Interrater Reliability of Historical Virtual Audits Using Archived Google Street View Imagery

被引:4
|
作者
Harding, Alyson B. [1 ]
Glynn, Nancy W. [2 ]
Studenski, Stephanie A. [3 ]
Clarke, Philippa J. [4 ]
Divecha, Ayushi A. [2 ]
Rosso, Andrea L. [2 ]
机构
[1] Univ Minnesota, Div Environm Hlth Sci, Minneapolis, MN USA
[2] Univ Pittsburgh, Dept Epidemiol, Pittsburgh, PA 15261 USA
[3] Univ Pittsburgh, Sch Med, Pittsburgh, PA USA
[4] Univ Michigan, Inst Social Res, Ann Arbor, MI USA
关键词
built environment; Google maps; mobility; BUILT ENVIRONMENT; OLDER-ADULTS; PHYSICAL-ACTIVITY; MOBILITY; DISABILITY; MORTALITY;
D O I
10.1123/japa.2019-0331
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Impaired mobility occurs in up to half of community-dwelling older adults and is associated with poor health outcomes and high health care costs. Although the built environment impacts mobility, most studies of older adults lack information about environmental-level factors. In-person observational audits can be utilized but cannot assess the historical environment. We applied a 78-item checklist to archived Google Street View imagery to assess historical residence access and neighborhood characteristics. Interrater reliability between two raters was tested on 50 addresses using prevalence-adjusted and bias-adjusted kappa (PABAK). The mean PABAK for all items was .75, with 81% of the items having substantial (PABAK >=.61) or almost perfect (PABAK >=.81) agreement. Environmental assessment using archived virtual imagery has excellent reliability for factors related to residence access and many neighborhood characteristics. Archived imagery can assess past neighborhood characteristics, facilitating the use of historical environment data within existing cohorts.
引用
收藏
页码:63 / 70
页数:8
相关论文
共 50 条
  • [1] Virtual audits of the urban streetscape: comparing the inter-rater reliability of GigaPan® to Google Street View
    Katherine N. Bromm
    Ian-Marshall Lang
    Erica E. Twardzik
    Cathy L. Antonakos
    Tamara Dubowitz
    Natalie Colabianchi
    International Journal of Health Geographics, 19
  • [2] Virtual audits of the urban streetscape: comparing the inter-rater reliability of GigaPan® to Google Street View
    Bromm, Katherine N.
    Lang, Ian-Marshall
    Twardzik, Erica E.
    Antonakos, Cathy L.
    Dubowitz, Tamara
    Colabianchi, Natalie
    INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS, 2020, 19 (01)
  • [3] The utility of street view imagery in environmental audits for runnability
    Harden, Stella R.
    Schuurman, Nadine
    Larson, Hana
    Walker, Blake B.
    APPLIED GEOGRAPHY, 2024, 162
  • [4] The severity of pedestrian crashes: an analysis using Google Street View imagery
    Hanson, Christopher S.
    Noland, Robert B.
    Brown, Charles
    JOURNAL OF TRANSPORT GEOGRAPHY, 2013, 33 : 42 - 53
  • [5] Measuring visual enclosure for street walkability: Using machine learning algorithms and Google Street View imagery
    Yin, Li
    Wang, Zhenxin
    APPLIED GEOGRAPHY, 2016, 76 : 147 - 153
  • [6] Google Street View shows promise for virtual street tree surveys
    Berland, Adam
    Lange, Daniel A.
    URBAN FORESTRY & URBAN GREENING, 2017, 21 : 11 - 15
  • [7] Estimating city-level travel patterns using street imagery: a case study of using Google Street View in Britain
    Goel, Rahul
    Garcia, Leandro
    Goodman, Anna
    Johnson, Rob
    Aldred, Rachel
    Murugesan, Manoradhan
    Brage, Soren
    Bhalla, Kavi
    Woodcock, James
    JOURNAL OF PHYSICAL ACTIVITY & HEALTH, 2018, 15 (10): : S69 - S70
  • [8] Estimating city-level travel patterns using street imagery: A case study of using Google Street View in Britain
    Goel, Rahul
    Garcia, Leandro M. T.
    Goodman, Anna
    Johnson, Rob
    Aldred, Rachel
    Murugesan, Manoradhan
    Brage, Soren
    Bhalla, Kavi
    Woodcock, James
    PLOS ONE, 2018, 13 (05):
  • [9] Using Google Street View for virtual observations of neighborhoods and dwelling units: A feasibility study
    Yan, Ting
    Yang, Xin
    Sun, Hanyu
    Cantor, David
    PLOS ONE, 2024, 19 (08):
  • [10] Using Deep Learning and Google Street View Imagery to Assess and Improve Cyclist Safety in London
    Rita, Luis
    Peliteiro, Miguel
    Bostan, Tudor-Codrin
    Tamagusko, Tiago
    Ferreira, Adelino
    SUSTAINABILITY, 2023, 15 (13)