Anxiety among fathers during the prenatal and postpartum period: a meta-analysis.

INTRODUCTION: The purpose of this review was to determine the prevalence of anxiety among fathers during the perinatal (pre- and post-natal) period. METHODS: A systematic search was conducted to identify studies published between 1995-2020. One hundred and seventy-two of the records met inclusion criteria and full texts were screened for eligibility. The authors followed PRISMA guidelines to extract the data. RESULTS: A total of 23 studies, representing 40,124 participants, are included in this meta-analysis. The overall random effects estimate of paternal perinatal anxiety was 10.69% (95% confidence interval (CI): 8.14 - 13.91%). Rates of paternal perinatal anxiety demonstrated significant heterogeneity that was large in magnitude (Q = 304,494, p < .001, I2 = 99.93 and τ2 = .5381). Study quality rating did not appear to moderate rates of paternal perinatal anxiety (low: 10.74%; 95% CI: 6.56-17.11%; high: 10.65%; 95% CI: 6.02- 18.15%). DISCUSSION: Paternal perinatal anxiety rates in this meta-analysis are considerably higher than the global WHO regional prevalence rates for anxiety among men suggesting the transition into parenthood may place men at greater risk for anxiety.

A large-scale analysis of bioinformatics code on GitHub.

In recent years, the explosion of genomic data and bioinformatic tools has been accompanied by a growing conversation around reproducibility of results and usability of software. However, the actual state of the body of bioinformatics software remains largely unknown. The purpose of this paper is to investigate the state of source code in the bioinformatics community, specifically looking at relationships between code properties, development activity, developer communities, and software impact. To investigate these issues, we curated a list of 1,720 bioinformatics repositories on GitHub through their mention in peer-reviewed bioinformatics articles. Additionally, we included 23 high-profile repositories identified by their popularity in an online bioinformatics forum. We analyzed repository metadata, source code, development activity, and team dynamics using data made available publicly through the GitHub API, as well as article metadata. We found key relationships within our dataset, including: certain scientific topics are associated with more active code development and higher community interest in the repository; most of the code in the main dataset is written in dynamically typed languages, while most of the code in the high-profile set is statically typed; developer team size is associated with community engagement and high-profile repositories have larger teams; the proportion of female contributors decreases for high-profile repositories and with seniority level in author lists; and, multiple measures of project impact are associated with the simple variable of whether the code was modified at all after paper publication. In addition to providing the first large-scale analysis of bioinformatics code to our knowledge, our work will enable future analysis through publicly available data, code, and methods. Code to generate the dataset and reproduce the analysis is provided under the MIT license at https://github.com/pamelarussell/github-bioinformatics. Data are available at https://doi.org/10.17605/OSF.IO/UWHX8.

Domains of quality for clinical ethics case consultation: a mixed-method systematic review.

BACKGROUND: "Clinical ethics consultation" (CEC) is the provision of consultative services by an individual or team with the aim of helping health professionals, patients, and their families grapple with difficult ethical issues arising during health care. There are almost 25,000 articles in the worldwide literature on CEC, but very few explicitly address measuring the quality of CEC. Many more address quality implicitly, however. This article describes a rigorous protocol for compiling the diverse literature on CEC, analyzing it with a quality measurement lens, and seeking a set of potential quality domains for CEC based on areas of existing, but hitherto unrecognized, consensus in the literature. METHODS/DESIGN: This mixed-method systematic review will follow a sequential pattern: scoping review, qualitative synthesis, and then a quantitative synthesis. The scoping review will include categorizing all quality measures for CEC discussed in the literature, both quantitative and qualitative. The qualitative synthesis will generate a comprehensive analytic framework for understanding the quality of CEC and is expected to inform the quantitative synthesis, which will be a meta-analysis of studies reporting the effects of CEC on pre-specified clinical outcomes. DISCUSSION: The literature on CEC is broad and diverse and has never been examined with specific regard to quality measurement. We propose a novel mixed-methods approach to compile and synthesize this literature and to derive a framework for assessing quality in CEC. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015023282.