Applied Science, Faculty of
Community and Regional Planning (SCARP), School of
DSpace
UBCV
Nasim, Usman
Master of Arts in Planning - MAP
University of British Columbia
With the rise of physical inactivity among children, there has been a decline in children’s active school travel (AST) like walking and bicycling to and from school. The school journeys are a prime opportunity for introducing children to active travel modes. To address lack of physical activity and a decline in AST among children, a variety of transportation policies and programs have been developed. The objective of this thesis is to evaluate the impact of the School Travel Planning (STP) encouragement program on children’s active travel mode share to school. A quasi-experimental design was used to compare active mode share at two elementary schools that organize a ‘Walk and Roll to School’ (WNR) week program with two control schools in Vancouver, British Columbia. The observational counts were carried out at the four study schools to collect data on children’s mode of travel to school. The counts were conducted in four waves. A difference-in-differences approach was used to estimate the intervention effect of the WNR week program. An audit of pedestrian and bicycling facilities was also conducted near the study schools to assess infrastructure barriers to AST. The results from the study suggest no significant immediate impact of the WNR week program on children’s active mode share (walking, bike, and other non-motorized modes like scooter, skateboard, and rollerblade) to school during or shortly after the WNR week. Changes in active mode share to study schools over the weeks investigated were not significantly different from those in the control schools and appeared to be primarily influenced by the weather and daylight conditions. However, because the WNR week is an ongoing annual event at the school since 2013, there could be a long-term positive effect on AST, which was present in the “before” observation and not be observed in this study. It is recommended to possibly consider implementing alternatives to STP interventions to influence children’s travel behaviour to schools for achieving immediate and short term gains. Also, studying the long term impacts of STP programs on children’s AST rates to and from schools and to include control schools in analysis for future research.
EVALUATING THE IMPACT OF UBC’s ‘WALK AND ROLL TO SCHOOL WEEK’ PROGRAM ON CHILDREN’S ACTIVE TRAVEL MODE SHARE TO SCHOOL by Usman Nasim B. Plan, School of Planning and Architecture, New Delhi, 2015 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN PLANNING in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) September 2020 © Usman Nasim, 2020 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: EVALUATING THE IMPACT OF UBC’s ‘WALK AND ROLL TO SCHOOL WEEK’ PROGRAM ON CHILDREN’S ACTIVE TRAVEL MODE SHARE TO SCHOOL submitted by Usman Nasim in partial fulfillment of the requirements for the degree of Master of Arts in Planning Examining Committee: Dr. Alexander York Bigazzi, SCARP & Civil Engineering, UBC Supervisor Dr. Maged Senbel, SCARP, UBC Supervisory Committee Member Additional Supervisory Committee Members: Dr. Omar Swei, Civil Engineering, UBC Supervisory Committee Member iii Abstract With the rise of physical inactivity among children, there has been a decline in children’s active school travel (AST) like walking and bicycling to and from school. The school journeys are a prime opportunity for introducing children to active travel modes. To address lack of physical activity and a decline in AST among children, a variety of transportation policies and programs have been developed. The objective of this thesis is to evaluate the impact of the School Travel Planning (STP) encouragement program on children’s active travel mode share to school. A quasi-experimental design was used to compare active mode share at two elementary schools that organize a ‘Walk and Roll to School’ (WNR) week program with two control schools in Vancouver, British Columbia. The observational counts were carried out at the four study schools to collect data on children’s mode of travel to school. The counts were conducted in four waves. A difference-in-differences approach was used to estimate the intervention effect of the WNR week program. An audit of pedestrian and bicycling facilities was also conducted near the study schools to assess infrastructure barriers to AST. The results from the study suggest no significant immediate impact of the WNR week program on children’s active mode share (walking, bike, and other non-motorized modes like scooter, skateboard, and rollerblade) to school during or shortly after the WNR week. Changes in active mode share to study schools over the weeks investigated were not significantly different from those in the control schools and appeared to be primarily influenced by the weather and daylight conditions. However, because the WNR week is an ongoing annual event at the school since 2013, there could be a long-term positive effect on AST, which was present in the “before” observation and not be observed in this study. iv It is recommended to possibly consider implementing alternatives to STP interventions to influence children’s travel behaviour to schools for achieving immediate and short term gains. Also, studying the long term impacts of STP programs on children’s AST rates to and from schools and to include control schools in analysis for future research. v Lay Summary This research evaluated the effectiveness of UBC’s WNR week program on children’s active travel modes share in two elementary schools located in the University Endowment Lands. Observational counts of children's modes were conducted to collect data on travel mode share. The study found no significant immediate impact of the WNR week program on children’s active mode share to school during or shortly after the WNR week. Changes in active mode share to study schools over the weeks investigated were not significantly different from those in the control schools and appeared to be primarily influenced by the weather and daylight. However, there could be a long-term effect of a multi-year program, which would not be observed in this study. The findings of the study will help in evaluating the effectiveness of a multi STP strategies, i.e., encouragement, education, and enforcement interventions on children’s AST to school. vi Preface This research was conducted by Usman Nasim under the supervision of Dr. Alexander York Bigazzi (Associate Professor at the University of British Columbia). Usman was responsible for conducting a literature review, preparing and administering data collection, and data processing and analysis. The survey conducted in this research was approved by the Behavioral Research Ethics Board (BREB) requirements under the project titled “Evaluating the impact of the 'Walk and Roll to School Week' program on children's mode of travel to school," UBC BREB Number: H19-02534. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ................................................................................................................................ ix List of Figures .................................................................................................................................x List of Abbreviations ................................................................................................................. xiii Acknowledgements .................................................................................................................... xiv Dedication .....................................................................................................................................xv Chapter 1: Introduction ............................................................................................................... 1 1.1 School Travel Planning (STP) .......................................................................................... 2 1.2 STP process ................................................................................................................. 3 1.3 STP Programs ............................................................................................................. 5 1.4 Impact of STP programs ............................................................................................. 9 1.5 Case of UBC’s STP Program .................................................................................... 11 Chapter 2: Literature Review .................................................................................................... 17 2.1 Evaluation of STP programs ........................................................................................... 18 2.2 Mode Share Measurement Methods ............................................................................... 38 2.3 Difference-in-Differences ............................................................................................... 42 Chapter 3: Methodology ........................................................................................................... 47 viii 3.1 Contacting the study schools .......................................................................................... 47 3.2 Mode Share Data Collection ........................................................................................... 48 3.3 Data Analysis .................................................................................................................. 54 Chapter 4: Results ..................................................................................................................... 56 4.1 Observational counts ....................................................................................................... 56 4.2 Statistical analysis ........................................................................................................... 63 Chapter 5: Pedestrian and Bicycling Facility Audit ................................................................. 67 5.1 Audit of UBC elementary schools .................................................................................. 73 5.2 Findings .......................................................................................................................... 76 Chapter 6: Discussion ............................................................................................................... 96 6.1 Limitations ...................................................................................................................... 98 6.2 Future research ................................................................................................................ 99 6.3 Conclusions ..................................................................................................................... 99 6.4 Recommendations ......................................................................................................... 100 Bibliography ...............................................................................................................................101 Appendices ..................................................................................................................................109 Appendix A: Observational Counts Tally Forms……………………………………....109 Appendix B: Study Information Sheet………………………………………………....111 Appendix C: Observational Counts Training Manual……………...………………….112 Appendix D: Scooter, skateboard and roller-blades share (in percentage points)...…...129 ix List of Tables Table 1: STP Program Evaluations ............................................................................................... 19 Table 2: Observational Counts days ............................................................................................. 50 Table 3: Weather information on observation days at Vancouver International Airport ............. 53 Table 4: Daylight timings on observation days in Vancouver, BC .............................................. 54 Table 5: Number of students observed ......................................................................................... 56 Table 6: Logistic regression model of children’s active travel modes ......................................... 66 Table 7: Street Audit Tools ........................................................................................................... 68 Table 8: Street Audit Segments .................................................................................................... 75 x List of Figures Figure 1: STP stakeholders at the regional/municipal and school levels ........................................ 2 Figure 2: STP process ..................................................................................................................... 5 Figure 3: Five E's of STP (Source: Adapted from Safe Routes to School, 2019) .......................... 6 Figure 4: STP Programs and Implementing partners ...................................................................... 9 Figure 5: Impacts of STP programs .............................................................................................. 10 Figure 6: Study Schools ................................................................................................................ 14 Figure 7: Transit stops near University Hill Elementary School .................................................. 14 Figure 8: Transit stops near Norma Rose Point Elementary School ............................................ 15 Figure 9: Transit stops near Sir Sandford Fleming Elementary School ....................................... 16 Figure 10: Transit stops near Sit Matthew Begbie Elementary School ........................................ 16 Figure 11: Literature Review Sections ......................................................................................... 17 Figure 12: Mode share measurement methods ............................................................................. 39 Figure 13: Logic and assumptions underlying the difference-in-differences ............................... 43 Figure 14: Time series data to check for parallel trends between the treatment group and the control group before the start of the treatment .............................................................................. 44 Figure 15: Overview of Methodology .......................................................................................... 47 Figure 16: Contacting study schools ............................................................................................. 48 Figure 17: Mode share data collection .......................................................................................... 49 Figure 18: Location of observers at University Hill Elementary School ...................................... 51 Figure 19: Location of observers at Norma Rose Point Elementary School ................................ 51 Figure 20: Location of observers at Sir Sandford Fleming Elementary ....................................... 52 xi Figure 21: Location of observers at Sir Matthew Begbie Elementary School ............................. 52 Figure 22: Walking share in study schools across four waves ..................................................... 57 Figure 23: School wise walking share in schools across four waves ........................................... 58 Figure 24: Bicycling share in study schools across four waves .................................................... 59 Figure 25: School wise bicycling share in schools across four waves ......................................... 60 Figure 26: Car share in study schools across four waves ............................................................. 62 Figure 27: School wise car share in schools across four waves ................................................... 63 Figure 28: Segments for street audit ............................................................................................. 73 Figure 29: Segment 1 - From intersection b/w Theology Mall & Iona Drive to intersection, b/w Iona drive & Wesbrook Mall ........................................................................................................ 76 Figure 30: Street view of location A and B at segment 1 ............................................................. 77 Figure 31: Segment 2 - From intersection b/w Iona drive & Wesbrook Mall to intersection b/w Wesbrook ...................................................................................................................................... 78 Figure 32: Street view of location A and B at segment 2 ............................................................. 79 Figure 33: Segment 3 - From intersection Wesbrook Mall & Chancellor Blvd to intersection b/w Chancellor ..................................................................................................................................... 80 Figure 34: Street view of location A, B and C at segment 3 ........................................................ 81 Figure 35: Segment 4 - From intersection Chancellor Blvd & Acadia Road to intersection b/w Chancellor Blvd & Hamber Road ................................................................................................. 82 Figure 36: Street view of location A and B at segment 4 ............................................................. 83 Figure 37: Segment 5 - From intersection Chancellor Blvd & Acadia Road to intersection b/w Acadia Road & College Highroad ................................................................................................ 84 Figure 38: Street view of location A, B and C at segment 5 ........................................................ 85 xii Figure 39: Segment 6 - From intersection b/w Acadia Road & College Highroad to intersection b/w Acadia Road & Toronto Road ............................................................................................... 86 Figure 40: Street view of location A and B at segment 6 ............................................................. 87 Figure 41: Segment 7 - From intersection b/w Acadia Road & Toronto Road to intersection b/w Acadia Road & Melfa Road .......................................................................................................... 88 Figure 42: Street view of location A, B and C at segment 7 ........................................................ 89 Figure 43: Segment 8 - From intersection b/w Acadia Road & Melfa Road to intersection b/w Thunderbird Blvd & Osoyoos Crescent ........................................................................................ 90 Figure 44: Street view of location A, B and C at segment 8 ........................................................ 91 Figure 45: Segment 9 - From intersection b/w Thunderbird Blvd & Osoyoos Crescent to intersection b/w Fairview Place & Acadia Road .......................................................................... 92 Figure 46: Street view of location A, B and C at segment 9 ........................................................ 93 Figure 47: Segment 10 - From intersection b/w Thunderbird Blvd & Osoyoos Crescent to intersection b/w Fairview Place & Acadia Road .......................................................................... 94 Figure 48: Street view of location A, B, C and D at segment 10 .................................................. 94 xiii List of Abbreviations ANC Active Neighborhood Checklist AST Active School Travel BREB Behavioral Research Ethics Board C+CP Campus and Community Planning DID Difference – in – Differences PTA Parent Teacher Association SRTS Safe Routes to School STP School Travel Planning TCPS Tri-Council Policy Statement UEL University Endowment Lands UNA University Neighborhood Association WNR Walk and Roll to School xiv Acknowledgements How could I forget to mention The bicycle is a good invention -The Bicycle Song, Red Hot Chilli Peppers (2006) I would like to express my gratitude and appreciation for my supervisor Dr. Alex Bigazzi, whose guidance, support, and encouragement has been invaluable throughout this study. Also thankful to the University of British Columbia’s Campus and Community Planning (C+CP) and TransLink for funding this research. xv Dedication I dedicate my thesis work to my loving family. - A special feeling of gratitude to my mother, Hina Nasim whose encouragement and push for tenacity ring in my ears. - To my late father, Nasim Ahmed for being the BESTest friend I ever had. - My sisters Nida, Seema and Ilma have never left my side and are very special. - My brothers Usama, Shadab and Asjad for filling in for my responsibilities. - Special love to my nieces and nephews: Abisha, Aleeza, Umar, Huzaifa and Hamna. xvi गए िदन के तनहा था मैं अंजुमन में यहा ंअब मेर ेराज़दा ँऔर भी ह ै*** Gaye din ke tanha tha mein anjuman mein Yahaan ab mere raazdaan aur bhi hai *** There are many here now congenial confidant Gone are days I was alone, somehow inconsistent *** ~ Iqbal1 Chapter 1: Introduction The Canadian federal government developed first set of physical activity guidelines for children and youth in 2002 (Janssen et al., 2010), and despite that only 9.3 per cent of children between the age 5 to 17 years meet recommended daily moderate-to-vigorous physical activity (MVPA) of 60 minutes (Public Health Agency of Canada, 2017). As these physically inactive children progress into their adulthood, the lack of physical movement in their lifestyle may lead to serious chronic health issues such as low bone density, hypertension (i.e., high blood pressure), type 2 diabetes, and obesity (Centers for Disease & Prevention, 2011). In Canada, one in seven children and youth are now classified as obese (Rao et al., 2016) and the obesity rates among Canadian children aged between 3 to 19 years has more than doubled since the late 1970s (Carroll et al., 2015). With the rise of physical inactivity among children, there has been a decline in children’s active school travel (AST) like walking and bicycling to and from school (McDonald, 2007). In Canada, less than one-third of students from grades 6 to 10 reported using active travel modes to school (Government of Canada, 2016). The share of walking trips in Toronto, Ontario for children aged 11 to 13 years and 14 to 15 years dropped from 53 per cent to 42.5 per cent and 38.6 per cent to 30.7 per cent between 1986 and 2006 respectively (Buliung et al., 2009). However, this is not only the case in Canada. A consistent decline in active school travel trips is observed in other western nations. The US data suggest declines ranging from 48 per cent to 13 per cent since the late 1960s (Ham et al., 2008); Australia, 44 per cent to 22 per cent since 1971 (van der Ploeg et al., 2007); and in the UK 75 per cent to 53 per cent for 5 to 10-year-olds, and 60 per cent to 44 per cent for 11 to 16-year-olds since the mid-1970s (Pooley et al., 2005). 2 To address the lack of physical activity and a decline in AST among children, a variety of transportation policies and programs have been developed. In the U.S., the Federal Safe Routes to School (SRTS) program was introduced with the objective of funding infrastructure projects aiming at increasing children’s active travel to and from school (SRTS, 2019). In Canada, a nationwide initiative known as Active and Safe Routes to School (ASRTS) has sponsored School Travel Planning (STP) since 2006 to support AST (Active and Safe Routes to School, 2018). 1.1 School Travel Planning (STP) School Travel Planning (STP) is a community-based approach that aims to increase the number of children using active modes of travel for their school journeys. Through the STP process, the STP facilitator brings together a range of stakeholders at the school level i.e. teachers, principals, students, and parents and at the regional level i.e. municipalities, school boards, student transportation services, public health agencies, and police department to work together in identifying barriers and collectively plan for solutions that increase the number of students choosing active travel modes to schools (Figure 1). Figure 1: STP stakeholders at the regional/municipal and school levels (Source: Adapted from Green Communities Canada, 2018) 3 1.2 STP process There are six phases involved in the STP process (Figure 2). Phase 1 of the process deals with establishing the STP committee at the regional/ municipal and at the school levels. The regional/ municipal STP committee is a high-level group of stakeholders consisting of school boards, public health agencies, elected officials, transportation and land use planners, traffic engineers, and police & by-law services. In Canada, several regional STP committees have already been set up, for instance, Ecology Action Centre in Nova Scotia, Velo Quebec in Quebec, Green Communities Canada in Ontario, Green Action Centre in Manitoba, SHAPE in Alberta, Saskatchewan in Motion in Saskatchewan and HASTe BC (not currently operational) and HUB cycling in British Columbia. The school STP committee consists of teachers, principals, students, parents, and local interest groups like residents associations. The school STP committee involves undertaking tasks like selecting interested schools, gathering information about selected schools i.e. number of students, school bell times, having school bus service, and the number of parking spaces. The school STP committee is also responsible for making the timeline for different tasks of the STP like activities involving students such as data collection or implementing education and encouragement activities. In Phase 2, relevant information about the schools is collected to understand the school travel issues and to make a case for why certain issues deserve the attention of the STP committee. The school data collected in this phase forms the baseline for comparing with data collected at later stages and to measure the progress. The data collected in this phase includes children’s travel mode share to and from schools, parental perceptions related to the school 4 journeys, maps showing students home locations, the school location, and catchment area, and traffic volumes and the speed limit in front of or near the school. In Phase 3, the action plan is developed based on the issues and barriers identified in Phase 2. Several tasks are needed for preparing the action plans. These include doing preliminary research on effective solutions with a particular school’s challenges. Once the solutions are finalized for an action plan it needs to get approval from the STP committee. In Phase 4, solutions proposed in the Action Plan developed in Phase 3 gets implemented. This is the longest and the most important part of the STP initiative. The Action Plan developed may be modified by adding new actions as new information becomes available and also postponing some actions which prove challenging to be implemented within the specified time frame. Phase 5 mainly deals with evaluating the progress of the solution implemented under the STP Action Plan. The follow-up data like children’s travel mode share to and from schools, parental perceptions related to the school journeys, and traffic volumes and speed in front of and near the school is collected and compared with baseline data collected in Phase 2. It also involves sharing results and progress to maintain enthusiasm in the STP process moving forward. 5 Figure 2: STP process 1.3 STP Programs STP implements different programs using the Five E’s i.e. education, encouragement, engineering, enforcement, and evaluation (Figure 3) to influence children’s and parents' travel mode (Figure 4). A few of the key programs under each ‘E’ are discussed, along with their implementing partners. 6 Figure 3: Five E's of STP (Source: Adapted from Safe Routes to School, 2019) Education a) Bicycle Skills Clinic – the program offers an opportunity for students and their parents to learn and practice bicycle handling skills. During the program, the students visit volunteers, teachers, and bicycling promoting organization staff at the activity stations to learn different skills on how to bicycle safely and confidently. They are generally implemented by active travel promoting organization, the City and, the participating schools. b) Bicycle Maintenance Courses – the program teaches students bicycle maintenance skills like fixing a flat tire. The students are provided with hands-on learning opportunities. These programs are often organized by the schools and local bike shops. c) Community education and awareness campaign – the objective of these programs are to provide walking, bicycling, and driving safety information and resources for individuals within the school community. Workshops and community events are organized providing 7 information on safe bicycling and walking. They are generally organized by collaboration between the City, school boards, and police departments. Engineering a) Walk Audits – the objective of the walk audit is to assess the physical condition of walking and bicycling facilities. The obstruction in using active travel modes are documented using walk audit tools. These are organized by the bicycling and walking organizations, police departments, and the PTAs. b) Walking & Biking Routes Map – these maps take into account where there are sidewalks, marked crosswalks, crossing guards, and other things that make it safer and more comfortable for students walking and bicycling. The maps are prepared by the City, school boards, and walking and bicycling organization. c) Arrival & Dismissal Assessment - these are the assessment of the infrastructure in the drop-off/pick-up areas, or on the streets around the schools, and recommend infrastructure as well as operational changes. They are conducted by the school, the City, and the school board. Encouragement a) Competitions & contests – the idea is to incentivize students using active travel modes in school journeys. These activities require minimal resources and are used by schools to encourage the use of walking and bicycling. They are generally organized by the PTA, bike shop, or other local businesses. b) Walking School Bus & Bike Trains – a group of students collectively bicycling or walking to school led by a leader, usually a parent volunteer. They can operate once a 8 month, once a week, or every day and are organized by the PTA, community, and family members. c) Walk & Bike to School Days - these events are a simple way to introduce schools, families, and community groups to walking and bicycling. Students and parents are encouraged to use active travel modes on designated days. Several partners collaborate in organizing these events like the PTA, police and health departments, the City, school boards, and walking and bicycling organizations. Enforcement a) Student Safety Patrol – the program’s objective is to enforce safe walking and bicycling behavior near the schools. The patrol members are the upper-grade students who direct other students and teach traffic safety on a peer-to-peer basis. The patrols are organized by the PTAs, school boards, the City and the police department. b) Crossing guards - Crossing guards help reinforce safe behaviors at schools and can be paid staff or volunteers and are often organized or hired by the City and or school boards. c) Safety reminders at drop-off/pick-up - School staff or volunteers remind drivers of safe behaviors by handing out flyers with information about procedures and following the rules. They are organized by the school administration. Evaluation a) Surveys – the surveys help in revealing parents' concern of driving students to schools and also provide insight into what changes might encourage a shift in their behavior. They are conducted by the school boards, the City, and walking and bicycling organizations. 9 b) Travel tallies – these are surveys intended to collect data on the travel mode share of students. They are conducted by the school boards, the City, and walking and biking organizations. c) Program tracking & periodic assessment – the objective of these assessments is to track the effectiveness of different STP programs and identify areas that need improvements. These are conducted by the school boards, the PTA, and the City. Figure 4: STP Programs and Implementing partners 1.4 Impact of STP programs STP programs influence students' choice of travel modes for their school trips by organizing different programs under the Five E’s, as explained in the previous section. The goal of each program is to encourage students and parents to use active travel modes to and from schools. The shift towards active travel modes further may impact other key areas like student’s 10 and parents' health, safety, social interaction, environment, and costs (Figure 5). These are further explained in the below section. a) Health – the shift to active travel modes impacts the time spent doing physical activity in children and family members. This change in physical activity levels influences mental and physical health. b) Safety – improvements in the walking and bicycling infrastructure and road safety knowledge impacts the number of road injuries and speed violations near schools. c) Social Interaction – community engagement programs allow the school community to engage in interactions. Events like WSB and bike trains motivates students to make new friends from different grades as well as schools. d) Environment – the change in the number of students being driven to schools impacts the air and noise pollution near the school zones. e) Cost – avoiding the usage of cars provides household savings from reduced gas and personal vehicle use, as well as savings on the cost of student busing. Figure 5: Impacts of STP programs 11 1.5 Case of UBC’s STP Program The University of British Columbia’s Campus and Community Planning (C + CP) and the University Neighborhood Association (UNA) organizes a week-long program known as ‘Walk and Roll to School Week’ in the two elementary schools (Norma Rose Point Elementary and University Hill Elementary) located in the University Endowment Lands (UEL) in Vancouver since 2013. The ‘Walk and Roll to School Week’ is one of the ‘Encouragement’ programs aiming to increase active school travel. The UBC’s ‘Walk and Roll to School Week’ event is organized in May and October. To make the week more effective, other STP strategies i.e., Es are part of the program. UBC’s ‘Walk and Roll to School Week’ is a combination of encouragement, education, and enforcement. The following actions form the part of the program. Encouragement a) Awards and prizes for participating children: these are incentives (hats for walkers and cyclists (to stay extra-visible) and reflective stickers and bike lights) awarded to students at the participating schools for taking part in the event. b) Dedicated routes for Walking School Bus and Bike trains: these are streets or roads dedicated to the movements of WSB and bike trains. The students assemble at a designated meeting place and walks and bicycle to schools. Education c) Bike safety checks at schools: Krank it up! These are free on-site bike tune-ups stations set up at the participating schools organized by the UBC’s Bike Co-op. d) Distributing educational materials on safe walking and riding behaviors: the guide for teaching skills for safe walking and bicycling and related health benefits for using active travel modes. 12 e) Bicycle riding course: A bicycle riding course was given to students by UBC’s Bike Co-op on two days of the WNR week, where the intervention schools students were made to bicycle avoiding obstacles (cones) within the school's premises. Enforcement f) Crossing Monitors: Community volunteers were stationed at the mid-block crossing and along Chancellor Boulevard each morning, to remind students to be careful. g) Placing RCMP officers: RCMP officers for enforcing speed limits near schools were carried out. The objective of such events is to spread awareness about the benefits of using active travel modes and to influence children’s travel behavior towards using active modes to schools by creating excitement and shifting norms through events, activities, prizes, and incentives. Several cities and school boards in Canada are organizing such week-long encouragement (City of Vancouver ‘Walk + Bike + Roll’, Region of Peel including cities like Brampton, Mississauga, and Town of Caledon ‘Walk + Roll’, Toronto School District Board ‘Bike to School Week’ and City of Surrey ‘Walk and Roll to School Week’.) The research focused on the effectiveness of the STP encouragement programs is still emerging with initial findings suggesting modest short term gains (Buliung et al., 2011, Mammen et al., 2014 & Buckley et al., 2013). Unfortunately, no evaluation of a week-long multi-intervention STP program i.e., encouragement, education, and enforcement having WSB, bike trains, car free-zones, and incentives, have been done to see the impact on children’s AST. In the Canadian context, it is advised that case studies be utilized to examine STP program effectiveness (Mammen et al., 2014). We followed this suggestion and offered a case study 13 evaluation of UBC’s ‘Walk and Roll to School Week’ encouragement STP program. The findings will inform on the effectiveness of STP program.. To guide this study, we posed the following research questions: a) Is there an impact of ‘Walk and Roll to School Week’ program on children’s active travel (walking, bike and other non-motorized modes like scooter, skateboards and roller blades) mode shares to school during and immediately after the program, and b) Is the impact on children’s active travel modes share sustained weeks after the program? The physical audit of pedestrian and bicycling facilities was conducted near study schools to assess physical barriers to AST. 1.5.1 Study schools The intervention schools i.e., Norma Rose Point and University Hill, are both located in the UEL and are at a distance of 1.25 km apart. The Norma Rose Point is located between the W 16th Avenue and University Boulevard and University Hill on the Chancellor Boulevard. Both schools are accessible by transit ( Figure 7 and Figure 8). According to the Census 2016, the median household income of the residents near the intervention schools i.e., in UEL, was between $30,000 and $49,999, which was lower than the national average of $57,000 (Canadian Income Survey, 2016). The lower-income could be explained as the majority of residents are university students. The control schools i.e., Sir Matthew Begbie and Sir Sandford Fleming, are both located in the City of Vancouver. Both schools are located approximately 6.5 km between each other and accessible by transit ( Figure 9 and Figure 10). The median household income of the residents lies in the range of $50,000 and $74,000. 14 Figure 6: Study Schools Figure 7: Transit stops near University Hill Elementary School 15 Figure 8: Transit stops near Norma Rose Point Elementary School 16 Figure 9: Transit stops near Sir Sandford Fleming Elementary School Figure 10: Transit stops near Sit Matthew Begbie Elementary School 17 Chapter 2: Literature Review The prevalence of overweight and obesity in children and youth has been rising in Canada (Buliung et al., 2011). Between the years 1978 and 2004, the combined overweight or obesity rate for children between 2 to 17 years increased from 15 per cent to 26 per cent (Shields, 2005) and over half of the children aged between 5 to 17 years rely solely on inactive modes of transportation to and from school (Craig et al., 2001). Transportation scholars have acknowledged early childhood intervention as an approach to achieving long term sustainable transport practices (Wellar, 2007). School journeys are a prime opportunity for introducing children to active travel modes (Tudor-Locke et al., 2001). Therefore, interventions focused on increasing children’s AST are needed to involve children in physical activity (McMinn et al., 2012). Also, engaging in AST then, may develop into persistent, environmentally sustainable travel practices through time (Evenson et al., 2003). Figure 11: Literature Review Sections The literature review is divided into three parts (Figure 11). The first part reviews the existing literature on evaluations of the STP interventions. The second part examines the children’s mode share data collection methods available, and the third explains the ‘Difference in – Differences’ approach used for statistical analysis of UBC’s STP program effectiveness on children’s AST. 18 2.1 Evaluation of STP programs Assessments of interventions focusing on increasing children’s AST through STP programs have been carried out. Researchers have used different types of interventions i.e., education, engineering, enforcement, encouragement, and evaluation, to increase AST. This section details the existing research evaluating the effectiveness of different STP program interventions i.e., education, engineering, enforcement, and encouragement on children’s AST. All the studies reviewed have an ‘evaluation’ component attached to them. Therefore, no separate section on ‘evaluation’ is done (Table 1). 19 Table 1: STP Program Evaluations Author, (Study Region) Intervention and Setting Intervention Type Methods Results Boarnet et al., 2007, (California, US) Traffic improvements near elementary schools; 10 elementary schools; duration 2002-2003 Engineering, evaluation Family questionnaires and observational counts; during 2-day periods both before & after the construction of the SRTS project Significant increase in AST Buckley et al., 2013, (Idaho, Moscow, US) Designated AST day; 3 elementary school (2 intervention and 1 control) students (n=475) Encouragement, evaluation Design: quasi-experimental Observational counts; on five days; one day the week before the event, the day before the event, the day of the event, one day a week later, and one day two weeks after the event Increase in AST sustained at 2-week follow-up relative to the control school (χ2 = 11.6; p = 0.009) 20 Buliung et al., 2011, (4 Canadian provinces: Ontario, Alberta, British Columbia, Nova Scotia) STP pilot program and the entire STP process in predominantly suburban settings; 12 elementary schools (grades K-5, K-9) with 5012 students aged 4 to 14 years Education, enforcement, engineering, encouragement, evaluation Design: Observational Hands-up classroom surveys to capture to and from school transport mode, family questionnaires; one-year follow-up AST across all schools increased from 43.8% (baseline) to 45.9% (follow-up); p-value is unavailable Bungum et al., 2014, (Las Vegas, Nevada, US) Designated AST day; students (n=148) of grades K to 5 of two elementary schools (intervention=1 and control=1) aged 5 to 11 years Encouragement, evaluation Design: quasi-experimental Observational counts; in three waves; first, on a day week before the NMD, second, on NMD and third one week later NMD Increase in AST by 7.4 percentage points on the day of the event. AST was then significantly higher than in the control school (χ2 = 27.2; p < .001; d = 0.29). AST dropped to 21 baseline rates at 1-week assessment Coombes et al., 2016, (Norwich, UK) a nine-week ‘Beat the Street’ program; 2 schools ( intervention=1 and control=1) with 80 students aged 8 to 10 years; duration (May and July 2014) Encouragement, evaluation Design: quasi-experimental In-class student questionnaire; baseline (May 2014), during the intervention (July 2014), and post-intervention (October 2014) At 7-week follow-up: no difference in AST between groups. At 20-week follow-up: 10% increase in AST in the intervention group and 7% decrease in control group (p = 0.056) Cuffe et al., 2012, (Boulder, Colorado, US) Intervention incentivizing children using active travel modes; 7 elementary schools; duration (2007-2010) Encouragement, evaluation Radio-frequency ID (RFID) tags; baseline and one-year follow-up Significantly increased the probability of AST by 4.2– 17.6%–20.4%. Increases the probability of participating child rides by 13.6% 22 Ducheyne et al., 2014, (Flanders, Belgium) Four-week long Cycling training; 3 elementary schools (intervention=2 and control=1) with 134 fourth grade students Education, evaluation Design: Randomized Control Trial (RCT) family questionnaires; one-week and five months follow-up Changes in weekly time spent cycling did not differ between intervention and control group (F = 1.9; p > 0.05) Goodman et al., 2016, (England) Bikeability, a week-long national cycle training program for children; 3336 elementary schools (intervention=2563 and control=773) children aged between 10 to 11 years Education, evaluation Design: a retrospective natural experiment Family questionnaires Bikeability training was more likely to cycle at least once a week (OR = 1.26; 95% CI = 1.16-1.37) Johnson et al., 2016, (Cambridgeshire and six other English Bikeability, a week-long national cycle training program for children; 25 Education, evaluation Design: RCT An in-class student reported, Bikeability Adjusted odds ratio (OR) for year 6 pupils for the association 23 local authority, England) elementary schools with 1345 students aged 5 to 6 years School Travel Survey, May and June 2014 between Bikeability and an increased self-reported level of cycling was 1·01 (95% confidence interval (CI) 0·75–1·38). Not statistically significant Kearns et al., 2003, (Auckland, New Zealand) 15-months long WSB intervention, ‘Zippy Walking Bus’; one elementary school (Gladstone School) with 850 students from grade 1 to 6 Encouragement, evaluation Family questionnaires and hands-up survey; baseline and 15-months follow up 19.5 fewer cars arriving outside Gladstone School at both drop-off and pick-up times on an average day; no hypothesis test performed Macdonald et al., 2013, (Oregon, US) Eugene SRTS funded project; 9 elementary Engineering, evaluation Family questionnaires and in-class student Increases in 24 schools and 5; duration four years (2007-2011) middle schools (intervention=9 and control=5) Design: Quasi-experimental questionnaire; baseline and six-months follow-up walking and biking of 5-20 percentage points Macdonald et al., 2014, (Florida, Oregon, Texas, District of Columbia, US) SRTS funded projects; 801 schools of which (intervention=378 and Control=423) with 65,000 students; duration five years (2007-2012) Engineering, evaluation Design: Quasi-experimental Family questionnaires and in-class student questionnaire Increase of 3 per cent in AST, (a relative increase of 18%). Walking and bicycling increased by 1.1 per cent (p = .002) with each year of participation Mammen et al., 2014, (Canada) STP approach; 53 elementary schools spread across Canada with children Education, enforcement, engineering, Family questionnaires and hands-up survey 17% of parents reported driving less. Of these, about 83% reported 25 aged 6 to 14 years; duration 2 years (2010-2012) encouragement, evaluation switching from driving to AST. No baseline data available and no hypothesis test performed Martin et al., 2018, (Cordoba, Spain) 14-week long WSB intervention; 55 elementary school children aged between 5 to 12 years; between 2014-2015 Encouragement, evaluation Mobile phone application 43.7 per cent of participant completely or partially changed their modes of transportation to school from automobile to walking; no hypothesis test performed McKee et al., 2007, (West Curriculum intervention for one school term; 2 elementary schools Education, evaluation Computerized mapping program; baseline and ten-weeks follow up Post-intervention, the mean distance traveled to school by walking by 26 Dunbartonshire, Scotland) (intervention=1 and control=1) with 60 grade 5 students aged between 9 to 10 years Design: Quasi-experimental intervention children increased significantly from baseline, from 198 to 772 m (389% increase). McMinn et al., 2012, (Glasgow, Scotland) Travelling Green, a 6-week school-based intervention; 5 elementary schools with 166 students (intervention=79 and control=87) aged between 8 to 9 years Education, evaluation Design: Quasi-experimental In-class student questionnaire; baseline and one-week follow up No significant impact on AST Mendoza et al., 2009, (Seattle, Washington, US) One-year long WSB intervention; 653 ethnically diverse students aged between 5 and 11 years in Encouragement, evaluation Design: quasi-experimental In-class student questionnaire; baseline and one-year follow-up Higher proportions of students (n = 643, p = 0.001)) walked to the intervention (25% +/- 27 three elementary schools (one school intervention and 2 schools as control) 2%) versus the control schools (7% +/- 1%) Mendoza et al., 2011, (Houston, TX, US) Five-weeks long WSB intervention; eight elementary schools (intervention=4 and control=4) with 149 fourth grade students average 10 years Encouragement, evaluation Design: RCT In-class student questionnaire Intervention schools students increased their weekly percent AST from 23.8% ± 9.2% at baseline to 54.0% ± 9.2% at follow-up, whereas control children decreased their weekly percent AST from 40.2% ± 8.9% to 32.6% ± 8.9% (p < .0001; d = 0.40) 28 Ragland et al., 2014, (California, US) State-funded SRTS project, specifically safety study; eight schools with 2000 students Engineering, evaluation Family questionnaires Living within 250 ft of an SRTS project increased the probability that a child walks to school (coefficient = 0.82, Z-statistic = 2) Villa-Gonzalez et al., 2015, (Granada, Spain) The six-month-long intervention aimed at increasing AST through changing children safety perceptions and attitudes; 5 elementary schools (intervention=3 and control=2) with 206 children aged 8 to 11 years Education, evaluation Design: Observational In-class student reported; baseline and six-months follow up Increase in the frequency of active trips in intervention schools (0.6 ± 0.2) relative to control schools (−0.4 ± 0.3) [p = 0.019; d = 0.40] 29 2.1.1 Education The ‘education’ programs are designed to providing students, parents, and the community with the skills of safe walking and bicycling aiming to increase active travel share in school journeys (Safe Routes to School, 2019). Research has been done assessing the effectiveness of education interventions like road safety workshops (Buliuing et al., 2011), bicycle maintenance training (Ducheyne et al., 2014, Goodman et al., 2016, Johnson et al., 2016) and sessions on health benefits of using AST (McMinn et al., 2012, Villa-Gonzalez et al., 2015). Education STP programs were found to be the most widely implemented type of intervention (38 per cent of all interventions) in a two year STP pilot implementing a combination of education, encouragement and engineering programs in 12 elementary schools (grades K-5, K-9) having a total of 5012 students aged 4 to 14 years across four Canadian provinces (Alberta, Nova Scotia, Ontario, and British Columbia) with parents reporting road safety education (24 per cent) as the most effective programs in influencing their child’s travel mode to school (Buliung et al., 2011). Besides road safety education, training on bicycle maintenance is often organized. The four-week bicycling training course teaching bicycling skills to 135 fourth grade students of the three elementary schools in Flanders, Belgium was found to significantly improve students bicycling skills (walking with the bicycle, mounting the bicycle, braking and dismounting the bicycle, one-handed steering and signaling, looking left, right and over left shoulder while cycling) at a one-week and five months follow-up, however, no significant impact on children’s bicycling rate to schools was found (Ducheyne et al., 2014). No impact on children’s bicycling rate could be explained as the training was only intended to improve the bicycling skills and not to improve the traffic skills. Perhaps, a significant impact on the bicycling rate may be found if 30 training focused more on real-world cycling experiences so that students can experience school journeys. However, (Goodman et al., 2016 and Johnson et al., 2016) found that with training on real-world bicycling experience, the length of intervention could be important as they found no significant increase on children’s bicycling rate to schools after being given week-long bicycling skills and maintenance program, ‘Bikeability’ in 3336 elementary school children aged between 10 to 11 years in England. In another assessment (Steer Davies Gleave, 2012) of the same ‘Bikeability’ program found significant increase on children’s bicycling rate to school but this time in older students i.e. three secondary schools students aged between 11 to 15 years, which suggests education interventions like bicycle maintenance that requires dealing with bicycles like lifting them may be more effective in older students. Researchers also found the type of person (teacher, school staff, researcher, etc.) responsible for delivering education intervention in schools, and the weather conditions could be important factors. (McMinn et al., 2012) designed a study to evaluate the effectiveness of a six-week-long STP education program called ‘Travelling Green’ (13 in-class road safety and health benefits sessions delivered by class teachers) on walking rate of 166 elementary school students in Glasgow (Strathclyde), Scotland. The five-day children’s modes share measurement pre and post the program found no significant impact on children’s walking rate to school. The authors suggested weather conditions (favorable in pre and less favorable in the post) during measurement periods, and the implementation of the program by class teachers rather than research team (teachers have busy schedules, and so an additional initiative to be implemented may be viewed as burdensome and therefore poorly delivered) as the factors for the result. 31 In another study, (McKee et al., 2007) found a significant impact on the walking rate to school in 60 grade 5 students aged between 9 to 10 years in West Dunbartonshire, Scotland following the same STP program, i.e. ‘Travelling Green’, however, the measurements were taken between the Easter and summer breaks when the conditions are favorable for walking and the sample size was small. Addressing (Ducheyne et al., 2014 and McMinn et al., 2012) concerns of lack of real-world experience and delivery of the program by teachers, (Villa-Gonzalez et al., 2015) designed a study to evaluate the effectiveness of a six-month-long STP education program in 206 children aged 8 to 11 years in Granada, Spain. The intervention included an in-class session on reading a story and performing scenes related to active commuting to school, and outdoor sessions (in school neighborhood) on safe walking and bicycling. The authors found a significant increase in the children’s walking rate to school at a six-month follow-up. This present literature on education STP interventions suggests that a combination of real-world experience (on-road walking and bicycle sessions), program delivery by the research team, or a dedicated STP coordinator and a long period intervention could be promising in increasing children’s AST. 2.1.2 Engineering The ‘engineering’ STP programs are designed to improve and assess the physical conditions of walking and bicycling infrastructure in the school zones to increase students' AST. The idea is to create physical improvements to the streets and neighborhoods that make walking and bicycling more comfortable and convenient while decreasing the risk of injury and increasing road safety (Safe Routes to School, 2019). The majority of the assessments done for engineering STP interventions were carried out in the US for traffic improvements made using 32 SRTS funding (Boarnet et al., 2007, Macdonald et al., 2013, Macdonald et al., 2014, Ragland et al., 2014). In Canada, (Mammen et al., 2014) evaluated a combination of engineering improvements and educational programs at the national level. (Boarnet et al., 2007) designed a study to evaluate the impact of a sample of 10 traffic improvement projects of the total 186 projects funded under California’s SRTS program between the spring of 2002 and fall of 2003. Each of the ten projects was located near ten elementary schools as they often sited to serve local populations, suggesting that walking might be feasible for many elementary school students who live nearby (EPA, 2003). The study found of all the six types of traffic improvements made (sidewalk improvements, traffic calming and speed reduction, pedestrian and bicycle crossing projects, bicycle facilities, traffic control devices, and traffic diversion improvements), sidewalk, and traffic signal improvements projects had significantly increased children’s AST. However, the study did not include control schools, and the findings may be confounded with other factors. (MacDonald et al., 2013) included control schools in their assessment of SRTS improvement in Eugene’s, Oregon, and found no significant increase in AST rates following improvement to sidewalks and crosswalks in 15 schools (9 intervention and 5 control) from 2007 to 2011. However, one crucial factor was that many study schools were located close to residential areas and already have an existing sidewalk, and walking to school was possible. However, in another study (Macdonald et al., 2014), evaluating SRTS engineering improvement projects in 801 schools (378 schools as intervention and 423 as control) with 65,000 students in the District of Columbia, Florida, Oregon, and Texas. The authors used National Center for SRTS data on students' travel mode from 2007 to 2012 to see the change in children’s rate of AST and predicted that with each additional year of SRTS participation led, on 33 average 5.5 per cent, to more walking and bicycling in intervention schools. (Ragland et al., 2014) carried out evaluation of another SRTS funded improvement program in the US state of California. Analysis of a sample of eight schools with data on 2000 students' travel mode, the authors found that living within 250 ft of an SRTS project increased the probability that a child walks to school. Attempts have been made to evaluate a combination of engineering improvements with other interventions like educational programs. (Mammen et al., 2014) carried out the first national-level assessment of STP programs. A sample of 53 elementary schools spread across Canada with children aged 6 to 14 years was evaluated to see the impact children’s AST following a combination of engineering and education STP programs between 2010 and 2012. The engineering improvements included programs for sidewalk improvements, and traffic calming in school zones and education as parent and child safety education/workshop and promotional materials/banners posted in and around the schools. The study found no significant increase in children’s rate of AST. However, the authors noted that aggregating AST change at a national level is misleading given the school-specific nature of the STP intervention in addressing localized challenges to AST which may be met with varying levels of success in such a short timeframe. The review of the existing literature assessing the STP engineering program’s effectiveness on students AST suggests that there could be no significant impact on students AST following engineering improvements if walking and bicycling to school is possible and the majority of students live close to schools. Priority should be to assess the local infrastructure challenges to AST and addressing those challenges. The best approach is making schools 34 accessible by foot and bike should be considered long before a school is ever built and should be part of the development approval. 2.1.3 Enforcement Enforcement STP programs are aimed at deterring unsafe traffic behaviors and encourage safe habits by people walking, bicycling, and driving in school neighborhoods and along school routes (Safe Routes to School, 2019). Programs are often organized in collaboration with local law enforcement agencies (Green Communities Canada, 2018). The review of existing literature revealed that there is a lack of assessment of ‘only enforcement STP interventions’ on children’s AST. Enforcement primarily involved engagement with law enforcement on-site to ensure adherence to speed and parking regulations (Buliung et al., 2011), measures such as the funding of street crossing guards, the placement of speed feedback trailers near schools, and increased police presence to enforce speed limits in school zones (MacDonald et al., Mammen et al., 2014 and MacDonald et al., 2014). However, research is available assessing enforcement STP interventions when used with other types of STP programs i.e., education, engineering, and encouragement (Buliung et al., 2011, Mammen et al., 2014, MacDonald et al., 2013, MacDonald et al., 2014). Future research is needed to assess ‘enforcement only’ intervention on children’s AST. However, this lack of research in assessing ‘enforcement only’ is attributed to the fact that interventions with enforcement activities had smaller increases in rates of AST than those without, perhaps because enforcement activities have a more direct impact on the safety of children already using AST rather than the choice to use AST (Stewart et al., 2014). 35 2.1.4 Encouragement Encouragement STP programs are aimed at generating enthusiasm and increasing AST through organizing events, activities, and giving prizes and incentives to students using active modes during the program (Green Communities Canada, 2018). One of the most common programs organized is ‘Walking School Buses’ (WSB) (Martin et al., 2018). One of the early assessments of WSB was carried out by (Kearns et al., 2003) in Auckland, New Zealand. The program called ‘Zippy Walking Bus’ began in one elementary school (Gladstone School) with 850 students in grades 1 to 6. The study found that the WSB intervention led to an estimated 19.5 fewer cars arriving outside Gladstone School at both drop-off and pick-up times on an average day after its operations of 15 months and with the help of 21 trained volunteers. The encouraging results could be related to the long continuous operations of WSB with the assistance from interested volunteers. However, no statistical analysis was done to test the significance of WSB on children’s AST. Later studies carried out ran statistical tests for the significance of WSBs. (Mendoza et al., 2011) assessed AST among 149 fourth grade students in eight elementary schools (four intervention and four control) of Houston, Texas following a five-week-long WSB program and found a significant increase in weekly AST. Three WSB were operated for five days a week on three routes of 0.8 mile average, each with 8 to 12 children per 2 staff members. A pilot assessment of year-long WSB programs carried out by (Mendoza et al., 2009) in Seattle, Washington involving 653 ethnically diverse students aged between 5 and 11 years in three elementary schools (one school intervention and 2 schools as control) found significantly higher proportions of students in the intervention school at a 12 months follow-up. Similar to 36 their earlier assessment (Mendoza et al., 2009) of WSB, the study also hired a paid part-time WSB coordinator who was responsible for implementing and maintaining the program. The use of mobile applications in operating WSB can have positive impacts on AST. (Martin et al., 2018) found 43.7 per cent of the 55 elementary school children aged between 5 to 12 years who participated in a 14-week long WSB intervention in Cordoba, Spain completely or partially changed their modes of transportation to school from automobile to walking. However, besides using the mobile application (for parents to track their children), the WSB also hired paid professional WSB monitors, one for 12 children and one WSB coordinator who managed and supervised all WSBs. Another approach is to incorporate the gamification components into the program. (Coombes et al., 2016) evaluated a nine-week ‘Beat the Street’ program, which aimed to encourage students to use active modes through the use of walk tracking technology linked to a reward scheme in Norwich, the UK between May and October 2014. Before the program, the students were issued smartcards, which they were required to touch on sensors known as ‘beat boxes’ installed on 40 lamp posts in the school zone. Each time, they touch the smartcard on the censor, they won a point which they can use to buy books. The study assessed the program’s impact on AST in 80 students (51 in intervention and 29 in control) aged 8 to 10 years; of two primary schools found a significant increase in weekly active modes usage in the intervention group after a 20-week follow up. Encouragement program incentivizing elementary school children using active travel modes was assessed by (Cuffe et al., 2012) in seven elementary schools in Boulder, Colorado, between 2007 and 2010. At participating schools, principals specified “prize periods” which usually lasted one week. Children who rode their bicycle to school each day of a prize period 37 were entered into a lottery to win a ten-dollar cash prize or a ten-dollar voucher to a local bicycle store. The study found a 13.6 per cent increase in participants' bicycle ridership. Another type of encouragement STP programs includes organizing ‘walk school days.’ (Bungum et al., 2014) evaluated the effectiveness of a one day ‘walk school day’ called ‘Nevada Moves Day’ in Henderson, Nevada, in shifting students to AST. The mode share data of students (n=148) of grades K to 5 of two elementary schools (each intervention and control) was collected in three waves; first, on a day week before the NMD, second, on NMD and third one week later NMD. Students who participated were given promotional materials like stickers reading, “I walked to school! Nevada Moves Day.” The study found a significant increase in students' AST on NMD, but the active modes share returned to the baseline levels in one week. The return to baseline share may be attributed to that fact it was only ‘one-day’ intervention and promoted as using AST on that day. However, long-lasting effects on AST could be observed if the intervention was longer. Another evaluation of a one-day encouragement intervention called “Fill the Racks!” was done by (Buckley et al., 2013) in Idaho, Moscow, in the fall of 2012. The travel mode share data of 3 elementary school (2 intervention and 1 control) students (n=475) were collected on five days; one day the week before the event, the day before the event, the day of the event, one day a week later, and one day two weeks after the event. The study found a significant increase in students AST on the event day, and unlike (Bungum et al., 2014), the effect of the event was sustained two weeks after the event. This sustained impact could be due to the fact that two other such AST encouragement events are organized in the schools the same year; “International Walk to School Day” or “iWalk” in fall and the “Polar Walk” in winter. In other words, the spring 38 event seemed to propel students to start walking or bicycling to school a little earlier than they might have otherwise. The review of present literature on encouragement STP program evaluation suggests the most promising results on increasing students' AST. The use of paid staff for organizing continuous WSBs programs in elementary schools could be an effective intervention in motivating students to use AST. The use of mobile applications in WSBs could also motivate parents to send their kids to schools in WSBs as they can keep real-time track of their children. The literature suggests the use of incentives and prizes can be another positive intervention. However, short term interventions, i.e., single day walk to school events, could have mixed results. It is appropriate to increase their time length or to make them a monthly affair. The key gap found in literature is the lack of research evaluating the effectiveness of a multiple approach (encouragement, education and enforcement) weeklong STP intervention on children’s AST to school. Also, no evaluation of a STP intervention has been done using the difference-in-differences approach. The findings of the study will help in evaluating the effectiveness of a multi STP strategies on children’s AST to school. 2.2 Mode Share Measurement Methods A variety of methods have been used in collecting the children’s mode share data to and from schools to evaluate the effectiveness of STP programs on children’s AST. These measurement methods involve self-report measures like counting the number of hands using different travel modes by teachers, program staff, and/or volunteers by simply going to classrooms at participating schools and asking students how they get to and from school (Builing et al., 2011, Mendoza et al., 2009, Macdonald, et al., 2013, Steer Davies Gleave, 2012, Hinckson et al., 2011 and Mammen et al.,2014), a self-reported in-class questionnaire filled by students 39 (Villa-gonzalez et al., 2015, Harvey et al., 2015, Mendoza et al., 2011, Hoelscher et al., 2016, McMinn et al., 2012, Lachapelle et al., 2012, Faulkner et al., 2014, Coombes et al., 2016, and Christiansen et al., 2014), and take home questionnaires filled by parents on information about their children’s travel mode (Ducheyne et al., 2014, Vanvolleghem et al., 2014, Goodman et al., 2016, Boarnet et al., 2007, and Mammen et al., 2014). Other methods involve objective measures like counting students by trained observers at the primary drop off and pick up locations at the schools using different travel modes (Buckley et al., 2013, Bungum et al., 2014, Rothmans et al. 2014, and Rothmans et al., 2016) and using technology in collecting students travel data like the use of radio-frequency identification (RFID) tags (Cuffe et al., 2012), students touching swipe cards at the sensors placed near school gates (Hunter et al., 2015) and mobile application (Martin et al., 2018) (Figure 12). Figure 12: Mode share measurement methods Two methods commonly used to measure school travel mode are family reported measures and Hands-Up counts (Sersli et al., 2019). However, (Sirard et al., 2005) noted the limitations of self-report measures, such as low survey response rates and recall bias, and have 40 promoted the use of objective measures such as observational counts. Also, (Suminski et al., 2006) assessed the reliability of observational counts and have found high values for inter-rater and test-retest reliability (i.e. coefficients greater than 0.9). However, each method has its strengths, limitations, and strategic use. Observational counts require no family or teacher participation, relieving schools of the burden of data collection. Also (Sersli et al., 2019) noted that observational counts are more advantageous particularly when a large number of schools are included in the research, especially across districts or cities, it may be more efficient to work with trained observers than to liaise and build partnerships in tens or hundreds of schools. However, weather conditions and poor sightlines due to narrow streets and idling vehicles may affect the data quality. The data may not be collected for students arriving or leaving schools out of the observation time window (e.g., 15 minutes before and after the school starts or ends), which could result in data bias. The Hands-up method is simple and inexpensive (de Wit et al., 2012). Researchers are not required to recruit additional manpower to collect data instead, data can be collected by teachers or school staff by giving them hour-long training. However, as the surveys are administered by teachers, there could be differences in the ways teachers conduct them across classrooms. Also, (McMinn et al., 2012) noted that teachers have busy schedules, and so an additional initiative to be implemented may be viewed as burdensome and, therefore, could be poorly delivered. The accuracy of the data may be subject to some variation across year groups and schools. For example, younger children might be inclined to ‘vote’ in the same way as their friends for want of not being seen as ‘different’ by their peers. This means certain modes are potentially under or over-represented (Steer Davies Gleave, 2012). Similarly, in-class 41 questionnaires have the advantage of administering the survey by teachers, but the influence of fellow students and data quality is the limitation. The family surveys can best provide data on child and family level determinants of travel behavior (Sersli et al., 2019). However, low response rates may limit their utility. Also, (Ragland et al., 2014) suggest the use of self-reported data from the parent survey is not a good substitute for actual counts of the modes by which children arrive at school. Studies that are aimed to assess the intervention at a classroom level, hands-up, or family surveys may be an appropriate method, but it is recommended not to use the hands-up method when large size classes or younger children are involved (Steer Davies Gleave, 2012). However, observational counts is an appropriate option when assessing an intervention at the school level. (Sersli et al., 2019) recommends using observational counts when multiple schools are involved and recommend using more than two observers at each school to overcome challenges due to poor sightlines, multiple entrances, restricted drop-off areas, or with large student populations. Other methods using technology (RFID, swipe cards) can generate reliable data, but the cost of implementation is an issue. 2.2.1 Data collection periods The present literature showed variations in the follow-up evaluation periods of the STP program’s impact on AST. Depending on how long the intervention was in effect and for how long after the intervention the impacts are assessed, researchers have used different follow-up periods from 1 day to 4 weeks (Buckley et al., 2013, Bungum et al., 2014, Sersli et al., 2019), from six weeks up to a year (McKee et al., 2007, Buliung et al., 2011, Hinckson et al., 2011, Mammen et al., 2014, Villa-gongalez et al., 2015, Ducheyne et al., 2014) and as long as three years (Hoelscher et al., 2016). 42 2.2.2 School selection parameters Different parameters for selecting intervention and control schools have been observed. However, the most commonly used parameters were that of socioeconomic factors, i.e., family income (Villa-gongalez et al., 2015, Mendoza et al., 2011, Hinckson et al., 2011, Christiansen et al., 2014, Mammen et al., 2014) which could be important as parent’s income could influence children’s travel mode (McDonald, 2008). Other factors found were the location (i.e., urban or rural) (McKee et al., 2007) as the built environment around the school could be a motivator in using AST (Frank et al., 2003). Some researchers used schools who are interested in having STP programs in their schools (Hunter et al., 2015, Buliung et al., 2011) and just by randomly selecting (Ducheyne et al., 2014). 2.3 Difference-in-Differences A difference-in-differences (DID) evaluation combines methods of simple difference analysis (measures the impact by comparing the post-treatment situation of those that participated in a program with a comparison group that did not) and pre-post analysis (measures the change in outcomes over time for participants of a program) to take into account both the differences between the two groups and changes over time. The effect is calculated by measuring the change over time for the treated group and the comparison group and then taking the difference between these two differences (Pomeranz, 2018). In the regression analysis, the DID model can is represented by the interaction term between the treatment group and the post-treatment period: Equation 1: Outcome Yit = α + β1 Ti + β2 postt + β3 Ti * postt + εit 43 where Yit represents the variable of interest for individual i in period t, Ti is a binary variable indicating whether or not individual i participated in the program, and postt is a binary variable indicating the period following the program, β3 is the difference-in-differences estimator and εit represents the error term. The DID estimation uses the change over time for the untreated group as the counterfactual for the change over time of the treated group (Bertrand et al., 2004). That is, it controls for all the characteristics that do not change over time (both observable and unobservable) and for all the changes over time that affect the treated and untreated group in the same manner (Figure 13). Figure 13: Logic and assumptions underlying the difference-in-differences The key assumption of DID is that without the program, the change over time would have been the same in both groups. This is often referred to as the common or parallel trend assumption. It is therefore important to have a longer time series to see whether the treatment and control groups evolved in parallel before the start of the treatment. The finding of a parallel 44 trend before and a difference after treatment gives credibility to the conclusion that the treatment caused the effect (Figure 14). Figure 14: Time series data to check for parallel trends between the treatment group and the control group before the start of the treatment The advantage of DID is that it controls for all the characteristics that do not change over time (both observable and unobservable) and for all the changes over time that affect the treated and untreated group in the same manner. It is typically impossible to assess whether the intervention group and control group are meeting the parallel trend assumption in the absence of treatment using the difference-in-differences approach. The results would have been biased if the intervention group would have had a different trend over time than the control group in the absence of treatment. (Pomeranz, 2018). 45 2.3.1 DID Examples A study by (Card et al., 1994) evaluated the impact of an increase in the minimum wage (the treatment) from $4.25 to $5.05 per hour on the employment (the outcome) in New Jersey using the DID method. The study surveyed 410 fast-food restaurants in New Jersey (the treatment group) and eastern Pennsylvania (the control group) before and after the rise in the minimum wage. The outcome equation was defined as Yit as the employment of a fast-food restaurant, Ti as an indicator of whether or not a restaurant is in New Jersey or Pennsylvania and postt as an indicator of whether the observation is from before or after the minimum wage hike (refer Equation 1) found no indication that rise in the minimum wage reduced the employment. Similarly, (Ngo et al., 2018) used the DID method to evaluate the impact of Comox-Helmcken Greenway (Comox Greenway) in Vancouver, Canada construction on energy use, and GHG emissions. The data were collected once before the intervention, i.e., time 1 (October 2012 – March 2013) and again after the greenway was open in June 2013, i.e., time 2 (October 2014 – March 2015). A total of 556 participants (239 = treatment group; living within 300m of the Comox Greenway and control group; and 285 = control group; living further than 300m of the Comox Greenway) data were analyzed. The outcome equation was defined as Yit as average daily energy or emission, Ti as an indicator, if the participant lives within 300m of Comox Greenway and postt as an indicator of whether the observation is from before or after the Comox Greenway construction (refer Equation 1), found 20.90 percent reduction in daily transportation GHG emissions due to greenway construction. A study by (Galiani et al., 2005) evaluated the impact of the privatization of water services on the mortality of children under age 5 in Argentina. The DID estimator equation was defined as Yit as the mortality rate in municipality ‘i’ in year ‘t’. Ti as an indicator If the 46 municipally has private service or not, postt as an indicator of whether the observation is from before or after the privatization of water services. The study found that child mortality fell by 8 per cent in the areas that privatized their water services. The present study applied the DID method to evaluate the UBC’s encouragement intervention on children’s AST. The mode share data at the baseline of the intervention and control schools were used with ‘children’s mode of travel’ defined as the dependent variable with group variables (schools) and time. The parallel trend assumption was met for analysis. 47 Chapter 3: Methodology The chapter is divided into four parts. The first part, details about the process of contacting the study schools, second, talks about the mode share data collection method, third, about the data analysis and fourth about the process of conducting the street audit (Figure 15). Figure 15: Overview of Methodology 3.1 Contacting the study schools To evaluate the effectiveness of the UBC’s WNR week, the study schools, i.e., schools with the WNR week program (intervention schools) and without WNR week (control schools), were contacted. As for the intervention, schools that were organizing the UBC’s WNR week were selected. The University Hill Elementary School and Norma Rose Point Elementary School have been organizing the UBC’s WNR week since 2013 and 2015, respectively. As for the control, schools not organizing UBC’s WNR week were selected. Other criteria for selecting the control schools included the size of the school, household income, and access to transit. Two schools, i.e., Sir Sandford Fleming Elementary School and Sir Matthew Begbie Elementary School, were selected. The UBC C+CP coordinator was responsible for coordinating between the UBC, UNA, and the schools. The coordinator was the nodal person in planning and designing the WNR week program in schools and was in communication with the study schools and the UNA. The coordinator of UBC C+CP contacted the study schools in August 2019. An email detailing the 48 study’s objective and data collection was sent to the principals of the intervention and control schools. The approval from the principals of all the four schools was received by September 2019 in the form of an electronic mail (Figure 16). Figure 16: Contacting study schools 3.2 Mode Share Data Collection The observational counts were carried at the four study schools to collect data on children’s mode of travel to school. The observational counts conducted were approved by the UBC’s Behavioral Research Ethics Board (BREB) with UBC BREB Number: H19-02534. A total of 11 observers were divided into four teams (each having 2 to 3 observers for every school). All the observers received a one-hour training session on conducting observational counts. The training was organized two weeks before the scheduled start of the counts. All the observers were given data collection kits which included observational counts tally forms (Appendix A), BREB certificate (Appendix B), a study information sheet (Appendix C), an orange vest and clipboard, and a training manual (Appendix D) after they receive the training 49 session. Every observer completed the Tri-Council Policy Statement (TCPS 2: Core) training online before doing the field observations (Figure 17). Figure 17: Mode share data collection Observational counts were conducted in four waves (Table 2). The children’s AST share in study schools during the WNR week i.e. wave 2 was compared with the baseline i.e. wave 1 (in the week before WNR week). The comparison informed on the immediate impact on AST due to WNR week. The counts in the week after the WNR week i.e. wave 3, informed on the short term impact of the WNR week on children’s AST. Finally, the counts after five weeks from WNR week i.e. wave 4, showed the sustained impacts of the WNR week. All the counts were conducted between 30 minutes before (i.e. 08:30 am), and 15 minutes after (09:15 am) the school entry bell i.e. 09:00 am. The observational counts between 08:30 am to 09:15 am are suitable as it captured the majority of the students arriving at schools starting 30 minutes before and 15 minutes after the school starts. All the counts were carried out on Thursdays. A trial observational count was conducted two days prior to the scheduled start of the counts i.e. October 15, 2019. The trial observational counts helped in identifying the best suitable observer locations at the schools to limit the obstructions caused by parked vehicles or trees. Also, the trial observations helped in letting the parents know beforehand about the study and counts. Parents who approached the observers were handed over the study information sheet and 50 were briefed about the observational counts. The trial survey helped observers in conducting counts without being asked questions by parents during the actual counts. Table 2: Observational Counts days Item Date Wave 1 (week before WNR week) October 17, 2019 (Thursday) Wave 2 (during WNR week) October 24, 2019 (Thursday) Wave 3 (week after the WNR week) October 31, 2019 (Thursday) Wave 4 (5 weeks after WNR week) November 28, 2019 (Thursday) The observers counted the number of children using different active modes (walk, bicycle, skateboard, scooter, rollerblades, and tricycle) and car to reach school. Also, only if the student was seen coming out of the car was counted for car mode, otherwise they were observed as a walker. Also, students whose mode of travel was not seen were not counted like students in the playground. All observers reached their schools 15 minutes before the start of counts i.e. 08:15 am to meet other observers and to do a walk around to get a feel for the situation at that school. Two observers conducted the observational counts at the University Hill Elementary School, and three each at Norma Rose Point, Sir Sandford Fleming and Sir Matthew Begbie elementary schools (Figure 18, Figure 19, Figure 20, and Figure 21). Each observer was assigned a specific entry gate to school to avoid the double counting. 51 Figure 18: Location of observers at University Hill Elementary School Figure 19: Location of observers at Norma Rose Point Elementary School 52 Figure 20: Location of observers at Sir Sandford Fleming Elementary Figure 21: Location of observers at Sir Matthew Begbie Elementary School 53 Weather The weather on the first wave i.e. October 17, 2019, was rainy with a wind speed of 19.6 km/hr and a temperature of 10.9 °C. On the following waves, there was not much variation in the wind speeds, and it remained between 8.0 to 8.6 km/hr; however, the temperature dropped considerably in the waves 2 to 4 from 10.3 °C in wave 2, 5.4 °C and to 0.5 °C in wave 4. The conditions were cloudy on wave 2 and 3 and were clear on wave 4 (Table 3). Table 3: Weather information on observation days at Vancouver International Airport Date Temperature (°C) Wind Speed (km/hr) Conditions October 17, 2019 10.9 19.6 Rain October 24, 2019 10.3 8.6 Cloudy October 31, 2019 5.4 8.0 Cloudy November 28, 2019 0.5 8.3 Clear Source: https://climate.weather.gc.ca/ & Counts observers Daylight The duration of daylights decreased continuously from wave 1 (October 17, 2019) to wave 4 (November 28, 2019). In wave 1, the daylight duration was 10 hrs 42 mins, which reduced to 8 hrs 32 mins in wave 4 (Table 4). All the data collection observations were taken after sunrise across all four waves. 54 Table 4: Daylight timings on observation days in Vancouver, BC Date Sunrise Sunset Day Length October 17, 2019 07:36 am 06:18 pm 10 hrs 42 mins October 24, 2019 07:47 am 06:05 pm 10 hrs 17 mins October 31, 2019 07:58 am 05:52 pm 9 hrs 54 mins November 28, 2019* 07:42 am 04:18 pm 8 hrs 32 mins Source: https://www.timeanddate.com/ *Daylight Saving Time ended Issue and challenges faced The observers found counting modes on wave 1 difficult due to weather conditions. The high wind speed and rain made it difficult to fill the count tally forms. Some observers noted that it was particularly challenging to stand to hold an umbrella and clipboard while observing children’s travel modes. Extra attention was required to note the mode of children who were being dropped by their parents’ car at a distance from school gates. Also, poor sightlines due to idling vehicles at the school gates made it difficult to observe some students. Some students were observed coming to school before the observation started i.e. 8:30 am. 3.3 Data Analysis The Difference - in - Differences method was applied to estimate the impact of the UBC’s WNR week program on children’s mode of travel to school. The data tally forms from all the four waves were collected and digitized for analysis. The logistic regression analyses were carried out using STATA (version 16). The outcome equation for regression was defined as Yit as dummy dependent variable, i.e., mode of travel, active mode (walk, bicycle, skateboard, scooter, rollerblades, and tricycle) =1 and otherwise=0. The Yit represents the variable of interest for 55 individual i in period t, Ti is a binary variable indicating whether or not individual i participated in the program, and postt is a binary variable indicating the period following the program, β3 is the difference-in-differences estimator and εit represents the error term. The comparison of the dummy time variable was carried out in three pairs. First, to compare the change in WNR week and baseline, i.e., wave 1 with wave 2=1 and wave 1=0 to see the immediate impact. Second, to see the short-term impact of WNR week i.e., comparison with wave 3 with wave 2=1 and wave 3=0, and third, to see the sustained impact of WNR week with wave 4 with wave 2=1 and wave 4=0. As the sustained impact of WNR week is estimated in separate pairwise comparisons, it is implicit that comparison between wave 1 and wave 4 has already been carried out and no comparison was necessary between wave 1 and wave 4. The intervention effect term used for each comparison was Ti * postt. Outcome equation: Yit = α + β1 Ti + β2 postt + β3 Ti * postt + εit The syntax command used in STATA for carrying out logistic regression was ‘logit mode school period interaction’ defined as the name of the dependent variable i.e. ‘mode’ of travel used by children, followed by the names of the independent variables i.e. ‘school’ (intervention or control school) and ‘period’ (during WNR week or not) and the ‘interaction,’ i.e. between ‘school’ and ‘period’. 56 Chapter 4: Results 4.1 Observational counts On average, 1614 students were observed during each wave, both in the intervention and control schools. On average, 922 students in the intervention and 692 students in the control schools were observed in the four waves of data collection ( Table 5). The maximum number of students in the intervention schools were observed during the WNR week i.e. 987 across four data collection days. The least number of students, 887, were observed five weeks after the WNR week in the intervention schools. The number of students in the control schools remained stable across the four data collection days. The maximum number of students were observed in the week after WNR week. i.e. 719 and the least a week before WNR week i.e. 674. Table 5: Number of students observed Data Period Intervention Schools Control Schools Total Wave 1 (week before WNR week) 906 674 1580 Wave 2 (during WNR week) 987 696 1683 Wave 3 (week after the WNR week) 908 719 1627 Wave 4 (5 weeks after WNR week) 887 678 1565 Average 922 692 1614 4.1.1 Walking Figure 22 shows the walking share of the total counts in the intervention and control schools across the four waves. The collected data suggested an increase in walking in both 57 intervention and control schools during the WNR week. The share of walking increased by 6.9 and 11.2 percentage points from the baseline (wave 1) in intervention and control schools respectively. However, walking share dropped in the week following WNR i.e. in wave 3. There was a reduction of 4.8 and 5.6 percentage points in intervention and control schools, respectively. The reduction in walking share further dropped after five weeks following the WNR week i.e. 5.8 and 6.8 percentage points in intervention and control schools respectively. Figure 22: Walking share in study schools across four waves Figure 22 shows the school wise walking share of the total counts. The data showed an increase in walking share in both the intervention schools. There was an increase of 9.8 and 5.8 percentage points in the Norma Rose Point and University Hill Elementary schools respectively. However, there was a reduction in walking share in both intervention schools in wave 3. The walking share reduced by 3.1 and 9.3 percentage points in the Norma Rose Point and University 58 Hill Elementary schools respectively. There was a reduction of 8.8 and 2.8 percentage points from wave 2 in Norma Rose Point and University Hill Elementary schools, respectively after five weeks following WNR week. A similar trend was observed in the walking share of control schools. An increase of 15.7 and 3.9 percentage points in wave 2 in comparison with baseline i.e. wave 1 was observed in Sir Sandford Fleming and Sir Matthew Begbie elementary schools, respectively. Also, a reduction of 8.4 and 1.2 percentage points in comparison with wave 2 was found in wave 3 in Sir Sandford Fleming and Sir Matthew Begbie elementary schools respectively. Further reduction in control schools was found in wave 4 by 7.2 and 5.6 percentage in comparison with wave 2. Also, more than half of the total students observed in the control schools were already walking to schools. Figure 23: School wise walking share in schools across four waves 59 4.1.2 Bicycling Figure 24 shows the share of children using bicycles and other active modes i.e. scooter, skateboards, and rollerblades of the total counts in the intervention and control schools across the four waves. As the number of children using scooters, skateboards, and rollerblades was very small, they were combined with bicycle and referred to as ‘bicycle’ only (Appendix E). The share of bicycles increased during WNR week by 6.8 and 0.9 percentage points in intervention and control schools respectively from the baseline i.e. wave 1. However, the share dropped in the wave 3 by 3.8 percentage points in intervention and 0.5 percentage points in control schools. In wave 4, i.e. five weeks after the WNR week, the share further dropped and was returned to baseline i.e. wave 1 share. Figure 24: Bicycling share in study schools across four waves 60 Figure 25 shows the school wise bicycling share of the total counts. The data showed an increase in bicycling share in both the intervention schools. There was an increase of 4.8 and 10.1 percentage points in the Norma Rose Point and University Hill Elementary schools respectively. However, there was a reduction in bicycling share in both intervention schools in wave 3. The bicycling share reduced by 3.2 and 4.6 percentage points in the Norma Rose Point and University Hill Elementary schools respectively. There was a reduction of 7.9 and 6.7 percentage points from wave 2 in Norma Rose Point and University Hill elementary schools after five weeks following WNR week. A similar trend was observed in the bicycling share of control schools. However, the share of bicycling of the total counts in control schools was very low. Figure 25: School wise bicycling share in schools across four waves 61 4.1.3 Car Figure 26 shows the car share of the total counts in the intervention and control schools across the four waves. The collected data suggested a reduction in car usage during the WNR week by 13.8 and 12.1 percentage points in the intervention and control schools respectively. Also, during the WNR week, the weather conditions were favorable to walking and bicycling with no rain and lower wind speed as compared with wave 1. The car share increased in the week after the WNR week by 8.6 percentage points in intervention and 6.1 percentage points in control schools. In the five weeks after the WNR week, the car-share increased by 4.7 and 7.5 percentage points in intervention and control schools respectively, however, the car-share reduced when compared with the baseline by 9.1 percentage points in intervention and 4.6 percentage points control schools. The reduction in car share in wave 4 when compared with baseline could be due to clear weather conditions in wave 4. 62 Figure 26: Car share in study schools across four waves Error! Reference source not found. shows the school wise car share of the total counts. The data showed a reduction in car share in both the intervention schools. There was a reduction of 14.7 and 15.9 percentage points in the Norma Rose Point and University Hill Elementary schools respectively. However, there was an increase in car share in both intervention schools in wave 3. The car share increased by 6.4 and 13.9 percentage points in the Norma Rose Point and University Hill Elementary schools respectively. There was an increase of 3.8 and 9.5 percentage points from wave 2 in Norma Rose Point and University Hill Elementary schools respectively after five weeks following WNR week. A similar trend was observed in the car share of control schools. A reduction of 16.8 and 4.2 percentage points in wave 2 in comparison with baseline i.e. wave 1 was observed in Sir Sandford Fleming and Sir Matthew Begbie elementary schools respectively. However, an 63 increase in car share was found in waves 3 and 4. The car share of the total counts increased by 9 and 1.1 percentage points in Sir Sandford Fleming and Sir Matthew Begbie elementary schools respectively in wave 3 in comparison with wave 2. Similarly, the chare share increased by 8 and 5.9 percentage points in Sir Sandford Fleming and Sir Matthew Begbie elementary schools respectively in wave 4 in comparison with wave 2 Figure 27: School wise car share in schools across four waves 4.2 Statistical analysis Table 6 shows the Difference – in – Differences analysis results for children’s active modes share i.e. walk and bicycle across the four waves of data collection. To evaluate the impact of WNR week on children’s active travel mode to school, attention is given to the interaction effect term (group * time). 64 4.2.1 Walking In wave 2 & 1, the students in the intervention schools were significantly less likely to walk than students in the control schools (p=0.001). Also, students in wave 2 i.e. during the WNR week are significantly more likely to walk than in wave 1 i.e. during the week before the WNR week (p=0.001). However, no statistically significant impact of the intervention (group and time) was found on the walking share of students between waves 1 and 2 (p=0.19). In wave 2 & 3, students in the intervention schools were significantly less likely to walk than in control schools (p=0.001). Also, students in wave 2 were significantly more likely to walk than in wave 3 i.e. week after the WNR week (p=0.03). However, no statistically significant impact of the intervention (group and time) was found on the walking share of students between waves 2 and 3 (p=0.74). Similarly, no statistically significant impact of the intervention (group and time) was found on the walking share of students between waves 2 and 4 i.e. five after the WNR week (p=0.70). 4.2.2 Bicycling In wave 2 & 1, the students in the intervention schools were significantly more likely to bicycle than students in the control schools (p=0.001). However, students in wave 2 were significantly not likely to bicycle than in wave 1 week (p=0.35). Also, no statistically significant impact of the intervention (group and time) was found on the bicycling share of students between waves 1 and 2 (p=0.98). In wave 2 & 3, students in the intervention schools were significantly more likely to bicycle than in control schools (p=0.001). However, students in wave 2 were significantly not likely to walk than in wave 3 (p=0.30). However, no statistically significant impact of the intervention (group and time) was found on the bicycling share of students between waves 2 and 3 (p=0.58). Similarly, no statistically significant impact (p<0.05) of the intervention 65 (group and time) was found on the bicycling share of students between waves 2 and 4 i.e. five after the WNR week (p=0.08). 4.2.3 Active Modes (walk and bicycle) In wave 2 & 1, the students in the intervention schools were significantly less likely to use active modes than students in the control schools (p=0.05). Also, students in wave 2 were significantly more likely to use active modes than in wave 1 (p=0.001). However, no statistically significant impact of the intervention (group and time) was found on the active modes share of students between waves 1 and 2 (p=0.70). In wave 2 & 3, students in the intervention schools were significantly less likely to walk than in control schools (p=0.001). Also, students in wave 2 were significantly more likely to use active modes than in wave 3 i.e. week after the WNR week (p=0.02). However, no statistically significant impact of the intervention (group and time) was found between waves 2 and 3 (p=0.51). Similarly, no statistically significant impact of the intervention (group and time) was found on active modes share of students between waves 2 and 4 i.e. five after the WNR week (p=0.40). No statistically significant impact was observed across all three models (Wave 2 & 1, Wave 2 & 3, and Wave 2 & 4) for walking, bicycling, and combination walking and bicycling modes. No statistically significant differences were found between active modes shares patterns of the intervention and control schools across the 4 observation waves. 66 Table 6: Logistic regression model of children’s active travel modes Mode Wave 2 & 1 Wave 2 & 3 Wave 2 & 4 β SE P β SE P β SE P Walk Group (1=Intervention) -0.53 0.10 0.001 -0.67 0.10 0.001 -0.66 0.10 0.001 Time (1=Wave 2) 0.47 0.11 0.001 0.24 0.11 0.030 0.29 0.11 0.010 Intervention Effect (Group X Time) -0.19 0.15 0.190 -0.05 0.14 0.740 -0.05 0.15 0.700 Bicycle Group (1=Intervention) 2.98 0.59 0.001 3.40 0.58 0.001 4.86 1.00 0.001 Time (1=Wave 2) 0.66 0.70 0.350 0.73 0.70 0.300 1.77 1.08 0.100 Intervention Effect (Group X Time) 0.02 0.72 0.980 -0.39 0.72 0.580 -1.85 1.08 0.080 Active modes (walk and bicycle) Group (1=Intervention) -0.20 0.10 0.050 -0.24 0.10 0.020 -0.02 0.10 0.850 Time (1=Wave 2) 0.51 0.11 0.001 0.27 0.11 0.020 0.33 0.11 0.440 Intervention Effect (Group X Time) 0.06 0.15 0.700 0.10 0.15 0.510 -0.13 0.15 0.400 67 Chapter 5: Pedestrian and Bicycling Facility Audit The chapter describes the method used and findings of an audit of pedestrian and bicycling infrastructure near the intervention schools i.e. Norma Rose Point and University Hill Elementary Schools. Research has found safety near schools as an important factor in parents’ decision of their children AST usage (Panter et al., 2013). The audit was a standalone exercise and had no relation to the WNR week analysis. The observations from the audit were recorded, and infrastructure improvements are proposed to remove physical barriers to AST usage. In Canada, over half of the children aged between 5 to 17 years rely solely on inactive modes of transportation to and from school (Craig et al., 2001). The most commonly reported barriers to AST given by parents to involve student safety, in particular traffic speeds, traffic volume, and lack of sidewalks (Chaufan et al., 2012). The engineering related improvements in the school's zones that increase pedestrian and bicycle safety may also influence AST rates among children (Ragland et al., 2014). Researchers have found reductions in pedestrian injuries and crash among school children near traffic improvements under the SRTS program in the US (DiMaggio et al., 2013) and a significant increase in children’s AST(McDonald et al., 2013). It is therefor, critical to address the physical barriers to AST near the schools to increase AST rates. Walking and bicycling infrastructure audit tools can help identify key intersections or areas where physical and environmental changes could assist in improving opportunities to be more physically active. The factors important to making an active travel-friendly environment include, but are not limited to, street lighting, sidewalk width and condition, traffic volume, presence of bicycle lanes, topography, and presence of dogs, trash, and debris (Safe Routes to School, 2019). There are various assessment tools ( Table 7) available to identify and address barriers to active travel infrastructure and vary based on the scope of the evaluation, length, 68 questions asked, complexity, and audience intended for. These tools are further detailed in this section. Table 7: Street Audit Tools Assessment Tool Author (Year) Potential Users Summary Active Neighborhood Checklist - Protocol, Version 2.0 Washington University of St. Louis (2011) Community members, researchers This is an observational tool designed to assess key street-level features of the neighborhood environment that are thought to be related to physical activity behavior. Walk Audit Tool Kit AARP (2016) Community members This toolkit focuses on crossings, sidewalks, safety, and comfort and appeal, and provides an overall rating system. The toolkit also includes proposed solutions, and there is a separate leaders’ guide that is a companion piece. 69 Healthy and Complete Communities in Delaware: The Walkability Assessment Tool Institute for Public Administration, University of Delaware (2010) Technical practitioners like engineers, planners, government agency staff, researchers The tool involves a three-step process designed to aid local governments in determining their town’s walkability Microscale Audit of Pedestrian Streetscapes (MAPS) Abbreviated Version The University of California, San Diego (2014) Researchers, technical practitioners (Engineers, planners, the government agency staff, etc.) The Microscale Audit of Pedestrian Streetscapes (MAPS) has a beginner, intermediate, and advanced version. This is the intermediate version, which is intended to be used by people with some level of technical knowledge but is much shorter than the full version of MAPS. Walkability and Bikability Checklist National Centre for Safe Routes to School Safe Routes to School A simple one-page questionnaire with five (walkability) and six (bikablity) questions, and a 1 to 6 scale for each one. Add up rankings to get a score based out of 30 points total. 70 Audience (school boards, municipality), community members Community Walking and Bicycling Audit Tool Wisconsin Partnership for Activity and Nutrition (2012) Community members, researchers The tool asks 25 questions on different characteristics like land use environment, transportation facilities, walking and bicycling environment and aesthetics and allows the observer to score them a) Active Neighborhood Checklist - Protocol, Version 2.0, Washington University of St. Louis, 2011: The Active Neighborhood Checklist is 3 pages observational tool designed to assess key street-level features of the neighborhood environment that are thought to be related to physical activity behavior. The data collected can be used to generate data for a needs assessment or research, to raise community awareness about the role of the environment in supporting or discouraging physical activity, or to mobilize community members to advocate for change. Its simple format, lay terminology, item specificity, and relatively short length were intended to make the tool user-friendly for multiple community stakeholders. The Checklist assesses five general areas: land use, public transit stops, street characteristics, quality of the environment for a pedestrian, and places to walk and bicycle. An area for note-taking follows each section to allow auditors to describe features or perceptions that may not 71 be captured in the tool. Mostly a checklist with yes/no answers and some space for taking notes are provided. b) Walk Audit Tool Kit, AARP, 2016: It is 6 pages document intended to be used by the community members and focuses on crossings, sidewalks, safety, and comfort and appeal, and provides an overall rating system. The toolkit also includes proposed solutions, and there is a separate leaders’ guide that is a companion piece. c) Healthy and Complete Communities in Delaware: The Walkability Assessment Tool, Institute for Public Administration, University of Delaware, 2010: The tool involves a three-step process designed to aid local governments in determining their town’s walkability. The first step is the ‘pre-assessment questionnaire’ which is intended to help answer the “who, what, why, and how” questions related to evaluating the walkability of an area or specific neighborhood within a jurisdiction. It requires thoughtful consideration of who will be responsible for conducting the assessment and what will be done with the assessment results. The second step is an “in-the-field” assessment checklist designed to rate specific walkability elements of a defined area within the municipality. These elements include the condition and maintenance of walking facilities (e.g., sidewalks, curbs), pedestrian amenities, safety, and destinations available within the area. The third step is designed to help analyze the results of the first two steps and identify major issues and problem areas. It provides an opportunity to summarize results, consider potential changes, and identify the next steps in improving the overall walkability of the town or city. It is intended to be used by the technical practitioners like engineers, planners, government agency staff, etc. 72 d) Walkability and Bikability Checklist, National Centre for Safe Routes to School: It is a one-page questionnaire with five questions (walkability) and six questions (bikability) and a 1-6 scale for each one intended to be used by Safe Routes to School Stakeholders like school boards, municipality and, community members to assess walking and bicycling environment. The points out of a total of 30 points can be calculated from basic questions like ‘Did you have room to walk?’, ‘Was it easy to cross streets?’, ‘Did drivers behave well?’, ‘Was it easy to follow rules?’, ‘Was your walk pleasant?’, ‘Did you have a place to bicycle safely?’, ‘How was the surface you rode on?’, ‘How were the intersections you rode through?’, ‘Did drivers behave well’, ‘Was it easy for you to use your bikes?’ and ‘What did you do to make your ride safer?’. The checklist also includes a list of actions to be taken to improve your neighborhood walkability based on the score for each question. e) Microscale Audit of Pedestrian Streetscapes (MAPS) Abbreviated Version, University of California, San Diego, 2014: It is a four pages tool intended to be used by Researchers, Technical (engineers, planners, government agency staff, etc.) to collect audit data on the pedestrian environment and walkability in neighborhoods. The tool has two other versions, a ‘mini’ version intended for practitioner, advocacy, and community member use and a ‘full’ version, which is a detailed tool intended to be used by researchers. f) Community Walking and Bicycling Audit Tool, Wisconsin Partnership for Activity and Nutrition, 2012: It is an 11-page document intended to be used by the community members and researchers. The tool asks 25 questions on different characteristics like land use environment, transportation facilities, walking, and bicycling environment, and aesthetics and allows observers to score them. A total score of 100 points can be calculated (each question with 4 points max; 0 for poor/none and 4 for a lot/excellent). Three additional 73 questions asking about walking, bicycling, and speed limits asked. One big advantage of the tool is to quantitatively assess the physical conditions of the street or route. 5.1 Audit of UBC elementary schools The pedestrian and bicycling facility audit was carried out along the designated ‘walking school bus’ routes (Figure 28). Two WSB routes were operated by parent volunteers during the WNR week. The total length of the corridor audited was 4.29 km (Table 8). The Active Neighborhood Checklist – Version 2.0 (Washington University of St. Louis, 2011) was adopted for the audit. The tool is used to assess key street-level features of the neighborhood environment that are thought to be related to physical activity behavior. Figure 28: Segments for street audit 74 The audit was conducted on foot between March 6 and 7, 2020 from 10 am to 2 pm. The weather was clear with bright light conditions. The copies of the audit form (15; each for a segment and five extra), google image of each segment, clipboards, and pencil were taken. The images were captured using the mobile camera. Both sides of each segment were audited. The filled audit forms were then collated to gather information. 75 Table 8: Street Audit Segments Segments # Intersection b/w Intersection b/w Length (m) 1 Theology Mall & Iona Drive Iona drive & Wesbrook Mall 190 2 Iona drive & Wesbrook Mall Wesbrook Mall & Chancellor Blvd 122 3 Wesbrook Mall & Chancellor Blvd Chancellor Blvd & Acadia Road 485 4 Chancellor Blvd & Acadia Road Chancellor Blvd & Hamber Road 286 5 Chancellor Blvd & Acadia Road Acadia Road & College Highroad 458 6 Acadia Road & College Highroad Acadia Road & Toronto Road 440 7 Acadia Road & Toronto Road Acadia Road & Melfa Road 532 8 Acadia Road & Melfa Road Thunderbird Blvd & Osoyoos Crescent 745 9 Thunderbird Blvd & Osoyoos Crescent Fairview Place & Acadia Road 292 10 Thunderbird Blvd & Osoyoos Crescent Thunderbird Blvd & Larkin Drive 740 Total 4290 76 5.2 Findings The pedestrian and bicycling facility audit was carried out along the designated WSB route. The total length of the corridor audited was 4.3 km. The Active Neighborhood Checklist – Version 2.0 was adopted for the audit. Segment 1: From intersection b/w Theology Mall & Iona Drive to intersection, b/w Iona drive & Wesbrook Mall Source: Google Earth Figure 29: Segment 1 - From intersection b/w Theology Mall & Iona Drive to intersection, b/w Iona drive & Wesbrook Mall 77 A B Figure 30: Street view of location A and B at segment 1 Land use: The residential and educational buildings are present on both sides of the segment. The residential buildings are primarily condominiums between 1 to 4 stories. The educational buildings include the Vancouver School of Economics and Saint Mark’s College and Church. There is on-street parking and a small parking lot (less than 30 spaces) available as well as underground parking for the residential buildings. Public transportation: There are no transit stops in this segment. Street characteristics: The segment is a narrow shared street with a posted speed limit of 30 km/hr. It is a two-lane street with no marking. There are no traffic calming measures present in the segment. Quality of environment: The segment has no commercial buildings adjacent to the sidewalk. There is also no availability of benches and water fountains. One pool is located in the residential apartment buildings and can be seen from the sidewalk. 78 Walking and bicycling facility: The sidewalks are present both sides of the segment with no buffer b/w the curb and sidewalk. The sidewalk is not continuous on one side. No major bumps or permanent obstruction was observed. There is no dedicated bike lane along the segment. Suggested treatments: • Addition of road marking between lanes. Segment 2: From intersection b/w Iona drive & Wesbrook Mall to intersection b/w Wesbrook Mall & Chancellor Blvd Source: Google Earth Figure 31: Segment 2 - From intersection b/w Iona drive & Wesbrook Mall to intersection b/w Wesbrook 79 A B Figure 32: Street view of location A and B at segment 2 Land use: The single-family homes are located on the east and north-west of the segment. There is a small parking lot (less than 30 spaces) on the west, which is mainly used by the people coming to Saint Mark’s College and Church. Public transportation: There are no transit stops in this segment. Street characteristics: The segment is a narrow shared street with a posted speed limit of 30 km/hr. It is a two-lane street with a yellow division marking. The segment has a crosswalk marking and stop signage at the intersection. Quality of environment: The segment has no commercial buildings adjacent to the sidewalk. There is also no availability of benches and water fountains. The trees along the segment provide a good amount of shade. The slope of the segment is flat. 80 Walking and bicycling facility: The sidewalk is present only on one side of the segment with no buffer b/w the curb and sidewalk. The sidewalk is continuous on one side. No major bumps or permanent obstruction was observed. There is no dedicated bike lane along the segment. Suggested treatments: • Addition of sidewalk on the east side of the segment. Segment 3: From intersection Wesbrook Mall & Chancellor Blvd to intersection b/w Chancellor Blvd & Acadia Road Source: Google Earth Figure 33: Segment 3 - From intersection Wesbrook Mall & Chancellor Blvd to intersection b/w Chancellor 81 A B C Figure 34: Street view of location A, B and C at segment 3 Land use: The segment has single-family on both sides with no availability of parking on either side. Public transportation: There are transit stops available on both sides. Street characteristics: The segment is an arterial road with a posted speed limit of 50 km/hr. It is a four-lane road with a buffered with a tree median. The segment does not have a crosswalk marking and stop signage at the intersection. Quality of environment: There is construction being done in 3 three houses along the segment. There is also no availability of benches and water fountains. The trees along the segment provide a lot of shade. The slope of the segment is flat. Walking and bicycling facility: The sidewalk is present on both sides of the segment with trees buffer b/w the curb and sidewalk. The sidewalk is continuous on both sides. Due to construction, some part of the segment is difficult to walk. No major bumps or permanent obstruction was observed. There are marked dedicated bike lanes along the segment. Suggested treatments: • Addition of crosswalk markings. 82 • Removal of construction debris from the sidewalk. Segment 4: From intersection Chancellor Blvd & Acadia Road to intersection b/w Chancellor Blvd & Hamber Road Source: Google Earth Figure 35: Segment 4 - From intersection Chancellor Blvd & Acadia Road to intersection b/w Chancellor Blvd & Hamber Road 83 A B Figure 36: Street view of location A and B at segment 4 Land use: The segment has a single-family home and Pacific Spirit Regional Park on the south with UEL Office and UEL Public Works Yard on the north. Public transportation: There is one transit stop available on the north side of the segment. Street characteristics: The segment is an arterial road with a posted speed limit of 50 km/hr. It is a four-lane road with a buffered tree median. The segment does not have a crosswalk marking and stop signage at the intersection. Quality of environment: There is no availability of benches and water fountains. The trees along the segment provide a lot of shade. The slope of the segment is flat. Walking and bicycling facility: The sidewalk is present on both sides of the segment with trees buffer b/w the curb and sidewalk. The sidewalk is continuous on both sides. No major bumps or permanent obstruction was observed. There are marked dedicated bike lanes along the segment. Suggested treatments: • Addition of crosswalk markings. 84 Segment 5: From intersection Chancellor Blvd & Acadia Road to intersection b/w Acadia Road & College Highroad Source: Google Earth Figure 37: Segment 5 - From intersection Chancellor Blvd & Acadia Road to intersection b/w Acadia Road & College Highroad 85 A B C Figure 38: Street view of location A, B and C at segment 5 Land use: The segment has single-family homes and multi-unit homes (2-4 units) on both sides of the segment with no on-street parking. Public transportation: There is no transit stop available on the segment. Street characteristics: The segment is a narrow shared street with a posted speed limit of 30 km/hr. It is a two-lane street with no division marking. The segment has a crosswalk marking and stop signage at the intersection. Quality of environment: There is no availability of benches and water fountains. The trees along the segment provide a lot of shade. The slope of the segment is flat. Walking and bicycling facility: The sidewalk is present on both sides of the segment with trees buffer b/w the curb and sidewalk. The sidewalk is continuous on both sides. No major bumps or permanent obstruction was observed. There are no marked dedicated bike lanes along the segment. Suggested treatments: • Addition of lane division marking. • Addition of bike lane marking. 86 Segment 6: From intersection b/w Acadia Road & College Highroad to intersection b/w Acadia Road & Toronto Road Source: Google Earth Figure 39: Segment 6 - From intersection b/w Acadia Road & College Highroad to intersection b/w Acadia Road & Toronto Road 87 A B Figure 40: Street view of location A and B at segment 6 Land use: The segment has single-family homes, multi-unit homes (2-4 units) and condominiums (more than 4 units and 1-4 stories) on both sides of the segment with no on-street parking. Public transportation: There is no transit stop available on the segment. Street characteristics: The segment is a narrow shared street with a posted speed limit of 30 km/hr. It is a two-lane street with no division marking. The segment has a crosswalk marking and stop signage at the intersection. Quality of environment: There is no availability of benches and water fountains. The trees along the segment provide a lot of shade. The slope of the segment is flat. Walking and bicycling facility: The sidewalk is present on both sides of the segment with trees buffer b/w the curb and sidewalk. The sidewalk is continuous on both sides. No major bumps or permanent obstruction was observed. There are no marked dedicated bike lanes along the segment. Suggested treatments: 88 • Addition of lane division marking. • Addition of bike lane marking. Segment 7: From intersection b/w Acadia Road & Toronto Road to intersection b/w Acadia Road & Melfa Road Source: Google Earth Figure 41: Segment 7 - From intersection b/w Acadia Road & Toronto Road to intersection b/w Acadia Road & Melfa Road 89 A B C Figure 42: Street view of location A, B and C at segment 7 Land use: The segment has Acadia Park residence consisted of condominiums (more than 4 units and 1-4 stories) and a community center on the west side and, multi-unit homes (2-4 units) on the south-east side. There is on-street parking available on both sides. Public transportation: There is no transit stop available on the segment. Street characteristics: The segment is a narrow shared street with a posted speed limit of 30 km/hr. It is a two-lane street with yellow line division marking. The segment has a crosswalk marking and stop signage at the intersection. Quality of environment: There is no availability of benches and water fountains. The trees along the segment provide a lot of shade. The slope of the segment is flat. There is construction in progress for a residential apartment building on the west side. Walking and bicycling facility: The sidewalk is present on both sides of the segment with trees buffer b/w the curb and sidewalk on one side. The sidewalk is continuous on both sides. Due to construction, some part of the segment of one side is not open for walking. There are no marked dedicated bike lanes along the segment. Suggested treatments: 90 • Addition of lane division marking. • Addition of bike lane marking. Segment 8: From intersection b/w Acadia Road & Melfa Road to intersection b/w Thunderbird Blvd & Osoyoos Crescent Source: Google Earth Figure 43: Segment 8 - From intersection b/w Acadia Road & Melfa Road to intersection b/w Thunderbird Blvd & Osoyoos Crescent 91 A B C Figure 44: Street view of location A, B and C at segment 8 Land use: The segment has single-family homes, multi-unit homes (2-4 units) and condominiums (more than 4 units and 1-4 stories) on both sides of the segment with on-street parking. There are an elementary school on the east side and child care services. Public transportation: There is no transit stop available on the segment. Street characteristics: The segment is a narrow shared street with a posted speed limit of 30 km/hr. It is a two-lane street with yellow line division marking. The segment has a crosswalk marking and stop signage at the intersection. Quality of environment: There is a playground with recreation equipment and a child care service along the segment. The trees along the segment provide a lot of shade. The slope of the segment is flat. Walking and bicycling facility: The sidewalk is present on both sides of the segment without buffer b/w the curb and sidewalk on one side. The sidewalk is continuous on both sides. No major bumps or permanent obstruction was observed. There are marked dedicated bike lanes along the segment. Suggested treatments: 92 • Re-painting of bike lanes and crosswalks. Segment 9: From intersection b/w Thunderbird Blvd & Osoyoos Crescent to intersection b/w Fairview Place & Acadia Road Source: Google Earth Figure 45: Segment 9 - From intersection b/w Thunderbird Blvd & Osoyoos Crescent to intersection b/w Fairview Place & Acadia Road 93 A B C Figure 46: Street view of location A, B and C at segment 9 Land use: The segment has Fairview and Acadia Park Residences both consisted of condominiums (more than 4 units and 1-4 stories) on the north side. The segment has large parking on the south side. Public transportation: There is no transit stop available on the segment. Street characteristics: The segment is a narrow shared street with no vehicular cross through. The segment has a crosswalk marking and stop signage at the intersection. Quality of environment: There are small playgrounds on both sides of the segment with benches and recreational equipment. The trees along the segment provide a lot of shade. The slope of the segment is flat. Walking and bicycling facility: The sidewalk is present on both sides of the segment with trees buffer b/w the curb and sidewalk on one side. The sidewalk is continuous on both sides. 94 Segment 10: From intersection b/w Thunderbird Blvd & Osoyoos Crescent to intersection b/w Fairview Place & Acadia Road Source: Google Earth Figure 47: Segment 10 - From intersection b/w Thunderbird Blvd & Osoyoos Crescent to intersection b/w Fairview Place & Acadia Road A B C D Figure 48: Street view of location A, B, C and D at segment 10 Land use: The segment has a mix of residential, institutional, and office buildings on both sides. The residential part consists of UBC’s Thunderbird student residence (more than 4 units, 1-4 95 stories) and multi-unit homes and condominiums (more than 4 stories). On the north, there is a Thunderbird parkade of 4 levels and large (more than 30 spaces) off street parking lot. Public transportation: There are transit stops available on the segment. Street characteristics: The segment is a shared street with a posted speed limit of 30 km/hr. It is a two-lane street with yellow line division marking. The segment has a crosswalk marking and stop signage at the intersection. Quality of environment: On the west-south, there is Jim Taylor Park and Old Barn Community Centre. Towards the north of the segment, there UBC skate park. The trees along the segment provide a lot of shade. The slope of the segment is flat. Walking and bicycling facility: The sidewalk is present on both sides of the segment with trees buffer b/w the curb and sidewalk on one side. The sidewalk is continuous on both sides. No major bumps or permanent obstruction was observed. There are marked dedicated bike lanes along the segment. Suggested treatments: • Re-painting of bike lanes and crosswalks. 96 Chapter 6: Discussion This thesis is conducted to answer two specific questions: c) Is there an impact of UBC’s ‘Walk and Roll to School Week’ STP program on children’s active travel (walking, bike and other non-motorized modes like scooter, skateboards and roller blades) mode shares to school during and immediately after the program, and d) Is the impact on children’s active travel modes share sustained weeks after the program? The results from the study suggest that there is no significant impact of the ‘WNR week’ program on children’s active mode share (walking, bike and other non-motorized modes like scooter, skateboards and roller blades) to school during the WNR week or in the week after the program when compared with the change in AST rates in control schools. Thus, there is no measurable short-term effect on active modes share. The increase in AST rates observed in the intervention and control schools during the WNR week was most likely due to the weather and daylight conditions. On the day of baseline data collection, i.e., a week before the WNR week, it rained, whereas the weather was clear with no rain on the day of data collection during the WNR week. A simple before and after mode share difference analysis would have mistakenly attributed the increase to the STP intervention, whereas the difference-in-differences study design successfully controlled for weather effects. Unlike our findings, an evaluation of a one day STP encouragement program, ‘International Walk to School Day’ carried out by Buckley et al. (2013) in Moscow, Idaho found a significant increase in children’s AST rates in two elementary schools;- however, the study did not include control schools. Another evaluation of an STP program using control schools was carried out by Bungum et al. (2014) for assessing the impact of ‘Nevada Moves Day’ in two 97 elementary schools located in Henderson, Nevada. The study found a significant increase (p<.001) of children’s AST rates to school during the intervention day. However, the intervention was only for one day, unlike UBC’s program, which lasted for an entire week. It could be easier for parents to use AST with their children only for a day as compared to change their travel mode for a complete week. A two-day bicycle riding course was not able to significantly increase the bicycling share of children in intervention schools. The research carried out by Ducheyne et al. (2014), and Goodman et al. (2016) suggest training should focus more on real-world cycling experiences so that student can experience school journeys and get lessons on traffic skills like one-handed steering and signaling, looking left, right and over left shoulder while cycling. There could be a significant change in children’s bicycling rates had there been a more prolonged dosage of more than two days, and having students experience real-world bicycling as found by Villa-Gonzalez et al. (2015). One of the reasons for not having a significant increase in children’s AST rates due to UBC’s WNR week could be the age of students in elementary schools. Research from McMinn et al. (2012) found that parents are likely the primary decision-makers regarding children aged between eight to nine years of their commuting mode. This suggests that even if a child wanted to change their travel behaviors, they would have limited autonomy to do so because parents are the gatekeepers to this behavior. This is supported by previous research carried out by Faulkner et al. (2010) and McDonald et al. (2008) indicating that children's mode of travel is influenced by their home environment, their parent's work situation, and the mode of travel that their parents perceive to be easiest and most convenient. 98 A significant increase in children’s AST rates could be observed had there been a use of the mobile application for parents to track the movement of their children while using WSBs to reach their schools. Research by Martin et al. (2018) found that the use of mobile applications in WSBs could motivate parents to send their children to schools in WSBs as they can keep real-time track of their children. The other reason responsible could be the use of school staff like teachers in delivering the program. McMinn et al. (2012) found that implementing STP programs by school teachers may impact the program’s effectiveness, and it is preferred to implement the STP programs by the paid staff and research team. The implementation of the program by class teachers could be poorly delivered as they have busy schedules, and so an additional initiative to be implemented may be viewed as burdensome. Our study design having control schools accounted for the weather impacts on the children’s AST rates. Weather’s effect on children’s AST rates is supported by research carried out by Suminski et al. (2006) in two elementary schools in the US. The study observed several children observed, deviated substantially on days when weather conditions varied substantially. 6.1 Limitations We only assessed the number of children using active modes to reach school. We did not count students using active transport at afternoon dismissal. This is important as research indicates that more children walk home than to school (Schlossberg et al., 2006). The parents who drive their children to school while on their way to work are not available to drive them back home at the end of the school day. The study was conducted in a small sample of four schools. A bigger sample with more schools spread over the large geographical area may have had reported a significant impact. A 99 bigger sample would be more representative of students’ mode shares in schools located in different zones of the city. It is possible to have different effects of weather and daylight conditions on children’s AST rates in intervention and control schools. The control schools were located in higher income area and are more sensitive to weather and daylight conditions. However, if control schools were selected with similar characteristics (school size, household income, accessibility to transit and, active travel infrastructure around schools) to that of intervention schools, than the change in AST rates from wave 1 (no WNR week) to wave 2 (with WNR week) would be significantly higher in intervention schools as compared with control schools. Also, the DID approach used would not control for weather and daylight effects. It is typically impossible to assess whether the intervention schools and control schools are meeting the parallel trend assumption in the absence of the WNR week program using the difference-in-differences approach. The results would have been biased if the intervention schools would have had a different trend over time than the control schools in the absence of WNR week program. 6.2 Future research The future research can focus on evaluating the impact of STP interventions on children’s AST rates to and from school with a bigger sample of schools having similar characteristics like school size, household income, accessibility to transit and, active travel infrastructure around schools. 6.3 Conclusions The results from the study suggest that there is no significant impact of the UBC’s WNR week program on children’s active mode share (walking, bike and other non-motorized modes 100 like scooter, skateboards and roller blades) to school during the WNR week and in the week after the program when compared with the change in AST rates in control schools. Thus, there is no measurable short-term effect on active modes share. However, there could be a long-term effect of a multi-year program, which would not be observed in this study. UBC's ‘walk and roll to school week’ program has been run since 2013, and so any long-term effect would have been present in the before period. The study did not evaluate the multi-year impact of UBC’s WNR week program. It could be possible that there would have been an increase in the AST rates of the intervention schools over the past years. 6.4 Recommendations It is recommended to possibly consider implementing alternatives to STP interventions to influence children’s travel behaviour to schools for achieving immediate and short term gains. With STP programs, do not expect short term changes in children’s AST rates. It is recommended to consider studying the long term (multi years) impacts of STP programs on children’s AST rates to and from schools. It is recommended to include control schools in analysis for future research. 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Thesis/Dissertation
eng
Planning
Vancouver : University of British Columbia Library
Attribution-NoDerivatives 4.0 International
Graduate
Evaluating the impact of UBC’s ‘walk and roll to school week’ program on children’s active travel mode share to school
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