The relationship between student's perceptions of their school environment and academic achievement.

Research within an educational context has demonstrated the importance of variables such as socioeconomic status, gender and school attendance as predictors of academic achievement, however research investigating the role of the physical learning environment on academic achievement is more limited and what research has been conducted often focuses on objective characteristics such as temperature, air quality and noise. In contrast this study measures students' subjective perceptions of their physical school environment and explores how these perceptions along with socioeconomic status, gender and school attendance relate to academic achievement. In addition, we also examined a range of other important variables that could be potential mediating factors between environmental perceptions and academic achievement. The study was conducted with 441, S5 students in five secondary schools in Scotland. Students completed a questionnaire that measured their perceptions of their school environment, their behavior in school, and their learning goals. In addition, data on student academic achievement, attendance and socioeconomic status was provided by the Local Authority. Regression analysis indicates that students' subjective perceptions of their physical school environment, along with attendance, socioeconomic status and gender are all significantly related to academic achievement. In addition, subsequent analysis indicates that the relationship between students' subjective perceptions of their physical school environment and academic achievement is mediated by important "in-school behaviours," namely engaging behavior and environmental difficulty. The implications of these findings are discussed in terms of the direct and indirect relationship between student perceptions of their school environment and their academic achievement.

Comparing Objective and Subjective Measures of Parkinson's Disease Using the Parkinson's KinetiGraph.

Background: Parkinson's disease (PD) is a neurodegenerative disease that can lead to impaired motor function and execution of activities of daily living (ADL). Since clinicians typically can only observe patients' symptoms during visits, prescribed medication schedules may not reflect the full range of symptoms experienced throughout the day. Therefore, objective tools are needed to provide comprehensive symptom data to optimize treatment. One such tool is the Parkinson's KinetiGraph® (PKG), a wearable sensor that measures motor symptoms of Parkinson's disease. Objective: To build a mathematical model to determine if PKG data measuring Parkinson's patients' motor symptoms can predict patients' ADL impairment. Methods: Thirty-four patients with PD wore the PKG device for 6 days while performing their ADL. Patients' PKG scores for bradykinesia and dyskinesia, as well as their responses to a questionnaire asking if their ADL-level had been impacted by various motor symptoms, were used to build a multiple regression model predicting the patients' Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part II scores. Results: Calculation of bradykinesia score response to medication showed that using a dosage response time of 30 min yielded a greater bradykinesia response than when the response time was set to 40, 50, 60, 70, 80, or 90 min. The overall multiple regression model predicting MDS-UPDRS part II score was significant (R 2 = 0.546, p < 0.001). Conclusion: The PKG's ability to provide motor symptom data that correlates with clinical measures of ADL impairment suggests that it has strong potential as a tool for the assessment and management of Parkinson's disease motor symptoms.