Literature DB >> 19452567

Do doctors need statistics? Doctors' use of and attitudes to probability and statistics.

Louise Swift1, Susan Miles, Gill M Price, Lee Shepstone, Sam J Leinster.   

Abstract

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. Copyright 2009 John Wiley & Sons, Ltd.

Entities:  

Mesh:

Year:  2009        PMID: 19452567     DOI: 10.1002/sim.3608

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  13 in total

1.  Principles for the ethical analysis of clinical and translational research.

Authors:  Jonathan A L Gelfond; Elizabeth Heitman; Brad H Pollock; Craig M Klugman
Journal:  Stat Med       Date:  2011-07-12       Impact factor: 2.373

2.  Biostatistics Faculty and NIH Awards at U.S. Medical Schools.

Authors:  Guangxiang Zhang; John J Chen
Journal:  Am Stat       Date:  2015-02       Impact factor: 8.710

3.  Familiarity of physicians, translational researchers, nurses, and other health professionals with evidence-based medicine terms and resources.

Authors:  Donatella Ugolini; Georgia Casanova; Marcello Ceppi; Francesca Mattei; Monica Neri
Journal:  J Cancer Educ       Date:  2014-09       Impact factor: 2.037

4.  Statistics teaching in medical school: opinions of practising doctors.

Authors:  Susan Miles; Gill M Price; Louise Swift; Lee Shepstone; Sam J Leinster
Journal:  BMC Med Educ       Date:  2010-11-04       Impact factor: 2.463

5.  Application of biostatistics in research by teaching faculty and final-year postgraduate students in colleges of modern medicine: A cross-sectional study.

Authors:  Ad Gore; Yr Kadam; Pv Chavan; Gb Dhumale
Journal:  Int J Appl Basic Med Res       Date:  2012-01

6.  Factors influencing health professions students' use of computers for data analysis at three Ugandan public medical schools: a cross-sectional survey.

Authors:  Ian G Munabi; William Buwembo; Francis Bajunirwe; David Lagoro Kitara; Ruberwa Joseph; Kawungezi Peter; Celestino Obua; John Quinn; Erisa S Mwaka
Journal:  BMC Res Notes       Date:  2015-02-25

7.  A nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support.

Authors:  Brian Connolly; K Bretonnel Cohen; Daniel Santel; Ulya Bayram; John Pestian
Journal:  BMC Bioinformatics       Date:  2017-08-07       Impact factor: 3.169

Review 8.  Foundational Statistical Principles in Medical Research: A Tutorial on Odds Ratios, Relative Risk, Absolute Risk, and Number Needed to Treat.

Authors:  Thomas F Monaghan; Syed N Rahman; Christina W Agudelo; Alan J Wein; Jason M Lazar; Karel Everaert; Roger R Dmochowski
Journal:  Int J Environ Res Public Health       Date:  2021-05-25       Impact factor: 3.390

9.  Attitudes towards statistics of graduate entry medical students: the role of prior learning experiences.

Authors:  Ailish Hannigan; Avril C Hegarty; Deirdre McGrath
Journal:  BMC Med Educ       Date:  2014-04-04       Impact factor: 2.463

10.  Critical appraisal of RCTs by 3rd year undergraduates after short courses in EBM compared to expert appraisal.

Authors:  B Buchberger; J T Mattivi; C Schwenke; C Katzer; H Huppertz; J Wasem
Journal:  GMS J Med Educ       Date:  2018-05-15
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.