Pedestrian road crossing behavior (PEROB): Development and psychometric evaluation

ABSTRACT

Objective: The aim of this study was to develop a theory-based questionnaire to measure road crossing attitudes and potentially risky pedestrian behavior.

Methods: A cross-sectional validation study was carried out on a total sample of 380 young adults aged 18 to 25 years who live in Tehran, Iran. Data were collected from January 27 to May 20, 2015, using a self-administered structured pool of 76 items that was developed from research on the theory of planned behavior. A panel of subject-matter experts evaluated the items for content validity index and content validity ratio, and the questionnaire was pretested. Exploratory factor analysis (EFA) was performed to test construct validity. The Cronbach's alpha coefficient and intraclass correlation coefficient (ICC) analyses were done to assess internal consistency and stability of the scale.

Results: From the initial 76 items, 38 items were found to be appropriate for assessing the pedestrian road crossing behavior (PEROB) of young adults in Tehran. A 9-factor solution revealed an exploratory factor analysis that jointly accounted for 63.8% of the variance observed. Additional analyses also indicated acceptable results for the internal consistency with Cronbach's alpha value ranging from 0.67 to 0.88 and ICC values ranging from 0.64 to 0.96.

Conclusions: This psychometric evaluation of a self-administered instrument resulted in a reliable and valid instrument to assess young adult pedestrians' self-reported road crossing attitudes and behaviors in Tehran. Further development of the instrument is needed to assess its applicability to other road users, particularly older pedestrians.

KEYWORDS:

• Pedestrian
• road-crossing behaviors
• safety
• psychometrics

Acknowledgments

We appreciate the support of the Iranian Students Polling Agency (ISPA) for the involvement in data collection.

Funding

This study was financially supported by a grant from Tehran University of Medical Sciences (Code Number: 93–03-27–26623).