Poor Representation of Rural Counties of the United States in Some Measures of Consumer Broadband.

IF 1.5 Q3 HEALTH CARE SCIENCES & SERVICES
Telemedicine reports Pub Date : 2024-10-08 eCollection Date: 2024-01-01 DOI:10.1089/tmr.2024.0048
Cari A Bogulski, Maysam Rabbani, Corey J Hayes, Aysenur Betul Cengil, Catherine C Shoults, Hari Eswaran
{"title":"Poor Representation of Rural Counties of the United States in Some Measures of Consumer Broadband.","authors":"Cari A Bogulski, Maysam Rabbani, Corey J Hayes, Aysenur Betul Cengil, Catherine C Shoults, Hari Eswaran","doi":"10.1089/tmr.2024.0048","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Telehealth has the potential to mitigate the lack of health care access in rural and underserved communities; however, telehealth is only viable where sufficiently high-speed internet broadband is available to patients. Existing broadband data sets may not accurately reflect the state of broadband, particularly in rural communities. We examined consumer internet speed test data from two organizations to see if the number of tests per 1,000 residents varied across county-level rurality.</p><p><strong>Methods: </strong>We analyzed county-level data from Measurement Labs (M-Lab) and Ookla for Good (Ookla fixed and mobile) across the calendar years 2020 and 2021. We used the number of tests conducted per 1,000 residents within United States counties as the outcome variable, and Rural-Urban Continuum Codes (RUCC) as the main independent variable of interest.</p><p><strong>Results: </strong>Using negative binomial models with robust standard errors, we found that the number of fixed speed tests conducted per 1,000 residents was generally lower in rural counties relative to counties with over one million residents. However, we found no associations between any categories of county-level rurality for the number of mobile tests conducted per 1,000 residents. Patterns of association with other covariates emerged as significant in some models and not in others, suggesting key differences among users generating speed tests among these data sources.</p><p><strong>Conclusions: </strong>Our findings demonstrate the poor representation of residents from very rural counties in M-Lab and Ookla fixed data sets of user-generated internet speed tests. Additional data are needed to inform broadband infrastructure investment to identify those communities most left behind by broadband expansion efforts.</p>","PeriodicalId":94218,"journal":{"name":"Telemedicine reports","volume":"5 1","pages":"290-303"},"PeriodicalIF":1.5000,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11491573/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Telemedicine reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1089/tmr.2024.0048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Telehealth has the potential to mitigate the lack of health care access in rural and underserved communities; however, telehealth is only viable where sufficiently high-speed internet broadband is available to patients. Existing broadband data sets may not accurately reflect the state of broadband, particularly in rural communities. We examined consumer internet speed test data from two organizations to see if the number of tests per 1,000 residents varied across county-level rurality.

Methods: We analyzed county-level data from Measurement Labs (M-Lab) and Ookla for Good (Ookla fixed and mobile) across the calendar years 2020 and 2021. We used the number of tests conducted per 1,000 residents within United States counties as the outcome variable, and Rural-Urban Continuum Codes (RUCC) as the main independent variable of interest.

Results: Using negative binomial models with robust standard errors, we found that the number of fixed speed tests conducted per 1,000 residents was generally lower in rural counties relative to counties with over one million residents. However, we found no associations between any categories of county-level rurality for the number of mobile tests conducted per 1,000 residents. Patterns of association with other covariates emerged as significant in some models and not in others, suggesting key differences among users generating speed tests among these data sources.

Conclusions: Our findings demonstrate the poor representation of residents from very rural counties in M-Lab and Ookla fixed data sets of user-generated internet speed tests. Additional data are needed to inform broadband infrastructure investment to identify those communities most left behind by broadband expansion efforts.

在消费者宽带的某些衡量标准中,美国农村县的代表性较差。
导言:远程医疗有可能缓解农村和医疗服务不足社区缺乏医疗服务的问题;但是,远程医疗只有在为患者提供足够高速的互联网宽带的情况下才可行。现有的宽带数据集可能无法准确反映宽带状况,尤其是农村社区的宽带状况。我们研究了两家机构提供的消费者网速测试数据,以了解每千名居民的测试次数在不同的县级农村地区是否存在差异:我们分析了 Measurement Labs(M-Lab)和 Ookla for Good(Ookla 固定和移动)在 2020 和 2021 日历年提供的县级数据。我们将美国各县每千名居民的测试次数作为结果变量,将农村-城市连续代码(RUCC)作为主要的自变量:通过使用带有稳健标准误差的负二项模型,我们发现相对于居民人数超过一百万的县,农村县每千名居民进行的固定速度测试次数普遍较低。但是,我们没有发现任何类别的县级农村地区与每千名居民进行的移动测试次数之间存在关联。与其他协变量的关联模式在某些模型中具有显著性,而在其他模型中则没有,这表明在这些数据源中进行速度测试的用户之间存在关键差异:我们的研究结果表明,在用户生成的网速测试的 M-Lab 和 Ookla 固定数据集中,农村地区居民的代表性很低。我们需要更多的数据来为宽带基础设施投资提供信息,以确定那些被宽带扩展工作抛在后面的社区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
1.80
自引率
0.00%
发文量
0
审稿时长
8 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信