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Statistical Methods for Item Reduction in a Representative Lifestyle Questionnaire: Pilot Questionnaire Study.

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Reducing lifestyle questionnaire items using variance inflation factor (VIF) and factor analysis (FA) identified redundant sleep and stress questions. Employing multiple methods ensures robust item reduction for better respondent engagement.

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Area of Science:

  • Health Informatics
  • Psychometrics
  • Statistical Modeling

Background:

  • Item reduction in questionnaires enhances respondent engagement and reduces errors.
  • A posteriori validation of questionnaire items is often overlooked in healthcare.
  • Utilizing multiple methods for item reduction ensures robust and reliable results.

Purpose of the Study:

  • Compare item reduction results from variance inflation factor (VIF) and factor analysis (FA).
  • Analyze discrepancies between VIF and FA in a lifestyle questionnaire.
  • Evaluate the impact of different reduction methods on original questionnaire items.

Main Methods:

  • Lifestyle questionnaire developed from multiple sources, administered to 79 participants at risk for metabolic syndrome.
  • Item reduction performed using VIF and exploratory factor analysis (FA).
  • Data adequacy and sampling adequacy tests confirmed structural detection validity.

Main Results:

  • Both VIF and FA identified redundant sleep items (daily/weekly) and stress items (monthly).
  • VIF suggested greater item reduction for daily questions, while FA suggested greater reduction for weekly questions.
  • Adequacy tests consistently validated the item reduction findings.

Conclusions:

  • VIF and FA yield both overlapping and distinct results, highlighting the need for multiple item reduction approaches.
  • Significant redundancy exists in sleep-related items, suggesting the lifestyle questionnaire can be shortened.
  • Multi-method validation strengthens the reliability of item reduction in questionnaire design.