Search

Background: The GRADE-CERQual (Grading of Recommendations Assessment, Development and Evaluation-Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE working group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) relevance, (3) coherence and (4) adequacy of data. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual's coherence component., Methods: We developed the coherence component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual coherence component within several qualitative evidence syntheses before agreeing on the current definition and principles for application., Results: When applying CERQual, we define coherence as how clear and cogent the fit is between the data from the primary studies and a review finding that synthesises that data. In this paper, we describe the coherence component and its rationale and offer guidance on how to assess coherence in the context of a review finding as part of the CERQual approach. This guidance outlines the information required to assess coherence, the steps that need to be taken to assess coherence and examples of coherence assessments., Conclusions: This paper provides guidance for review authors and others on undertaking an assessment of coherence in the context of the CERQual approach. We suggest that threats to coherence may arise when the data supporting a review finding are contradictory, ambiguous or incomplete or where competing theories exist that could be used to synthesise the data. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase.

Background: The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) working group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations; (2) coherence; (3) adequacy of data; and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual's adequacy of data component., Methods: We developed the adequacy of data component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual adequacy of data component within several qualitative evidence syntheses before agreeing on the current definition and principles for application., Results: When applying CERQual, we define adequacy of data as an overall determination of the degree of richness and the quantity of data supporting a review finding. In this paper, we describe the adequacy component and its rationale and offer guidance on how to assess data adequacy in the context of a review finding as part of the CERQual approach. This guidance outlines the information required to assess data adequacy, the steps that need to be taken to assess data adequacy, and examples of adequacy assessments., Conclusions: This paper provides guidance for review authors and others on undertaking an assessment of adequacy in the context of the CERQual approach. We approach assessments of data adequacy in terms of the richness and quantity of the data supporting each review finding, but do not offer fixed rules regarding what constitutes sufficiently rich data or an adequate quantity of data. Instead, we recommend that this assessment is made in relation to the nature of the finding. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase.

Objective: Electronic data collection (EDC) has become a suitable alternative to paper based data collection (PBDC) in biomedical research even in resource poor settings. During a survey in Nepal, data were collected using both systems and data entry errors compared between both methods. Collected data were checked for completeness, values outside of realistic ranges, internal logic and date variables for reasonable time frames. Variables were grouped into 5 categories and the number of discordant entries were compared between both systems, overall and per variable category. Results: Data from 52 variables collected from 358 participants were available. Discrepancies between both data sets were found in 12.6% of all entries (2352/18,616). Differences between data points were identified in 18.0% (643/3580) of continuous variables, 15.8% of time variables (113/716), 13.0% of date variables (140/1074), 12.0% of text variables (86/716), and 10.9% of categorical variables (1370/12,530). Overall 64% (1499/2352) of all discrepancies were due to data omissions, 76.6% (1148/1499) of missing entries were among categorical data. Omissions in PBDC (n = 1002) were twice as frequent as in EDC (n = 497, p < 0.001). Data omissions, specifically among categorical variables were identified as the greatest source of error. If designed accordingly, EDC can address this short fall effectively. [ABSTRACT FROM AUTHOR]

Background: Pakistan has been showing consistently the highest prevalence of consanguinity. The popularity of consanguineous marriages is not declining in the country, because of social, cultural, and religious beliefs as well as economic advantages. However, couples also face various health-related implications, such as poor pregnancy outcomes or multiple reproductive and fertility consequences, having adverse effects on mothers and their children. This research investigated the trend of consanguineous marriages and their association with women's reproductive health and fertility behavior in Pakistan from 1990 to 2018., Methods: This study is based on secondary data analysis, using all four waves of the Pakistan Demographic Health Surveys carried out from 1990 to 2018. The analysis is limited to women aged 15-49 years, who had given birth in the previous five years preceding each survey. Sampling weights were calculated and subsequently weighted analysis was conducted. Descriptive statistics, bivariable and multivariable logistic regression analysis were performed to determine the association of consanguinity with multiple characteristics related to socio-demographics, co-variates, and women's reproductive health and fertility behaviors., Results: The findings revealed a high but overall stable trend of consanguinity prevalence of about 63% during the last three decades. Consanguineous marriages were more prevalent amongst young and uneducated women, living in rural areas, with poorer wealth status and having less exposure to mass media to access information. A strong association of consanguinity was observed with women's reproductive health and fertility behavior, particularly for women who gave first birth at a younger age, had multi-gravida pregnancies, multi-parity, pregnancy termination, ANC visits, and higher fertility., Conclusion: Consanguineous marriages are predominant in the patriarchal society of Pakistan. Findings revealed that consanguinity contributes significantly to women's reproductive health and fertility behaviors. Appropriate counseling, educational, and health promotional programs related to consanguinity should be designed and launched at the community level to raise awareness about risks towards women's reproductive health and fertility., (© 2022. The Author(s).)

Objective To examine the psychometric properties of the online administered parental version of the Strength and Difficulties Questionnaire (SDQ), and to provide parental norms from a nationwide Swedish sample. Methods A total of 1443 parents from of a national probability sample of 2800 children aged 10-13 years completed the SDQ online or as usual (i.e., using paper-and-pencil). Results The SDQ subscales obtained from the online administration showed high internal consistency (polychoric ordinal alpha), and confirmatory factor analysis of the SDQ five factor model resulted in excellent fit. The Total Difficulties score of the SDQ and its other subscales were significantly related to the Disruptive Behavior Disorders (DBD) rating scale. Norms for the parent version of SDQ obtained from the Internet were identical to those collected using paper-and-pencil. They were thus combined and are presented sorted by child gender and age. Conclusions The SDQ seems to be a reliable and valid instrument given its high internal consistency, clear factor structure and high correlation with other instruments capturing the intended constructs. Findings in the present study support its use for online data collection, as well as using norms obtained through paper-and-pencil-administration even when SDQ has been administrated online. [ABSTRACT FROM AUTHOR]

Background: The analysis of large-scale gene expression data is a fundamental approach to functional genomics and the identification of potential drug targets. Results derived from such studies cannot be trusted unless they are adequately designed and reported. The purpose of this study is to assess current practices on the reporting of experimental design and statistical analyses in gene expression-based studies. Methods: We reviewed hundreds of MEDLINE-indexed papers involving gene expression data analysis, which were published between 2003 and 2005. These papers were examined on the basis of their reporting of several factors, such as sample size, statistical power and software availability. Results: Among the examined papers, we concentrated on 293 papers consisting of applications and new methodologies. These papers did not report approaches to sample size and statistical power estimation. Explicit statements on data transformation and descriptions of the normalisation techniques applied prior to data analyses (e.g. classification) were not reported in 57 (37.5%) and 104 (68.4%) of the methodology papers respectively. With regard to papers presenting biomedical-relevant applications, 41(29.1 %) of these papers did not report on data normalisation and 83 (58.9%) did not describe the normalisation technique applied. Clustering-based analysis, the t-test and ANOVA represent the most widely applied techniques in microarray data analysis. But remarkably, only 5 (3.5%) of the application papers included statements or references to assumption about variance homogeneity for the application of the t-test and ANOVA. There is still a need to promote the reporting of software packages applied or their availability. Conclusion: Recently-published gene expression data analysis studies may lack key information required for properly assessing their design quality and potential impact. There is a need for more rigorous reporting of important experimental factors such as statistical power and sample size, as well as the correct description and justification of statistical methods applied. This paper highlights the importance of defining a minimum set of information required for reporting on statistical design and analysis of expression data. By improving practices of statistical analysis reporting, the scientific community can facilitate quality assurance and peer-review processes, as well as the reproducibility of results. [ABSTRACT FROM AUTHOR]

Background: Sustaining health promotion programs (HPP) is critical to maintain their intended health benefits, community capacity, and to optimize resources and investment. However, not all programs are sustained beyond their initial implementation period. This is partly due to uncertainty regarding sustainability: lack of a clear definition; infrequent use of a sustainability framework; and lack of understanding of the factors that influence sustainability. The aim of this systematic review is to identify barriers and facilitators that promote or inhibit the sustainability of HPP, particularly those that can be considered in program planning.Methods: Two search strategies were used: 1) electronic database searching; and 2) grey literature searching. Inclusion criteria included papers published since 1998, in English, focusing on the sustainability of HPP that explicitly used a sustainability framework and specifically reported on facilitators and barriers to sustainability. Exclusion criteria included papers that addressed environmental, system or sector sustainability. Quality assessment was conducted on all included papers and a quality assessment tool was developed for grey literature. Data analysis included a thematic analysis, using an a priori framework to initially code barriers and facilitators, which were then grouped into factors for HPP sustainability. Factors were then analyzed for frequency, importance, and relevance, and categorized into one of three tiers.Results: Sixteen papers were included in this review. Eleven definitions of sustainability and 13 sustainability frameworks were used. A total of 83 barriers and 191 facilitators were identified and categorized into 14 factors: nine from the a priori framework, and five additional ones based on the results of our analysis. Tier 1 factors were the most important for sustainability with organizational capacity scoring the highest; tier 3, the least important.Conclusion: This review provides clarity regarding existing definitions of sustainability and sustainability frameworks. It identifies fourteen factors that influence program sustainability, which practitioners can consider when planning, developing and implementing HPP. In addition, it is important for practitioners to clearly articulate program elements that should be sustained, define sustainability as it relates to the context of their program, select a sustainability framework to guide their work, and consider these factors for sustainability. [ABSTRACT FROM AUTHOR]

Deprivation of oxygen in an infant during and after birth leads to birth asphyxia, which is considered one of the leading causes of death in the neonatal period. Adequate resuscitation activities are performed immediately after birth to save the majority of newborns. The primary resuscitation activities include ventilation, stimulation, drying, suction, and chest compression. While resuscitation guidelines exist, little research has been conducted on measured resuscitation episodes. Objective data collected for measuring and registration of the executed resuscitation activities can be used to generate temporal timelines. This paper is primarily aimed to introduce methods for analyzing newborn resuscitation activity timelines, through visualization, aggregation, redundancy and dimensionality reduction. We are using two datasets: 1) from Stavanger University Hospital with 108 resuscitation episodes, and 2) from Haydom Lutheran Hospital with 76 episodes. The resuscitation activity timelines were manually annotated, but in future work we will use the proposed method on automatically generated timelines from video and sensor data. We propose an encoding generator with unique codes for combination of activities. A visualization of aggregated episodes is proposed using sparse nearest neighbor graph, shown to be useful to compare datasets and give insights. Finally, we propose a method consisting of an autoencoder trained for reducing redundancy in encoded resuscitation timeline descriptions, followed by a neighborhood component analysis for dimensionality reduction. Visualization of the resulting features shows very good class separability and potential for clustering the resuscitation files according to the outcome of the newborns as dead, admitted to NICU or normal. This shows great potential for extracting important resuscitation patterns when tested on larger datasets., (© 2024. The Author(s).)

Background: Clinical reasoning is at the core of health professionals' practice. A mapping of what constitutes clinical reasoning could support the teaching, development, and assessment of clinical reasoning across the health professions. Methods: We conducted a scoping study to map the literature on clinical reasoning across health professions literature in the context of a larger Best Evidence Medical Education (BEME) review on clinical reasoning assessment. Seven databases were searched using subheadings and terms relating to clinical reasoning, assessment, and Health Professions. Data analysis focused on a comprehensive analysis of bibliometric characteristics and the use of varied terminology to refer to clinical reasoning. Results: Literature identified: 625 papers spanning 47 years (1968–2014), in 155 journals, from 544 first authors, across eighteen Health Professions. Thirty-seven percent of papers used the term clinical reasoning; and 110 other terms referring to the concept of clinical reasoning were identified. Consensus on the categorization of terms was reached for 65 terms across six different categories: reasoning skills, reasoning performance, reasoning process, outcome of reasoning, context of reasoning, and purpose/goal of reasoning. Categories of terminology used differed across Health Professions and publication types. Discussion: Many diverse terms were present and were used differently across literature contexts. These terms likely reflect different operationalisations, or conceptualizations, of clinical reasoning as well as the complex, multi-dimensional nature of this concept. We advise authors to make the intended meaning of 'clinical reasoning' and associated terms in their work explicit in order to facilitate teaching, assessment, and research communication. [ABSTRACT FROM AUTHOR]

Background: In the data pipeline from the data collection process to the planned statistical analyses, initial data analysis (IDA) typically takes place between the end of the data collection and do not touch the research questions. A systematic process for IDA and clear reporting of the findings would help to understand the potential shortcomings of a dataset, such as missing values, or subgroups with small sample sizes, or shortcomings in the collection process, and to evaluate the impact of these shortcomings on the research results. A clear reporting of findings is also relevant when making datasets available to other researchers. Initial data analyses can provide valuable insights into the suitability of a data set for a future research study. Our aim was to describe the practice of reporting of initial data analyses in observational studies in five highly ranked medical journals with focus on data cleaning, screening, and reporting of findings which led to a potential change in the analysis plan.Methods: This review was carried out using systematic search strategies with eligibility criteria for articles to be reviewed. A total of 25 papers about observational studies were selected from five medical journals published in 2018. Each paper was reviewed by two reviewers and IDA statements were further discussed by all authors. The consensus was reported.Results: IDA statements were reported in the methods, results, discussion, and supplement of papers. Ten out of 25 papers (40%) included a statement about data cleaning. Data screening statements were included in all articles, and 18 (72%) indicated the methods used to describe them. Item missingness was reported in 11 papers (44%), unit missingness in 15 papers (60%). Eleven papers (44%) mentioned some changes in the analysis plan. Reported changes referred to missing data treatment, unexpected values, population heterogeneity and aspects related to variable distributions or data properties.Conclusion: Reporting of initial data analyses were sparse, and statements on IDA were located throughout the research articles. There is a lack of systematic reporting of IDA. We conclude the article with recommendations on how to overcome shortcomings in the practice of IDA reporting in observational studies. [ABSTRACT FROM AUTHOR]

Background: A proposal to encourage the preregistration of research on research integrity was developed and adopted as the Amsterdam Agenda at the 5th World Conference on Research Integrity (Amsterdam, 2017). This paper reports on the degree to which abstracts of the 6th World Conference in Research Integrity (Hong Kong, 2019) reported on preregistered research. Methods: Conference registration data on participants presenting a paper or a poster at 6th WCRI were made available to the research team. Because the data set was too small for inferential statistics this report is limited to a basic description of results and some recommendations that should be considered when taking further steps to improve preregistration. Results: 19% of the 308 presenters preregistered their research. Of the 56 usable cases, less than half provided information on the six key elements of the Amsterdam Agenda. Others provided information that invalidated their data, such as an uninformative URL. There was no discernable difference between qualitative and quantitative research. Conclusions: Some presenters at the WCRI have preregistered their research on research integrity, but further steps are needed to increase frequency and completeness of preregistration. One approach to increase preregistration would be to make it a requirement for research presented at the World Conferences on Research Integrity. [ABSTRACT FROM AUTHOR]

Background: The proliferation of instruments that define instrument-specific metrics impedes progress in comparative assessment across populations. This paper explores a method to extract a common metric from related but different instruments and transform the original measurements into scores with a standard unit of measurement. Methods: Existing data from four assessment instruments of child development, collected from three different samples of children, were used to create "equate clusters" of items that measure the same behaviour in (slightly) different ways. A probability model was formulated to identify best items and groups to serve as anchors linking the instruments, assuming that items in an anchoring or "active" equate cluster are psychometrically equivalent. Quantification and inspection of item characteristic curves were used to resolve which equate clusters should be active. We simulated the impact of various analytic choices. Results: Simulation confirmed the feasibility of creating a common metric from data collected with different instruments from respondent samples with different abilities. The method performed as expected in an application in early childhood development. Conclusions: The use of equate clusters is an intuitive and flexible way to establish a common metric across instruments and facilitates the transformation of measurements obtained to a standardized scale. Standardizing instrument scores to a common metric allows for population-level comparisons on a global scale. [ABSTRACT FROM AUTHOR]

Purpose: On average, about 50% of cancer patients use complementary and alternative medicine (CAM) in addition to conventional cancer treatment. Since there is a high need for information, patients often search for information about CAM and share experiences with peers, especially in self-help groups. In this study, we tested and evaluated an educational concept developed for group leaders of cancer self-help groups on how to approach the topic of CAM in their peer groups. Methods: The educational concept has been developed and piloted with health care professionals and representatives from different self-help organizations in Germany. It aims to inform and discuss the possibilities and limitations of CAM in terms of scientific evidence, to reflect user behavior, and to provide a guide on how to find and evaluate reliable and evidence-based information sources. First, self-help group leaders took part in an on-site training where they were educated on various CAM topics with the goal of being able to conduct the educational concept in their respective self-help groups. Then, the educated group leaders performed this concept in their groups. The educational concept was evaluated by both the group leaders and participants with respect to acceptance, usefulness, and satisfaction using paper-pencil questionnaires. The study was conducted in Germany based on an observational study design with a six-month follow-up. For the analyses, descriptive and univariate statistics for dependent samples were used. Results: A total of n = 50 interested group leaders conducted the educational program in their groups. The most common implementation barriers were organizational or structural problems, as well as the feeling of being overwhelmed with managing the program in their groups. A total of n = 423 participants were educated with this program by their respective group leaders. The majority felt satisfied with the educational program and improved their knowledge about CAM. At the six months follow-up (T2), significantly more participants had consulted their physicians to inform themselves about CAM and felt more confident in finding reliable information about CAM. Conclusions: In this observational study, we have managed to successfully implement an educational concept with respect to the topic of CAM in cancer self-help groups. Based on the results, the concept approach will be modified to include both a CAM- professional and group leader to train the self-help groups. In the future, the effects of the program should be tested by a randomized trial. [ABSTRACT FROM AUTHOR]

Background: New graduate nurses often have certain potential safety hazards for patients due to insufficient knowledge and lack of clinical practice ability. To address these challenges, China has implemented a standardized training strategy. The improvements in the quality of this training involve not only the intervention of teaching methods but also the consideration of personality traits. Methods: The application software based on the BFI-2 Chinese scale was utilized to administer personality tests to nursing students; nursing students were invited to scan the QR code and voluntarily fill in a questionnaire, including basic information, personality test results, and a professional self-efficacy test scale; offline paper-based theoretical examination results of nursing students were collected before and after training. The data was then analyzed using SPSS software version 26.0, which involved descriptive analysis, one-way between-groups analysis of variance (ANOVA) and Spearman correlation analysis. Results: Based on the data, there were no observable differences in the theoretical results before and after training across different personality traits. In terms of skill assessment, conscientiousness exhibited the highest score at 78.91 ± 2.98 points, while negative emotionality showed the lowest score at 74.59 ± 2.12 points. These differences between different personality traits are statistically significant (P < 0.001). In terms of professional self-efficacy, conscientiousness scored the highest at 98.48 ± 12.69, while negative emotionality scored the lowest at 85.89 ± 11.71, with significant differences between different personality traits (P < 0.001). Professional self-efficacy was negatively correlated with agreeableness (r = -0.150, P = 0.044) and positively correlated with conscientiousness (r = -0.310, P < 0.001). Skill scores were negatively correlated with negative emotionality (r = -0.257, P < 0.001) and positively correlated with conscientiousness (r = 0.182, P = 0.014). Conclusions: This study shows that personality traits affect the skills test results and professional self-efficacy of nursing students. Conscientiousness scored the highest in this study, while negative emotionality scored the lowest. Therefore, personalized training plans are recommended to improve the quality of care for such nursing students and to further enhance patient safety. [ABSTRACT FROM AUTHOR]

Addressing health inequity is a central component of the Sustainable Development Goals and a priority of the World Health Organization (WHO). WHO supports countries in strengthening their health information systems in order to better collect, analyze and report health inequality data. Improving information and research about health inequality is crucial to identify and address the inequalities that lead to poorer health outcomes. Building analytical capacities of individuals, particularly in low-resource areas, empowers them to build a stronger evidence-base, leading to more informed policy and programme decision-making. However, health inequality analysis requires a unique set of skills and knowledge. This paper describes three resources developed by WHO to support the analysis of inequality data by non-statistical users using Microsoft Excel, a widely used and accessible software programme. The resources include a practical eLearning course, which trains learners in the preparation and reporting of disaggregated data using Excel, an Excel workbook that takes users step-by-step through the calculation of 21 summary measures of health inequality, and a workbook that automatically calculates these measures with the user's disaggregated dataset. The utility of the resources is demonstrated through an empirical example. [ABSTRACT FROM AUTHOR]

Background: Osteonecrosis of the femoral head (ONFH) is a serious condition that causes bone tissue death, femoral head collapse, and hip joint destruction. Early intervention through hip-preserving treatment is crucial to slow down disease progression, preserve hip joint function, and improve the quality of life of patients. We analyzed the knowledge map, research gaps, and future research directions in the field of hip-preserving treatment for early ONFH. Methods: All publications related to hip-preserving treatment for early ONFH published between 2010 and 2023 were identified from the Web of Science Core Collection and analyzed using VOSviewer 1.6.19, CiteSpace 6.2.R2, and Scimago Graphica 1.0.35. Results: In total, 234 articles were analyzed. The results showed an exponential growth trend in the number of publications related to hip-preserving treatment for early ONFH in the past decade. China and the USA were the main contributors. International Orthopaedics published the most papers in this field, whereas Bone and Joint Surgery-American Volume had the highest average citation count per article. Several stable research topics were noted in this field, including core decompression (CD), osteotomy, bone transplantation in hip-preserving surgery, and cell therapy, which have become research hotspots in hip-preserving treatment. Conclusions: Hip-preserving treatment for early ONFH has received increasing attention, and research in this field is expected to grow. Stable research topics include core decompression (CD), osteotomy, bone transplantation, and cell therapy. Future research is predicted to focus on cell therapy and combination therapy, resulting in an increasing number of publications on hip-preserving treatment for early ONFH. [ABSTRACT FROM AUTHOR]

Background: This study aims to investigate the influence of different dentin pretreatment procedures on the resulting abrasive dentin wear. Methods: Two groups (A, B) of 60 dentin samples each were prepared. Group A was brushed with an abrasive slurry (RDA = 85) and group B with a different abrasive slurry (RDA = 174). Four subgroups in each group (n = 15) were created (A1–A4) and (B1–B4). The subgroups were pretreated as follows: A1 + B1 with 1200-grit grinding paper, A2 + B2 with 1200- and 2000-grit papers, A3 + B3 with 1200-, 2000-, and 4000-grit papers, A4 + B4 with 1200-, 2000-, 4000-grit papers and with 1000 brushing strokes with a slurry of Elmex toothpaste. All samples were brushed for 25 min at 120 strokes/min. Abrasive dentin wear was measured for each sample profilometrically and the subgroups were compared with each other within the same group. Repeated measures one-way ANOVA was conducted to compare the subgroups and pairwise contrasts were estimated for multiple testing according to Tukey (α = 0.05). Results: The resulting abrasive dentin wear in group A ranged between 15.3 ± 3.4 µm and 17.3 ± 5.5 µm and between 20.3 ± 6.8 µm and 22.5 ± 2.6 µm in group B. No statistically significant difference was noticed between any subgroups within the same group (p ˃ 0.05). Conclusions: Different dentin pretreatment procedures do not affect the resulting abrasive dentin wear independent of the RDA value of the employed abrasive slurry. [ABSTRACT FROM AUTHOR]

Background: As medical education develops into a varied and well-developed field of research, the issue of quality research anchored in or generating theory has gained increasing importance. Medical education researchers have been criticized of not connecting their work to relevant theory. This paper set out to analyse how researchers can connect to theory in medical education. The goal of this paper is to provide an accessible framework for those entering medical education research, regarding how theory may become an integral part of one's work. Methods: Fifteen purposefully selected researchers in medical education were asked to nominate papers they considered influential in medical education. Through this process 41 papers were identified and included in the study. Results: The papers were analysed with thematic content analysis, which resulted in three approaches to the use of theory: as close-up exploration; as a specific perspective; and as an overview. The approaches are exemplified by quotes from the papers included in our dataset and further illuminated by a metaphoric story. Conclusions: We conclude by pointing at the importance of making explicit how theory is used in medical education as a way to collaboratively take responsibility for the quality of medical education research. [ABSTRACT FROM AUTHOR]

Background: Co-occurring physical and mental health conditions are common, but effective and sustainable interventions are needed for primary care settings. Purpose: Our paper analyzes the effectiveness of a Solution-Focused Brief Therapy (SFBT) intervention for treating depression and co-occurring health conditions in primary care. We hypothesized that individuals receiving the SFBT intervention would have statistically significant reductions in depressive and anxiety symptoms, systolic blood pressure (SBP), hemoglobin A1C (HbA1c), and body mass index (BMI) when compared to those in the control group. Additionally, we hypothesized that the SFBT group would have increased well-being scores compared to the control group. Methods: A randomized clinical trial was conducted at a rural federally qualified health center. Eligible participants scored ≥ 10 on the Patient Health Questionnaire (PHQ-9) and met criteria for co-occurring health conditions (hypertension, obesity, diabetes) evidenced by chart review. SFBT participants (n = 40) received three SFBT interventions over three weeks in addition to treatment as usual (TAU). The control group (n = 40) received TAU over three weeks. Measures included depression (PHQ-9) and anxiety (GAD-7), well-being (Human Flourishing Index), and SFBT scores, along with physical health outcomes (blood pressure, body mass index, and hemoglobin A1c). Results: Of 80 consented participants, 69 completed all measures and were included in the final analysis. 80% identified as female and the mean age was 38.1 years (SD = 14.5). Most participants were white (72%) followed by Hispanic (15%) and Black (13%). When compared to TAU, SFBT intervention participants had significantly greater reductions in depression (baseline: M = 18.17, SD = 3.97, outcome: M = 9.71, SD = 3.71) and anxiety (baseline: M = 14.69, SD = 4.9, outcome: M = 8.43, SD = 3.79). SFBT intervention participants also had significantly increased well-being scores (baseline: M = 58.37, SD = 16.36, outcome: M = 73.43, SD = 14.70) when compared to TAU. Changes in BMI and blood pressure were not statistically significant. Conclusion: The SFBT intervention demonstrated efficacy in reducing depressive and anxiety symptoms and increasing well-being but did not affect cardio-metabolic parameters over a short period of intervention. Trial Registration: The study was pre-registered at ClinicalTrials.gov Identifier: NCT05838222 on 4/20/2023. *M = Mean, SD = Standard deviation. [ABSTRACT FROM AUTHOR]

Background: With the emergence of Oxford Nanopore technology, now the on-site sequencing of 16S rRNA from environments is available. Due to the error level and structure, the analysis of such data demands some database of reference sequences. However, many taxa from complex and diverse environments, have poor representation in publicly available databases. In this paper, we propose the METASEED pipeline for the reconstruction of full-length 16S sequences from such environments, in order to improve the reference for the subsequent use of on-site sequencing. Results: We show that combining high-precision short-read sequencing of both 16S and full metagenome from the same samples allow us to reconstruct high-quality 16S sequences from the more abundant taxa. A significant novelty is the carefully designed collection of metagenome reads that matches the 16S amplicons, based on a combination of uniqueness and abundance. Compared to alternative approaches this produces superior results. Conclusion: Our pipeline will facilitate numerous studies associated with various unknown microorganisms, thus allowing the comprehension of the diverse environments. The pipeline is a potential tool in generating a full length 16S rRNA gene database for any environment. [ABSTRACT FROM AUTHOR]

Background: When potentially associated with the likelihood of outcome, missing participant data represents a serious potential source of bias in randomized trials. Authors of systematic reviews frequently face this problem when conducting meta-analyses. The objective of this study is to conduct a systematic survey of the relevant literature to identify proposed approaches for how systematic review authors should handle missing participant data when conducting a meta-analysis. Methods: We searched MEDLINE and the Cochrane Methodology register from inception to August 2014. We included papers that devoted at least two paragraphs to discuss a relevant approach for missing data. Five pairs of reviewers, working independently and in duplicate, selected relevant papers. One reviewer abstracted data from included papers and a second reviewer verified them. We summarized the results narratively. Results: Of 9,138 identified citations, we included 11 eligible papers. Four proposed general approaches for handling dichotomous outcomes, and all recommended a complete case analysis as the primary analysis and additional sensitivity analyses using the following imputation methods: based on reasons for missingness (n = 3), relative to risk among followed up (n = 3), best-case scenario (n = 2), and worst-case scenario (n = 3). Three of these approaches suggested taking uncertainty into account. Two papers proposed general approaches for handling continuous outcomes, and both proposed a complete case analysis as the reference analysis and the following imputation methods as sensitivity analyses: based on reasons for missingness (n = 2), based on the mean observed in the same trial or other trials (n = 1), and based on informative missingness differences in means (n = 1). The remaining eligible papers did not propose general approaches but addressed specific statistical issues. Conclusions: All proposed approaches for handling missing participant data recommend conducting a complete case analysis for the primary analysis and some form of sensitivity analysis to evaluate robustness of results. Although these approaches require further testing, they may guide review authors in addressing missing participant data. [ABSTRACT FROM AUTHOR]

Background: To assess the ability of fluorescence imaging to detect a dose response relationship between fluorosis severity and different levels of fluoride in water supplies compared to remote photographic scoring in selected populations participating in an observational, epidemiological survey in Chiang Mai, Thailand. Methods: Subjects were male and female lifetime residents aged 8-13 years. For each child the fluoride content of cooking water samples (CWS) was assessed to create categorical intervals of water fluoride concentration. Fluorescence images were taken of the maxillary central incisors and analyzed for dental fluorosis using two different software techniques. Output metrics for the fluorescence imaging techniques were compared to TF scores from blinded photographic scores obtained from the survey. Results: Data from 553 subjects were available. Both software analysis techniques demonstrated significant correlations with the photographic scores. The metrics for area effected by fluorosis and the overall fluorescence loss had the strongest association with the photographic TF score (Spearman's rho 0.664 and 0.652 respectively). Both software techniques performed well for comparison of repeat fluorescence images with ICC values of 0.95 and 0.85 respectively. Conclusions: This study supports the potential use of fluorescence imaging for the objective quantification of dental fluorosis. Fluorescence imaging was able to discriminate between populations with different fluoride exposures on a comparable level to remote photographic scoring with acceptable levels of repeatability. [ABSTRACT FROM AUTHOR]

Background: To determine the severity of dental fluorosis in selected populations in Chiang Mai, Thailand with different exposures to fluoride and to explore possible risk indicators for dental fluorosis. Methods: Subjects were male and female lifetime residents aged 8.13 years. For each child the fluoride content of drinking and cooking water samples were assessed. Digital images were taken of the maxillary central incisors for later blind scoring for TF index (10% repeat scores). Interview data explored previous cooking and drinking water use, exposure to fluoride, infant feeding patterns and oral hygiene practices. Results: Data from 560 subjects were available for analysis (298 M, 262 F). A weighted kappa of 0.80 was obtained for repeat photographic scores. The prevalence of fluorosis (TF 3+) for subjects consuming drinking and cooking water with a fluoride concentration of <0.9 ppm was 10.2%. For subjects consuming drinking and cooking water >0.9 ppm F the prevalence of fluorosis (TF 3+) rose to 37.3%. Drinking and cooking water at age 3, water used for infant formula and water used for preparing infant food all demonstrated an increase in fluorosis severity with increase in water fluoride level (p<0.001). The probability estimate for the presentation of aesthetically significant fluorosis was 0.53 for exposure to high fluoride drinking (.0.9 ppm) and cooking water (.1.6 ppm). Conclusions: The consumption of drinking water with fluoride content >0.9 ppm and use of cooking water with fluoride content >1.6 ppm were associated with an increased risk of aesthetically significant dental fluorosis. Fluoride levels in the current drinking and cooking water sources were strongly correlated with fluorosis severity. Further work is needed to explore fluorosis risk in relation to total fluoride intake from all sources including food preparation. [ABSTRACT FROM AUTHOR]

Background: The initial version of SEDA assists life science researchers without programming skills with the preparation of DNA and protein sequence FASTA files for multiple bioinformatics applications. However, the initial version of SEDA lacks a command-line interface for more advanced users and does not allow the creation of automated analysis pipelines. Results: The present paper discusses the updates of the new SEDA release, including the addition of a complete command-line interface, new functionalities like gene annotation, a framework for automated pipelines, and improved integration in Linux environments. Conclusion: SEDA is an open-source Java application and can be installed using the different distributions available (https://www.sing-group.org/seda/download.html) as well as through a Docker image (https://hub.docker.com/r/pegi3s/seda). It is released under a GPL-3.0 license, and its source code is publicly accessible on GitHub (https://github.com/sing-group/seda). The software version at the time of submission is archived at Zenodo (version v1.6.0, http://doi.org/10.5281/zenodo.10201605). [ABSTRACT FROM AUTHOR]

Background: Cough is one of the most common presenting problems for patients in primary care and is largely managed in primary care clinical settings. Family physicians' familiarity with chronic cough guidelines and the extent to which these guidelines translate into everyday practice have not been well described. The objective of this study was to characterize current diagnosis, treatment, and referral practices among family physicians and to identify potentially impactful strategies to optimize chronic cough management in primary care. Methods: We conducted a cross-sectional survey of 5,000 family physicians to explore diagnosis, treatment, and referral practices related to chronic cough management in adults in primary care. Respondents completed the survey via paper or online. The outcome measures were self-reported numeric ratings and responses related to the survey elements. Results: 588 surveys were completed (11.8% response rate). About half (49.6%) of respondents defined chronic cough in a manner consistent with the American College of Chest Physicians (ACCP) chronic cough guidelines, with the rest differing in opinion primarily regarding duration of symptom presentation. Respondents reported trying to rule out most common causes of chronic cough themselves before referring (mean 3.41 on a 4-point scale where 4 is "describes me completely") and indicated a desire for more resources to help them manage and treat chronic cough. Years in practice and rural/urban setting influenced diagnosis and referral practices. Conclusions: Family physicians see chronic cough as a complicated condition that can be and is often diagnosed and treated entirely in a primary care setting. They also value the ability to refer in complex cases. Our results support that family physicians provide evidence-based management of chronic cough. [ABSTRACT FROM AUTHOR]

Multimodal integration combines information from different sources or modalities to gain a more comprehensive understanding of a phenomenon. The challenges in multi-omics data analysis lie in the complexity, high dimensionality, and heterogeneity of the data, which demands sophisticated computational tools and visualization methods for proper interpretation and visualization of multi-omics data. In this paper, we propose a novel method, termed Orthogonal Multimodality Integration and Clustering (OMIC), for analyzing CITE-seq. Our approach enables researchers to integrate multiple sources of information while accounting for the dependence among them. We demonstrate the effectiveness of our approach using CITE-seq data sets for cell clustering. Our results show that our approach outperforms existing methods in terms of accuracy, computational efficiency, and interpretability. We conclude that our proposed OMIC method provides a powerful tool for multimodal data analysis that greatly improves the feasibility and reliability of integrated data. [ABSTRACT FROM AUTHOR]

Background: Gender dysphoria among transgender adolescents has predominantly been examined in relation to body dissatisfaction. While in adult transgender samples, body dissatisfaction is higher than in cisgender controls, this has so far rarely been investigated for adolescents. In the context of a cisnormative society, the impact of influences from the social environment on body dissatisfaction and gender dysphoria has been neglected in research. Therefore, this study aimed to (1) provide a detailed analysis of body dissatisfaction among young transgender people and (2) investigate whether body dissatisfaction and gender dysphoria are associated with experiences of minority stress such as trans hostility and poor peer relations (PPR). Methods: The paper presents a cross-sectional study among a sample of transgender adolescents, presenting at a specialized outpatient counseling clinic (N = 99; age M = 15.36, SD = 1.85). First, body dissatisfaction (assessed by the Body-Image-Scale; BIS), was explored and compared to data from a population-based control group of cisgender peers (N = 527; age M = 14.43, SD = 0.97). Second, within a clinic-referred transgender subsample (n = 74), associations between body dissatisfaction and gender dysphoria (measured by Utrecht Gender Dysphoria Scale; UGDS), PPR (measured by the Youth-Self-Report; YSR-R), and trans hostile experiences (assessed in clinical interview) were examined by correlations, t-tests and multivariate regression. Results: Transgender adolescents reported more body dissatisfaction than cisgender peers. The dissatisfaction with sex characteristics, non-hormonal reactive body regions and the total score for body dissatisfaction were positively related with gender dysphoria. The majority had experienced trans hostility in the present and/or past (54.1%) and PPR (63.5%). More body dissatisfaction was correlated with more PPR regarding visible body parts i.e., hair, overall appearance and muscles, whilst PPR and gender dysphoria were not associated. Transgender adolescents who experienced trans hostility showed higher gender dysphoria and PPR, but not more body dissatisfaction. In multiple regression, trans hostility predicted gender dysphoria, whilst age and PPR predicted body dissatisfaction. Discussion: Experiences of minority-stress differentially interact with body dissatisfaction and gender dysphoria among transgender adolescents. Social correlates of body dissatisfaction and gender dysphoria must be considered when working with young transgender people. [ABSTRACT FROM AUTHOR]

An organism's observable traits, or phenotype, result from intricate interactions among genes, proteins, metabolites and the environment. External factors, such as associated microorganisms, along with biotic and abiotic stressors, can significantly impact this complex biological system, influencing processes like growth, development and productivity. A comprehensive analysis of the entire biological system and its interactions is thus crucial to identify key components that support adaptation to stressors and to discover biomarkers applicable in breeding programs or disease diagnostics. Since the genomics era, several other 'omics' disciplines have emerged, and recent advances in high-throughput technologies have facilitated the generation of additional omics datasets. While traditionally analyzed individually, the last decade has seen an increase in multi-omics data integration and analysis strategies aimed at achieving a holistic understanding of interactions across different biological layers. Despite these advances, the analysis of multi-omics data is still challenging due to their scale, complexity, high dimensionality and multimodality. To address these challenges, a number of analytical tools and strategies have been developed, including clustering and differential equations, which require advanced knowledge in bioinformatics and statistics. Therefore, this study recognizes the need for user-friendly tools by introducing Holomics, an accessible and easy-to-use R shiny application with multi-omics functions tailored for scientists with limited bioinformatics knowledge. Holomics provides a well-defined workflow, starting with the upload and pre-filtering of single-omics data, which are then further refined by single-omics analysis focusing on key features. Subsequently, these reduced datasets are subjected to multi-omics analyses to unveil correlations between 2-n datasets. This paper concludes with a real-world case study where microbiomics, transcriptomics and metabolomics data from previous studies that elucidate factors associated with improved sugar beet storability are integrated using Holomics. The results are discussed in the context of the biological background, underscoring the importance of multi-omics insights. This example not only highlights the versatility of Holomics in handling different types of omics data, but also validates its consistency by reproducing findings from preceding single-omics studies. [ABSTRACT FROM AUTHOR]

Background: Scoping reviews and evidence maps are forms of evidence synthesis that aim to map the available literature on a topic and are well-suited to visual presentation of results. A range of data visualisation methods and interactive data visualisation tools exist that may make scoping reviews more useful to knowledge users. The aim of this study was to explore the use of data visualisation in a sample of recent scoping reviews and evidence maps on health topics, with a particular focus on interactive data visualisation. Methods: Ovid MEDLINE ALL was searched for recent scoping reviews and evidence maps (June 2020-May 2021), and a sample of 300 papers that met basic selection criteria was taken. Data were extracted on the aim of each review and the use of data visualisation, including types of data visualisation used, variables presented and the use of interactivity. Descriptive data analysis was undertaken of the 238 reviews that aimed to map evidence. Results: Of the 238 scoping reviews or evidence maps in our analysis, around one-third (37.8%) included some form of data visualisation. Thirty-five different types of data visualisation were used across this sample, although most data visualisations identified were simple bar charts (standard, stacked or multi-set), pie charts or cross-tabulations (60.8%). Most data visualisations presented a single variable (64.4%) or two variables (26.1%). Almost a third of the reviews that used data visualisation did not use any colour (28.9%). Only two reviews presented interactive data visualisation, and few reported the software used to create visualisations. Conclusions: Data visualisation is currently underused by scoping review authors. In particular, there is potential for much greater use of more innovative forms of data visualisation and interactive data visualisation. Where more innovative data visualisation is used, scoping reviews have made use of a wide range of different methods. Increased use of these more engaging visualisations may make scoping reviews more useful for a range of stakeholders. [ABSTRACT FROM AUTHOR]

Background: Given the developmental vulnerability of justice-involved youth, providing a safe environment in secure facilities is a paramount, yet challenging task. Within this complexity, a sound security framework is key. The security framework exists on three dimensions: physical, procedural and relational security. Existing knowledge points at the importance of a shift in focus on physical and procedural security towards relational security as the core of the security framework. At the same time there is a dearth of knowledge on relational security, particularly in the context of youth justice. This paper explores relational security and its working mechanisms in practice. Methods: This paper draws on findings of a comprehensive three-year evaluation of three small-scale, community-embedded facilities that are grounded in relational security. The approach of the evaluation was derived from action research, involving a cyclic process alternating between action, research and critical reflection, while engaging all stakeholders in the research process. The action research cycle involved qualitative research (a total of 63 semi-structured interviews) incorporating the perspective of staff, youth and parents. Results: Relational security is grounded in three distinct, but interrelated, elements – staff's basic attitude, a constructive alliance between staff and youth, staff presence – and promotes a safe and therapeutic environment through several mechanisms. Conclusions: Relational security can be defined in a practical conceptualization; outlining a way of working that guides staff in how to establish a safe and therapeutic environment in secure facilities. This conceptualization finds support in the well-established literature covering the therapeutic alliance and can be substantiated by two aligning theories concerning youth justice strategies: social-ecological theory and self-determination theory. Relational security is not only a way of working, but also a way of being. It encompasses a vision about security and mentality towards justice-involved youth that sees them not merely as 'risks to be managed', but primarly as 'resources to be developed'. [ABSTRACT FROM AUTHOR]

Background: The literature on qualitative data analysis mostly concerns analyses pertaining to an individual research question and the organization of data within that research question. Few authors have written about the entire qualitative dataset from which multiple and separate analyses could be conducted and reported. The concept of analytic direction is a strategy that can assist qualitative researchers in deciding which findings to highlight within a dataset. The objectives of this paper were to: 1) describe the importance of analytic direction in qualitative research, and 2) provide a working example of the concept of analytic direction.Methods: A qualitative dataset from one of the author's research programs was selected for review. Ten potential analytic directions were identified after the initial phenomenological analysis was conducted. Three analytic directions based on the same coding template but different content areas of the data were further developed using phenomenological analysis (n = 2) and qualitative description (n = 1) and are the focus of this paper. Development and selection of these three analytic directions was determined partially relying on methodological criteria to promote rigour including a comprehensive examination of the data, the use of multiple analysts, direct quotations to support claims, negative case analysis, and reflexivity.Results: The three analytic directions addressed topics within the scope of the overall research question. Each analytic direction had its own central point or story line and each highlighted a different perspective or voice. The use of an inductive and deductive approach to analysis and how the role of theory was integrated varied in each analytic direction.Conclusions: The concept of analytic direction enables researchers to organize their qualitative datasets in order to tell different and unique "stories". The concept relies upon, and promotes, the conduct of rigourous qualitative research. [ABSTRACT FROM AUTHOR]

Background: Treatment burden can be defined as the self-care practices that patients with chronic illness must perform to respond to the requirements of their healthcare providers, as well as the impact that these practices have on patient functioning and well being. Increasing levels of treatment burden may lead to suboptimal adherence and negative outcomes. Systematic review of the qualitative literature is a useful method for exploring the patient experience of care, in this case the experience of treatment burden. There is no consensus on methods for qualitative systematic review. This paper describes the methodology used for qualitative systematic reviews of the treatment burdens identified in three different common chronic conditions, using stroke as our exemplar. Methods: Qualitative studies in peer reviewed journals seeking to understand the patient experience of stroke management were sought. Limitations of English language and year of publication 2000 onwards were set. An exhaustive search strategy was employed, consisting of a scoping search, database searches (Scopus, CINAHL, Embase, Medline & PsycINFO) and reference, footnote and citation searching. Papers were screened, data extracted, quality appraised and analysed by two individuals, with a third party for disagreements. Data analysis was carried out using a coding framework underpinned by Normalization Process Theory (NPT). Results: A total of 4364 papers were identified, 54 were included in the review. Of these, 51 (94%) were retrieved from our database search. Methodological issues included: creating an appropriate search strategy; investigating a topic not previously conceptualised; sorting through irrelevant data within papers; the quality appraisal of qualitative research; and the use of NPT as a novel method of data analysis, shown to be a useful method for the purposes of this review. Conclusion: The creation of our search strategy may be of particular interest to other researchers carrying out synthesis of qualitative studies. Importantly, the successful use of NPT to inform a coding frame for data analysis involving qualitative data that describes processes relating to self management highlights the potential of a new method for analyses of qualitative data within systematic reviews. [ABSTRACT FROM AUTHOR]

Background: Differences in the preparation, staining and scanning of digital pathology slides create significant pre-analytic variability. Algorithm-assisted tools must be able to contend with this variability in order to be applicable in clinical practice. In a previous study, a decision support algorithm was developed to assist in the diagnosis of Hirschsprung's disease. In the current study, we tested the robustness of this algorithm while assessing for pre-analytic factors which may affect its performance. Methods: The decision support algorithm was used on digital pathology slides obtained from four different medical centers (A-D) and scanned by three different scanner models (by Philips, Hamamatsu and 3DHISTECH). A total of 192 cases and 1782 slides were used in this study. RGB histograms were constructed to compare images from the various medical centers and scanner models and highlight the differences in color and contrast. Results: The algorithm was able to correctly identify ganglion cells in 99.2% of cases, from all medical centers (All scanned by the Philips slide scanner) as well as 95.5% and 100% of the slides scanned by the 3DHISTECH and Hamamatsu brand slide scanners, respectively. The total error rate for center D was lower than the other medical centers (3.9% vs 7.1%, 10.8% and 6% for centers A-C, respectively), the vast majority of errors being false positives (3.45% vs 0.45% false negatives). The other medical centers showed a higher rate of false negatives in relation to false positives (6.81% vs 0.29%, 9.8% vs 1.2% and 5.37% vs 0.63% for centers A-C, respectively). The total error rates for the Philips, Hamamatsu and 3DHISTECH brand scanners were 3.9%, 3.2% and 9.8%, respectively. RGB histograms demonstrated significant differences in pixel value distribution between the four medical centers, as well as between the 3DHISTECH brand scanner when compared to the Philips and Hamamatsu brand scanners. Conclusions: The results reported in this paper suggest that the algorithm-based decision support system has sufficient robustness to be applicable for clinical practice. In addition, the novel method used in its development – Hierarchial-Contexual Analysis (HCA) may be applicable to the development of algorithm-assisted tools in other diseases, for which available datasets are limited. Validation of any given algorithm-assisted support system should nonetheless include data from as many medical centers and scanner models as possible. [ABSTRACT FROM AUTHOR]

Background: Bushmeat is a resource exploited by thousands of people around the world, especially in tropical and neotropical regions, constituting an important source of protein and income. But what is known, so far, about the consumption and trade of wild vertebrate meat (hereinafter "bushmeat") in a megadiverse country like Brazil? This question was answered through a systematic survey of publications on the consumption and trade of wild vertebrate meat made in Brazil between 2011 and 2021. Methods: We selected 63 scientific articles available on "Google Scholar," "Science Direct," "Scopus," " Web of Science" and "Portal de Periódico da CAPES." The articles were categorized as: exclusive to (1) consumption or (2) bushmeat trade, totals of 54 and three articles, respectively; both (3) consumption and trade bushmeat, totaling six articles. We applied a nonparametric Spearman's correlation analysis to verify the association between the number of papers and the species richness of wild vertebrates cited for consumption by Brazilian state. Results: The results revealed that the publications were concentrated in the Northeast (36), North (26) and Southeast (1) regions, distributed across 16 states of the federation. These data reinforce the need for more researches in states and other regions of the country. Our research hypothesis was confirmed, since the richness of species cited for meat consumption was positively associated with the amount of work carried out by the states of the federation. We identified a total of 321 species of wild vertebrates mentioned in the categories involving the consumption of bushmeat. We had a greater bird species richness mentioned for consumption (170) to the detriment of mammals (107), reptiles (40) and amphibians (4). Furthermore, in the articles involving the bushmeat trade categories we had 57 species of vertebrates mentioned, with mammals being the most representative in terms of species richness (29), to the detriment of birds (20) and reptiles (8). These data reinforce that birds and mammals have been the groups most used both for consumption and trade in bushmeat in the country's regions, and it is necessary to mitigate the hunting exploitation of these groups. We recorded that socioeconomic, biological, environmental and sociocultural factors were the most cited predictors of the consumption and trade of bushmeat in the articles. We identified that the bushmeat trade chain is dynamic and ramified, made up of several actors, including specialized and diversified hunters, intermediaries, market sellers, market vendors, restaurant owners and final customers. Public markets and open-air fairs were the most cited places for buying and selling wild meat in commerce. Conclusions: In general, our results indicate that we have made significant advances in publications on the consumption and trade of bushmeat in Brazil over the last few years. However, we highlight the need to better understand the patterns of consumption and trade of bushmeat in different regions of the country, as well as the factors associated with the dynamics of the trade chain and uses of wildlife by local communities. We emphasized that a multidimensional understanding of hunting activities is important to face socio-ecological problems and improve the conservation of target species which have continually been explored for uses by populations in different regions of the world. [ABSTRACT FROM AUTHOR]

This document is a response to concerns raised about a previous article on B chromosomes and their evolutionary dynamics. The authors acknowledge the valid concerns and provide corrections and clarifications. They address issues with the availability of sequenced data and inaccuracies in supplementary figures and tables. The authors also discuss errors and corrections in a study on B chromosomes in different species, including mistakes in referencing, figure citation, and data analysis. They emphasize the need for standardized protocols and bioinformatic tools to improve the study of B chromosomes and acknowledge the challenges and gaps in understanding their genomic content. [Extracted from the article]

Background: Given India's high patient load on the existing healthcare setup, as well as political, social, and organizational challenges, the nursing sector is facing various problems, therefore leading to substandard nursing experiences leading to poor patient care at the parallel healthcare setups, specifically homecare. This paper presents self-managed organizations (SMOs) characterized by a horizontal management structure as an effective alternative to existing hierarchical management structures overladen with bureaucracy. Therefore, we are exploring the strategies at self-managed homecare organizations that can make nursing a better and more productive experience. Method: This study utilized Constructivist Grounded Theory (CGT), employing semi-structured interviews to explore nursing dynamics in horizontal organizational structures. It delved into crucial aspects like finances, organizational structure, value systems, information flow, and conflict resolution within SMOs. The methodology involved theoretical sampling, prioritizing expert self-management knowledge over mere representativeness. Seven nurses, twelve management members, and fifteen patients from self-managed homecare organizations contributed to the examination of nursing experiences. Constant comparative analysis of data led to the identification of the Qualitative Success Enablers (QSEs), revealing three themes: Insightfulness, Enhancing Nursing Experience through Job Enrichment, and Autonomy-Enabled Intrapreneurship. Results: The findings indicate that the horizontal management structure represented by the studied organization in India has shown considerable success in times laden with uncertainties during the COVID-19 pandemic, especially during the delta wave, which revealed the frailty of existing healthcare infrastructure. The organization successfully maintained a better nursing experience and gained patient and employee satisfaction, as revealed by in-depth semi-structured interviews and constant comparative analysis. Conclusion: In a world of unique challenges, we stand on the brink of significant transformations. SMOs are vital in India's homecare sector for enhancing nursing experiences and overall organizational performance. Fostering a trust-based environment within SMOs is integral to delivering effective services. The autonomy to design nursing jobs, insightfulness, and innovativeness in the nursing job through suitable training activities, various job enrichment methods, and finding meaningfulness in a job through softer aspects of caregiving result in an enhanced nursing experience at SMOs. This groundbreaking approach can be extended to other homecare organizations in India, relieving the strain on the existing healthcare system. [ABSTRACT FROM AUTHOR]

Background: Interrupted time series (ITS) analysis is a time series regression model that aims to evaluate the effect of an intervention on an outcome of interest. ITS analysis is a quasi-experimental study design instrumental in situations where natural experiments occur, gaining popularity, particularly due to the Covid-19 pandemic. However, challenges, including the lack of a control group, have impeded the quantification of the effect size in ITS. The current paper proposes a method and develops a user-friendly R package to quantify the effect size of an ITS regression model for continuous and count outcomes, with or without seasonal adjustment. Results: The effect size presented in this work, together with its corresponding 95% confidence interval (CI) and P-value, is based on the ITS model-based fitted values and the predicted counterfactual (the exposed period had the intervention not occurred) values. A user-friendly R package to fit an ITS and estimate the effect size was developed and accompanies this paper. To illustrate, we implemented a nation population-based ITS study from January 2001 to May 2021 covering the all-cause mortality of Israel (n = 9,350 thousand) to quantify the effect size of Covid-19 exposure on mortality rates. In the period unexposed to the Covid-19 pandemic, the mortality rate decreased over time and was expected to continue decreasing had Covid-19 not occurred. In contrast, the period exposed to the Covid-19 pandemic was associated with an increased all-cause mortality rate (relative risk = 1.11, 95% CI = 1.04, 1.18, P < 0.001). Conclusion: For the first time, the effect size in ITS: was quantified, can be estimated by end-users with an R package we developed, and was demonstrated with data showing an increase in mortality following the Covid-19 pandemic. ITS effect size reporting can assist public health policy makers in assessing the magnitude of the entire intervention effect using a single, readily understood measure. [ABSTRACT FROM AUTHOR]

Plant metabolomics is an important research area in plant science. Chemometrics is a useful tool for plant metabolomic data analysis and processing. Among them, high-order chemometrics represented by tensor modeling provides a new and promising technical method for the analysis of complex multi-way plant metabolomics data. This paper systematically reviews different tensor methods widely applied to the analysis of complex plant metabolomic data. The advantages and disadvantages as well as the latest methodological advances of tensor models are reviewed and summarized. At the same time, application of different tensor methods in solving plant science problems are also reviewed and discussed. The reviewed applications of tensor methods in plant metabolomics cover a wide range of important plant science topics including plant gene mutation and phenotype, plant disease and resistance, plant pharmacology and nutrition analysis, and plant products ingredient characterization and quality evaluation. It is evident from the review that tensor methods significantly promote the automated and intelligent process of plant metabolomics analysis and profoundly affect the paradigm of plant science research. To the best of our knowledge, this is the first review to systematically summarize the tensor analysis methods in plant metabolomic data analysis. [ABSTRACT FROM AUTHOR]

Background: Task-shared care is a demonstrated approach for integrating mental health into maternal and child healthcare (MCH) services. Training and continued support for frontline providers is key to the success of task sharing initiatives. In most settings this is provided by mental health specialists. However, in resource constrained settings where specialists are in short supply, there is a need to explore alternative models for providing training and supportive supervision to frontline maternal care providers. This paper reports on the impact of a cascade training (train-the-trainers) approach in improving the knowledge and attitudes of primary healthcare workers (PHCW) to perinatal depression. Methods: Senior primary health care providers selected from across participating local government areas were trained to provide training to other PHCWs. The training sessions facilitated by these trainers were observed and rated for fidelity by specialist trainers, while the trainees provided their impression of and satisfaction with the training sessions using predesigned assessment forms. Training outcomes assessed included knowledge of depression (using mhGAP training questions and knowledge of depression questionnaire) and attitude towards providing care for depression (revised depression attitude questionnaire (R-DAQ)) measured pre and post training as well as six months after training. Results: Trainees were 198 PHCWs (94.4% female), who routinely provide MCH services in 28 selected primary care clinics and had between 6- and 34-years' experience. Training was provided by 11 trained trainers who were general physicians or senior nurses. Training sessions were rated high in fidelity and on training style. Sessions were rated excellent by 77.8% of the trainees with the trainers described as knowledgeable, effective and engaging. Knowledge of depression mean score improved from a pre-training level of 12.3 ± 3.5 to 15.4 ± 3.7, immediately post-training and 14.7 ± 3.2, six months post-training (both comparisons: p < 0.001). The proportion of PHCW workers endorsing statements indicative of positive attitudes on the professional confidence and the generalist perspective modules of the R-DAQ also increased with training. Conclusion: Our findings suggest that cascade training can be an effective model for rapidly providing training and upskilling frontline PHCWs to deliver care for women with perinatal depression in resource limited settings. Trial registration: This study was retrospectively registered 03 December 2019. https://doi.org/10.1186/ISRCTN 94,230,307. [ABSTRACT FROM AUTHOR]

Squiggle data is the numerical output of DNA and RNA sequencing by the Nanopore next generation sequencing platform. Nanopore sequencing offers expanded applications compared to previous sequencing techniques but produces a large amount of data in the form of current measurements over time. The analysis of these segments of current measurements require more complex and computationally intensive algorithms than previous sequencing technologies. The purpose of this study is to investigate in principle the potential of using quantum computers to speed up Nanopore data analysis. Quantum circuits are designed to extract major features of squiggle current measurements. The circuits are analyzed theoretically in terms of size and performance. Practical experiments on IBM QX show the limitations of the state of the art quantum computer to tackle real life squiggle data problems. Nevertheless, pre-processing of the squiggle data using the inverse wavelet transform, as experimented and analyzed in this paper as well, reduces the dimensionality of the problem in order to fit a reasonable size quantum computer in the hopefully near future. [ABSTRACT FROM AUTHOR]

Background: There is a workforce shortage in the children's hospice sector, but there has been little research on the specific challenges of working in this setting and on how these challenges might be alleviated. To identify appropriate interventions to improve staff wellbeing, the drivers of wellbeing in children's hospices need to be known and measured. This paper reports on the development of two measures, one for work-related rewards and one for work-related stressors, for use in children's hospice care teams. Methods: A mixed-methods, four-stage study; the first three phases focused on the development of the scales, and the last stage focused on the validation of the scales. Participants of all stages were children's hospice care team staff members in the UK. Stage 1: survey assessing the relevance and comprehensiveness of the original scale items (N = 60); Stages 2 (focus groups; N = 16) and 3 (cognitive interviews; N = 14) to assess content validity; Stage 4: UK-wide survey (N = 414) to validate the final version of the new, children's hospice-specific scales using Rasch Analysis (RA) and Confirmatory Factor Analysis (CFA). Results: Due to poor fitting indices shown in the results from the RA, five items (out of 36) were removed from the new rewards scale used in the UK-wide survey and 20 (out of 62) were removed from the new stressors scale. CFA also supported the removal of the items and showed a one-factor structure for the rewards scale and a three-factor structure for the stressors scale were adequate—the sub-scales for the stressors scale related to caring for an ill or dying child ("Child" sub-scale), working with parents and families ("Parent" sub-scale), and stressors related to organisational factors, such as team conflict and workload ("Organisation" sub-scale). Conclusions: Both of the new scales showed good psychometric properties and can be useful in clinical settings and research to assess the perceived intensity of the work-related rewards and stressors for children's hospice staff. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis to project them into the future. Statisticians in Israel were involved in these processes early in the pandemic in some silos as an ad-hoc unorganized effort. Informal discussions within the statistical community culminated in a roundtable, organized by three past presidents of the Israel Statistical Association, and hosted by the Samuel Neaman Institute in April 2021. The meeting was designed to provide a forum for exchange of views on the profession's role during the COVID-19 pandemic, and more generally, on its influence in promoting evidence-based public policy. This paper builds on the insights and discussions that emerged during the roundtable meeting and presents a general framework, with recommendations, for involving statisticians and statistics in decision-making. [ABSTRACT FROM AUTHOR]

Accurate estimate of relatedness is important for genetic data analyses, such as heritability estimation and association mapping based on data collected from genome-wide association studies. Inaccurate relatedness estimates may lead to biased heritability estimations and spurious associations. Individual-level genotype data are often used to estimate kinship coefficient between individuals. The commonly used sample correlation-based genomic relationship matrix (scGRM) method estimates kinship coefficient by calculating the average sample correlation coefficient among all single nucleotide polymorphisms (SNPs), where the observed allele frequencies are used to calculate both the expectations and variances of genotypes. Although this method is widely used, a substantial proportion of estimated kinship coefficients are negative, which are difficult to interpret. In this paper, through mathematical derivation, we show that there indeed exists bias in the estimated kinship coefficient using the scGRM method when the observed allele frequencies are regarded as true frequencies. This leads to negative bias for the average estimate of kinship among all individuals, which explains the estimated negative kinship coefficients. Based on this observation, we propose an unbiased estimation method, UKin, which can reduce kinship estimation bias. We justify our improved method with rigorous mathematical proof. We have conducted simulations as well as two real data analyses to compare UKin with scGRM and three other kinship estimating methods: rGRM, tsGRM, and KING. Our results demonstrate that both bias and root mean square error in kinship coefficient estimation could be reduced by using UKin. We further investigated the performance of UKin, KING, and three GRM-based methods in calculating the SNP-based heritability, and show that UKin can improve estimation accuracy for heritability regardless of the scale of SNP panel., (© 2022. The Author(s).)

Biclustering algorithm is an effective tool for processing gene expression datasets. There are two kinds of data matrices, binary data and non-binary data, which are processed by biclustering method. A binary matrix is usually converted from pre-processed gene expression data, which can effectively reduce the interference from noise and abnormal data, and is then processed using a biclustering algorithm. However, biclustering algorithms of dealing with binary data have a poor balance between running time and performance. In this paper, we propose a new biclustering algorithm called the Adjacency Difference Matrix Binary Biclustering algorithm (AMBB) for dealing with binary data to address the drawback. The AMBB algorithm constructs the adjacency matrix based on the adjacency difference values, and the submatrix obtained by continuously updating the adjacency difference matrix is called a bicluster. The adjacency matrix allows for clustering of gene that undergo similar reactions under different conditions into clusters, which is important for subsequent genes analysis. Meanwhile, experiments on synthetic and real datasets visually demonstrate that the AMBB algorithm has high practicability., (© 2022. The Author(s).)

Background: Patient and public involvement (PPI) is increasingly seen as essential to health service research. There are strong moral and ethical arguments for good quality PPI. Despite the development of guidance aimed at addressing the inconsistent reporting of PPI activities within research, little progress has been made in documenting the steps taken to undertake PPI and how it influences the direction of a study. Without this information, there are minimal opportunities to share learnings across projects and strengthen future PPI practices. The aim of this paper is to present details on the processes and activities planned to integrate PPI into the qualitative research component of a mixed-methods, multi-site study evaluating the implementation of a smart template to promote personalised primary care for patients with multiple long-term conditions. Methods: This proposal describes the processes and activities planned to integrate PPI into the development and piloting of qualitative data collection tools (topic guides for both practice staff and patients) and a tailored data analysis package developed for PPI members incorporating broad concepts and specific methods of qualitative data analysis. Discussion: Outputs relating to PPI activity may include clear, concise and suitably worded topic guides for qualitative interviews. Piloting of the topic guides via mock interviews will further develop researchers' skills including sensitisation to the experiences of participants being interviewed. Working with PPI members when analysing the qualitative data aims to provide reciprocal learning opportunities and may contribute to improving the overall rigour of the data analysis. The intent of publishing proposed PPI activities within this project is to inform the future delivery of high quality PPI. Plain English summary: Patient and public involvement (PPI) improves healthcare research, however, there is little published evidence of proposed PPI activities within a research study. The aim of this article is to describe the proposed PPI activities which are to be integrated into a study implementing a smart template to promote personalised care for people with multiple long-term conditions within primary care in the United Kingdom. The proposal describes the ways in which PPI members will be included within the data collection and analysis phases of a research study which includes interviews with primary care staff and patients. PPI members will be asked to develop questions for these interviews and to take part in a mock interview whereby a researcher interviews a PPI member. The proposal also provides details on qualitative data analysis workshops which will be specifically developed for PPI members. The impact of PPI activities could include clear, concise and suitably worded questions used within the interviews. Piloting of these questions via mock interviews may enable researchers to further develop their interviewing skills. It is anticipated that involving PPI members when analysing qualitative data will provide opportunities for reciprocal learning and lead to rich interpretations of the data, inclusive of the PPI members' perspectives. Publishing a record of planned PPI activities and potential impacts demonstrates the rationale and considerations made by the team to ensure that involvement in this study is meaningful and has potential benefits for all involved. The team hopes this proposal will support others with the planning and delivery of PPI activities. In future publications, we will reflect on the learnings, challenges, and outcomes from the PPI activities detailed in this proposal. [ABSTRACT FROM AUTHOR]

Background: In high-dimensional data (HDD) settings, the number of variables associated with each observation is very large. Prominent examples of HDD in biomedical research include omics data with a large number of variables such as many measurements across the genome, proteome, or metabolome, as well as electronic health records data that have large numbers of variables recorded for each patient. The statistical analysis of such data requires knowledge and experience, sometimes of complex methods adapted to the respective research questions. Methods: Advances in statistical methodology and machine learning methods offer new opportunities for innovative analyses of HDD, but at the same time require a deeper understanding of some fundamental statistical concepts. Topic group TG9 "High-dimensional data" of the STRATOS (STRengthening Analytical Thinking for Observational Studies) initiative provides guidance for the analysis of observational studies, addressing particular statistical challenges and opportunities for the analysis of studies involving HDD. In this overview, we discuss key aspects of HDD analysis to provide a gentle introduction for non-statisticians and for classically trained statisticians with little experience specific to HDD. Results: The paper is organized with respect to subtopics that are most relevant for the analysis of HDD, in particular initial data analysis, exploratory data analysis, multiple testing, and prediction. For each subtopic, main analytical goals in HDD settings are outlined. For each of these goals, basic explanations for some commonly used analysis methods are provided. Situations are identified where traditional statistical methods cannot, or should not, be used in the HDD setting, or where adequate analytic tools are still lacking. Many key references are provided. Conclusions: This review aims to provide a solid statistical foundation for researchers, including statisticians and non-statisticians, who are new to research with HDD or simply want to better evaluate and understand the results of HDD analyses. [ABSTRACT FROM AUTHOR]

Background: Modern sequencing technologies have generated low-cost microbiome survey datasets, across sample sites, conditions, and treatments, on an unprecedented scale and throughput. These datasets often come with a phylogenetic tree that provides a unique opportunity to examine how shared evolutionary history affects the different patterns in host-associated microbial communities., Results: In this paper, we describe an R package, phyloMDA, for phylogeny-aware microbiome data analysis. It includes the Dirichlet-tree multinomial model for multivariate abundance data, tree-guided empirical Bayes estimation of microbial compositions, and tree-based multiscale regression methods with relative abundances as predictors., Conclusion: phyloMDA is a versatile and user-friendly tool to analyze microbiome data while incorporating the phylogenetic information and addressing some of the challenges posed by the data., (© 2022. The Author(s).)

Purpose: Tanzania has implemented policies that aim at improving health sector performance as well as the general health status of citizens. Establishment of community insurance fund, increase government budget allocation in health sector, establishment of institutions for critical and special diseases like Tanzania Ocean road cancer institute, Muhimbili Orthopaedic Institute and many other that aim at improving sector efficiency. These efforts and policies had a direct impact on improving the health sector and achieving Sustainable Development Goals (SDGs). Despite these improvement efforts, the health sector continues to face enormous challenges. Among the major challenges identified is the level of inefficiencies in healthcare delivery. It is for this reason; this paper examines the scale efficiency level in Tanzania's public hospitals. Methods: Using data from the Ministry of Health, this paper employs the Input based Data Envelopment Analysis (DEA) to examine Tanzania's public hospital efficiency levels. DEA has been applied because it can handle multiple inputs and output that can have different units simultaneously. Results: Findings showed that the average scale efficiency was 78.6%.and 72.9%for regional and district hospitals respectively. Additionally, 43.8% of the regional referral hospitals attained the most productive scale size compared to 21.05% in district hospitals. Conclusion: The study concludes that there is dire need for the ministry of health to consider resource reallocation across public hospitals. Periodic re-estimation of efficiency levels coupled with increased health care input injection is of urgent need. [ABSTRACT FROM AUTHOR]

Introduction: Enterococcus faecalis (E. faecalis) is the most commonly isolated bacterium from infected root canals. It is found in the form of a biofilm, which makes it more resistant to antimicrobials, and requires optimal chemomechanical strategies to maximize root canal disinfection. Aim: To evaluate the efficacy of 4 different endodontic file systems against E. faecalis biofilm growth in root canals using colony-forming units per milliliter (CFU/mL) and scanning electron microscope (SEM). Methods: Eighty-five extracted human mandibular premolars with straight root canals and apical diameters not larger than the #15 K-file were randomly selected. After performing a pilot study (n = 15) to determine the ideal incubation period for E. faecalis biofilm development, sixty-five root canals were infected with E. faecalis, incubated for 3 weeks, and then mechanically prepared using one of four single files (XP-endo Shaper, Hyflex EDM, One Curve, and Fanta. AFTM F One) (n = 15). Five infected root canals were excluded for the positive control. Five non-contaminated root canals were included for the negative control. Samples were collected using sterile paper points pre- and post-instrumentation to determine the bacterial load (CFU/mL). Root canals from each group were topographically evaluated at the coronal, middle, and apical segments using scanning electron microscope (SEM). Bacterial reduction data were estimated and statistically analyzed by Kruskal–Wallis and Mann–Whitney U tests (post hoc test) (P ≤.05). Results: XP-endo Shaper, Hyflex DEM, and One Curve significantly could eradicate E. faecalis biofilms in infected root canals with no significant difference among them compared to Fanta. AF™ F One. Conclusion: None of the systems were capable of completely eliminating biofilms. XP-endo Shaper, Hyflex EDM, and One Curve mechanically eliminated E. faecalis biofilms compared to Fanta. AF™ F One from infected root canals. [ABSTRACT FROM AUTHOR]