bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Pandemic of the unvaccinated”? At midlife, white people are less vaccinated but still at less risk of Covid-19 mortality in Minnesota
Authors: Wrigley-Field Elizabeth , Berry Kaitlyn M. , Stokes Andrew C. , Leider Jonathon P. 
Published: March 2022

ABSTRACTIntroductionRecent research underscores the exceptionally young age distribution of Covid-19 deaths in the United States compared with international peers. This brief characterizes how high levels of Covid mortality at midlife ages (45-64) are deeply intertwined with continuing racial inequity in Covid-19 mortality.MethodsMortality data from Minnesota in 2020-2022 were analyzed in June 2022. Death certificate data and published vaccination rates in Minnesota allow vaccination and mortality rates to be observed with greater age and temporal precision than national data.ResultsBlack, Hispanic, and Asian adults under age 65 were all more highly vaccinated than white populations of the same ages during most of Minnesota’s substantial and sustained Delta surge and all of the subsequent Omicron surge. However, white mortality rates were lower than those of all other groups. These disparities were extreme; at midlife ages (ages 45-64), during the Omicron period, more highly-vaccinated populations had COVID-19 mortality that was 164% (Asian-American), 115% (Hispanic), or 208% (Black) of white Covid-19 mortality at these ages. In Black, Indigenous, and People of Color (BIPOC) populations as a whole, Covid-19 mortality at ages 55-64 was greater than white mortality at 10 years older.ConclusionsThis discrepancy between vaccination and mortality patterning by race/ethnicity suggests that, if the current period is a “pandemic of the unvaccinated,” it also remains a “pandemic of the disadvantaged” in ways that can decouple from vaccination rates. This result implies an urgent need to center health equity in the development of Covid-19 policy measures.
Automatic time in bed detection from hip-worn accelerometers for large epidemiological studies: The Tromsø Study
Authors: Weitz Marc , Syed Shaheen , Hopstock Laila A. , Morseth Bente , Henriksen André , Horsch Alexander 
Published: March 2022

AbstractAccelerometers are frequently used to assess physical activity in large epidemiological studies. They can monitor movement patterns and cycles over several days under free-living conditions and are usually either worn on the wrist or the hip. While wrist-worn accelerometers have been frequently used to additionally assess sleep and time in bed behavior, hip-worn accelerometers have been widely neglected for this task due to their primary focus on physical activity. Here, we present a new method with the objective to identify the time in bed to enable further analysis options for large-scale studies using hip-placement like time in bed or sedentary time analyses. We introduced new and accelerometer specific data augmentation methods, such as mimicking a wrongly worn accelerometer, additional noise, and random croping, to improve training and generalization performance. Subsequently, we trained a neural network model on a sample from the population-based Tromsø Study and evaluated it on two additional datasets. Our algorithm achieved an accuracy of 94% on the training data, 92% on unseen data from the same population and comparable results to consumer-wearable data obtained from a demographically different population. Generalization performance was overall good, however, we found that on a few particular days or participants, the trained model fundamentally over- or underestimated time in bed (e.g., predicted all or nothing as time in bed). Despite these limitations, we anticipate our approach to be a starting point for more sophisticated methods to identify time in bed or at some point even sleep from hip-worn acceleration signals. This can enable the re-use of already collected data, for example, for longitudinal analyses where sleep-related research questions only recently got into focus or sedentary time needs to be estimated in 24h wear protocols.
Fed-GLMM: A Privacy-Preserving and Computation-Efficient Federated Algorithm for Generalized Linear Mixed Models to Analyze Correlated Electronic Health Records Data
Authors: Yan Zhiyu , Zachrison Kori S. , Schwamm Lee H. , Estrada Juan J. , Duan Rui 
Published: March 2022

AbstractLarge collaborative research networks provide opportunities to jointly analyze multicenter electronic health record (EHR) data, which can improve the sample size, diversity of the study population, and generalizability of the results. However, there are challenges to analyzing multicenter EHR data including privacy protection, large-scale computation, heterogeneity across sites, and correlated observations. In this paper, we propose a federated algorithm for generalized linear mixed models (Fed-GLMM), which can flexibly model multicenter longitudinal or correlated data while accounting for site-level heterogeneity. Fed-GLMM can be applied to both federated and centralized research networks to enable privacy-preserving data integration and improve computational efficiency. By communicating only a limited amount of summary statistics, Fed-GLMM can achieve nearly identical results as the gold-standard method where the GLMM is directly fitted on the pooled dataset. We demonstrate the performance of Fed-GLMM in both numerical experiments and an application to longitudinal EHR data from multiple healthcare facilities.
Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling
Authors: Dao Binh T. , Nguyen Thang V. , Pham Hieu H. , Nguyen Ha Q. 
Published: March 2022

AbstractPurposeA fully automated system for interpreting abdominal computed tomography (CT) scans with multiple phases of contrast enhancement requires an accurate classification of the phases. Current approaches to classify the CT phases are commonly based on 3D convolutional neural network (CNN) approaches with high computational complexity and high latency. This work aims at developing and validating a precise, fast multi-phase classifier to recognize three main types of contrast phases in abdominal CT scans.MethodsWe propose in this study a novel method that uses a random sampling mechanism on top of deep CNNs for the phase recognition of abdominal CT scans of four different phases: non-contrast, arterial, venous, and others. The CNNs work as a slice-wise phase prediction, while the random sampling selects input slices for the CNN models. Afterward, majority voting synthesizes the slice-wise results of the CNNs, to provide the final prediction at scan level.ResultsOur classifier was trained on 271,426 slices from 830 phase-annotated CT scans, and when combined with majority voting on 30% of slices randomly chosen from each scan, achieved a mean F1-score of 92.09% on our internal test set of 358 scans. The proposed method was also evaluated on 2 external test sets: CTPAC-CCRCC (N = 242) and LiTS (N = 131), which were annotated by our experts. Although a drop in performance has been observed, the model performance remained at a high level of accuracy with a mean F1-score of 76.79% and 86.94% on CTPAC-CCRCC and LiTS datasets, respectively. Our experimental results also showed that the proposed method significantly outperformed the state-of-the-art 3D approaches while requiring less computation time for inference.ConclusionsIn comparison to state-of-the-art classification methods, the proposed approach shows better accuracy with significantly reduced latency. Our study demonstrates the potential of a precise, fast multi-phase classifier based on a 2D deep learning approach combined with a random sampling method for contrast phase recognition, providing a valuable tool for extracting multi-phase abdomen studies from low veracity, real-world data.
impaired bed mobility in prediagnostic and de novo Parkinson’s disease
Authors: Dijkstra Femke , de Volder Ilse , Viaene Mineke , Cras Patrick , Crosiers David 
Published: March 2022

AbstractBackgroundWearable technology research suggests that nocturnal movements are disturbed in early Parkinson’s disease (PD). In this study, we investigate if patients also already experience impaired bed mobility before PD diagnosis. Furthermore, we explore its association with motor and nonmotor features and its value for phenoconversion and disease progression prediction.MethodsPPMI data were downloaded for de novo PD subjects, subjects at-risk for developing a synucleinopathy (with isolated REM sleep behavior disorder, hyposmia or a pathogenic mutation) and controls. Impaired bed mobility was assessed with the MDS-UPDRS part 2 item 9. A frequency analysis was performed. Multivariable logistic regression analyses were used to investigate the association with other PD variables. Cox proportional-hazards models were used to test if difficulties with turning in bed could predict phenoconversion. Linear mixed models were used to evaluate if difficulties with turning in bed could predict disease progression.ResultsOf the at-risk subjects, 9.2-12.5% experienced difficulties with turning in bed vs. 25.0% of de novo PD subjects and 2.5% of controls. Impaired turning ability was associated with MDS-UPDRS motorscore (axial signs in the at-risk group, bradykinesia in the de novo PD group) and SCOPA-AUT score (gastrointestinal symptoms). In addition, difficulties with turning in bed were a significant predictor for phenoconversion in the at-risk group and for development of motor complications in the de novo PD group.ConclusionOur findings suggest that difficulties with turning in bed can be helpful as clinical symptom for a prodromal PD screening and for motor complication prediction in early PD.HighlightsSubjective difficulties with turning in bed are a prodromal PD symptom.Impaired bed mobility predicts synucleinopathy phenoconversion in at-risk groups.Impaired bed mobility predicts development of motor complications in de novo PD.
Community Engagement to support COVID-19 Vaccine Uptake: A living systematic review protocol
Authors: Gilmore Brynne , Gerlach Nina , Lopes Claudia Abreu , Diallo Alpha Ahmadou , Bhattacharyya Sanghita , de Claro Vergil , Ndejjo Rawlance , Nyamupachitu- Mago Elizabeth , Tchetchia Adalbert 
Published: March 2022

AbstractBackgroundWidespread vaccination against Coronavirus Disease 2019 (COVID-19) is one of the most effective ways to control, and ideally, end the global COVID-19 pandemic. Vaccine hesitancy and vaccine rates vary widely across countries and populations and are influenced by complex socio-cultural, political, economic, and psychological factors. Community engagement is an integral strategy within immunisation campaigns and has been shown to improve vaccine acceptance. As evidence on community engagement to support COVID-19 vaccine uptake is emerging, this review aims to lessen the knowledge-to-practice gap by providing regular evidence on current best-practice.MethodologyA living systematic review will be conducted which includes an initial systematic review and bi-monthly review updates. Searching and screening for the review and subsequent updates will be done in four streams: a systematic search of six databases, grey literature review, preprint review, and citizen sourcing. All articles will be collated into Covidence, where screening will be done by a minimum of two reviewers at title/abstract and full-text. Data will be extracted across pre-defined data extraction tables, and synthesis will occur using the convergent integrated approach. Updates to the review resulting from the subsequent bi-monthly searches will be shared in an open-access platform. The protocol has been registered with PROSPERO: CRD42022301996.DiscussionGiven the variation in vaccination rates across different contexts and the recognition that high vaccination coverage is required to reduce COVID-19 transmission and to stop the emergence of new variants, it is imperative the global community implements strategies that will improve uptake and that this work is widely shared and contextualised. Community engagement to promote vaccine uptake is highly encouraged, and recent studies highlight its potential to influence vaccine rates, particularly across populations that are marginalised. The high-priority research needed on this topic, and the rapidly changing evidence base, supports the conduct of a living systematic review.
More or less deadly? A mathematical model that predicts SARS-CoV-2 evolutionary direction
Authors: Xu Zhaobin , Zeng Qiangcheng 
Published: March 2022

AbstractSARS-CoV-2 has caused tremendous deaths world wild. It is of great value to predict the evolutionary direction of SARS-CoV-2. In this paper, we proposed a novel mathematical model that could predict the evolutionary trend of SARS-CoV-2. We focus on the mutational effects on viral assembly capacity. A robust coarse-grained mathematical model is constructed to simulate the virus dynamics in the host body. Both virulence and transmissibility can be quantified in this model. The relationship between virulence and transmissibility can be simulated. A delicate equilibrium point that optimizing the transmissibility can be numerically obtained. Based on this model, we predict the virulence of SARS-CoV-2 might further decrease, accompanied by an enhancement of transmissibility. However, this trend is not continuous; its virulence will not disappear but remains at a relatively stable range. We can also explain the cross-species transmission phenomenon of certain RNA virus based on this model. A small-scale model which simulates the virus packing process is also proposed. It can be explained why a small number of mutations would lead to a significant divergence in clinical performance, both in the overall particle formation quantity and virulence. This research provides a mathematical attempt to elucidate the evolutionary driving force in RNA virus evolution.
Determinants of CEO compensation: evidence from Pakistan
Authors: Khursheed Aisha , Sheikh Nadeem Ahmed 
Published: March 2022

Purpose
The purpose of this paper is to investigate the impact of firm-specific (i.e. firm size, profitability, leverage, dividend, growth opportunities, management quality and firm age) and country-specific (i.e., gross domestic product [GDP] growth) variables on compensation/remuneration offered to chief executive officers (CEOs) working in different industries of Pakistan.

Design/methodology/approach
Panel data techniques, namely, pooled ordinary least squares, fixed effects and random effects methods are used to estimate the results. Moreover, Hausman test is used to choose which estimation method, either fixed effects or random effects, is better to explain the results.

Findings
Firm size, profitability, leverage, growth opportunities and age are some important firm-specific factors that have mixed (i.e. positive/negative) impact on CEO compensation in different industries. Variations in results are due to industry dynamics. However, it is important to mention that three key variables, namely, dividend, management quality and GDP growth have shown consistent positive impact on CEO compensation in most of the industries. In sum, results show that firm-specific and country-specific variables have material effects on CEO compensation. Moreover, results are found consistent with the predictions of agency theory and human capital theory.

Practical implications
The authors are sure that findings of this study provide some support to the board of directors to determine the pay slice for CEOs. Moreover, findings provide support to the regulatory authorities in formulating mechanisms to determine the compensation package for CEOs working in different industries and to improve the Code of Corporate Governance.

Originality/value
To the best of the authors’ knowledge, no empirical study in Pakistan has yet estimated the effects of firm-specific and country-specific variables on compensation offered to CEOs working in different industries. Thus, industry-wise analysis provides some new insights to the decision-makers and lays some foundation upon which a more detail analysis could be based.
The role of reaction to feedback in the relationship between performance management, job satisfaction and the leader–member exchange (LMX)
Authors: Cesário Francisco , Rodrigues Antero , Castanheira Filipa , Sabino Ana 
Published: March 2022

PurposeDue to the importance of performance management in any organizational structure, the present study aims to analyze the mediating role of an employee's reaction to the employee's supervisor' feedback on the impact of the performance management system on job satisfaction and supervisor–employee relationship.Design/methodology/approachA quantitative study was conducted, with data collected by questionnaire, where 1815 workers from a customer service company in Portugal participated and with the data analyzed using structural equation model.FindingsThree effects were observed in this study: first, the importance of performance management on the reaction to feedback and on the supervisor–employee relationship; second, reaction to feedback fully mediated the effect of performance management on job satisfaction and third, reaction to feedback partially mediated the effect of the performance management on the supervisor–employee relationship.Originality/valueDespite the growing interest in research on performance management, this study suggests that there are still some areas in need of additional research attention, namely on the important role that adequate feedback to the employee on his/her performance can have. Implications for research on performance management are developed.
Gender differences in extractive activities: evidence from Ghana
Authors: Baah-Boateng William , Twum Eric Kofi , Akyeampong Emmanuel Kwaku 
Published: March 2022

PurposeThe study seeks to examine women’s participation in Ghana’s extractive growth-driven economy and the quality of this participation in terms of employment status and earnings relative to their male counterparts and establish whether these differences constitute discrimination for policy attention.Design/methodology/approachThe study adopts both quantitative and qualitative methodological approaches to assess the extent of gender inequality in employment and earnings in the Ghanaian extractive sector and the sources of these differences. It computes three segregation indices to ascertain the degree of unequal gender distribution of employment based on nationally representative labour force and living standards surveys followed by quantitative analysis of gender earnings differences using Oaxaca–Blinder decomposition technique. This is complemented by the results of Focus Group Discussion to go behind the numbers and examine the sources of the employment and earnings differences between men and women in extractive activities.FindingsThe authors observe lower participation of women in the extractive sector, with a considerable degree of gender segregation and existence of gender earnings gap in favour of men due to differences in observable characteristics such as age, education and occupational skills. There is also evidence of existence of discrimination against women and indication of barriers that impede women’s involvement in high-earning extractive activities in Ghana. The study suggests measures to remove these barriers and improve women’s education particularly in science, technology, engineering and mathematics to address the gender imbalance in extractive activities in Ghana.Social implicationsWomen’s low involvement in the strong extractive growth-driven process has implication for undermining the effort of empowering women economically.Originality/valueThe study draws argument from the literature and adopts a combination of quantitative and qualitative techniques to establish gender in terms of employment distribution and earnings in favour of males in the Ghanaian extractive sector. This has the effect of undermining women’s economic empowerment and exacerbating gender inequality in the country.
Physician's online image and patient's choice in the online health community
Authors: Ouyang Peng , Wang Jian-Jun 
Published: March 2022

PurposeThe impact of image is widely investigated in various research fields. However, its effect in online health communities is rarely studied. In this research, the authors develop a theoretical model to assess the impact of physicians' image on patients' choices in online health communities.Design/methodology/approachThe authors developed a web crawler based on R language program to collect more than 40,000 physicians' images and other related information from their homepages in Haodf.com–a leading online health community in China. The features of physicians' images are computed by Face++ Application Programming Interface (API) through the following variables: beauty, smile and skin status.FindingsThe empirical results derive the following findings: (1) physician's beauty or physical attractiveness has no significant effect on patients’ choice; (2) Smile has a positive effect on patients’ choices; (3) Physician's skin status also positively affects patients' choices; (4) Physician's professional capital strengthens the effect of beauty, smile and skin status on patients' choices; (5) Beauty and skin status are the substitutes for each other, and smile and skin status are the substitutes for each other too.Research limitations/implicationsAlso, this study provides implications for both physicians and online health community platform managers.Originality/valueThis study provides new evidence in understanding the impact of physician's online image and contributes to the literature on signaling theory, impression management theory and patients' choices.
Understanding the cultural underpinnings of managerial performance reporting (MPR) in Ghana
Authors: Nsor-Ambala Randolph 
Published: March 2022

Purpose
This study aims to explore the main features of managerial performance reporting (MPR) in Ghana and applied a national social-cultural framework to understanding the MPR practices.

Design/methodology/approach
It is a qualitative study based on responses from mid-level managerial employees within the top companies in Ghana dubbed Ghana Club 100 (GC100). GC100 includes a balanced mix of companies across varied industry classifications and local and multinational companies (MNCs). This enriches the data and deviates from similar studies that have usually relied on data from multinational companies.

Findings
There is evidence that while MPR practices in Ghana do not significantly deviate from western approaches, the underlying reasons for such managerial practices and actions may defer on national socio-cultural lines. This study discusses how various cultural attributions explain the features and motivations for MPR practices in Ghana, including a difference in expectations about the purpose of an MPR.

Practical implications
MNCs must be guided by the findings of this study in their drive to inculcate standardised practices across organisations. It is also essential for MNCs to appreciate the more than usual reliance on verbal cues and symbols in interpreting the appropriate course of action. Regulators must consider systematic activities that reduce the tension and suspicion between them and business actors to improve information transparency. Whistleblowing schemes, while helpful, may not be effective because organisational agents within MPR practice consider themselves part of an “in-group” and manage their dissonance through categorisation, rationalisation and superficial attention to standards. Because of the excessive use of unwritten cues, auditors must consider visits to the client’s operational premises and other independent observation efforts vital to their evidence gathering process.

Originality/value
To the best of the author’s knowledge, this paper is among the first to evaluate MPR practices based on direct responses from “persons close to the MPR action” rather than the current overreliance on secondary data sources such as content analysis.