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Strategies and Lessons Learned During Cleaning of Data From Research Panel Participants: Cross-sectional Web-Based Health Behavior Survey Study.

Mariana ArevaloNaomi C BrownsteinJunmin WhitingCathy D MeadeClement K GwedeSusan T VadaparampilKristin J TilleryJessica Yasmine IslamAnna R GiulianoShannon M Christy
Published in: JMIR formative research (2022)
Examining data integrity and promoting transparency of data cleaning reporting is imperative for web-based survey research. Ensuring a high quality of data both prior to and following data collection is important. Our systematic approach helped eliminate records flagged as being of questionable quality. Data cleaning and management procedures should be reported more frequently, and systematic approaches should be adopted as standards of good practice in this type of research.
Keyphrases
  • electronic health record
  • cross sectional
  • big data
  • healthcare
  • primary care
  • public health
  • emergency department
  • machine learning
  • quality improvement
  • artificial intelligence
  • climate change