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Pesticide applicators questionnaire content validation: A fuzzy delphi method.

S K Manakandan1, I Rosnah2, J Mohd Ridhuan3

  • 1The National University of Malaysia, UKM Medical Centre, Department of Community Health, Occupational Health Unit, Kuala Lumpur, Malaysia. drrose@ppukm.ukm.edu.my.

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Summary
This summary is machine-generated.

The Fuzzy Delphi method (FDM) successfully achieved expert consensus on questionnaire items for noise and chemical exposure, refining survey content for occupational health studies.

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Area of Science:

  • Occupational and Environmental Health
  • Survey Methodology
  • Psychometrics

Background:

  • Selecting appropriate survey questionnaire items is critical for study validity.
  • Irrelevant items can mislead research, while omitting key items compromises quality.
  • The Fuzzy Delphi method (FDM) offers a scientific approach to achieve expert consensus on item appropriateness.

Purpose of the Study:

  • To obtain expert consensus on the suitability of pre-selected questionnaire items.
  • To refine survey content related to noise and chemical exposure in occupational health.
  • To enhance the quality and relevance of survey instruments through expert validation.

Main Methods:

  • A panel of sixteen experts in occupational and environmental health participated.
  • A questionnaire with six constructs (knowledge, attitude, practice for noise and chemical exposure) was developed.
  • The Fuzzy Delphi method, utilizing Triangular Fuzzy Numbers and Defuzzification, was applied for validation.

Main Results:

  • A 100% expert response rate was achieved with high average Likert scores.
  • All six constructs met the initial FDM prerequisite (d ≤ 0.2).
  • Seven items (12% of total) were discarded due to insufficient expert consensus (<75%) in specific constructs.

Conclusions:

  • Expert consensus was successfully obtained using the Fuzzy Delphi method for the questionnaire.
  • The refined questionnaire is suitable for further construct validation.
  • FDM effectively reduced ambiguity and discrepancy in expert opinions, enhancing item selection quality.