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Statement of the Problem: Understanding physical activity (PA) behaviors in children with cerebral palsy (CP) who are non-ambulatory is important to design optimal fitness interventions that reduce sedentary behaviors and promote health. There is a growing body of evidence for children with CP who are ambulatory that indicates they have decreased PA as compared to neurotypical peers. These children are at risk for poor health status and in need of adapted strategies to promote activity and reduce sedentary behaviors. However, information on PA behaviors is limited for children with CP who are non-ambulatory. Evaluating the amount and intensity of PA in children with CP who are non-ambulatory is challenging because of the heterogeneous nature of the disease and the limited repertoire of movements available to these children. Developing assessments that accurately describe PA in this population is essential to understand the nature of these limitations and to develop targeted interventions. Materials & Methods: In Study 1, PA amount and intensity in children with CP who were non-ambulatory were examined using PA (accelerometers) and HR monitors along with video observation and parent journaling over 7 days. Children were observed during a range of daily tasks to provide a detailed observation in their home and school. Parents were asked to rate their opinion of their child’s level of PA intensity during these tasks (easy, medium or hard), and these ratings were compared to the PA intensity derived from the PA and HR monitors. Levels of agreement were reported between parent report and HR and PA monitors during video recording. In Study 2, Interviews with parents of children with CP who were non-ambulatory and physical therapists (PTs) working with this population were conducted to understand how they operationalized PA and to evaluate the face validity of the Patient Reported Outcome Measurement Information System (PROMIS) ® PA parent proxy short form 8a survey as a measure of PA in this population. Each child was classified by Gross Motor Functional Classification Scale (GMFCS), the eating, drinking, classification scale (EDACS), the communication and feeding classification scale (CFCS), and the manual abilities classification scale (MACS).Results: For Study 1, 10 children and families participated in the exploratory observation with a video recording of PA in the home. A minimum of 4 consecutive days of monitor wear data was obtained for 7 of the 10 children; 3 children experienced equipment or use malfunction. There was a positive correlation between the parent level of PA intensity and intensity measured by the HR monitors, but no correlation with the PA monitors. The level of agreement of parent-reported PA intensity and HR monitors were correlated with PediCAT daily activity and mobility scores and the EDACS, CFCS, and MACS, There was no correlation between the parent responses and PA monitor-derived PA intensity levels with any functional measure. The PA monitor-derived level of intensity was correlated with the parent-reported PROMIS T-scores. No correlation was seen with the HR monitors. For Study 2, 22 PTs and 15 parents of children with CP who were non-ambulatory participated in the interviews. The PT’s and parents’ interview responses generated shared opinions about PA and how it should be operationally defined in this population. Four major themes emerged: a) PA is defined by functional activities and active movement; b) PA is challenging to measure objectively in this population; c) the environment plays a crucial role in supporting PA; and d) personal factors influence PA uptake. Both parents and PTs believed PA in this population should be increased to improve health related benefits. PA definition focused on active mobility and independent motor control by PTs, whereas the parent's definition of PA highlighted the functional and mobility achievements of their children with examples of communication and use of assistive technology and adaptive equipment. Level of assistance was used by both PTs and parents to indicate PA measurement. Parents and PTs agreed on the appropriateness of various questions on PROMIS scale, with the most appropriate questions being those that inquired about PA frequency during the week (Questions 6 and 7) Conclusions: Accelerometers, HR monitoring, and video monitoring can provide insight into daily PA in children with CP who are non-ambulatory. PA derived from HR monitors was correlated with parent-reported PA intensity during specific daily tasks, suggesting that HR monitors may better reflect PA intensity than accelerometry-based monitors in this population. In capturing PA over a longer period (e.g., 1 week), the PROMIS parent-proxy measure correlated with PA monitor-derived levels of intensity. PA monitors may best reflect general activity levels throughout the week rather than specific intensity levels during daily activities. Defining PA in children with CP who are non-ambulatory is challenging, however, parents and PTs provided insights into methods that can be used to conceptualize this challenging construct. The PROMIS short form 8a PA had some qualities that were deemed appropriate by PTs and parents alike with a preference for specific questions (Questions 6 and 7) for children with CP who are non-ambulatory. Methods to address the implementation of cardiovascular and fitness goals in this population need to be further explored.

[Truncated abstract] The main purpose of this research was to conduct a series of studies with the aim of contributing information about methods for measuring and analyzing physical environmental attributes of neighbourhoods and the influence of these attributes on specific types of physical activity behaviour. Furthermore, this research examined the moderating affect of the objective physical environment on the relationship between cognitions and physical activity behaviours and the mediating role of the cognitions on the associations between the objective physical environment and physical activity. The research included secondary analyses of data collected as part of the Studies of Environmental and Individual Determinants of Physical Activity (SEID1 and SEID2: Corti 1998; Pikora 2003) and the Physical Activity in Localities and Community Environments study (PLACE: Leslie et al. 2005a; Leslie et al. 2005b). Demographic, cognitive, social and behavioural data from the baseline and follow-up surveys from SEID1 (Corti 1998), and objectively measured built environmental data from SEID2 (Pikora 2003) were analyzed. ... A stronger association between frequency of past trying and recreational walking was also found for respondents residing in neighbourhoods with more recreational destinations (β = 0.11), compared with fewer destinations (β = 0.00). These findings show some evidence that the built environment can affect exercise-related cognitions, which in turn influence physical activity. Findings of this and other research (Owen et al. 2000; Humpel et al. 2002; Saelens et al. 2003b; Foster & Hillsdon 2004; McCormack et al. 2004; Owen et al. 2004; Badland & Schofield 2005; Duncan et al. 2005; Heath et al. 2006) support the need to create supportive environments that encourage both recreational and transport-related physical activity. Providing more opportunities and a greater variety of destinations close to home could encourage physical activity participation, and may even assist some individuals to achieve sufficient levels to accrue health benefits. However, additional research is necessary to understand how both the perceived and objectively measured built environment influences physical activity and to provide evidence of temporal causality between environments, cognitions, and physical activity behaviour.