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Related Experiment Videos

How unclear terms affect survey data.

F J Fowler1

  • 1Center for Survey Research, University of Massachusetts, Boston.

Public Opinion Quarterly
|February 2, 1993
PubMed
Summary
This summary is machine-generated.

Clear survey questions are crucial for accurate data. This study shows that poorly defined terms in health surveys lead to biased results, emphasizing the need for term clarification to reduce systematic error.

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Area of Science:

  • Survey methodology
  • Health research
  • Measurement error

Background:

  • Writing clear survey questions is a goal, but ensuring consistent understanding of key terms is not standard practice.
  • Researchers often assume ambiguity in survey questions won't significantly impact results.
  • National health surveys may contain poorly defined terms, potentially affecting data reliability.

Purpose of the Study:

  • To investigate the impact of poorly defined terms in survey questions on data estimates.
  • To demonstrate how clarifying key terms can alter survey results.
  • To highlight the importance of evaluating and defining terms in survey instruments.

Main Methods:

  • Seven questions from national health surveys were selected.
  • Special pretest procedures were used to assess respondent understanding of key terms.

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  • Questions were revised to clarify ambiguous terms, and estimates were compared.

    • Main Results:

    • Pretesting revealed that several questions contained poorly defined terms.
    • Revising questions to clarify terms led to significantly different estimates.
    • This indicates that unclear terms can introduce systematic bias into survey data.

    Conclusions:

    • Ambiguous terms in survey questions can lead to biased estimates.
    • Evaluating survey questions for term clarity and defining unclear terms are essential steps.
    • These practices can effectively reduce systematic error in survey measurement and improve data quality.