Validating the O&M VISSIT: Determining Appropriate Service Intensity

Abstract

Introduction A national validation study on the Orientation and Mobility Visual Impairment Scale of Service Intensity of Texas ( O&M VISSIT) was conducted. Methods Fifty-two of the original 115 interested participants completed the study that used a mixed-methods research design. After finishing the O&M VISSIT for a student, participants completed a survey to determine the scale's validity and reliability. Participants were from urban, suburban, and rural areas and represented a wide range of geographic areas in the United States. Results The results of the national study demonstrate support for significance in relation to content, consequential, social, content, and construct validity, as well as support for significance in relation to internal consistency reliability. Data supporting validity included 88% of study participants who reported that the tool matched their professional judgment for determining the needs of students and recommending the type and amount of service needed. Data supporting the reliability of the tool was calculated using Cronbach's alpha, which showed how well the tool measured the needs of students. The Cronbach's alpha of the O&M VISSIT was .901, which supports significant internal consistency reliability. Discussion The results support the reliability and validity of the O&M VISSIT, as well as positive feedback related to the ease of use and prospective repeated use of the tool in the future. The tool provides a reliable and valid means for O&M specialists to determine appropriate amounts of both direct and collaborative consultation services for their students receiving O&M training. Implications for Practitioners Study participants found the O&M VISSIT to be a practical and functional tool to reflect the needs of students based on an O&M evaluation and could turn the students’ needs into recommendations for type and amount of itinerant O&M services. Practitioners can rely on the statistical validity and reliability data to justify their recommendations for O&M services as research-based decisions.