Several factors can threaten data integrity in epidemiological research:
Human Error: Data entry mistakes, mislabeling of samples, and errors in data coding can introduce inaccuracies. Technical Issues: Software bugs, hardware failures, and data corruption during storage or transmission can compromise data integrity. Bias: Selection bias, information bias, and confounding can all distort the data and lead to incorrect conclusions. Fraud: Deliberate manipulation of data for personal or professional gain undermines the trustworthiness of research findings.
