Literature DB >> 33585125

Trends in the Usage of Statistical Software and Their Associated Study Designs in Health Sciences Research: A Bibliometric Analysis.

Emad Masuadi1, Mohamud Mohamud2, Muhannad Almutairi3, Abdulaziz Alsunaidi3, Abdulmohsen K Alswayed3, Omar F Aldhafeeri3.   

Abstract

Background The development of statistical software in research has transformed the way scientists and researchers conduct their statistical analysis. Despite these advancements, it was not clear which statistical software is mainly used for which research design thereby creating confusion and uncertainty in choosing the right statistical tools. Therefore, this study aimed to review the trend of statistical software usage and their associated study designs in articles published in health sciences research. Methods This bibliometric analysis study reviewed 10,596 articles published in PubMed in three 10-year intervals (1997, 2007, and 2017). The data were collected through Google sheet and were analyzed using SPSS software. This study described the trend and usage of currently available statistical tools and the different study designs that are associated with them. Results Of the statistical software mentioned in the retrieved articles, SPSS was the most common statistical tool used (52.1%) in the three-time periods followed by SAS (12.9%) and Stata (12.6%). WinBugs was the least used statistical software with only 40(0.6%) of the total articles. SPSS was mostly associated with observational (61.1%) and experimental (65.3%) study designs. On the other hand, Review Manager (43.7%) and Stata (38.3%) were the most statistical software associated with systematic reviews and meta-analyses. Conclusion In this study, SPSS was found to be the most widely used statistical software in the selected study periods. Observational studies were the most common health science research design. SPSS was associated with observational and experimental studies while Review Manager and Stata were mostly used for systematic reviews and meta-analysis.
Copyright © 2021, Masuadi et al.

Entities:  

Keywords:  healthcare publications; pubmed; sas; spss; stata; statistical software; study design

Year:  2021        PMID: 33585125      PMCID: PMC7872865          DOI: 10.7759/cureus.12639

Source DB:  PubMed          Journal:  Cureus        ISSN: 2168-8184


  5 in total

1.  Association between study design and citation counts of articles published in the American Journal of Orthodontics and Dentofacial Orthopedics and Angle Orthodontist.

Authors:  Veerasathpurush Allareddy; Min Kyeong Lee; Andrea Shah; Satheesh Elangovan; Chin-Yu Lin
Journal:  Orthodontics (Chic.)       Date:  2012

2.  Guidelines for statistical reporting in articles for medical journals. Amplifications and explanations.

Authors:  J C Bailar; F Mosteller
Journal:  Ann Intern Med       Date:  1988-02       Impact factor: 25.391

3.  Study designs, use of statistical tests, and statistical analysis software choice in 2015: Results from two Pakistani monthly Medline indexed journals.

Authors:  Masood Ali Shaikh
Journal:  J Pak Med Assoc       Date:  2017-09       Impact factor: 0.781

4.  Study designs and statistical methods in the Journal of Family and Community Medicine: 1994-2010.

Authors:  Abdullah S Aljoudi
Journal:  J Family Community Med       Date:  2013-01

5.  Statistical software applications used in health services research: analysis of published studies in the U.S.

Authors:  Allard E Dembe; Jamie S Partridge; Laurel C Geist
Journal:  BMC Health Serv Res       Date:  2011-10-06       Impact factor: 2.655

  5 in total
  2 in total

1.  The protective role of statins in COVID-19 patients: a retrospective observational study.

Authors:  Srikanth Umakanthan; Sanjum Senthil; Stanley John; Mahesh K Madhavan; Jessica Das; Sonal Patil; Ragunath Rameshwaram; Ananya Cintham; Venkatesh Subramaniam; Madhusudan Yogi; Abhishek Bansal; Sumesh Achutham; Chandini Shekar; Vijay Murthy; Robbin Selvaraj
Journal:  Transl Med Commun       Date:  2021-09-25

2.  bp: Blood pressure analysis in R.

Authors:  John Schwenck; Naresh M Punjabi; Irina Gaynanova
Journal:  PLoS One       Date:  2022-09-09       Impact factor: 3.752

  2 in total

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