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Related Experiment Videos

Establishing drug use questionnaire concurrent validity: methodological considerations.

P D Sarvela1

  • 1College of Education, Southern Illinois University-Carbondale 62901.

Health Values
|October 6, 1990
PubMed
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Evaluating drug education programs requires valid data. Self-report questionnaires, when validated against urinalysis, can provide reliable data for effective program evaluation.

Area of Science:

  • Health Education
  • Drug Use Research
  • Program Evaluation

Background:

  • Comprehensive drug education programs are increasingly called for, presenting opportunities for health education specialists.
  • However, the effectiveness of many existing drug education programs is questionable, necessitating thorough evaluation.
  • High-quality program evaluations depend on valid data collection procedures.

Purpose of the Study:

  • To assess the validity of self-report questionnaires in drug use studies.
  • To determine if urinalysis-based concurrent validity studies can enhance confidence in self-report data.
  • To inform best practices for evaluating drug education programs.

Main Methods:

  • Utilizing self-report questionnaires as a common data collection method in drug use studies.

Related Experiment Videos

  • Conducting urinalysis-based concurrent validity studies to assess questionnaire accuracy.
  • Comparing self-report data with objective laboratory test results.

    • Main Results:

    • Self-report questionnaires can achieve validity comparable to laboratory tests when validated.
    • Urinalysis-based validation increases investigator confidence in self-report questionnaire data.
    • This validation method supports the use of self-report questionnaires in drug education program evaluations.

    Conclusions:

    • Validated self-report questionnaires are a reliable tool for collecting data in drug use research.
    • Urinalysis-based concurrent validity studies are crucial for ensuring data accuracy.
    • Effective evaluation of drug education programs can be supported by robust, validated data collection methods.