Evidence map›Paper›PMID 35854710›Full record

ArticleInternational journal of translational medical research and public health2022

Building Physician-Scientist Skills in R Programming:A Short Workshop Report.

Muktar H Aliyu, Mahmoud U Sani, Donna J Ingles, Fatima I Tsiga-Ahmed, Baba M Musa, M Shannon Byers, Deepa Dongarwar, Hamisu M Salihu, C William Wester

Abstract read
In one paragraph

Article in International journal of translational medical research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Muktar H AliyuVanderbilt Institute for Global Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Mahmoud U SaniBayero University, Kano, Nigeria.
Donna J InglesVanderbilt University, Nashville, TN, USA.
Fatima I Tsiga-AhmedBayero University & Aminu Kano Teaching Hospital, Kano, Nigeria.
Baba M MusaAfrican Center of Excellence for Population Health and Policy, Bayero University, Kano, Nigeria.
M Shannon ByersVanderbilt Institute for Global Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Deepa DongarwarBaylor College of Medicine, Department of Family and Community Medicine, Houston, Texas, USA.
Hamisu M SalihuBaylor College of Medicine, Department of Family and Community Medicine, Houston, Texas, USA.
C William WesterVanderbilt Institute for Global Health, Vanderbilt University Medical Center, Nashville, TN, USA.

Funding

Vanderbilt-Nigeria Building Research Capacity in HIV and Non-communicable Diseases (NCDs) (V-BRCH) 2D43TW011544 · FIC · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Aishatu Adamu, Muktar Hassan Aliyu · 2020 to 2026
$2.1M
Vanderbilt-Nigeria Biostatistics Training Program (VN-BioStat)D43TW012268 · FIC · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Muktar Hassan Aliyu, Nafiu Hussaini · 2022 to 2026
$1.5M
FIC NIH HHS D43 TW011544FIC NIH HHS D43 TW012268
6 · The paper itself

Abstract

Introduction: Statistical analysis programs require coding experience and a basic understanding of programming, skills which are not taught as part of medical school or residency curricula. Methods: We conducted a five-day course for early-career Nigerian physician-scientists interested in learning common statistical tests and acquiring R programming skills. The workshop included didactic presentations, small group learning activities, and interactive discussions. A baseline questionnaire captured participant demographics and solicited participants' level of confidence in understanding/performing common statistical tests. REDCap questionnaires were emailed to obtain feedback on educational format and content. A post-workshop assessment covered participants' overall impression of the program. Results: A total of 23 participants attended the program. Most participants were male (n=14, 60.9%) and at an early stage in their career (assistant professor, n=20, 87.0%). Approximately 70% of respondents indicated having received some prior training in statistics. The proportion of participants without experience using R and SAS software (90% and 85%, respectively) was greater than the corresponding proportions for Stata (55%) and SPSS (20%). Prior to the workshop, most respondents expressed being "not at all confident" in performing one-way ANOVA (60%), logistic regression (68%), simple linear regression (60%), and McNemar's test (80%). There was a statistically significant post-workshop improvement in the level of confidence in understanding and performing common statistical tests. The course was rated on a 0-100 scale as "moderately difficult" (mean ± SD: 51.7 ± 19.5). Most participants felt comfortable in putting the knowledge learned into practice (82.2 ± 17.1). Conclusion and Public Health Implications: Introductory R can be taught to junior physician-scientists in resource-limited settings and can inform the development and implementation of similar training initiatives in analogous settings.

Indexed as

Low- and Middle-Income CountriesPhysician-ScientistsR ProgrammingStatistical Analysis Training

Identifiers

PMID35854710
PMCPMC9289956

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.