There is little published evidence on what doctors do in their work that requires probability and statistics, yet the General Medical Council (GMC) requires new doctors to have these skills. This study investigated doctors' use of and attitudes to probability and statistics with a view to informing undergraduate teaching.An email questionnaire was sent to 473 clinicians with an affiliation to the University of East Anglia's Medical School.Of 130 respondents approximately 90 per cent of doctors who performed each of the following activities found probability and statistics useful for that activity: accessing clinical guidelines and evidence summaries, explaining levels of risk to patients, assessing medical marketing and advertising material, interpreting the results of a screening test, reading research publications for general professional interest, and using research publications to explore non-standard treatment and management options.Seventy-nine per cent (103/130, 95 per cent CI 71 per cent, 86 per cent) of participants considered probability and statistics important in their work. Sixty-three per cent (78/124, 95 per cent CI 54 per cent, 71 per cent) said that there were activities that they could do better or start doing if they had an improved understanding of these areas and 74 of these participants elaborated on this. Themes highlighted by participants included: being better able to critically evaluate other people's research; becoming more research-active, having a better understanding of risk; and being better able to explain things to, or teach, other people.Our results can be used to inform how probability and statistics should be taught to medical undergraduates and should encourage today's medical students of the subjects' relevance to their future careers.
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http://dx.doi.org/10.1002/sim.3608 | DOI Listing |
PLoS One
January 2025
Department of Medicine Epidemiology and Population Sciences, Baylor College of Medicine, Houston, Texas, United States of America.
Objectives: It is significant to know how much early detection and screening could reduce the proportion of occult metastases and benefit NSCLC patients.
Methods: We used previously designed and validated mathematical models to obtain the characteristics of LC in the population including undetectable metastases at the time of diagnosis. The survival was simulated using the survival functions from Surveillance, Epidemiology and End Results (SEER) data stratified by stage.
PLoS One
January 2025
Carrera de Medicina Humana, Universidad Científica del Sur, Lima, Perú.
Objective: To investigate gender disparities in applications and admissions to the medical residency programs in Peru, focusing on differences in application and admission proportions between male and female.
Methods: We conducted a cross-sectional study to assess the proportions of female applicants and admissions to medical residency programs in Peru from 2016 to 2023. Bayesian multilevel linear models were employed, incorporating random intercepts and slopes by specialty to account for variability across specialties.
PLoS One
January 2025
Department of Mathematics, College of Science, University of Hafr Al Batin, Hafar Al-Batin, Saudi Arabia.
In this paper, we propose a new flexible statistical distribution, the Topp-Leone Exponentiated Chen distribution, to model real-world data effectively, with a particular focus on COVID-19 data. The motivation behind this study is the need for a more flexible distribution that can capture various hazard rate shapes (e.g.
View Article and Find Full Text PDFJAMA Health Forum
January 2025
Department of Health Policy and Management, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania.
Importance: 2021 Advance child tax credit (ACTC) monthly payments were associated with reduced US child poverty rates; however, policymakers have expressed concerns that permanent adoption would increase parental substance use.
Objective: To assess whether 2021 ACTC monthly payments were temporally associated with changes in substance use among parents compared with adults without children.
Design, Setting, And Participants: The primary sample included adults aged 18 to 64 years who responded to the National Survey on Drug Use and Health in 2021.
Bull Math Biol
January 2025
Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, 20899, USA.
Immune events such as infection, vaccination, and a combination of the two result in distinct time-dependent antibody responses in affected individuals. These responses and event prevalence combine non-trivially to govern antibody levels sampled from a population. Time-dependence and disease prevalence pose considerable modeling challenges that need to be addressed to provide a rigorous mathematical underpinning of the underlying biology.
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