Recruitment and Screening
To recruit individuals into WalkIT-A, two primary recruitment techniques were used: traditional flyer-based marketing and partnership with local high school districts to approve promotion by physical activity teachers at local schools. For the first technique, several different flyers were created geared towards either the adolescent or parent audience. They contained a brief description of the study’s purpose along with a link to the respective online Qualtrics screening survey. These flyers were put up at various brick-and-mortar locations, including bulletin boards at coffee shops, gyms, and restaurants. These flyers were also distributed electronically to various schools and personnel. Individuals who completed the screening survey and were deemed eligible received a follow-up email providing further information on the study and inviting them and a parent/guardian to schedule a visit to the Arizona Biomedical Collaborative office in downtown Phoenix for their initial baseline tests and measurements.
Baseline Office Visit
Eligible participants and their parent or guardian were invited to the ASU School of Nutrition and Health Promotion downtown Phoenix office for an initial visit with the research team. During this in-person meeting, the parent completed a consent form, allowing their child to participate in the study, while the child completed an assent form. Following this, both parent and participant were asked to provide baseline information through online Qualtrics surveys (reference Appendix A). These surveys were meant to ensure the adolescent participant did not have any limiting medical issues, to gauge perceived activity levels of the adolescent, and to determine demographic and neighborhood data of the family.
After completion of all surveys, anthropometric and physiologic measures, including height, weight, BMI, and blood pressure, were collected from the adolescent. The adolescent was then equipped with a wireless, chest strap heart rate monitor and directed to begin the treadmill graded exercise test. During the treadmill test, the adolescent walked at a steady pace with gradually increasing incline until the predicted submaximal heart rate was reached.
The aim of the intervention was to increase PA behavior through shaping step counts to a target of 11,500 steps per day. The FitBit Zip was utilized to objectively measure PA. FitBit’s algorithms define active minutes as any step-based activity above 3 METs. Minutes are only awarded after 10 minutes of continuous moderate-to-intense activity in order to align with CDC recommendations.10 Because children and adolescents have higher resting expenditure than adults, a generally accepted cutoff for 6 to 17 year olds for moderate activity is 4 METs and for vigorous activity is 7 METs.11 To reflect this MVPA range, FitBit’s “Very Active Minutes” were recorded in addition to step count. Though FitBit does not define the exact MET cutoff for their “very active minutes”, it can be assumed to be significantly above the 3 MET “active minute” threshold.
Follow up visit:
After the 11.5-week study period, parents and participants were invited back for a post visit. During this final visit, both the parent and child completed a follow-up Qualtrics survey (Appendix B). The adolescent then performed a second treadmill graded exercise test following the same procedures as the initial visit and was compensated with a $15 gift card.
Upon participant completion of the withdrawal phase of the study, data was compiled and analyzed across all three phases (baseline, intervention, withdrawal). For each phase, the average step count and average number of very active minutes were calculated. For each phase the standard deviation of step count and very active minutes was also calculated. The data was plotted separated according to phase. These data trends were then plotted using an annotated graph against daily high temperature and high school calendar events (e.g. finals week, end of semester, days off). Trends in the data were observed in relation to seasonal and school-dependent variation. The variability across phases was observed by looking at similarities and differences between participants. Lastly, changes in pre- to post-intervention anthropometric measures were calculated for each participant by observing the percent difference from beginning to end.
Due to technical difficulties and unforeseen environmental complexities, each participant experienced days in which data could not be recorded. All statistical analysis was carried out as best was possible with acknowledgement to any missing data and its possible effects.