Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Watersportlaan 2, 9000 Ghent, Belgium.
Int J Health Geogr. 2014 Jun 10;13:19. doi: 10.1186/1476-072X-13-19.
Google Street View provides a valuable and efficient alternative to observe the physical environment compared to on-site fieldwork. However, studies on the use, reliability and validity of Google Street View in a cycling-to-school context are lacking. We aimed to study the intra-, inter-rater reliability and criterion validity of EGA-Cycling (Environmental Google Street View Based Audit - Cycling to school), a newly developed audit using Google Street View to assess the physical environment along cycling routes to school.
Parents (n = 52) of 11-to-12-year old Flemish children, who mostly cycled to school, completed a questionnaire and identified their child's cycling route to school on a street map. Fifty cycling routes of 11-to-12-year olds were identified and physical environmental characteristics along the identified routes were rated with EGA-Cycling (5 subscales; 37 items), based on Google Street View. To assess reliability, two researchers performed the audit. Criterion validity of the audit was examined by comparing the ratings based on Google Street View with ratings through on-site assessments.
Intra-rater reliability was high (kappa range 0.47-1.00). Large variations in the inter-rater reliability (kappa range -0.03-1.00) and criterion validity scores (kappa range -0.06-1.00) were reported, with acceptable inter-rater reliability values for 43% of all items and acceptable criterion validity for 54% of all items.
EGA-Cycling can be used to assess physical environmental characteristics along cycling routes to school. However, to assess the micro-environment specifically related to cycling, on-site assessments have to be added.
与现场实地考察相比，谷歌街景为观察物理环境提供了一种有价值且高效的替代方法。然而，在骑车上学的背景下，关于谷歌街景的使用、可靠性和有效性的研究还很缺乏。我们旨在研究 EGA-Cycling（基于谷歌街景的环境评估-骑车上学）的内部和间一致性可靠性以及效标效度，EGA-Cycling 是一种新开发的使用谷歌街景评估上学骑车路线沿线物理环境的评估方法。
11 至 12 岁的弗拉芒儿童的父母（n=52），他们的孩子大多骑车上学，他们填写了一份问卷，并在街道地图上确定了孩子的上学骑车路线。确定了 50 条 11 至 12 岁儿童的骑车路线，并根据谷歌街景使用 EGA-Cycling（5 个分量表；37 个项目）对识别路线上的身体环境特征进行评分。为了评估可靠性，两位研究人员进行了审核。通过将基于谷歌街景的评分与现场评估的评分进行比较，来检验审核的效标效度。
内部一致性可靠性很高（kappa 范围 0.47-1.00）。间一致性可靠性（kappa 范围-0.03-1.00）和效标效度评分（kappa 范围-0.06-1.00）的差异很大，所有项目中有 43%的项目具有可接受的间一致性可靠性值，所有项目中有 54%的项目具有可接受的效标效度值。
EGA-Cycling 可用于评估上学骑车路线沿线的身体环境特征。然而，要评估与骑车具体相关的微观环境，必须增加现场评估。
