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Psychometrics of the Self-Report Safe Driving Behavior Measure for Older Adults
Author(s) -
Sherrilene Classen,
Pey-Shan Wen,
Craig A. Velozo,
Michel Bédard,
Sandra Winter,
Babette Brumback,
Desiree N. Lanford
Publication year - 2012
Publication title -
american journal of occupational therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.646
H-Index - 82
eISSN - 1943-7676
pISSN - 0272-9490
DOI - 10.5014/ajot.2012.001834
Subject(s) - measure (data warehouse) , psychometrics , psychology , poison control , clinical psychology , human factors and ergonomics , injury prevention , applied psychology , medicine , medical emergency , computer science , data mining
We investigated the psychometric properties of the 68-item Safe Driving Behavior Measure (SDBM) with 80 older drivers, 80 caregivers, and 2 evaluators from two sites. Using Rasch analysis, we examined unidimensionality and local dependence; rating scale; item- and person-level psychometrics; and item hierarchy of older drivers, caregivers, and driving evaluators who had completed the SDBM. The evidence suggested the SDBM is unidimensional, but pairs of items showed local dependency. Across the three rater groups, the data showed good person (≥3.4) and item (≥3.6) separation as well as good person (≥.93) and item reliability (≥.92). Cronbach's α was ≥.96, and few items were misfitting. Some of the items did not follow the hypothesized order of item difficulty. The SDBM classified the older drivers into six ability levels, but to fully calibrate the instrument it must be refined in terms of its items (e.g., item exclusion) and then tested among participants of lesser ability.

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