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.

While different definitions for the diagnosis of metabolic syndrome (MetS) have been proposed, their applicability brings confusion about which criteria should be used in clinical practice. This was an observational cross-sectional study conducted during October 2008. in 3 university hospital centers in the north, midst and south of the Serbia. 1715 patients were recruited from outpatient clinical practice and primary health care offices: 37% males and 63% females, aged 34-80 years. To evaluate the impact of different criteria in discriminating high risk population for coronary artery disease (CAD) we used NCEP-ATP III, AHA/NHLBI and IDF definitions. 21,7% (373) from the patients included in the study sustained CAD. The prevalence of MetS in the CAD group was 84,7%, 86,1% and 82,0%, respectively, compared with 58,3%, 60,6% and 61,2% in the control group (p<0.0001). ROC curves ploted by the probabilities for CAD calculated in the logistic models for each definition (adjusted for age, sex, smoking and educational status) indicated that NCEP-ATP III and NHLBI-AHA definitions had a better predictive accuracy compared with IDF (p=0,006 and p=0,016, respectively). When the waist girth is introduced in NCEP-ATP III and NHLBI-AHA definitions as obligatory, this distinction was lost. The NCEP-ATP III and AHA/NHLBI definition is more suitable for discrimination of MetS diagnosis, than the later proposed IDF definition in the subjects of the given population. Inclusion of waist circumference as obligatory criteria failed to show increase in predictive accuracy for CAD.