Aims of the study
The use of self-report or administered-by-the-interviewer questionnaires for detection of hazardous or harmful alcohol or psychotropic substance use, though not mandatory for fitness-to-drive assessment, is nevertheless widespread. Even though they may be affected by an expected bias linked to social desirability, they may provide data that are not impaired by the bias linked to the interpretation of the answers by the expert. The aim of this study was to design a questionnaire specifically oriented to medical fitness-to-drive assessment, usable for various psychotropic substances, available in several languages, and to investigate some psychometric properties.
Methods
A questionnaire consisting of 21 questions and translated into ten languages was administered to 112 individuals who underwent medical fitness-to-drive assessment (71 cases for alcohol, 60 men, 11 women, 22 for cannabis 16 men, 6 women, and 19 cases for drugs other than cannabis, 15 men, 4 women. 58 questionnaires were filled in according to an administered-by-the-interviewer modality, 54 questionnaires were filled in according to a self-report delayed modality.
Results
The questionnaire designed for this study showed satisfactory face-validity, test-retest reliability, acceptability, and construct validity. Compared to validated questionnaires currently used in medical fitness-to-drive assessment, the designed questionnaire revealed modest advantages in terms of sensitivity and specificity. However, in comparison to validated questionnaires, the designed questionnaire showed some not negligible advantages in terms of greater acceptability, greater ease to fill in, and greater suitability in terms of understandability and multiculturalism.
Conclusions
Medical fitness-to-drive assessment in multicultural societies requires the use of cross- cultural and appropriate tools, thus allowing people who undergo such assessments to provide reliable information regardless of their mother tongue. Providing a questionnaire available in different languages might contribute to avoid disparities and ensure optimal assessment setting.