标题：Development and psychometric evaluation of waste separation beliefs and behaviors scale among female students of medical sciences university based on the extended parallel process model
摘要：The increasing production of un-recycled waste is a great threat to public health. Therefore, assessment and measurement of people’s beliefs and perceptions with regard to these threats can contribute to the development of suitable educational messages promoting waste separation behaviors. This study aimed to carry out the scale development and psychometric evaluation of behaviors and beliefs associated with waste separation among female students. This methodological research was performed in 2019. The primary questionnaire was developed based on the assessment of waste separation beliefs and behaviors based on the extended parallel process model. Afterwards, to confirm the content and face validity of the research tool, the opinions of 14 faculty members and certain students were asked for, respectively. In order to assess the construct validity of the questionnaire, exploratory factor analysis was performed based on the data collected from 386 female students in Isfahan University of Medical Sciences, Iran. The internal and external reliability of the tool was determined through estimating Cronbach’s alpha and test-retest based on intraclass correlation (ICC) index, respectively. The mean age and academic semester of the students were 22 ± 1.9 years and 5.58 ± 2.6, respectively. The primary version of the questionnaire was designed with 65 items; one item was omitted during the content validity process. Construct validity with factor analysis technique yielded nine dimensions including 64 items with a factor loading above 0.3. The overall reliability of the research tool was confirmed at Cronbach’s alpha of 0.87. Furthermore, the ICC of the entire questionnaire was 0.89. According to the results of the study, the final 64-item questionnaire could be used by various researchers to assess waste separation beliefs and behaviors considering suitable psychometric features.
