{"title":"利用智能手机用户的移动性来揭示实际的医疗旅行时间:以精神卫生机构为例","authors":"Lixiaona Yu , Tao Hu , Taiping Liu , Yunyu Xiao","doi":"10.1016/j.healthplace.2024.103375","DOIUrl":null,"url":null,"abstract":"<div><div>Travel time to health facilities is one of the most important factors in evaluating health disparity. Previous extensive research has primarily leveraged the driving time to the nearest health facility to gauge travel time. However, such ideal travel time (ITT) may not accurately represent real individual travel time to health services and is often underestimated. This study aims to systematically understand such gaps by comparing ITT to actual travel time (ATT) derived from smartphone-based human mobility data and further identifying how various population groups across regions are most likely to be affected. This study takes mental health as an example and compares ATT with ITT to mental health facilities. Results indicate that ITT and ATT demonstrate significant disparities between urban and rural areas. ITT is consistently underestimated across the contiguous US. We compare travel times among diverse sociodemographic groups across eight geographical regions. The findings suggest that different age groups have similar travel times to mental health facilities. However, racial groups exhibit varied travel times. Hispanics have a larger percentage of the population experiencing longer ATT than ITT. We also employed spatial and non-spatial regression models, such as Ordinary Least Squares, Spatial Lag Model, and Spatial Error Model, to quantify the correlation between travel times and socioeconomic status. The results revealed that the proportion of older adults and high school dropouts positively correlates with travel times in most regions. Areas with more non-Hispanics show positive correlations with both travel times. Overall, this study reveals pronounced discrepancies between ITT and ATT, underscoring the importance of using smartphone-derived ATT to measure health accessibility.</div></div>","PeriodicalId":49302,"journal":{"name":"Health & Place","volume":"90 ","pages":"Article 103375"},"PeriodicalIF":3.8000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using smartphone user mobility to unveil actual travel time to healthcare: An example of mental health facilities\",\"authors\":\"Lixiaona Yu , Tao Hu , Taiping Liu , Yunyu Xiao\",\"doi\":\"10.1016/j.healthplace.2024.103375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Travel time to health facilities is one of the most important factors in evaluating health disparity. Previous extensive research has primarily leveraged the driving time to the nearest health facility to gauge travel time. However, such ideal travel time (ITT) may not accurately represent real individual travel time to health services and is often underestimated. This study aims to systematically understand such gaps by comparing ITT to actual travel time (ATT) derived from smartphone-based human mobility data and further identifying how various population groups across regions are most likely to be affected. This study takes mental health as an example and compares ATT with ITT to mental health facilities. Results indicate that ITT and ATT demonstrate significant disparities between urban and rural areas. ITT is consistently underestimated across the contiguous US. We compare travel times among diverse sociodemographic groups across eight geographical regions. The findings suggest that different age groups have similar travel times to mental health facilities. However, racial groups exhibit varied travel times. Hispanics have a larger percentage of the population experiencing longer ATT than ITT. We also employed spatial and non-spatial regression models, such as Ordinary Least Squares, Spatial Lag Model, and Spatial Error Model, to quantify the correlation between travel times and socioeconomic status. The results revealed that the proportion of older adults and high school dropouts positively correlates with travel times in most regions. Areas with more non-Hispanics show positive correlations with both travel times. Overall, this study reveals pronounced discrepancies between ITT and ATT, underscoring the importance of using smartphone-derived ATT to measure health accessibility.</div></div>\",\"PeriodicalId\":49302,\"journal\":{\"name\":\"Health & Place\",\"volume\":\"90 \",\"pages\":\"Article 103375\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health & Place\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S135382922400203X\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health & Place","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S135382922400203X","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
摘要
前往医疗机构的旅行时间是评估健康差异的最重要因素之一。以往的大量研究主要利用到最近医疗机构的行车时间来衡量旅行时间。然而,这种理想旅行时间(ITT)可能无法准确代表个人前往医疗服务机构的实际旅行时间,而且往往被低估。本研究旨在通过比较 ITT 与基于智能手机的人员流动数据得出的实际旅行时间 (ATT),系统地了解这种差距,并进一步确定不同地区的不同人群最有可能受到的影响。本研究以心理健康为例,比较了前往心理健康设施的 ATT 和 ITT。结果表明,ITT 和 ATT 在城市和农村地区之间存在显著差异。在美国毗连地区,ITT 一直被低估。我们比较了八个地理区域不同社会人口群体的旅行时间。研究结果表明,不同年龄段的人群前往精神卫生机构的旅行时间相近。然而,种族群体的旅行时间却各不相同。西班牙裔人口中,ATT 比 ITT 长的比例更大。我们还采用了空间和非空间回归模型,如普通最小二乘法、空间滞后模型和空间误差模型,来量化旅行时间与社会经济地位之间的相关性。结果显示,在大多数地区,老年人和高中辍学者的比例与旅行时间呈正相关。非西班牙裔人口较多的地区与旅行时间均呈正相关。总体而言,这项研究揭示了 ITT 与 ATT 之间的明显差异,强调了使用智能手机得出的 ATT 来衡量健康可及性的重要性。
Using smartphone user mobility to unveil actual travel time to healthcare: An example of mental health facilities
Travel time to health facilities is one of the most important factors in evaluating health disparity. Previous extensive research has primarily leveraged the driving time to the nearest health facility to gauge travel time. However, such ideal travel time (ITT) may not accurately represent real individual travel time to health services and is often underestimated. This study aims to systematically understand such gaps by comparing ITT to actual travel time (ATT) derived from smartphone-based human mobility data and further identifying how various population groups across regions are most likely to be affected. This study takes mental health as an example and compares ATT with ITT to mental health facilities. Results indicate that ITT and ATT demonstrate significant disparities between urban and rural areas. ITT is consistently underestimated across the contiguous US. We compare travel times among diverse sociodemographic groups across eight geographical regions. The findings suggest that different age groups have similar travel times to mental health facilities. However, racial groups exhibit varied travel times. Hispanics have a larger percentage of the population experiencing longer ATT than ITT. We also employed spatial and non-spatial regression models, such as Ordinary Least Squares, Spatial Lag Model, and Spatial Error Model, to quantify the correlation between travel times and socioeconomic status. The results revealed that the proportion of older adults and high school dropouts positively correlates with travel times in most regions. Areas with more non-Hispanics show positive correlations with both travel times. Overall, this study reveals pronounced discrepancies between ITT and ATT, underscoring the importance of using smartphone-derived ATT to measure health accessibility.