Using global positioning systems to study health-related mobility and participation

Social Science and Medicine

Volumn 161, Issue , 2016, Pages 134-142

  Brusilovskiy, Eugene ^a   Klein, Louis A ^a   Salzer, Mark S ^a  

^a TEMPLE UNIVERSITY   (United States)

Author keywords

Community participation; Global positioning systems; GPS; Mobility; Spatiotemporal data mining; USA

Indexed keywords

ALGORITHM; DATA MINING; DISABILITY; GPS; LOCAL PARTICIPATION; MOBILITY; SPATIOTEMPORAL ANALYSIS; TRACKING; WORLD HEALTH ORGANIZATION;

ADULT; ALGORITHM; ARTICLE; COMMUNITY PARTICIPATION; COMPUTER PROGRAM; CONTROLLED STUDY; DAILY LIFE ACTIVITY; DATA ANALYSIS SOFTWARE; DATA MINING; DIVORCED PERSON; FEMALE; GEOGRAPHIC MAPPING; GLOBAL POSITIONING SYSTEM; GRADUATE; HIGH SCHOOL GRADUATE; HUMAN; INCOME; INTERNATIONAL CLASSIFICATION OF FUNCTIONING, DISABILITY AND HEALTH; MALE; MOBILE PHONE; OUTPATIENT CARE; PHYSICAL ACTIVITY; POSTGRADUATE EDUCATION; SEPARATED PERSON; SINGLE MAN; SOCIAL CLASS; SOCIAL PARTICIPATION; SPATIOTEMPORAL ANALYSIS; WALKING SPEED; WELLBEING; CELL TRACKING; EXERCISE; GEOGRAPHIC INFORMATION SYSTEM; HEALTH SERVICE; MIDDLE AGED; PENNSYLVANIA; PROCEDURES; RECREATIONAL PARK; STATISTICS AND NUMERICAL DATA; UTILIZATION;

ACTIVITIES OF DAILY LIVING; ADULT; CELL PHONE; CELL TRACKING; COMMUNITY PARTICIPATION; EXERCISE; FEMALE; GEOGRAPHIC INFORMATION SYSTEMS; HEALTH SERVICES; HUMANS; MALE; MIDDLE AGED; PARKS, RECREATIONAL; PHILADELPHIA;

EID: 84973352502     PISSN: 02779536     EISSN: 18735347     Source Type: Journal    
DOI: 10.1016/j.socscimed.2016.06.001     Document Type: Article

References (42)

1. Axhausen K.W., Rai R.K., Rieser M., Balmer M., Vaze V.S. Capturing human activity spaces 2006, ETH, Eidgenössische Technische Hochschule Zürich, IVT, Institut für Verkehrsplanung und Transportsysteme. 10.3929/ethz-a-005237115.
2. Ben-Zeev D., Scherer E.A., Wang R., Xie H., Campbell A. Next-generation psychiatric assessment: using smartphone sensors to monitor behavior and mental health. Psychiatr. Rehabil. J. 2015, 38(3):218-226.
3. Birant D., Kut A. ST-DBSCAN: an algorithm for clustering spatial-temporal data. Data Knowl. Eng. 2007, 60(1):208-221.
4. Bostelmann R., Schneller S., Cornelius J.F., Steiger H.J., Fischer I. A new possibility to assess the perioperative walking capacity using a global positioning system in neurosurgical spine patients: a feasibility study. Eur. Spine J. 2015, 1-6.
5. Buliung R.N., Kanaroglou P.S. Urban form and household activity-travel behavior. Growth Change 2006, 37(2):172-199.
6. Burns-Lynch W., Brusilovskiy E., Salzer M.S. Community participation facilitates recovery and quality of life: an empirical study. Isr. J. Psychiatry 2016, (in press).
7. Carpenter W.T., Gold J.M., Kovnick J., Appelbaum P.S. Decisional capacity for informed consent in schizophrenia research. Arch. General Psychiatry 2000, 57(6):533-538.
8. Clark R.A., Weragoda N., Paterson K., Telianidis S., Williams G. A pilot investigation using global positioning systems into the outdoor activity of pepole with severe traumatic brain injury. J. Neuroeng. Rehabil. 2014, 19:11-37.
9. Collins P., Al-Nakeeb Y., Lyons M. Tracking the commute home from school utilizing GPS and heart rate monitoring: establishing the contribution to free-living physical activity. J. Phys. Act. Health 2015, 12:155-162.
10. Eklund M., Leufstadius C., Bejerholm U. Time use among people with psychiatric disabilities: implications for practice. Psychiatr. Rehabil. J. 2009, 32(3):177-191.
11. Fan Y., Khattak A. Urban form, individual spatial footprints, and travel: examination of space-use behavior. Transp. Res. Rec. J. Transp. Res. Board 2008, 2082:98-106.
12. Harris F., Sprigle S., Sonenblum S.E., MSaurer C.L. The participation and activity measurement system: an example application among people who use wheeled mobility devices. Disabil. Rehabil. Assist. Technol. 2010, 5(1):48-57.
13. Hillier A. Childhood overweight and the built environment: making technology part of the solution rather than part of the problem. Ann. Am. Acad. Political Soc. Sci. 2008, 615(1):56-82.
14. Hillsdon M., Coombes E., Griew P., Jones A. An assessment of the relevance of the home neighbourhood for understanding environmental influences on physical activity: how far from home do people roam?. Int. J. Behav. Nutr. Phys. Act. 2015, 12(100).
15. Hordacre B., Barr C., Crotty M. Community activity and participation are reduced in transtibial amputee fallers: a wearable technology study. BMJ Innov. 2015, 1:10-16.
16. Jayaraman A., Deeny S., Eisenberg Y., Mathur G., Kuiken T. Global position sensing and step activity as outcome measures of community mobility and social interaction for an individual with a transfemoral amputation due to dysvascular disease. Phys. Ther. 2014, 94(3):401-410.
17. Ji Y., Zhang C., Zuo Z., Chang J. Mining user daily behavior based on location history. IEEE 14th International Conference on Communication Technology (ICCT) 2012.
18. Khetarpaul S., Chauhan R., Gupta S.K., Subramaniam L.V., Nambiar U. Mining GPS data to determine interesting locations. Proceedings of the 8th International Workshop on Information Integration on the Web: in Conjunction with WWW 2011 2011, 1-6. ACM, Hyderabad, India.
19. Lankton S., Sonenblum S.E., Sprigle S., Wolf J., Oliveira M. Use of GPS and Sensor-based Instrumentation as a Supplement to Self-report in Studies of Activity and Participation 2005, Paper presented at RESNA 28th International Annual Conference, Atlanta, GA.
20. Lu Y., Karimi H.A. Real-time sidewalk slope calculation through integration of GPS trajectory and image data to assist people with disabilities in navigation. Int. J. Geo-information 2015, 4(2):741-753.
21. Maitrey N., Vaghela D. Survey on different density based algorithms on spatial dataset. Int. J. Adv. Res. Comput. Sci. Manag. Stud. 2014, 2(2).
22. Parimala M., Lopez D., Senthilkumar N.C. A survey on density based clustering algorithms for mining large spatial databases. Int. J. Adv. Sci. Technol. 2011, 31(1).
23. Prociow P.A., Crowe J.A. Towards personalized ambient monitoring of mental health via mobile technologies. Technol. Health Care 2010, 18(4-5):275-284.
24. Rai R., Balmer M., Rieser M., Vaze V., Schönfelder S., Axhausen K. Capturing human activity spaces: new geometries. Transp. Res. Rec. J. Transp. Res. Board 2007, 2021:70-80.
25. Rogalsky J. The working poor and what GIS reveals about the possibilities of public transit. J. Transp. Geogr. 2010, 18(2):226-237.
26. Salzer M.S., Brusilovskiy E., Kottsieper P., Prvu-Bettger J. Measuring community participation of adults with psychiatric disabilities: reliability of two modes of data collection. Rehabil. Psychol. 2014, 59(2):211-219.
27. Salzer M.S., Kottsieper P., Brusilovskiy E. Intermethod reliability and factors affecting recall with the Temple university community participation measure. J. Ment. Health 2015, 24(4):189-195.
28. Trimble Navigation Limited Why Postprocess GPS Data? 2004, Mapping and GIS White Paper, Trimble Navigation Limited, Westminster, CO.
29. Ustun T.B., Chatterji S., Bickenbach J., Kostanjsek N., Schneider M. The international classification of functioning, disability and health: a new tool for understanding disability and health. Disabil. Rehabil. 2003, 25(11-12):565-571.
30. Villanueva K., Giles-Corti B., Bulsara M., McCormack G.R., Timperio A., Middleton N., Trapp G. How far do children travel from their homes? Exploring children's activity spaces in their neighborhood. Health & Place 2012, 18(2):263-273.
31. Vincenty T. Direct and inverse solutions of geodesics on the ellipsoid with application of nested equations. Surv. Rev. 1975, 23(176):88-93.
32. Wang M., Wang A., Li A. Mining spatial-temporal clusters from geo-databases. Advanced Data Mining and Applications 2006, vol. 4093:263-270. Springer, Berlin Heidelberg.
33. Wettstein M., Wahl H.-W., Diehl M. A multidimensional view of out-of-home behaviors in cognitively unimpaired older adults: examining differential effects of socio-demographic, cognitive, and health-related predictors. Eur. J. Ageing 2013, 1-13.
34. Wettstein M., Wahl H.-W., Heinik J., Landau R. Out-of-home behavior and cognitive impairment in older adults: findings of the SenTra project. J. Appl. Gerontol. 2012, 34(1):3-25.
35. Whiteneck G. Conceptual models of disability: past, present, and future. Workshop on Disability in America: a New Look-summary and Background 2006, The National Academies Press, Washington, DC. M. Field, A. Jette, L.M. Martin (Eds.).
36. World Health Organization ICF: International Classification of Functioning, Disability, and Health 2001, (Geneva).
37. Yanos P.T., Robilotta S.A. An examination of time-use among adults diagnosed with severe mental illnesses using daily interviews. Psychiatr. Rehabil. J. 2011, 34(3):243-247.
38. Yin L., Raja S., Epstein L., Roemmich J. Neighbourhood for playing: using gps, gis and accelerometry to delineate areas within which youth are physically active. Urban Stud. 2013, 2013:1-18.
39. Yue Y., Chen J., Zuo X., Xie X. Labeling personal characteristics from mobile phone traces. 2nd International Workshop on Mobile Sensing, IPSN'12 and CPSWeek 2012.
40. Zandbergen P.A., Barbeau S.J. Positional accuracy of assisted GPS data from high-sensitivity GPS-enabled mobile phones. J. Navig. 2011, 64(3):381-399.
41. Zhou C., Frankowski D., Ludford P., Shekhar S., Terveen L. Discovering personal gazetteers: an interactive clustering approach. Proceedings of the 12th Annual ACM International Workshop on Geographic Information Systems 2004, 266-273. ACM.
42. Zhou C., Ludford P., Frankowski D., Terveen L. How do people's concepts of place relate to physical locations?. INTERACT Conference. Rome, Italy 2005.