Design and implementation of data quality controls in the EQ-DAPHNIE study: insights from the pilot phase and 15-country analysis

EQ-DAPHNIE研究中数据质量控制的设计与实施:来自试点阶段和15个国家分析的启示

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Abstract

OBJECTIVE: The EQ-DAPHNIE (EuroQol Data for Assessment of Population Health Needs and Instrument Evaluation) project is a large, multi-country survey initiative designed to generate population norms and enable comparative research using self-reported health measures. This paper describes the quality control processes and summarizes data quality metrics from the United Kingdom (UK) pilot and full implementation across 15 countries. METHODS: Representative samples were recruited via Dynata, an online survey panel provider, using quota sampling by age, sex, income, community setting, and language (where applicable). The UK pilot (n = 3012) informed survey refinements ahead of full rollout (n = 68,411). Quality metrics included completion rates, bot detection, speeding, missing data, outliers, and quota achievement. RESULTS: Across countries, response rates ranged from 80.1 to 100%, with completion rates varying widely (22.9% in Brazil to 60.8% in Japan; average 42.4%). Bot exclusions averaged 3.0%, peaking in China (11.7%). Speeding was low (0.3% average), and duplicate records were rare. Completion times ranged from 18.3 (France) to 31.4 min (New Zealand). Missing data varied substantially (0.0-48.7%), with Japan and Spain showing the least. Quota fulfillment ranged from 68.7 to 98.6%. Consistency checks showed strong agreement for repeated items-marital status (92.8-98.9%) and age (92.3-98.7%). CONCLUSIONS: The quality control measures implemented throughout the EQ-DAPHNIE project effectively addressed common issues such as bot responses, speeding, and missing data, resulting in generally high-quality and representative datasets. However, variability across countries underscores the need to account for quality indicators when using the data for norm-setting or cross-country comparisons.

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