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

BMC Res Notes. 2015 Feb 25:8:54. doi: 10.1186/s13104-015-1013-3.

Abstract

Background: Effective utilization of computers and their applications in medical education and research is of paramount importance to students. The objective of this study was to determine the association between owning a computer and use of computers for research data analysis and the other factors influencing health professions students' computer use for data analysis.

Methods: We conducted a cross sectional study among undergraduate health professions students at three public universities in Uganda using a self-administered questionnaire. The questionnaire was composed of questions on participant demographics, students' participation in research, computer ownership, and use of computers for data analysis. Descriptive and inferential statistics (uni-variable and multi- level logistic regression analysis) were used to analyse data. The level of significance was set at 0.05.

Results: Six hundred (600) of 668 questionnaires were completed and returned (response rate 89.8%). A majority of respondents were male (68.8%) and 75.3% reported owning computers. Overall, 63.7% of respondents reported that they had ever done computer based data analysis. The following factors were significant predictors of having ever done computer based data analysis: ownership of a computer (adj. OR 1.80, p = 0.02), recently completed course in statistics (Adj. OR 1.48, p =0.04), and participation in research (Adj. OR 2.64, p <0.01).

Conclusions: Owning a computer, participation in research and undertaking courses in research methods influence undergraduate students' use of computers for research data analysis. Students are increasingly participating in research, and thus need to have competencies for the successful conduct of research. Medical training institutions should encourage both curricular and extra-curricular efforts to enhance research capacity in line with the modern theories of adult learning.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Computers / statistics & numerical data*
  • Female
  • Health Personnel / statistics & numerical data*
  • Humans
  • Logistic Models
  • Male
  • Schools, Medical / statistics & numerical data*
  • Statistics as Topic*
  • Students, Medical / statistics & numerical data*
  • Uganda
  • Universities