Using risk of bias domains to identify opportunities for improvement in food- and nutrition-related research: An evaluation of research type and design, year of publication, and source of funding

Autor: Patricia Splett, Mei Chun Chung, James Scott Parrott, E. F. Myers, D. Handu
Rok vydání: 2018
Předmět:
Research Report
Research design
Drug Research and Development
Systematic Reviews
Science Policy
Clinical Research Design
Nutritional Sciences
Cross-sectional study
Nutritional Status
lcsh:Medicine
Research and Analysis Methods
Logistic regression
Research Funding
law.invention
03 medical and health sciences
0302 clinical medicine
Randomized controlled trial
law
Medicine and Health Sciences
Humans
Clinical Trials
030212 general & internal medicine
Government Funding of Science
lcsh:Science
Research Integrity
Nutrition
Retrospective Studies
Multinomial logistic regression
Pharmacology
Multidisciplinary
lcsh:R
Biology and Life Sciences
Research Assessment
Randomized Controlled Trials
Critical appraisal
Cross-Sectional Studies
Systematic review
Research Design
Food
lcsh:Q
Observational study
Clinical Medicine
Psychology
Publication Bias
030217 neurology & neurosurgery
Research Article
Demography
Zdroj: PLoS ONE, Vol 13, Iss 7, p e0197425 (2018)
PLoS ONE
ISSN: 1932-6203
Popis: Purpose This retrospective cross-sectional study aimed to identify opportunities for improvement in food and nutrition research by examining risk of bias (ROB) domains. Methods Ratings were extracted from critical appraisal records for 5675 studies used in systematic reviews conducted by three organizations. Variables were as follows: ROB domains defined by the Cochrane Collaboration (Selection, Performance, Detection, Attrition, and Reporting), publication year, research type (intervention or observation) and specific design, funder, and overall quality rating (positive, neutral, or negative). Appraisal instrument questions were mapped to ROB domains. The kappa statistic was used to determine consistency when multiple ROB ratings were available. Binary logistic regression and multinomial logistic regression were used to predict overall quality and ROB domains. Findings Studies represented a wide variety of research topics (clinical nutrition, food safety, dietary patterns, and dietary supplements) among 15 different research designs with a balance of intervention (49%) and observation (51%) types, published between 1930 and 2015 (64% between 2000–2009). Duplicate ratings (10%) were consistent (κ = 0.86–0.94). Selection and Performance domain criteria were least likely to be met (57.9% to 60.1%). Selection, Detection, and Performance ROB ratings predicted neutral or negative quality compared to positive quality (p
Databáze: OpenAIRE
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