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      The Importance of Medical Students' Attitudes Regarding Cognitive Competence for Teaching Applied Statistics: Multi-Site Study and Meta-Analysis

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          Abstract

          Background

          The scientific community increasingly is recognizing the need to bolster standards of data analysis given the widespread concern that basic mistakes in data analysis are contributing to the irreproducibility of many published research findings. The aim of this study was to investigate students’ attitudes towards statistics within a multi-site medical educational context, monitor their changes and impact on student achievement. In addition, we performed a systematic review to better support our future pedagogical decisions in teaching applied statistics to medical students.

          Methods

          A validated Serbian Survey of Attitudes Towards Statistics (SATS-36) questionnaire was administered to medical students attending obligatory introductory courses in biostatistics from three medical universities in the Western Balkans. A systematic review of peer-reviewed publications was performed through searches of Scopus, Web of Science, Science Direct, Medline, and APA databases through 1994. A meta-analysis was performed for the correlation coefficients between SATS component scores and statistics achievement. Pooled estimates were calculated using random effects models.

          Results

          SATS-36 was completed by 461 medical students. Most of the students held positive attitudes towards statistics. Ability in mathematics and grade point average were associated in a multivariate regression model with the Cognitive Competence score, after adjusting for age, gender and computer ability. The results of 90 paired data showed that Affect, Cognitive Competence, and Effort scores demonstrated significant positive changes. The Cognitive Competence score showed the largest increase (M = 0.48, SD = 0.95). The positive correlation found between the Cognitive Competence score and students’ achievement (r = 0.41; p<0.001), was also shown in the meta-analysis (r = 0.37; 95% CI 0.32–0.41).

          Conclusion

          Students' subjective attitudes regarding Cognitive Competence at the beginning of the biostatistics course, which were directly linked to mathematical knowledge, affected their attitudes at the end of the course that, in turn, influenced students' performance. This indicates the importance of positively changing not only students’ cognitive competency, but also their perceptions of gained competency during the biostatistics course.

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          Most cited references8

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          Testing a tool for assessing the risk of bias for nonrandomized studies showed moderate reliability and promising validity.

          To develop and validate a new risk-of-bias tool for nonrandomized studies (NRSs). We developed the Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS). A validation process with 39 NRSs examined the reliability (interrater agreement), validity (the degree of correlation between the overall assessments of RoBANS and Methodological Index for Nonrandomized Studies [MINORS], obtained by plotting the overall risk of bias relative to effect size and funding source), face validity with eight experts, and completion time for the RoBANS approach. RoBANS contains six domains: the selection of participants, confounding variables, the measurement of exposure, the blinding of the outcome assessments, incomplete outcome data, and selective outcome reporting. The interrater agreement of the RoBANS tool except the measurement of exposure and selective outcome reporting domains ranged from fair to substantial. There was a moderate correlation between the overall risks of bias determined using RoBANS and MINORS. The observed differences in effect sizes and funding sources among the assessed studies were not correlated with the overall risk of bias in these studies. The mean time required to complete RoBANS was approximately 10 min. The external experts who were interviewed evaluated RoBANS as a "fair" assessment tool. RoBANS shows moderate reliability, promising feasibility, and validity. The further refinement of this tool and larger validation studies are required. Copyright © 2013 Elsevier Inc. All rights reserved.
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            Reinventing Biostatistics Education for Basic Scientists

            Numerous studies demonstrating that statistical errors are common in basic science publications have led to calls to improve statistical training for basic scientists. In this article, we sought to evaluate statistical requirements for PhD training and to identify opportunities for improving biostatistics education in the basic sciences. We provide recommendations for improving statistics training for basic biomedical scientists, including: 1. Encouraging departments to require statistics training, 2. Tailoring coursework to the students’ fields of research, and 3. Developing tools and strategies to promote education and dissemination of statistical knowledge. We also provide a list of statistical considerations that should be addressed in statistics education for basic scientists.
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              Attitudes towards statistics of graduate entry medical students: the role of prior learning experiences

              Background While statistics is increasingly taught as part of the medical curriculum, it can be an unpopular subject and feedback from students indicates that some find it more difficult than other subjects. Understanding attitudes towards statistics on entry to graduate entry medical programmes is particularly important, given that many students may have been exposed to quantitative courses in their previous degree and hence bring preconceptions of their ability and interest to their medical education programme. The aim of this study therefore is to explore, for the first time, attitudes towards statistics of graduate entry medical students from a variety of backgrounds and focus on understanding the role of prior learning experiences. Methods 121 first year graduate entry medical students completed the Survey of Attitudes toward Statistics instrument together with information on demographics and prior learning experiences. Results Students tended to appreciate the relevance of statistics in their professional life and be prepared to put effort into learning statistics. They had neutral to positive attitudes about their interest in statistics and their intellectual knowledge and skills when applied to it. Their feelings towards statistics were slightly less positive e.g. feelings of insecurity, stress, fear and frustration and they tended to view statistics as difficult. Even though 85% of students had taken a quantitative course in the past, only 24% of students described it as likely that they would take any course in statistics if the choice was theirs. How well students felt they had performed in mathematics in the past was a strong predictor of many of the components of attitudes. Conclusion The teaching of statistics to medical students should start with addressing the association between students’ past experiences in mathematics and their attitudes towards statistics and encouraging students to recognise the difference between the two disciplines. Addressing these issues may reduce students’ anxiety and perception of difficulty at the start of their learning experience and encourage students to engage with statistics in their future careers.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 October 2016
                2016
                : 11
                : 10
                : e0164439
                Affiliations
                [1 ]Institute for Medical Statistics and Informatics, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
                [2 ]Department of Internal Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, United States of America
                [3 ]Department of Primary Health Care and Public Health, Faculty of Medicine, University of East Sarajevo, Foca, Bosnia and Herzegovina
                [4 ]Department of Public Health, Medical Faculty, University of Pristina, Kosovska Mitrovica, Serbia
                University of Westminster, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: NMM DS.

                • Data curation: NMM SM JML GT ZB MS AC MG MK AI DS.

                • Formal analysis: NMM SM JML GT ZB MS NVM DS.

                • Funding acquisition: NMM SM DS.

                • Investigation: NMM SM JML GT ZB MS AC MG MK AI DS.

                • Methodology: NMM SM GT ZB DS.

                • Project administration: NMM SM MK AI DS.

                • Resources: NMM SM JML GT ZB MS AC MG MK AI DS.

                • Software: NMM GT ZB DS.

                • Supervision: NMM GT DS.

                • Validation: NMM SM JML GT ZB MS NVM DS.

                • Visualization: NMM JML ZB DS.

                • Writing – original draft: NMM SM JML ZB NVM DS.

                • Writing – review & editing: NMM SM JML GT ZB MS NVM AC MG MK AI DS.

                Article
                PONE-D-16-22373
                10.1371/journal.pone.0164439
                5072734
                27764123
                9fcff065-12c8-4ec3-9664-94ecdfd07a47
                © 2016 Milic et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 June 2016
                : 26 September 2016
                Page count
                Figures: 2, Tables: 4, Pages: 13
                Funding
                The authors have no support or funding to report.
                Categories
                Research Article
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Research and Analysis Methods
                Research Assessment
                Systematic Reviews
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                Computer and Information Sciences
                Computers
                Research and Analysis Methods
                Database and Informatics Methods
                Database Searching
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Biostatistics
                Social Sciences
                Sociology
                Education
                Schools
                Universities
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognition
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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