RESEARCH ARTICLE


Common Statistical and Research Design Problems in Manuscripts Submitted to High-Impact Public Health Journals



Alex H.S. Harris, Rachelle N. Reeder1, *, Jenny K. Hyun1
1 Center for Health Care Evaluation, VA Palo Alto Health Care System and Stanford University School of Medicine, 795 Willow Road (MPD-152), Menlo Park, CA 94025, USA
2 National Center for PTSD, VA Palo Alto Health Care System, 795 Willow Road, Menlo Park, CA 94025, USA


Article Metrics

CrossRef Citations:
5
Total Statistics:

Full-Text HTML Views: 178
Abstract HTML Views: 332
PDF Downloads: 341
Total Views/Downloads: 851
Unique Statistics:

Full-Text HTML Views: 117
Abstract HTML Views: 225
PDF Downloads: 273
Total Views/Downloads: 615



Creative Commons License
Submitted to High-Impact Public Health Journals Alex H.S. et al.; Licensee Bentham Open

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Center for Health Care Evaluation (MC:152), VA Palo Alto Health Care System, 795 Willow Road, Menlo Park, CA 94025, USA; Tel: 650-493-5000, ext. 27814; Fax: 650- 617-2690; E-mails: Rachelle.Reeder@va.gov


Abstract

Introduction:

Journal editors and statistical reviewers are often in the difficult position of catching statistical and research design problems after data have been collected and analyzed. The authors sought to learn from editors and reviewers of major public health journals what common statistical and design problems they find in submitted manuscripts and what they wished to communicate to authors regarding these issues.

Materials and Methodology:

Editors and statistical reviewers of 55 high-impact public health journals were surveyed to determine what statistical or design problems they encounter most often. The authors analyzed text responses using content analysis to identify major themes.

Results:

Editors and reviewers (n = 25) who handle manuscripts from 26 high impact public health journals responded to the survey. The most commonly cited problems included failure to adequately describe statistical models and map them onto research questions, inadequate consideration of sample size, poor control of confounding, and inappropriate reliance on parametric tests.

Conclusions:

The scientific quality of public health research and submitted reports could be greatly improved if researchers addressed frequently encountered methodological and analytic issues.