WebWalk: walking behavior on campus

1. WebWalk:walking behavior on campus Craig Zimring, Ph.D. Georgia Institute of Technology, College of Architecture September 5, 2007 Status Update craig.zimring@coa.gatech.edu

2. Research Purpose • How are path characteristics related to route selection on corporate campuses? • Develop tools… • Environmental Audit • Software/Database • Survey/Focus Group Guide • Develop initial understanding based on… • Pleasure • Comfort • Safety

3. Project Staff • Research Team: • Craig M Zimring, Ph.D. • Julie Gazmararian, MPH, Ph.D. • Mahbub Rashid, Ph.D., AIA • Phillip B.Sparling, Ed.D., FACSM • Sheila Bosch, Ph.D. • Michael Herndon, M.S. • Sharon Tsepas, M. Arch • Lu Yi, M. Arch • Advisory Committee: • Jeffrey Koplan, M.D., MPH • Kenneth E. Powell, M.D. • Philippe C. Dordai, AIA

4. Literature Review • Environmental factors can influence path choice • Path characteristics may induce people to walk further than they would otherwise • Hoogendoorn SP, Bovy 2002 • Joseph A, Zimring C, 2007 • Zimring, C et al, 2005

5. 2 3 1 Environmental Audit: Introduction • Describes physical attributes of path segments: • Safety • Comfort • Pleasurably

6. Environmental Audit: Genesis • Irvine-Minnesota Inventory (Boarnet, et al., 2006; Day, et al., 2005; Day, et al., 2006) • SPACES Tool (Systematic Pedestrian and Cycling Environmental Scan): University of Western Australia • Path Environment Audit Tool (Troped, et al., 2006)

7. Environmental Audit: Introduction • Examples: • Path Material • Path Width • Presence of Benches, etc. • Presence of Food/Coffee Shops • Quality/Type of Landscape • Building Maintenance • Surveillance from Buildings • Presence of Litter • Presence of Fountains/Bridges • Presence of Shading

8. Environmental Audit: Interrater Reliability • Interrater reliability vital • Process • Paths had wide array of characteristics • A lack of applicable standards • Measurement • Cohen’s Kappa (Cohen, 1960; Troped, et al., 2006; McGinn, et al. 2004) • K > .60 • Percent Agreement (Boarnet, et al., 2006) • P > 80% Agreement

9. Audit Tool: Inter-rater Reliability • Version One – developed at Georgia Tech, informed by visits to other sites. • Originally Low • Examined data entry • Refined audit form • Revisited segments • Rated photographs (Picasaweb) • Revised questions • Revisited GA Tech campus • Reviewed 30 segments at Bellsouth (Atlanta, GA) • Planned trip to Kimberly-Clark campus (Roswell, GA)

10. Environmental Audit: Tool • 28 Questions • multiple subparts • Designed to be used on every segment on site • Future versions may use hand-held electronic form • reduce data entry time • reduce possible errors

11. Environmental Audit: Training Protocol • 52-slide PowerPoint presentation • Includes quizzes • 14-page long form (Day, et al. 2005) • Supervised rating period

12. WebWalk Software: Introduction • PURPOSE OF THIS SOFTWARE • Based on Scalable Vector Graphics and JavaScript SVG JavaScript

13. WebWalk Software • Initial Login • One time survey • Subsequent Logins • Path selection • Every-time survey

14. One Time Survey • Based on IPAQ: • Physical activity • Also asks about: • Beliefs about physical activity • Demographics • Job Classification • Length of Time at Company/Campus

15. WebWalk Software

16. Every Time Survey • Date and Time • Intensity • Purpose of Trip • work-related • personal • combination

17. WebWalk Software • Web-based Application • Scalable Vector Graphics (SVG) • JavaScript/PHP • Internet Explorer • MySQL Server

18. Develop .SVG Map from Plans • Created with GIS Software • Best done from CAD plans • Can be done from overhead imagery • On-campus visit highly recommended

19. Data Analysis • Segment Scores • Pleasure • Comfort • Safety • Both Local and Relational Scores • Correlate Scores with Route Choice

20. Building A Building B Data Analysis: Assumptions

21. Building A Building B Data Analysis: Assumptions No Possible Conclusion

22. Building A Building B Data Analysis: Assumptions Possible Conclusion

23. Data Analysis: Assumptions • “Shortest” route • Metric Shortest Distance • Lowest angular turns • Most Integrated Paths (Space Syntax) • “Shortest” route may be 1 to 3 routes • Analysis will only examine environmental characteristic causality when routes chosen are not the “shortest.”

24. Data Analysis • Primary Analysis • Route Choice Based on: • Safety • Comfort • Pleasureability • Secondary Analysis • Route choice preferences based on demographic/job type • Differences in route choice based on time • avoiding non-shaded paths during mid-day • avoiding less safe paths early and late in day • Route choice based on different types of buildings • More leisurely routes from/to cafeteria, gym • Create weighted or modified route scores

25. Georgia Institute of Technology • Georgia Tech • Atlanta, GA • Full time faculty, staff, graduate students • Over 30 buildings • Over 500 path segments • Final usability test in progress

26. United Parcel Service • UPS World Headquarters • Atlanta, GA • Environmental Audit late September ‘07

27. Sprint/Nextel Corporation • Sprint National Headquarters • Overland Park, KS • Environmental Audit late September ‘07

28. Hypotheses/Questions • Relatively homogenous physical characteristics will play little role in route choice on Work-related trips once certain threshold levels have been reached. • Route choice on trips taken for Personal or Combination reasons will show more evidence of being influenced by path characteristics. • The presence of amenities, high quality landscaping, and other “pleasureable” factors will be highly correlated with the shortest paths between buildings; this correlation can be explained by the ability of planners and/or designers to anticipate the use of various paths.

29. Conclusion Thank you… • Craig Zimring Georgia Tech College of Architecture • craig.zimring@coa.gatech.edu 404.894.3915

30. References • Boarnet MG, Day K, Alfonzo M, Forsyth A, Oakes M. The Irvine-Minnesota Inventory to Measure Built Environments Reliability Tests Am J Prev Med 2006;30(2):153-159. • Cohen J. A Coefficient of Agreement for Nominal Scales, Env and Psych Meas, 1960;20(1):37-46. • Day K, Boarnet M, Alfonzo M. Irvine Minnesota Inventory for Observation of Physical Environment Features Linked to Physical Activity. Codebook. 2005. • Day K, Boarnet M, Alfonzo M, Forsyth A. The Irvine-Minnesota Inventory to Measure Built Environments Development. Am J Prev Med 2006;30(2):144-152. • Hoogendoorn SP, Bovy PHL. Pedestrian route-choice and activity scheduling theory and models. Transportation Research B 2002 • Joseph A, Zimring C. Where Active Older Adults Walk. Environment and Behavior 2007;39(1):75-105. • McGinn T, Wyer PC, Newman TB, Keitz S, Leipzig R, Guyatt G. Tips for learners of evidence-based medicine: 3. Measures of observer variability (kappa statistic). CMAJ, 2004;171(11):1369-1373. • Pikora T. Systematic Pedestrian and Cycling Environmental Scan (SPACES), Survey of the Physical Environment in Local Neighborhoods: Observer's Manual. Nedlands, Western Australia: University of Western Australia; 2002. • Troped PJ, Cromley EK, Fragala MS, Melly SJ, Hasbrouck HH, Gortmaker SL, Brownson RC. Development and Validity Testing of an Audit Tool for Trail/Path Characteristics: The Path Environment Audit Tool (PEAT). J of Phys Act and Health 2006;Sup1:S158-S175. • Zimring C, Joseph A, Nicoll GL, Tsepas S. Influences of building design and site design on physical activity: Research and intervention opportunities. Am J Prev Med 2005;28(2, Supplement 2), 186-193.