The Preparation of Future Statistically Oriented Physicians: A Single-Center Experience in Saudi Arabia.

Background and Objectives: Statistics are of paramount significance to physicians as they allow them to critically interpret the medical literature and to contribute to it. However, teaching statistics to medical students and physicians, as well as learning statistics, is nothing short of difficult and anxiety-inducing to a great extent. Materials and Methods: In this study, an example of a novel approach to teaching statistics to medical students is introduced at a single college of medicine in Saudi Arabia. In this retrospective report, a new approach that has been developed and delivered to students is described. Results: The approach, referred to as the personal experience pathway, is part of a major curriculum change to the MBBS program. The track presents statistics to students as a tool, rather than a subject, that students will need to interpret results, either present in the literature or those of the research projects they are conducting. The outcome of this process has been assessed through measuring students' scholarly output through student self-reporting and has been followed up over four student cohorts graduating between the years 2019 and 2022. The approach has successfully equipped students with a solid foundation of statistical understanding that has allowed them to publish in peer-reviewed journals. Such scholarly output has increased significantly over the last two years. Conclusions: The current study presents a framework through which the detailed curriculum plan could be applied to other medical schools, nationally and internationally, which will better prepare future statistically oriented physicians.

Statistical literacy and scientific reasoning & argumentation in physicians.

Objective: Statistical literacy (SL) of physicians, i.e. the ability to use and interpret statistical numbers in the context of science, is an essential prerequisite for risk estimation and communication. Together with scientific reasoning and argumentation (SRA) skills, SL provides the basis for evidence-based practice. Several studies suggest that in medical students both skills are underdeveloped. The aim of the present study was to investigate these skills in practicing physicians and how these skills were acquired. Methods: Data collection in N=71 physicians was conducted online and as paper pencil. SL was assessed with multiple-choice items. SRA skills evidence evaluation and drawing conclusions were measured with a decision scenario. Results: Study results indicated that physicians have medium levels of SL (M=17.58, SD=6.92, max 30 pts.) and SRA (evidence evaluation: M=7.75, SD=1.85, max 10 pts.; drawing conclusions: M=37.20, SD=5.35, max 60 pts.). Skills development via autodidactic learning activities (M=4.78, SD=1.13, range 1-6) was reported significantly more often than development during formal medical education (M=2.31, SD=1.46), t(71)=-9.915, p<.001, or in extracurricular activities (M=3.34, SD=1.87), t(71)=4.673, p<.001. The active involvement in research seemed decisive: The number of publications and time spent in research significantly correlated with SL, r(71)=.355, p=.002; respectively r(71)=.280, p=.018. SRA skills were predicted by the type of MD-thesis, ß=-.380, p=.016, and working in research, ß=3.355, p=.008. Conclusion: Active involvement in research activities seems to be a very important factor for the development of both SL and SRA skills. The implementation of systematic fostering of these skills during formal medical education seems warranted.

Shifting the focus away from binary thinking of statistical significance and towards education for key stakeholders: revisiting the debate on whether it's time to de-emphasize or get rid of statistical significance.

There has been a long-standing controversy among scientists regarding the appropriate use of P-values and statistical significance in clinical research. This debate has resurfaced through recent calls to modify the threshold of P-value required to declare significance, or to retire statistical significance entirely. In this article, we revisit the issue by discussing: i) the connection between statistical thinking and evidence-based practice; ii) some history of statistical significance and P-values; iii) some practical challenges with statistical significance or P-value thresholds in clinical research; iv) the on-going debate on what to do with statistical significance; v) suggestions to shift the focus away from binary thinking of statistical significance and towards education for key stakeholders on research essentials including statistical thinking, critical thinking, good reporting, basic clinical research concepts and methods, and more. We then conclude with remarks and illustrations of the potential deleterious public health consequences of poor methods including selective choice of analysis approach and misguided reliance on binary use of P-values to report and interpret scientific findings.

A teaching tool about the fickle p value and other statistical principles based on real-life data.

A poor understanding of statistical analysis has been proposed as a key reason for lack of replicability of many studies in experimental biomedicine. While several authors have demonstrated the fickleness of calculated p values based on simulations, we have experienced that such simulations are difficult to understand for many biomedical scientists and often do not lead to a sound understanding of the role of variability between random samples in statistical analysis. Therefore, we as trainees and trainers in a course of statistics for biomedical scientists have used real data from a large published study to develop a tool that allows scientists to directly experience the fickleness of p values. A tool based on a commonly used software package was developed that allows using random samples from real data. The tool is described and together with the underlying database is made available. The tool has been tested successfully in multiple other groups of biomedical scientists. It can also let trainees experience the impact of randomness, sample sizes and choice of specific statistical test on measured p values. We propose that live exercises based on real data will be more impactful in the training of biomedical scientists on statistical concepts.

How statistical learning interacts with the socioeconomic environment to shape children's language development.

Language is acquired in part through statistical learning abilities that encode environmental regularities. Language development is also heavily influenced by social environmental factors such as socioeconomic status. However, it is unknown to what extent statistical learning interacts with SES to affect language outcomes. We measured event-related potentials in 26 children aged 8-12 while they performed a visual statistical learning task. Regression analyses indicated that children's learning performance moderated the relationship between socioeconomic status and both syntactic and vocabulary language comprehension scores. For children demonstrating high learning, socioeconomic status had a weaker effect on language compared to children showing low learning. These results suggest that high statistical learning ability can provide a buffer against the disadvantages associated with being raised in a lower socioeconomic status household.

[Medical biostatistics with GMRC Shiny Stats - learning by doing]. / Biostatistiques médicales avec GMRC Shiny Stats ­ un outil de formation par la pratique.

Biostatistics are omnipresent in the scientific and medical literature and are an essential skill for any health student. We have developed a practical training tool - GMRC Shiny stats - an interactive application specifically dedicated to medical data statistical analysis. The application has been designed to provide an analysis workflow corresponding to the usual progression of an experienced statistician during data analysis. The most common statistical analyses can be performed (descriptive statistics, inferences according to frequentist methods, survival analyses, correlation, agreement measurements, etc.). GMRC Shiny stats is intuitive and user-friendly and assists students in choosing the most appropriate statistical tests. With all these functionalities, students can learn statistical analysis by doing. Getting involved in the statistical analysis and processing of their own data is likely to improve their biostatistics skills.

Integrating an Online Statistics Course With a Graduate Nursing Research Course for Enhanced Learning.

BACKGROUND: Exploration for innovative pedagogical techniques to teach statistics led to examination of the Open and Free Courses offered through the Carnegie Mellon University Online Learning Initiative (CMU OLI). This study examined the impact of the CMU OLI statistics course on graduate nursing students' course grades and course evaluations. METHOD: This retrospective study of a hybrid course compared three teaching modalities for statistics: 1) face-to-face workshop, 2) CMU OLI course, and 3) CMU OLI course plus online discussions. RESULTS: Mean grade point averages increased sequentially and significantly. Individual students' grades improved and student evaluations of instruction mean scores for critical thinking, teaching effectiveness, overall course rating, and overall learning increased significantly (p < .01). CONCLUSION: Future studies are needed that build knowledge of how open and free online courses can be used in nursing education to facilitate retention of content, allay statistics anxiety, and increase student motivation toward research. [J Nurs Educ. 2020;59(4):227-230.].

A cross-sectional assessment of statistical knowledge among pharmacy faculty.

INTRODUCTION: The debate about the optimal level of research methods incorporated in doctor of pharmacy curricula is ongoing. Yet relatively little has been published about the research-based knowledge of the faculty in these programs. This study seeks to assess pharmacy faculty members' knowledge of fundamental statistical concepts. METHODS: A cross-sectional survey included a random sample of US-based pharmacy schools. Invitations were sent to faculty in each selected pharmacy school to participate in the online survey comprised of demographic questions and a multiple-choice statistics knowledge assessment covering eight fundamental biostatistics concepts. Each question had three answer options, with an additional fourth 'opt-out' option for those wishing to avoid guessing. RESULTS: The random sample of selected pharmacy schools resulted in email invitations sent to 2036 faculty from 30 pharmacy schools. The final study sample consisted of 139 pharmacy faculty members with a mean of 10.2 years of experience as a faculty member. Over 95% of pharmacy faculty reported that they read peer-reviewed scientific journal articles, while nearly 99% said the understanding of statistics was either 'somewhat important' (35%) or 'very important' (64%) in their role as a researcher. Pharmacy faculty achieved a mean of 5.1 correct responses out of eight knowledge-based questions. CONCLUSIONS: Pharmacy faculty provided correct responses to 64% of the items about fundamental statistical concepts. These study results are useful for making decisions about biostatistics education and curriculum content, particularly as pharmacy programs continue to incorporate a prominent role for research.

Ten simple rules for writing statistical book reviews.

Statistical books can provide deep insights into statistics and software. There are, however, many resources available to the practitioner. Book reviews have the capacity to function as a critical mechanism for the learner to assess the merits of engaging in part, in full, or at all with a book. The "ten simple rules" format, pioneered in computational biology, was applied here to writing effective book reviews for statistics because of the wide breadth of offerings in this domain, including topical introductions, computational solutions, and theory. Learning by doing is a popular paradigm in statistics and computation, but there is still a niche for books in the pedagogy of self-taught and instruction-based learning. Primarily, these rules ensure that book reviews function as a form of short syntheses to inform and guide readers in deciding to use a specific book relative to other options for resolving statistical challenges.

Medical graduate views on statistical learning needs for clinical practice: a comprehensive survey.

BACKGROUND: This paper seeks to contribute to a reputable evidence base for required competencies across different topics in statistics and probability (statistical topics) in preparing medical graduates for clinical practice. This is in order to inform the prioritization of statistical topics within future undergraduate medical curricula, while exploring the need for preparing tomorrow's doctors to be producers, and not merely consumers, of statistics. METHODS: We conducted a comprehensive online survey from July 2013 to August 2014 for a target group of 462 medical graduates with current or prior experience of teaching undergraduate medical students of the University of Edinburgh of whom 278 (60.2%) responded. Statistical topics were ranked by proportion of respondents who identified the practice of statistics, performing statistical procedures or calculations using appropriate data, as a required competency for medical schools to provide in preparing undergraduate medical students for clinical practice. Mixed effects analyses were used to identify potential predictors for selection of the above competency and to compare the likelihood of this selection for a range of statistical topics versus critical appraisal. RESULTS: Evidence was gleaned from medical graduates' experiences of clinical practice for the need for, not only a theoretical understanding of statistics and probability but also, the ability to practice statistics. Nature of employment and statistical topic were highly significant predictors of choice of the practice of statistics as a required competency ((F = 3.777, p < 0.0005) and (F = 45.834, p < 0.0005), respectively). The most popular topic for this competency was graphical presentation of data (84.3% of respondents) in contrast to cross-over trials for the competency understanding the theory only (70.5% of respondents). Several topics were found to be more popular than critical appraisal for competency in the practice of statistics. CONCLUSIONS: The model of medical graduates as mere consumers of statistics is oversimplified. Contrary to what has been suggested elsewhere, statistical learning opportunities in undergraduate medicine should not be restricted to development of critical appraisal skills. Indeed, our findings support development of learning opportunities for undergraduate medical students as producers of statistics across a wide range of statistical topics.

Statistics for Immunologists

Statistical tests and graphs are an important part of any immunological research publication or presentation, but not all immunologists have the statistical expertise to choose the best methods to evaluate and represent their experiments. These protocols provide a brief overview of the statistical methods most relevant to immunology researchers, so they can either analyze their own data or better understand their statistician collaborators. Protocols cover the basics of t­tests, ANOVA, nonparametric tests, linear and nonlinear regression models, categorical response models, statistical design of experiments, and advanced methods like re­sampling tests, Bayesian statistics, and methods for high­throughput ­omics data. Each topic receives a brief overview of the theory and usage, followed by brief instructions and code examples for R software. These protocols should be useful to biologists who are learning statistics for the first time and biologists who would like a refresher on basic statistical methods.

Assessing minimal medical statistical literacy using the Quick Risk Test: a prospective observational study in Germany.

OBJECTIVES: To assess minimal medical statistical literacy in medical students and senior educators using the 10-item Quick Risk Test; to assess whether deficits in statistical literacy are stable or can be reduced by training. DESIGN: Prospective observational study on the students, observational study on the university lecturers. SETTING: Charité University Medicine medical curriculum for students and a continuing medical education (CME) course at a German University for senior educators. PARTICIPANTS: 169 students taking part in compulsory final-year curricular training in medical statistical literacy (63% female, median age 25 years). Sixteen professors of medicine and other senior educators attending a CME course on medical statistical literacy (44% female, age range=30-65 years). INTERVENTIONS: Students completed a 90 min training session in medical statistical literacy. No intervention for the senior educators. OUTCOME MEASURES: Primary outcome measure was the number of correct answers out of four multiple-choice alternatives per item on the Quick Risk Test. RESULTS: Final-year students answered on average half (median=50%) of the questions correctly while senior educators answered three-quarters correctly (median=75%). For comparison, chance performance is 25%. A 90 min training session for students increased the median percentage correct from 50% to 90%. 82% of participants improved their performance. CONCLUSIONS: Medical students and educators do not master all basic concepts in medical statistics. This can be quickly assessed with the Quick Risk Test. The fact that a 90 min training session on medical statistical literacy improves students' understanding from 50% to 90% indicates that the problem is not a hard-wired inability to understand statistical concepts. This gap in physicians' education has long-lasting effects; even senior medical educators could answer only 75% of the questions correctly on average. Hence, medical students and professionals should receive enhanced training in how to interpret risk-related medical statistics.

The impact of participatory teaching methods on medical students' perception of their abilities and knowledge of epidemiology and statistics.

Statistics and Epidemiology are crucial both in clinical decision-making and clinical research. Teaching these disciplines in a Bachelor's Degree in Medicine is a significant challenge. In this paper, we aim to describe two participatory teaching methods used in a yearlong second-year course that includes both Epidemiology and Statistics, and to analyze how these two methodologies affect the students' perception of the course and their abilities related to these subjects. Both methodologies consist in carrying out a specific practical activity. The first practical activity is carried out using a website and aims to help students understand concepts and interpret information; the second involves analyzing a database using a statistical package and, subsequently, producing a scientific report. In addition, we prepared a questionnaire to find out the students' perception of these issues. The nine questionnaire items were assessed using a rating scale and adapted to characteristics of the course, which covers Epidemiology and Statistics in an integrated manner. Then we assessed the differences in perception before and after the activities were carried out. The results show that the students' perception improved significantly in the following items: "importance of Statistics and Epidemiology in Medicine"; "usefulness in clinical practice"; "understanding concepts"; "ability to perform a statistical analysis"; and "ability to sort data". The difference was not significant in the remaining four items. In conclusion, the students' perception of their ability in Statistics and Epidemiology significantly improved after completing the practical activities, and their perception of importance and usefulness of these subjects also improved.

A proposal for a new PhD level curriculum on quantitative methods for drug development.

This paper provides an overview of "Improving Design, Evaluation and Analysis of early drug development Studies" (IDEAS), a European Commission-funded network bringing together leading academic institutions and small- to large-sized pharmaceutical companies to train a cohort of graduate-level medical statisticians. The network is composed of a diverse mix of public and private sector partners spread across Europe, which will host 14 early-stage researchers for 36 months. IDEAS training activities are composed of a well-rounded mixture of specialist methodological components and generic transferable skills. Particular attention is paid to fostering collaborations between researchers and supervisors, which span academia and the private sector. Within this paper, we review existing medical statistics programmes (MSc and PhD) and highlight the training they provide on skills relevant to drug development. Motivated by this review and our experiences with the IDEAS project, we propose a concept for a joint, harmonised European PhD programme to train statisticians in quantitative methods for drug development.

The importance of scientific competencies in German medical curricula - the student perspective.

BACKGROUND: Scientific competencies are of great importance for physicians; not only for conducting reliable research, but also for patient care. However, there is growing concern that a lack of scientific competencies among physicians may lead to a deterioration in the quality on biomedical research. This study aims at assessing medical students' perspectives on the implementation of scientific competency training in German medical curricula. METHODS: An online survey was conducted in order to collect German medical students' opinions on the importance of acquiring scientific competencies during their medical studies and to provide us with an assessment of their current levels of basic scientific competencies by having them conduct a self-evaluation. Moreover, we wanted to understand their perceptions of current curricular content and to receive suggestions for improving scientific competency training. Participants were reached via the mailing lists of the German Medical Students' Association, as well as of local medical student committees, and the German Medical Students' Associations social media channel on Facebook. RESULTS: In total, 2380 medical students from across all 37 German medical faculties participated in the survey. The majority of students agreed that the ability to critically evaluate the relevant literature is an important competency for physicians, and that every student should conduct a research project during their medical studies. However, the students evaluated their scientific competencies as unsatisfactory, especially with regard to statistics and scientific writing. They were strongly in favor of receiving extended research training. CONCLUSION: Our study provides insight into German medical students' self-perception in relation to both patient care and biomedical research, and makes recommendations for potential improvements in scientific training. The study demonstrates that scientific competencies are of great importance to medical students in Germany. Students are not lacking motivation for scientific practice and have numerous ideas for enhancing scientific teaching opportunities. Scientific training should follow a holistic approach based on three pillars: (i) a scientific core curriculum, (ii) intracurricular research projects, and (iii) special research programs for students strongly interested in medical research.

Postgraduate Medical Trainees Understanding of Biostatistics: A Pre- and Post-Research Methodology Workshop Experience.

OBJECTIVE: To evaluate understanding of biostatistics among postgraduate medical trainees before and after biostatistics workshop. STUDY DESIGN: Quasi experimental study. PLACE AND DURATION OF STUDY: Regional Centre, Islamabad, College of Physicians and Surgeons Pakistan, from March to September 2017. METHODOLOGY: Two hundred and seventy postgraduate trainees were enrolled after taking informed consent. Structured questionnaire containing 21 multiple choice questions regarding understanding and application of biostatistics was given to all participants on the first and the last day of workshop and compared pre- and post-workshop by McNemar test of significance. SPSS version 21 was used for data analysis with p-value <0.05 as significant level. RESULTS: The response rate was 100%. Among these participants, males were 81 (30%) and females were 189 (70%), mean age was 28.5 ±2.5 years. One hundred and twenty-five (46%) postgraduate trainees were from Islamabad. Most of the doctors were in the first year (37%) and second year (57%) of their training. With total correct answers of 42.9% (preworkshop) and 57% (post-workshop), p-value was <0.001. CONCLUSION: Understanding regarding application of biostatistics in research among PGTs improved significantly and immediately after teaching biostatistics in research methodology workshop.