Adopting Optimal Statistical Practices: Applied Researchers.

In keeping with this year's focus on how we might foster a culture of research that values and consistently adopts optimal statistical practices, this column entry highlights practices our applied researchers can take up that may help remedy the gap between recommended statistical practices and implementation. This installment specifically encourages increasing the transparency of analyses, teaming up with colleagues with quantitative expertise, and disseminating resources that highlight optimal practices. [J Nurs Educ. 2024;63(7):490-491.].

Adopting Optimal Statistical Practices: Graduate Programs.

In 2024, the Methodology Corner will briefly look at how we might foster enduring commitments from nurse education researchers to remain up-to-date on their statistical expertise and to use optimal statistical methods. The first column of the year specifically looks at how graduate programs might enrich their statistics curriculum in a manner that could foster an increasingly valid science of nursing education. [J Nurs Educ. 2024;63(3):197-198.].

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases.

BACKGROUND: Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome. METHODS: We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants. RESULTS: Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving. CONCLUSIONS: Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.

Improving Effect Size Interpretations.

We encourage our community of nurse education researchers to remember to assign interpretations to their effect size estimates. In general, our community is asked to reduce the use of rules-of-thumb and, instead, are encouraged to use empirical and contextual methods to assign interpretations to effect size estimates. [J Nurs Educ. 2023;62(11):653-654.].

From η2 to ω2: Adopt a Better Measure of Effect.

A cursory review of relevant research works published in the Journal of Nursing Education suggests that our community may unnecessarily rely on η2 when reporting results of their ANOVA models. Although η2 is convenient, the statistic possesses many limitations that warrant our community adopting a wider set of effect size statistics and practices to promote a valid science of nursing education. We specifically call attention in this article to ω2. [J Nurs Educ. 2023;62(9):532-533.].

Cohen's and Hedges' g.

A cursory review of relevant research works published in the Journal of Nursing Education suggests our community relies heavily on Cohen's d. Although Cohen's d is a valuable effect size, it possesses a number of limitations that warrants our community adopting a wider set of effect size statistics to help promote a valid science of nursing education. We specifically call attention to Hedges' g. [J Nurs Educ. 2023;62(5):316-317.].

Remember to Leverage Effect Size Estimates.

In 2023, the Methodology Corner column has opted to promote the efficacious use of effect sizes among our community of researchers. In this first entry of the year, we call attention to broad improvement in effect size reporting germane to our community, including more consistent reporting of effect sizes and their interpretations. [J Nurs Educ. 2023;62(2):116.].

Prevent Problematic Missing Data.

Over the course of 2022, we have encouraged our community to adopt increasingly effective methods of mitigating the harm missing data poses to a valid science of nursing education. With our last column entry for the year, we conclude our emphasis by looking at a few approaches to the prevention of problematic missingness that can be implemented prior to collecting data. [J Nurs Educ. 2022;61(11):657-658.].

Repair Your Missing Data.

This Methodology Corner encourages nurse educators to include reparative techniques in their analyses that better allay threats to validity introduced by missing data. This article specifically highlights the extra dependent variable technique that is accessible to researchers due to the simplicity of the approach and availability of popular software capable of implementing the repair. [J Nurs Educ. 2022;61(9):549-550.].

Study Your Missing Data.

This installment of the Methodology Corner raises the concern that our community may not be adequately attending to the threat missingness poses to valid nursing education research. To encourage the adoption of increasingly sound methodological practices, we highlight for our community that counts and relative frequencies and simple bivariate analyses are easily implemented tools that help formulate valid responses to missing data. [J Nurs Educ. 2022;61(5):280-281.].

Missing Data.

If left unattended, missingness can undermine the conclusions nurse researchers draw in their studies. Unfortunately, a cursory review of quantitative and mixed methods works recently published in the Journal of Nursing Education suggests missing data is left relatively unattended within our community. This column has recommended our researcher mitigate the emergence of missing data as much as possible, describe any missingness thoroughly, and adopt modern missing data techniques that help mitigate threats to validity introduced by missing data. Reviewers and editors are also encouraged to request from authors clear descriptions of the missingness in their studies as well as how they responded to any missingness. [J Nurs Educ. 2022;61(2):65-66.].

More Power Analyses Are Needed.

Nurse researchers have long been encouraged to consult a priori power analyses to help design studies that are robust to type II errors. Unfortunately, a cursory look at Journal of Nursing Education articles published in 2020 suggests that a priori power analyses may be used infrequently in our community. Consequently, this column requested that authors conduct power analyses using increasingly rigorous standards (e.g., power levels) and report their findings well to readers. When a priori power analyses are missing or not reported clearly, reviewers and editors are encouraged to request authors ameliorate the shortfalls in their manuscripts. [J Nurs Educ. 2021;60(11):605-606.].

Coefficient Omega.

This article raises the concern that nursing education research may be unduly subject to several limitations inherited from an overreliance on Cronbach's α. Consequently, researchers are encouraged to make greater use of coefficient omega since it is expected to perform just as well as or better than Cronbach's α, especially when tau-equivalence goes unmet. Several resources are noted that may help researchers estimate omega for composite measurements. [J Nurs Educ. 2021;60(8):429-430.].

Nursing Professionals' Stress Level During Coronavirus Disease 2019: A Looming Workforce Issue.

The purpose of this study was to assess the impact of coronavirus disease 2019 on perceived stress experienced by nurse practitioners/nurses and their desire to remain employed as health care providers. A cross-sectional survey of 40 questions was administered between May and September 2020 to a convenience sample of 433 nurse practitioners and nurses in Missouri and Georgia through a Qualtrics (Provo, UT) link provided via their professional organization listserv. Anxiety-related symptoms and perceived helplessness were correlated with personal protective equipment concerns and management approachability. Problematic stress was associated with willingness to leave their current job or the nursing profession altogether.

Reliability.

A cursory look at the measurement practices in the Journal of Nursing Education revealed several deficits that our community is encouraged to address. In 2020, a little less than half of our quantitative studies did not provide reliability estimates from their own data, opting instead to provide estimates reported in the literature or none at all. Of the studies that did supply estimates using their data, only Cronbach's alpha was reported. Unfortunately, limitations with Cronbach's alpha and inconsistent reporting practices are likely undermining the science of nursing education. Researchers are encouraged to estimate reliability using their own data with increasingly valid techniques. [J Nurs Educ. 2021;60(2):65-66.].

Infection by Hepatitis Delta Virus.

Hepatitis delta virus (HDV) and hepatitis B virus (HBV) are blood-borne viruses that infect human hepatocytes and cause significant liver disease. Infections with HBV are more damaging when there is a coinfection with HDV. The genomes and modes of replication of these two viruses are fundamentally different, except for the fact that, in nature, HDV replication is dependent upon the envelope proteins of HBV to achieve assembly and release of infectious virus particles, ones that use the same host cell receptor. This review focuses on what has been found of the various ways, natural and experimental, by which HDV particles can be assembled and released. This knowledge has implications for the prevention and treatment of HDV infections, and maybe for an understanding of the origin of HDV.

Student perceptions of online and in-person microbiology laboratory experiences in undergraduate medical education.

Background: Universities are facing increased budget constraints, often resulting in reduced funds to support microbiology laboratories. Online mock laboratory activities are often instituted as a cost-effective alternative to traditional wet labs for medical students.Objective: The purpose of this study was to examine students' perceptions of online and in-person microbiology lab learning experiences.Design: We investigated undergraduate medical student perception of the in-person and online microbiology lab experience; 164 first-year medical students participated in newly designed online labs, while 83 second-year medical students continued to use in-person labs. An online survey was administered to collect student opinions of the lab experience.Results: In terms of student self-reported learning styles, those students who attended the lab in person were more likely to report a tactile learning style (33% vs 16%) while those students who learned the material online reported a visual learning style preference (77% vs 61%; n = 264). Students felt that the online microbiology lab was more convenient for their schedules when compared to the in-person lab. A greater proportion of online students (12%) felt that they encountered brand-new material on the final quiz than in-person students (1%; n = 245). Even so, 43% of the online educated students and 37% of the in-person educated students perceived their assigned lab experiences to be the optimal lab design, and over 89% of both groups reported a desire for at least some in-person instruction in a wet-laboratory environment.Conclusions: Our findings suggest that, while students are strongly supportive of digital online lab activities, the overwhelming majority of students still report a desire for a blend of online and in-person, hands-on laboratory activities. These findings will further research directed towards student perception of the lab experience and aid in the adaptation of microbiology curriculums to accommodate both student and university needs.

The complete costs of genome sequencing: a microcosting study in cancer and rare diseases from a single center in the United Kingdom.

PURPOSE: The translation of genome sequencing into routine health care has been slow, partly because of concerns about affordability. The aspirational cost of sequencing a genome is $1000, but there is little evidence to support this estimate. We estimate the cost of using genome sequencing in routine clinical care in patients with cancer or rare diseases. METHODS: We performed a microcosting study of Illumina-based genome sequencing in a UK National Health Service laboratory processing 399 samples/year. Cost data were collected for all steps in the sequencing pathway, including bioinformatics analysis and reporting of results. Sensitivity analysis identified key cost drivers. RESULTS: Genome sequencing costs £6841 per cancer case (comprising matched tumor and germline samples) and £7050 per rare disease case (three samples). The consumables used during sequencing are the most expensive component of testing (68-72% of the total cost). Equipment costs are higher for rare disease cases, whereas consumable and staff costs are slightly higher for cancer cases. CONCLUSION: The cost of genome sequencing is underestimated if only sequencing costs are considered, and likely surpasses $1000/genome in a single laboratory. This aspirational sequencing cost will likely only be achieved if consumable costs are considerably reduced and sequencing is performed at scale.

Remission of Inflammatory Bowel Disease in Glucose-6-Phosphatase 3 Deficiency by Allogeneic Haematopoietic Stem Cell Transplantation.

Mendelian disorders in glucose-6-phosphate metabolism can present with inflammatory bowel disease [IBD]. Using whole genome sequencing we identified a homozygous variant in the glucose-6-phosphatase G6PC3 gene [c.911dupC; p.Q305fs*82] in an adult patient with congenital neutropenia, lymphopenia and childhood-onset, therapy-refractory Crohn's disease. Because G6PC3 is expressed in several haematopoietic and non-haematopoietic cells it was unclear whether allogeneic stem cell transplantation [HSCT] would benefit this patient with intestinal inflammation. We show that HSCT resolves G6PC3-associated immunodeficiency and the Crohn's disease phenotype. It illustrates how even in adulthood, next-generation sequencing can have a significant impact on clinical practice and healthcare utilization in patients with immunodeficiency and monogenic IBD.