Refine
Document Type
- Article (3)
Language
- English (3)
Has Fulltext
- yes (3)
Is part of the Bibliography
- no (3)
Keywords
- Agreement (1)
- Bland-Altman Plots (1)
- Measurement (1)
- Method-comparison studies (1)
- R project for statistical computing (1)
- Reliability (1)
- Validity (1)
- data quality (1)
- data quality monitoring (1)
- data reporting (1)
Institute
Publisher
- BioMed Central (BMC) (1)
- MDPI (1)
- Nature Publishing Group (1)
Data quality assessments (DQA) are necessary to ensure valid research results. Despite the growing availability of tools of relevance for DQA in the R language, a systematic comparison of their functionalities is missing. Therefore, we review R packages related to data quality (DQ) and assess their scope against a DQ framework for observational health studies. Based on a systematic search, we screened more than 140 R packages related to DQA in the Comprehensive R Archive Network. From these, we selected packages which target at least three of the four DQ dimensions (integrity, completeness, consistency, accuracy) in a reference framework. We evaluated the resulting 27 packages for general features (e.g., usability, metadata handling, output types, descriptive statistics) and the possible assessment’s breadth. To facilitate comparisons, we applied all packages to a publicly available dataset from a cohort study. We found that the packages’ scope varies considerably regarding functionalities and usability. Only three packages follow a DQ concept, and some offer an extensive rule-based issue analysis. However, the reference framework does not include a few implemented functionalities, and it should be broadened accordingly. Improved use of metadata to empower DQA and user-friendliness enhancement, such as GUIs and reports that grade the severity of DQ issues, stand out as the main directions for future developments.
Background
Multimedia multi-device measurement platforms may make the assessment of prevention-related medical variables with a focus on cardiovascular outcomes more attractive and time-efficient. The aim of the studies was to evaluate the reliability (Study 1) and the measurement agreement with a cohort study (Study 2) of selected measures of such a device, the Preventiometer.
Methods
In Study 1 (N = 75), we conducted repeated measurements in two Preventiometers for four examinations (blood pressure measurement, pulse oximetry, body fat measurement, and spirometry) to analyze their agreement and derive (retest-)reliability estimates. In Study 2 (N = 150), we compared somatometry, blood pressure, pulse oximetry, body fat, and spirometry measurements in the Preventiometer with corresponding measurements used in the population-based Study of Health in Pomerania (SHIP) to evaluate measurement agreement.
Results
Intraclass correlations coefficients (ICCs) ranged from .84 to .99 for all examinations in Study 1. Whereas bias was not an issue for most examinations in Study 2, limits of agreement for most examinations were very large compared to results of similar method comparison studies.
Conclusion
We observed a high retest-reliability of the assessed clinical examinations in the Preventiometer. Some disagreements between Preventiometer and SHIP examinations can be attributed to procedural differences in the examinations. Methodological and technical improvements are recommended before using the Preventiometer in population-based research.