the US Department of Commerce listed 259 colours with Schultz number imported during the 1913–1914 fiscal year, in quantities above 10,000 lb (4536 kg). Adding domestic products to the list, and removing duplicates, gave 289 individual colours with Schultz number imported and/or produced in the US. In addition, there were some imports of unknown composition: 96 azo, 23 sulphur, and 68 unclassified. Further review of census data from 1917 through the 1920’s suggested that less than one quarter of the dyes listed in theColour Indexwere imported or manufactured in significant amounts. The results of this analysis are presented as summary statistics, which are complemented by an open dataset publication to facilitate future research.

Missing data in longitudinal analysis has long been an important concern for drug developers and regulators. ICH published its E9 (R1) guidance in 2019, addressing the issue of estimands. In that guidance, five strategies are introduced. This manuscript focuses on the While on Treatment strategy, and attempts to propose average response over time as an alternative to last observation carried forward in the application of While on Treatment strategy. This is a simple summary statistics reflecting the average change a patient experiences during the trial. It is easy to interpret and easy to understand by non-statisticians. In clinical trials, with longitudinal data, average response over time has many applications. Two estimators are proposed to implement this estimand—simple mean over time, and standardized area under the curve (sAUC)

Розглянуто нові концептуальні підходи до використання великих масивів даних у соціогуманітарних дослідженнях і проаналізовано сучасні напрями їх використання у науково-дослідній діяльності гуманітарного спрямування. Обґрунтовано актуальність використання технологій Big Data в історичних наукових дослідженнях і використання таких технологій для побудови науково-дослідних кластерів з метою ефективного дослідження й опрацювання масових історичних джерел, а саме зведених статистичних даних. Опрацьовано зведені статистичні дані індустріального розвитку, перепису населення та експертного оцінювання соціо-економічного і демографічного розвитку Сполучених Штатів Америки та Української Радянської Соціалістичної Республіки у 1970-1980-х роках. Апробовано кількісний метод для отримання консолідованої статистики, що дасть змогу виявити особливості статистичної сукупності загалом і в окремих її компонентах, показати регулярність досліджуваних соціально-економічних явищ процесів. Оцінено вагомість консолідованих статистичних даних, опублікованих на вітчизняних та іноземних ресурсах для їх подальшого використання в історичних дослідженнях. Подано у форматі таблиці, змодельовано кліометричні характеристики консолідованих статистичних даних розвитку Сполучених Штатів Америки та України у 1970-х та у 1980-х роках. Обґрунтовано, що кліометричні характеристики консолідованої статистики розвитку Сполучених Штатів Америки та Української Радянської Соціалістичної Республіки у 1970-1980-х роках, які отримують за допомогою моделювання даних економічного розвитку, даних перепису населення, даних національного доходу та зайнятості, експертного оцінювання, можна використати як нове джерело для вивчення актуального історичного періоду.

Through ensemble encoding, the visual system compresses redundant statistical properties from multiple items into a single summary metric (e.g., average size). Numerous studies have shown that global summary information is extracted quickly, does not require access to single-item representations, and often interferes with reports of single items from the set. Yet a thorough understanding of ensemble processing would benefit from a more extensive investigation at the local level. Thus, the purpose of this study was to provide a more critical inspection of global-local processing in ensemble perception. Taking inspiration from Navon (Cognitive Psychology, 9(3), 353-383, 1977), we employed a novel paradigm that independently manipulates the degree of interference at the global (mean) or local (single item) level of the ensemble. Initial results were consistent with reciprocal interference between global and local ensemble processing. However, further testing revealed that local interference effects were better explained by interference from another summary statistic, the range of the set. Furthermore, participants were unable to disambiguate single items from the ensemble display from other items that were within the ensemble range but, critically, were not actually present in the ensemble. Thus, it appears that local item values are likely inferred based on their relationship to higher-order summary statistics such as the range and the mean. These results conflict with claims that local information is captured alongside global information in summary representations. In such studies, successful identification of set members was not compared with misidentification of items within the range, but which were nevertheless not presented within the set.

Hundreds of genome-wide association studies (GWAS) of human traits are performed each year. The results of GWAS are often published in the form of summary statistics. Information from summary statistics can be used for multiple purposes - from fundamental research in biology and genetics to the search for potential biomarkers and therapeutic targets. While the amount of GWAS summary statistics collected by the scientific community is rapidly increasing, the use of this data is limited by the lack of generally accepted standards. In particular, the researchers who would like to use GWAS summary statistics in their studies have to become aware that the data are scattered across multiple websites, are presented in a variety of formats, and, often, were not quality controlled. Moreover, each available summary statistics analysis tools will ask for data to be presented in their own internal format. To address these issues, we developed GWAS-MAP, a high-throughput platform for aggregating, storing, analyzing, visualizing and providing access to a database of big data that result from region- and genome-wide association studies. The database currently contains information on more than 70 billion associations between genetic variants and human diseases, quantitative traits, and "omics" traits. The GWAS-MAP platform and database can be used for studying the etiology of human diseases, building predictive risk models and finding potential biomarkers and therapeutic interventions. In order to demonstrate a typical application of the platform as an approach for extracting new biological knowledge and establishing mechanistic hypotheses, we analyzed varicose veins, a disease affecting on average every third adult in Russia. The results of analysis confirmed known epidemiologic associations for this disease and led us to propose a hypothesis that increased levels of MICB and CD209 proteins in human plasma may increase susceptibility to varicose veins.Ежегодно проводятся сотни полногеномных исследований ассоциаций (genome-wide association studies, GWAS) человеческих признаков. Результаты GWAS часто публикуют в форме сводных статистик. Информацию из сводных статистик можно использовать для решения различных задач – от фундаментальных исследований в области биологии и генетики до поиска потенциальных биомаркеров и мишеней терапевтического воздействия. Количество собранных научным сообществом сводных статистик GWAS быстро растет, однако использование данных затруднено из-за отсутствия общепринятых стандартов. В частности, исследователи, которые хотели бы применить сводные статистики GWAS в своей работе, сталкиваются с тем, что данные разбросаны по нескольким веб-сайтам, представлены в различных форматах, нередко без контроля качества. Более того, каждый доступный инструмент анализа сводных статистик запрашивает данные в своем собственном внутреннем формате. Для решения этих проблем мы разработали высокопроизводительную платформу GWAS-MAP для агрегации, хранения, анализа, визуализации и доступа к базе данных результатов полногеномных и региональных исследований ассоциаций. В настоящий момент на платформе содержится информация о более чем 70 миллиардах ассоциаций между вариантами геномной последовательности и болезнями, количественными и «омиксными» признаками человека. Платформа и база данных могут использоваться для изучения этиологии заболеваний человека, разработки предиктивных моделей риска, а также для поиска потенциальных биомаркеров и терапевтических воздействий. Применение платформы как инструмента для извлечения новых биологических знаний и формулировки гипотез о механизмах генетического контроля продемонстрировано на примере варикозной болезни нижних конечностей, заболевания, встречающегося у каждого третьего взрослого жителя России. Результаты проведенного анализа подтвердили известные эпидемиологические ассоциации для данного заболевания и позволили выдвинуть гипотезу о том, что уровень белков MICB и CD209 в плазме крови человека может влиять на риск варикозного расширения вен.

Large-scale genome-wide association (GWAS) studies provide opportunities for developing genetic risk prediction models that have the potential to improve disease prevention, intervention or treatment. The key step is to develop polygenic risk score (PRS) models with high predictive performance for a given disease, which typically requires a large training data set for selecting truly associated single nucleotide polymorphisms (SNPs) and estimating effect sizes accurately. Here, we develop a comprehensive penalized regression for fitting l(1) regularized regression models to GWAS summary statistics. We propose incorporating Pleiotropy and ANnotation information into PRS (PANPRS) development through suitable formulation of penalty functions and associated tuning parameters. Extensive simulations show that PANPRS performs equally well or better than existing PRS methods when no functional annotation or pleiotropy is incorporated. When functional annotation data and pleiotropy are informative, PANPRS substantially outperforms existing PRS methods in simulations. Finally, we applied our methods to build PRS for type 2 diabetes and melanoma and found that incorporating relevant functional annotations and GWAS of genetically related traits improved prediction of these two complex diseases.

The institute defines its aims and sets educational objectives adapted to these aims. The institute has a clear and distinct sense of its core values and character, of its distinctive elements, of its place both in colleges and in society, and of its contribution to the public good. The aims of the study were (i). To explore the practices for development of personality in institutions. (ii) To identify the role of administrators of institutes for students ‘personality development. (iii)To determine which sector is more competent in doing better personality development at higher secondary level in private and public sector institutes. With survey design the study was descriptive in its nature. The population of the study was all private and public colleges of Punjab Province. Six hundred and twenty-eight out of seven hundred and twenty students, and also thirty administrators out of thirty-two, participated in the research. Instrument was tested by conducting Pilot testing with (?=.87) reliability. Parametric statistics and summary statistics were menu plated to check the assumption, Normality tests and Boxplot were applied. To compare the private and public institutes, Non-parametric test was applied on the given information. It was concluded from the study that (i) Activities related to personality development, are doing in institutions. (ii) Administrators are doing their job in personality development among boys and girls at higher secondary level. (iii) Private sector is doing better job to the development of student’s personality than public sector.

Purpose: Because financial conflicts of interest (FCOIs) may potentially influence patient care, hospital drug formularies, and treatment guidelines, it is important that these are disclosed. The purpose of this observational study was to quantify the changes in FCOI among U.S.-based academic authors in industry-sponsored oncology trials after a high-impact publication. Methods: A list of all U.S.-based academic authors (authors) of industry-sponsored solid tumor clinical trials published between August 1, 2014, and December 31, 2015, in 6 high-impact journals (New England Journal of Medicine, Nature, Science, Lancet Oncology, Journal of Clinical Oncology, and Cancer Discovery) was assembled. Studies were limited to solid tumor oncology trials. After all authors were identified, direct and research funding was tabulated from CMS Open Payments for the year prior (Ypre) and the first 3 years following publication (Y1, Y2, Y3) in the high-impact journal. Summary statistics were tabulated and repeated-measures linear mixed-effects regression models were fit to examine changes after publication. Results: A total of 102 publications with a total of 620 authors were identified. No FCOI was declared by 11, 12, 21, and 24 authors in Ypre, Y1, Y2, and Y3, respectively. In Ypre, Y1, Y2, and Y3: median FCOI for direct payments was $16,702 (range: $0–$3,180,356), $20,830 (range: $0–$3,180,356), $22,031 (range: $0–$920,746), and $21,356 (range: $0–$920,707), respectively; while median research funding was $559,202 (range: $0–$19,973,818), $505,031 (range $0–$19,920,452), $502,726 (range: $0–$15,729,776), and $497,342 (range: $0–$43,036,716), respectively. There were nonsignificant increases in total direct payments and total direct payments received from the sponsor (P > 0.0125 for both) and statistically significant decreases in total associated research funding and total research funding from the research sponsor in Y1, Y2, and Y3 as compared to Ypre (P < 0.0001 for both). Conclusions: After publication of an industry-sponsored solid tumor clinical trial in a high-impact journal, authors had statistically significant decreases in research funding FCOI in the first 3 years postpublication compared to the year prior.

Summary Repurposing of existing antiviral drugs, immunological modulators, and supportive therapies represents a promising path toward rapidly developing new control strategies to mitigate the devastating public health consequences of the COVID‐19 pandemic. A comprehensive text‐mining and manual curation approach was used to comb and summarize the most pertinent information from existing clinical trials and previous efforts to develop therapies against related betacoronaviruses, particularly SARS and MERS. In contrast to drugs in current trials, which have been derived overwhelmingly from studies on taxonomically unrelated RNA viruses, a number of untested small molecule antivirals had previously demonstrated remarkable in vitro specificity for SARS‐CoV or MERS‐CoV, with high selectivity indices, EC50, and/or IC50. Due to the rapid containment of the prior epidemics, however, these were generally not followed up with in vivo animal studies or clinical investigations, and thus largely overlooked as treatment prospects in the current COVID‐19 trials. This brief review summarizes and tabulates core information on recent or ongoing drug repurposing‐focused clinical trials, while detailing the most promising untested candidates with prior documented success against the etiologic agents of SARS and/or MERS.

Purpose: Tax is an important stream of revenue for government’s development projects. However, tax compliance among SMEs is poor. Therefore, this study was conducted using SMEs in Lusaka, Zambia to evaluate and rank the factors that encourage non-compliance with tax obligation by SMEs.Methodology: The data analysis was done with the help of the statistical package for service solution (SPSS) and this hypothesis was tested with Microsoft Office Excel 2007 using the one sample z-test computed from the figures obtained in the summary statistics table.Findings: It was found that high tax rates and complex filing procedures are the most crucial factors causing non-compliance of SMEs. Other factors like multiple taxation and lack of proper enlightenment affect tax compliance among the SMEs interviewed only to a lesser extent.Unique contribution to theory, practice and policy: It is recommended that SMEs should be levied lower percentage of taxes to allow enough funds for business development and better chances of survival in a competitive market. The government should also consider increasing tax incentives such as exemptions and tax holidays as these will not only encourage voluntary compliance but also attract investors who are potential viable tax payers in the future.

Background The Oregon Occupational Public Health Program (OOPHP) monitors occupational health indicators (OHIs) to inform occupational safety and health (OSH) surveillance. In 2018, OOPHP evaluated the performance of the OSH surveillance system and identified areas for future improvement. Methods Following the Centers for Disease Control and Prevention (CDC) updated guidelines for evaluating public health surveillance systems, the OOPHP evaluation team engaged internal and external stakeholders using a mixed‐methods approach. Operational measures for ten surveillance attributes were developed. Multiple data collection methods resulted in credible evidence for evaluation conclusions. Analyses included summary statistics and qualitative analysis of interviews, a focus group, and online surveys. Results Twenty stakeholders took part in this evaluation, with an average participation rate of 55%. Results showed the Oregon OSH surveillance system was simple, flexible, and highly accepted by its stakeholders. Funding security presents challenges for stability. A lack of timeliness of OHIs, low relevance of OHIs to local OSH issues, and the system's ineffectual data dissemination all limit the usefulness of the OSH surveillance system. A review of key data sources for the system showed good data quality and predictive value positive, but relatively poor sensitivity and representativeness. Conclusions The evaluation team successfully adapted attributes and examples in the CDC guidelines to this Oregon OSH surveillance evaluation. The evaluation findings have informed the development of recommendations for improvements to OOPHP's OSH surveillance. Future research is needed to develop guidance specific to OSH surveillance evaluation.

Objective The Royal College of Physicians and Surgeons of Canada is implementing a competency-by-design (CBD) curriculum for residency training across Canada. Although praise and criticism have been published regarding competency-based residency training, little has been published from the resident perspective. The University of Calgary obstetrics and gynaecology residents were surveyed to gather information on their viewpoints and allow their expectations and concerns to be incorporated into the design and implementation process for the curriculum. Methods An anonymous survey was administered to residents from the University of Calgary obstetrics and gynaecology program. The survey contained a mixture of Likert-scale responses, multiple-choice questions, and free-text response questions. Summary statistics were used to analyze the Likert-scale and multiple-choice responses, and thematic analysis was performed on free-text responses (Canadian Task Force Classification Level III). Results The survey respondents identified several anticipated benefits and challenges regarding the CBD curriculum. Overall, resident respondents seemed optimistic about the curriculum redesign; however, many residents identified concerns, including potential impacts on work relationships, challenges with operating room and call scheduling given the less rigid structure of CBD, and the amount of time and effort that evaluation will require. Conclusion Residents offer a valuable perspective on CBD curriculum redesign and implementation. Gathering their input and including it in the curriculum redesign and implementation process will only strengthen the new curriculum and resident buy-in.

Aim The study aimed to assess the self-rated knowledge, attitude toward, and practice (KAP) of evidence-based medicine (EBM) among resident doctors in Nigeria. Methods This was a cross-sectional web-based survey among 238 resident doctors in four selected teaching hospitals in southern Nigeria. Survey questionnaire contained items assessing the KAP of EBM, familiarity with and understanding of key EBM terms, the use of EBM in decision making, barriers militating against EBM and ways to improve EBM adoption. Proportions and summary statistics were reported for the distribution of survey items. Results Mean number of years in clinical practice was 9.3 ± 4.5 years. Respondents were uniformly distributed in major clinical specialties. The majority (70.5%) were senior registrars. Respondents' understanding of EBM components included; current best clinical evidence (98.3%), clinical expertise (65.5%), and patients' choices (36.6%). Self-rated familiarity with EBM terms was high while perceived understanding of the terms was lower. The least understood concept was heterogeneity (20.6%). The attitude toward EBM was generally positive. Only about half (53.6%) had used medical bibliographic databases within the last 6 months prior to the survey. Barriers against EBM included lack of time (47.1%) and lack of requisite skills (32.4%). Suggestions to improve EBM adoption included training (58.1%), provision of free Wi-Fi, and free access to bibliographic databases (25.2%) and increased political will (23.1%). Conclusion A further understanding of the EBM concept, provision of enabling infrastructure, regular clinical audit and advocacy to hospital management and clinical consultants, may improve the level of adoption of EBM.

Objective This study aimed to explore the attitudes of obstetrics and gynaecology residents in Canada towards interventions that influence caesarean section rates. The study looked at residents’ attitudes towards four guidelines that support vaginal and assisted delivery (vaginal birth after caesarean section, induction of labour, operative vaginal birth, and fetal health surveillance in labour) and towards Society of Obstetricians and Gynaecologists of Canada (SOGC) guidelines in general. The study also sought to investigate whether these attitudes vary by residency training location. Methods An online survey of obstetrics and gynaecology residents across Canada was conducted. Residents responded to statements derived from guidelines using a five-point attitudinal scale and to an optional long-answer question about how residency has prepared them to make decisions around interventions. Descriptive summary statistics are used to present the findings (Canadian Task Force Classification III). Results A total of 27% of residents completed the survey. The majority demonstrated attitudes congruent with guidelines and favourable towards SOGC guidelines in general. Residents attitudes were least favourable towards electronic fetal monitoring, with 67.4% of responses congruent with the guideline. Attitudes were most aligned with the operative vaginal birth guideline, with 87.9% of responses congruent with the guideline. This sample was underpowered to detect statistically significant differences among residency programs, although there was some variation in attitudes across programs, with the most congruent scoring program at 81.8% congruent responses and the lowest at 66.7%. Conclusion Obstetrics and gynaecology residents in Canada have favourable attitudes towards interventions that support vaginal and assisted delivery. There was variability in observed attitudes across programs, although this was not statistically significant.

Non-compliance with respiratory protection programs among firefighters may put them at increased risk of injury and illness from occupational exposures during fire extinguishing activities. This research aims to characterize respiratory protection practices among Florida firefighters. This information will allow better understanding of factors that are associated with non-compliance with respiratory protection guidelines. A survey questionnaire was used to characterize Florida fire departments in this cross-sectional study. Four hundred and seventy-seven surveys were administered to Florida firefighters both in person and electronically to collect information regarding firefighter knowledge and participation in their respective respiratory protection programs during the past twelve months. Survey questions were developed from the model set by the National Fire Protection Association (NFPA) which provides standards and regulations regarding firefighter protections. Summary statistics regarding firefighter department size, coverage area, and firefighter employment type were produced. Multinomial logistic regression analysis was performed to evaluate factors that impact respiratory protection programs. The 477 respondents were 91% male with a mean age of 39 years old (range 21 - 65 years). The majority of respondents, 76%, were non-smokers, 21% former smokers, and 3% current smokers. In regard to ethnicity, respondents were 77% Caucasian, 13% Hispanic, 3% African American, and 4% other. Most respondents were career firefighters, 97%, with less than ten years of experience, 44%, working in a fire department with at least 21 firefighters, 98%. Most respondents, 80%, had a written respiratory program in place. The most cited reason for not having implemented a written respiratory protection program was lack of knowledge related to the program. Multinomial logistic regression analysis of departments with response areas of at least 250,000 square miles produced a statistically significant 0.444 (0.219 - 0.901 CI) odds ratio for having a written respiratory program as compared to those with a less than 10,000 square miles response area. Additional resources need to be given to Florida fire departments to ensure that all firefighters receive adequate respiratory protection in accordance with NFPA guidelines. There is an association between fire departments with large response areas and non-compliance with respiratory protection guidelines in regard to: having a written respiratory program, the frequency of respiratory fit testing, and the frequency of medical fitness testing. This suggests that rural fire departments need additional resources to ensure firefighters are adequately protected. Additional research should focus on why these differences exist in the rural fire departments. Respondents stating a lack of knowledge or no requirement for a written respiratory program suggest that future efforts should focus on respiratory protection education and training.

Increasing amounts of genetic data have led to the development of polygenic risk scores (PRSs) for a variety of diseases. These scores, built from the summary statistics of genome-wide association studies (GWASs), are able to stratify individuals based on their genetic risk of developing various common diseases and could potentially be used to optimize the use of screening and preventative treatments and improve personalized care for patients. Many challenges are yet to be overcome, including PRS validation, healthcare professional and patient education, and healthcare systems integration. Ethical challenges are also present in how this information is used and the current lack of diverse populations with PRSs available. In this review, we discuss the topics above and cover the nature of PRSs, visualization schemes, and how PRSs can be improved. With these tools on the horizon for multiple diseases, scientists, clinicians, health systems, regulatory bodies, and the public should discuss the uses, benefits, and potential risks of PRSs.

Background Approximately 116.4 million adults in the USA have hypertension, and the rates of uncontrolled hypertension remain higher among racial and ethnic minorities. There is a need for effective interventions that promote healthy behaviors and long-term behavioral change in the management of hypertension. The primary objective of this study was to determine the feasibility of developing a lifestyle intervention that would assess hypertension management and the use of technology among Blacks and Latinx with hypertension. The secondary objective is to explore perceptions of community-based resources for hypertension and preferences for a lifestyle intervention for hypertension among Blacks and Latinx with hypertension. Methods In this explanatory mixed-methods study, quantitative data were collected using surveys, participants reported their use of technology and adherence to antihypertensive medication. Participants were Black and Latinx adults with hypertension living in Central Pennsylvania, USA. Qualitative data were obtained from semi-structured interviews and focus groups, and participants were asked about managing hypertension, local resources, and preferences for a behavioral intervention. Data were examined using summary statistics for quantitative data and thematic analysis for qualitative data. Results Black and Latinx participants (n=30) completed surveys for the quantitative study. The majority (75%) of participants self-reported being confident in managing their medication without help and remembering to take their medication as prescribed. Fewer participants (54.2%) reported using technology to help manage medication. There were 12 participants in the qualitative phase of the study. The qualitative findings indicated that participants felt confident in their ability to manage hypertension and were interested in participating in a lifestyle intervention or program based online. Some participants reported a lack of resources in their community, while others highlighted local and national resources that were helpful in managing high blood pressure. Conclusion This study provides important insights on barriers and facilitators for managing hypertension, current use of technology and interest in using technology to manage hypertension, and preferences for future lifestyle interventions among racial and ethnic minorities. This study also provides insights to the health needs and resources available in this community and how future behavioral interventions could be tailored to meet the needs of this community. The findings of this study will be used to inform the tailoring of future lifestyle interventions; specifically, we will include text messaging reminders for medication and to disseminate educational materials related to hypertension and provide resources to connect study participants with local and national resources.

Funder: “Expanding excellence in England” award from Research England, Joint fine-mapping that leverages information between quantitative traits could improve accuracy and resolution over single-trait fine-mapping. Using summary statistics, flashfm (flexible and shared information fine-mapping) fine-maps signals for multiple traits, allowing for missing trait measurements and use of related individuals. In a Bayesian framework, prior model probabilities are formulated to favour model combinations that share causal variants to capitalise on information between traits. Simulation studies demonstrate that both approaches produce broadly equivalent results when traits have no shared causal variants. When traits share at least one causal variant, flashfm reduces the number of potential causal variants by 30% compared with single-trait fine-mapping. In a Ugandan cohort with 33 cardiometabolic traits, flashfm gave a 20% reduction in the total number of potential causal variants from single-trait fine-mapping. Here we show flashfm is computationally efficient and can easily be deployed across publicly available summary statistics for signals in up to six traits.

Unsupervised exploratory data analysis (EDA) is often the first step in understanding complex data sets. While summary statistics are among the most efficient and convenient tools for exploring and describing sets of data, they are often overlooked in EDA. In this paper, we show multiple case studies that compare the performance, including clustering, of a series of summary statistics in EDA. The summary statistics considered here are pattern recognition entropy (PRE), the mean, standard deviation (STD), 1-norm, range, sum of squares (SSQ), and X4, which are compared with principal component analysis (PCA), multivariate curve resolution (MCR), and/or cluster analysis. PRE and the other summary statistics are direct methods for analyzing data-they are not factor-based approaches. To quantify the performance of summary statistics, we use the concept of the "critical pair," which is employed in chromatography. The data analyzed here come from different analytical methods. Hyperspectral images, including one of a biological material, are also analyzed. In general, PRE outperforms the other summary statistics, especially in image analysis, although a suite of summary statistics is useful in exploring complex data sets. While PRE results were generally comparable to those from PCA and MCR, PRE is easier to apply. For example, there is no need to determine the number of factors that describe a data set. Finally, we introduce the concept of divided spectrum-PRE (DS-PRE) as a new EDA method. DS-PRE increases the discrimination power of PRE. We also show that DS-PRE can be used to provide the inputs for the k-nearest neighbor (kNN) algorithm. We recommend PRE and DS-PRE as rapid new tools for unsupervised EDA.

Approximate Bayesian Computation is widely used in systems biology for inferring parameters in stochastic gene regulatory network models. Its performance hinges critically on the ability to summarize high-dimensional system responses such as time series into a few informative, low-dimensional summary statistics. The quality of those statistics acutely impacts the accuracy of the inference task. Existing methods to select the best subset out of a pool of candidate statistics do not scale well with large pools of several tens to hundreds of candidate statistics. Since high quality statistics are imperative for good performance, this becomes a serious bottleneck when performing inference on complex and high-dimensional problems. This paper proposes a convolutional neural network architecture for automatically learning informative summary statistics of temporal responses. We show that the proposed network can effectively circumvent the statistics selection problem of the preprocessing step for ABC inference. The proposed approach is demonstrated on two benchmark problem and one challenging inference problem learning parameters in a high-dimensional stochastic genetic oscillator. We also study the impact of experimental design on network performance by comparing different data richness and data acquisition strategies.

Over the last decade the availability of SNP-trait associations from genome-wide association studies has led to an array of methods for performing Mendelian randomization studies using only summary statistics. A common feature of these methods, besides their intuitive simplicity, is the ability to combine data from several sources, incorporate multiple variants and account for biases due to weak instruments and pleiotropy. With the advent of large and accessible fully-genotyped cohorts such as UK Biobank, there is now increasing interest in understanding how best to apply these well developed summary data methods to individual level data, and to explore the use of more sophisticated causal methods allowing for non-linearity and effect modification. In this paper we describe a general procedure for optimally applying any two sample summary data method using one sample data. Our procedure first performs a meta-analysis of summary data estimates that are intentionally contaminated by collider bias between the genetic instruments and unmeasured confounders, due to conditioning on the observed exposure. These estimates are then used to correct the standard observational association between an exposure and outcome. Simulations are conducted to demonstrate the method’s performance against naive applications of two sample summary data MR. We apply the approach to the UK Biobank cohort to investigate the causal role of sleep disturbance on HbA1c levels, an important determinant of diabetes. Our approach can be viewed as a generalization of Dudbridge et al. (Nat. Comm. 10: 1561), who developed a technique to adjust for index event bias when uncovering genetic predictors of disease progression based on case-only data. Our work serves to clarify that in any one sample MR analysis, it can be advantageous to estimate causal relationships by artificially inducing and then correcting for collider bias., Author summary Uncovering causal mechanisms between risk factors and disease is challenging with observational data because of unobserved confounding. Mendelian randomization offers a potential solution by replacing an individual’s observed risk factor data with an unconfounded genetic proxy measure. Over the last decade an array of methods for performing Mendelian randomization studies (MR) using publicly available summary statistics gleaned from two separate genome-wide association studies. With the advent of large and accessible fully-genotyped cohorts such as UK Biobank, there is now increasing interest in understanding how best to apply these well-developed summary data methods to individual level data. In this paper we describe a general procedure for optimally applying any summary data MR method using individual level data from one cohort study. Our approach may at first seem nonsensical: we create summary statistics that are intentionally biased by confounding. This bias can, however, be very accurately estimated, and the estimate then used to correct the results of a standard observational analysis. We apply our new way of performing an MR analysis to data from UK Biobank to investigate the causal role of sleep disturbance on HbA1c levels, an important determinant of diabetes.

Most existing tools for constructing genetic prediction models begin with the assumption that all genetic variants contribute equally towards the phenotype. However, this represents a suboptimal model for how heritability is distributed across the genome. Therefore, we develop prediction tools that allow the user to specify the heritability model. We compare individual-level data prediction tools using 14 UK Biobank phenotypes; our new tool LDAK-Bolt-Predict outperforms the existing tools Lasso, BLUP, Bolt-LMM and BayesR for all 14 phenotypes. We compare summary statistic prediction tools using 225 UK Biobank phenotypes; our new tool LDAK-BayesR-SS outperforms the existing tools lassosum, sBLUP, LDpred and SBayesR for 223 of the 225 phenotypes. When we improve the heritability model, the proportion of phenotypic variance explained increases by on average 14%, which is equivalent to increasing the sample size by a quarter., Existing genetic prediction tools typically assume that genetic variants contribute equally towards the phenotype. The authors develop eight prediction tools that allow the user to specify the heritability model, and show that these tools enable substantially improved prediction of complex traits.

Genetic prediction of complex traits has great promise for disease prevention, monitoring, and treatment. The development of accurate risk prediction models is hindered by the wide diversity of genetic architecture across different traits, limited access to individual level data for training and parameter tuning, and the demand for computational resources. To overcome the limitations of the most existing methods that make explicit assumptions on the underlying genetic architecture and need a separate validation data set for parameter tuning, we develop a summary statistics-based nonparametric method that does not rely on validation datasets to tune parameters. In our implementation, we refine the commonly used likelihood assumption to deal with the discrepancy between summary statistics and external reference panel. We also leverage the block structure of the reference linkage disequilibrium matrix for implementation of a parallel algorithm. Through simulations and applications to twelve traits, we show that our method is adaptive to different genetic architectures, statistically robust, and computationally efficient. Our method is available at https://github.com/eldronzhou/SDPR., Author summary Recently there has been much interest in predicting an individual’s phenotype from genetic information, which has great promise for disease prevention, monitoring, and treatment. It has been found that there is great variation in the genetic architecture underlying different complex traits, including the number of genetic variants involved and the distribution of the effect sizes of genetic variants. How to model such genetic contribution is a key aspect for accurate prediction of complex traits. So far, most existing methods make specific assumptions about the shape of the genetic contribution. If these assumptions are not correct, the prediction accuracy might be compromised. Here we propose a method that learns the shape of the genetic contribution without making any explicit assumptions. We found that our method achieved robust performance when compared with other recently developed methods through simulation and real data analysis. Our method is also practically more feasible, since it supports the use of public summary statistics and consumes only small amount of computational resources.

The use of a variety of instruments for quality assurance, management, and enhancement in higher education is well recognized. This article investigated the instruClose Panelments used by Higher Education Institutions (HEIs) in Oman to measure, control, and manage the quality of their services in alignment with the standards set by Oman Academic Accreditation Authority (OAAA). Quality Assurance Managers (QAMs) from five HEIs were interviewed to identify the instruments used by them to fulfil the requirements of each standard and the way they make use of the data gathered by using these instruments. Findings from the study reveal that questionnaires and meetings are the most common instruments used by these institutions to measure, control and assure the efficacy of their current quality activities. In addition, HEIs use summary statistics to analyse data and then present them in meetings or through reports. On the other hand, it was found that substantial efforts are made to collect data but the efficient usage of data is missing. The QAMs reported a lack of awareness among the staff on the importance of collecting data since the staff members believe that these data are collected for documentation purposes only. This study emphasizes the importance of using the data gathered from different instruments in decision making and enhancing the quality of HEIs.

Purpose: The COVID-19 pandemic modified the Residency Match process for fourth-year medical students. In-person away rotations were discouraged, interviews were virtual, and traditional factors used to rank programs were absent. Here, we compare survey results administered to both the 2020 and 2021 Match applicants to assess the influence of the pandemic on the radiation oncology (RO) Match process. Methods: An institutional review board–approved prospective cross-sectional study was conducted. The 2020 and 2021 RO Match applicants at a large RO program were invited to participate. Descriptive summary statistics were assessed. Results: The 2020 and 2021 Matches each had 76 applicants complete the survey with response rates of 54% and 57%, respectively. The 2 groups were predominantly white, cisgender male, single, and without children. Whereas 11% of 2020 applicants did not complete away rotations, 45% of 2021 applicants did not. For 2021 Match applicants, 65% of away rotations were performed virtually, whereas 51% were not for medical school credit. Of the applicants, 84% were satisfied with virtual interviews and 72% felt cost savings were worth not having in-person interviews. Whereas 49% of Match 2020 applicants spent >$5000 in interview costs, 0% of the Match 2021 applicants did so, with 45% spending

Background Since the Global Burden of Disease study (GBD) has become more comprehensive, data for hundreds of causes of disease burden, measured using Disability Adjusted Life Years (DALYs), have become increasingly available for almost every part of the world. However, undergoing any systematic comparative analysis of the trends can be challenging given the quantity of data that must be presented. Methods We use the GBD data to describe trends in cause-specific DALY rates for eight regions. We quantify the extent to which the importance of ‘major’ DALY causes changes relative to ‘minor’ DALY causes over time by decomposing changes in the Gini coefficient into ‘proportionality’ and ‘reranking’ indices. Results The fall in regional DALY rates since 1990 has been accompanied by generally positive proportionality indices and reranking indices of negligible magnitude. However, the rate at which DALY rates have been falling has slowed and, at the same time, proportionality indices have tended towards zero. These findings are clearest where the focus is exclusively upon non-communicable diseases. Notably, large and positive proportionality indices are recorded for sub-Saharan Africa over the last decade. Conclusion The positive proportionality indices show that disease burden has become less concentrated around the leading causes over time, and this trend has become less prominent as the DALY rate decline has slowed. The recent decline in disease burden in sub-Saharan Africa is disproportionally driven by improvements in DALY rates for HIV/AIDS, as well as for malaria, diarrheal diseases, and lower respiratory infections.

While genome-wide association studies (GWASs) have been widely used to uncover associations between diseases and genetic variants, standard SNP-level GWASs often lack the power to identify SNPs that individually have a moderate effect size but jointly contribute to the disease. To overcome this problem, pathway-based GWASs methods have been developed as an alternative strategy that complements SNP-level approaches. We propose a Bayesian method that uses the generalized fused hierarchical structured variable selection prior to identify pathways associated with the disease using SNP-level summary statistics. Our prior has the flexibility to take in pathway structural information so that it can model the gene-level correlation based on prior biological knowledge, an important feature that makes it appealing compared to existing pathway-based methods. Using simulations, we show that our method outperforms competing methods in various scenarios, particularly when we have pathway structural information that involves complex gene-gene interactions. We apply our method to the Wellcome Trust Case Control Consortium Crohn’s disease GWAS data, demonstrating its practical application to real data.

The food security literature has reiterated the importance of having an indicator that simultaneously captures the different dimensions of the food security definition. In this regard, this study builds on previous studies using a harmonized food security indicator within a relatively high frequency panel data from Rwanda to examine the dynamics of household food security. Summary statistics show the transitory nature of food security where households go either from complete state of food insecurity to being partially food insecure or from being partially food insecure to being completely food secure during the harvesting seasons and later fall back to their initial state during the sowing and growing seasons. This underscores the intertemporal dimension and transitory nature of food security over time. We also employed a correlated random effects multinomial logit model to further identify the determinants of households being in any of the identified states of food security. Results suggest that agricultural seasons of major food crops do determine households’ state of food security. Also, household socio-demographic characteristics, household assets, income diversification, and location of the household dwelling are some of the consistent factors that increase or decrease the likelihood of the household being food insecure.

Meta-analysis has become an integral part of evidence-based decision-making processes and is being increasingly used in medical and non-medical disciplines. Aggregate data or summary statistics continue to be the mainstay of meta-analysis and are used by many professional societies to support clinical practice guidelines. Meta-analyses synthesize the summary statistics from independent trials by pooling them to estimate the underlying common effect size. The results represent the highest level of evidence but only if the chosen studies are of high quality and the selection criteria are fully satisfied. It is important to address the issues of defining an explicit and relevant question, exhaustively searching for the totality of evidence, meticulous and unbiased data transfer or extraction, assessment of between study heterogeneity and the use of appropriate statistical methods for estimating summary effect measures. This article reviews the methodology, benefits and drawbacks of performing a meta-analysis.

Objective: Continuous outcome measures are essential in rehabilitation research. Incomplete reporting of their mean and standard deviation, required for meta-analysis, potentially introduces bias and imprecision if it prevents studies being included. We aimed to determine how often systematic reviewers encounter missing mean or standard deviation values and to recommend practical statistical solutions. Design: 1. Cross-sectional survey of systematic review authors. 2. Reanalysis of Cochrane review data to evaluate how accurately statistical methods for recovering missing mean or standard deviation values estimate the true meta-analysis treatment effect. Setting: Rehabilitation intervention systematic reviews. Participants: Cochrane stroke rehabilitation review authors; stroke patients. Interventions: Reanalysis of a Cochrane review of early supported discharge services. Main measures: Hospital length of stay. Results: Survey responses covered 53 of 70 Cochrane reviews. Almost all studied continuous outcome measures, 68% encountering missing summary statistics. Various solutions were attempted but 76% of meta-analyses omitted at least one study due to missing information. In the review reanalysis ( N = 1055), a method based on the minimum and maximum performed best in recovering missing standard deviations; a method based on the median, lower and upper quartiles successfully estimated a missing mean. Conclusion: Practical statistical methods help reduce risk of bias, maximise the evidence included in rehabilitation meta-analyses and offer a clear hierarchy of solutions to handling unreported mean and standard deviation values.

Blockchain is an emergent technology that has attracted practitioner attention in the supply chain domain. Multiple motivators lead companies to incorporate blockchain technology into their supply chain. However, a number of barriers and challenges may impede the successful adoption of blockchains. The purpose of this paper is to explore how a variety of motivators and barriers are perceived by different companies from different industries. This paper summarizes survey data gathered from 173 respondents associated with the association of supply chain management, formerly APICS. Summary statistics on blockchain adoption by various types of companies are provided to help practitioners benchmark current practice. The paper presents preliminary findings on these dimensions with some insights provided.

BACKGROUND/OBJECTIVES Improving quality performance in home health is an increasingly high priority. The objective of this study was to examine trends in industry performance over time using three quality measures: a composite quality metric (Q index), an infection prevention measure (vaccination verification), and an outcome measure (hospital avoidance). DESIGN/SETTING/PARTICIPANTS/MEASURES We linked Home Health Compare and Provider of Services data from 2012 to 2016, which included 39 211 observations during the 5-year study period and 7670 agencies in 2016. The Q index was developed to allow comparability over time, equally weighting the contributions of each element. After examining summary statistics, we developed three regression models stratified by ownership (for-profit/nonprofit agency) and included two constructs of nurse staffing, in addition to controlling for known confounders. RESULTS Most agencies (80.4%) were for-profit agencies. The Q index and vaccination verification improved substantially over time, but there was no change in hospital avoidance. Ownership status was associated with all three measures (P

This book describes how to conduct a large-scale anthropometric survey in the military with a specific focus on the New Zealand Defence Force Anthropometry Survey. This book provides a historical introduction to surface kinanthropometry (Part I), 3D scanning technology (Part II) and an overview of military anthropometry surveys in Part IV. It also provides a description of the New Zealand Defence Force (NZDF) anthropometry survey in Part IV, conclusions in Part V and concludes with the measurement technique protocols and normative data for the NZDF kinanthropometry survey in Part VI. While surface anthropometry has traditionally been used to assess body composition through the internationally recognised methodology of the International Society for the Advancement of Kinanthropometry (ISAK), the commercialisation of three-dimensional photometry (3D scanning) has led to the adoption of new and often non-standardised, measurement techniques. We detail standardisation procedures for 3D scanning in terms of participant preparation, equipment calibration, test protocols, data reporting and data interpretation. We outline how 3D scanning works, what it is used to measure, and what the issues are surrounding its validity, practicality, and reliability. This book provides an essential reference for practitioners wishing to measure military physique. We have not presented 3-D assessment data (i.e. surface manifold, volumetric, symmetry or shape analysis). We have only extracted 1-D measures from 3D images in this eBook.

Background Female sex workers are extremely vulnerable and highly susceptible to being infected with human immunodeficiency virus. As a result, community-based targeted interventions have been recommended as one of the models of care to improve access to HIV services and continued engagement in care. We conducted a systematic review to (1) assess the effect of FSW-targeted community interventions on the improvement of HIV services access along the treatment cascade and (2) describe community-based interventions that positively affect continuation in HIV care across the HIV treatment cascade for FSWs in sub-Saharan Africa. Methods We defined the 5 steps that make up the HIV care cascade and categorized them as outcomes, namely, HIV testing and diagnosis, linkage to care, receipt of ART, and achievement of viral suppression. We conducted a systematic search of randomized controlled trials, cohort, and cross-sectional studies done in sub-Saharan African countries and published from 2004 to 2020. The period was selected based on the time span within which ART was scaled up through widespread roll-out of comprehensive HIV programs in sub-Saharan Africa. We reviewed studies with data on the implementation of community interventions for any of the HIV care cascade stage. The data were analyzed using random effects meta-analysis where possible, and for the rest of the studies, data were synthesized using summary statistics. Results The significant impact of the community interventions was observed on HIV testing, HIV diagnosis, and ART use. However, for HIV testing and ART use, the improvement was not sustained for the entire period of implementation. There were minimal interventions that had impact on HIV diagnosis, with only one community service delivery model showing significance. Generally, the interventions that had reasonable impact are those that implemented targeted and comprehensive package of HIV services provided at one location, and with unique strategies specific to each cascade stage. Conclusions The evidence brought forward from this review shows that the effect of community-based interventions varies across the different stages of HIV care cascade. A broad package of interventions including a combination of behavioral, biomedical, and structural, designed with specific strategies, unique to each cascade stage appears to be more effective, although information on long-term treatment outcomes and the extent to which FSWs remain engaged in care is sparse. There is need to conduct a further research to deepen the assessment of the effectiveness of community-based interventions on HIV care cascade for FSWs. This will enhance identification of evidence-based optimal interventions that will guide effective allocation of scarce resources for strategies that would have a significant impact on HIV service delivery. Systematic review registration PROSPERO CRD42020157623

Polygenic risk scores (PRSs) have wide applications in human genetics research, but often include tuning parameters which are difficult to optimize in practice due to limited access to individual-level data. Here, we introduce PUMAS, a novel method to fine-tune PRS models using summary statistics from genome-wide association studies (GWASs). Through extensive simulations, external validations, and analysis of 65 traits, we demonstrate that PUMAS can perform various model-tuning procedures using GWAS summary statistics and effectively benchmark and optimize PRS models under diverse genetic architecture. Furthermore, we show that fine-tuned PRSs will significantly improve statistical power in downstream association analysis. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-021-02479-9.

Background Patients with kidney disease are referred late to tertiary institutions with increased morbidity and mortality. The accurate diagnoses and management of kidney disease by primary healthcare staff is dependent on the requisite knowledge and availability of adequate laboratory services. We set out to describe the practice pattern of districts Hospitals. Methods We conducted a situational cross-sectional descriptive survey of district hospitals within the Ashanti region of Ghana. A structured questionnaire was designed via google survey and the links sent to medical superintendents and/or administrators for completion. Data was exported onto an Excel sheet and analyzed with Stata 13. Summary statistics with means ± standard deviation and medians with interquartile range were used where appropriate. Percentages and proportions were used for categorical data. Results We surveyed 26 hospitals in the Ashanti region of Ghana. This included 23(88.5%) public facilities. Most 25(96.2%) of hospitals had a dedicated diabetes mellitus clinic and 24(92.3%) had dedicated hypertension clinic. Only 5(19.2%) hospitals routinely requested urinalysis for patients with diabetes and hypertension during visits. Almost all 25(96.2%) hospitals could carry out routine urine analysis in their laboratory but only 16 (61.5%) of the hospitals could run serum urea and creatinine test. Most 25(96.2%) of respondents suggested that the training of health staff for the early diagnosis and management of kidney disease as key to improve care. Conclusion Primary healthcare staff in district hospitals do not routinely screen high risk patients for kidney disease and call for training to manage patients with kidney disease appropriately.

Widely applicable, accurate and fast inference methods in phylodynamics are needed to fully profit from the richness of genetic data in uncovering the dynamics of epidemics. Standard methods, including maximum-likelihood and Bayesian approaches, generally rely on complex mathematical formulae and approximations, and do not scale with dataset size. We develop a likelihood-free, simulation-based approach, which combines deep learning with (1) a large set of summary statistics measured on phylogenies or (2) a complete and compact representation of trees, which avoids potential limitations of summary statistics and applies to any phylodynamics model. Our method enables both model selection and estimation of epidemiological parameters from very large phylogenies. We demonstrate its speed and accuracy on simulated data, where it performs better than the state-of-the-art methods. To illustrate its applicability, we assess the dynamics induced by superspreading individuals in an HIV dataset of men-having-sex-with-men in Zurich. Our tool PhyloDeep is available ongithub.com/evolbioinfo/phylodeep.

Severe or major trauma is a pandemic and one of the leading causes of death and disability; It is distributed unequally worldwide with most of these deaths occurring in LMICs. The WHO estimates that in 2030 there will be 1.485.365 in the African region. Mozambique has no prehospital care system nor trauma centers despite having a high incidence of injuries. The few critical patients that arrive in the ER rely on self-arranged transport to reach emergency care and have a low chance of survival because of few resources and lack of training of the staff. Basic trauma resuscitation techniques are unknown to most hospital personnel in LMICs. The aim of this study is to evaluate the attitude and knowledge of the management of trauma care among clinical staff of three quaternary level Hospitals of Mozambique. It will be conducted a prospective cross-sectional study between April and May 2020, in Maputo, Beira and Nampula Central Hospitals. The participants will include the medical doctors and technicians (general practitioners, general surgeons, orthopedic surgeons and anesthetists) that work on an ER. Data will be collected using a three-part questionnaire including: demographic information, trauma knowledge questionnaire and trauma attitude questionnaire. All the data will be analysed using SPSS version 22.0. Standard descriptive and summary statistics will be generated for the demographic part of the survey. Independent t-test and one-way ANOVA will be used to compare the level of knowledge and attitude with each other and with the demographic variables.

Background Civil strife has long been recognized as a significant barrier in the fight against vaccine preventable diseases in several parts of the world. However, little is known about the impact of the ongoing civil strife on the immunisation system in the Northwest (NW) and Southwest (SW) regions of Cameroon, which erupted in late 2016. In this paper, we assessed the effect of the conflict on key immunisation outcomes in the North West and South West regions of Cameroon. Methods Data were obtained from the standard EPI data reporting tool, the District Vaccine and Data Management Tool (DVDMT), from all the districts in the two regions. Completed forms were then reviewed for accuracy prior to data entry at central level. Summary statistics were used to estimate the variables of interest for each region for the years 2016 (pre-conflict) and 2019 (during conflict). Results In the two regions, the security situation has deteriorated in almost all districts, which in turn has disrupted basic healthcare delivery in those areas. A total of 26 facilities were destroyed and 11 healthcare workers killed in both regions. Reported immunisation coverage rates for key antigens including, BCG, DPT-3 and MR, witnessed a dramatic decline between 2016 and 2019, ranging from 22% points decline for BCG in the NW and to 42% points decline for DPT-3 in the SW. Similarly, the proportion of districts with DPT-3 coverage of at least 80% dropped from 75% in 2016 to 11% in 2019 in the NW. In the SW this proportion dropped from 16% in 2016 to 0 % in 2019. Conclusion Our data demonstrates the marked negative impact of the ongoing civil strife on key immunisation outcomes in the two regions and the country at large. This decline could amplify the risk of vaccine preventable diseases vaccine preventable diseases outbreaks in the two regions. Besides the ongoing actions to contain the crises, effective strategies for reaching children in the conflict zones as well as the internally displaced population are needed. There is also the need to rebuild destroyed facilities as well as to protect health facilities and staff from targeted violence.

OBJECTIVE: To document dementia‐relevant state assisted living regulations and their changes over time as they pertain to licensed care settings. DATA SOURCES: For all states, current directories of licensed assisted living communities and state regulations for each year, 2007‐2018, were obtained from state agency websites and Nexis Uni, respectively. STUDY DESIGN: We identified multiple types of regulatory classifications for each state and documented the presence or absence of specific dementia care provisions in the regulations for each type by study year. Maps and summary statistics were used to compare results to previous research and document change longitudinally. DATA COLLECTION/EXTRACTION METHODS: We used a policy analysis approach to connect communities listed in directories to applicable regulatory text. Then, we employed policy surveillance and question‐based coding to record the presence or absence of specific policies for each classification and study year. PRINCIPAL FINDINGS: Our team empirically documented provisions requiring dementia‐specific training for administrators and direct care staff, and cognitive impairment screening for each study year. We found that 23 states added one or more of these requirements for one or more license types, but the states that had these provisions for all types of licensed assisted living declined from four to two. CONCLUSIONS: We identified significant, previously undocumented, within‐state policy variation for assisted living licensed settings between 2007 and 2018. Using the regulatory classification instead of the state as the unit of analysis revealed that many policy adoptions were limited to dementia‐designated settings. This suggests that people living with dementia in general assisted living are not afforded the same protections. We call our approach health services regulatory analysis and argue that it has the potential to identify gaps in existing policies, an important endeavor for health services research in assisted living and other care settings.