How to verify the reliability and validity of survey tools?

Reliability assesses measurement consistency, while validity determines if the tool accurately measures the intended construct. Verification ensures the survey yields trustworthy and meaningful data. Key principles involve distinct methods. Reliability is typically measured using internal consistency (Cronbach's alpha) for multi-item scales, test-retest correlation for stability over time, or inter-rater reliability when multiple coders exist. Validity verification employs content validity (expert review of item relevance and coverage), criterion validity (correlation with established measures), and construct validity (confirmatory factor analysis to test theoretical structure). Essential conditions include clear operational definitions of constructs, a sufficiently large representative sample, appropriate statistical methods, and minimizing response biases during survey design and administration. Implement verification sequentially. First, define constructs clearly. Next, pretest the survey for clarity. Then, collect pilot data from the target population. Analyze pilot data using statistical techniques: calculate internal consistency for reliability; employ exploratory/confirmatory factor analysis and correlations for construct and criterion validity. Refine items based on analysis. Full-scale data collection follows. Results are invalid without demonstrating adequate reliability and validity coefficients.