ABSTRACT
OBJECTIVE: Validate the Preschool Nutrition Education Practices Survey. DESIGN: Iterative approach combining design-based research and Standards for Educational and Psychological Testing. SETTING: Los Angeles, CA and Philadelphia, PA Early Care and Education (ECE) classrooms. PARTICIPANTS: Expert panel members (n = 7); ECE teachers: interviews (n = 8), pilot survey (n = 31), and final survey (n = 136). VARIABLES MEASURED: Early care and education nutrition education practices used in the classroom either during class time or mealtime. ANALYSIS: Qualitative content analysis was implemented for content, response process, and consequences of testing validity evidence. Rasch rating scale analysis was conducted for the response process and internal structure validity and reliability evidence. RESULTS: Qualitative field-testing produced strong content, response process, and consequences of testing validity evidence to inform survey modifications. Quantitative field-testing generated a psychometrically sound, well-targeted 12-item survey on a 4-point frequency scale with excellent item and person reliability (0.97 and 0.93 respectively) and separation (5.36 and 3.77 respectively); good Rasch Principal Components Analysis findings (60.3%); and productive item fit statistics (0.50-1.50 logits). CONCLUSIONS AND IMPLICATIONS: Robust validity (content, response process, consequences of testing, internal structure) and reliability evidence were demonstrated for using the Preschool Nutrition Education Practices Survey to assess ECE teachers' use of nutrition education practices. Future research is needed to examine its relationship to other variables, such as nutrition teaching efficacy, and to determine its ability to detect change in ECE nutrition education practices over time and across groups.
ABSTRACT
PURPOSE: Predictions are complex, multisensory, and dynamic processes involving real-time adjustments based on environmental inputs. Disruptions to prediction abilities have been proposed to underlie characteristics associated with autism. While there is substantial empirical literature related to prediction, the field lacks a self-assessment measure of prediction skills related to daily tasks. Such a measure would be useful to better understand the nature of day-to-day prediction-related activities and characterize these abilities in individuals who struggle with prediction. METHODS: An interdisciplinary mixed-methods approach was utilized to develop and validate a self-report questionnaire of prediction skills for adults, the Prediction-Related Experiences Questionnaire (PRE-Q). Two rounds of online field testing were completed in samples of autistic and neurotypical (NT) adults. Qualitative feedback from a subset of these participants regarding question content and quality was integrated and Rasch modeling of the item responses was applied. RESULTS: The final PRE-Q includes 19 items across 3 domains (Sensory, Motor, Social), with evidence supporting the validity of the measure's 4-point response categories, internal structure, and relationship to other outcome measures associated with prediction. Consistent with models of prediction challenges in autism, autistic participants indicated more prediction-related difficulties than the NT group. CONCLUSIONS: This study provides evidence for the validity of a novel self-report questionnaire designed to measure the day-to-day prediction skills of autistic and non-autistic adults. Future research should focus on characterizing the relationship between the PRE-Q and lab-based measures of prediction, and understanding how the PRE-Q may be used to identify potential areas for clinical supports for individuals with prediction-related challenges.
