Toward Equitable Access: Leveraging Crowdsourced Reviews to Investigate Public Perceptions of Health Resource Accessibility
Fuente:
arXiv
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| Autori principali: | , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
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| _version_ | 1866918220158468096 |
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| author | Xue, Zhaoqian Liu, Guanhong Zhang, Chong Wei, Kai Zeng, Qingcheng Hu, Songhua Hua, Wenyue Fan, Lizhou Zhang, Yongfeng Li, Lingyao |
| author_facet | Xue, Zhaoqian Liu, Guanhong Zhang, Chong Wei, Kai Zeng, Qingcheng Hu, Songhua Hua, Wenyue Fan, Lizhou Zhang, Yongfeng Li, Lingyao |
| contents | Monitoring health resource disparities during public health crises is critical, yet traditional methods, like surveys, lack the requisite speed and spatial granularity. This study introduces a novel framework that leverages: 1) crowdsourced Google Maps reviews (2018-2021) and 2) advanced NLP (DeBERTa) to create a high-resolution, spatial-temporal index of public perception of health resource accessibility in the United States. We then employ Partial Least Squares (PLS) regression to link this perception index to a range of socioeconomic and demographic drivers. Our results quantify significant spatial-temporal shifts in perceived access, confirming that disparities peaked during the COVID-19 crisis and only partially recovered post-peak. We identify political affiliation, racial composition, and educational attainment as primary determinants of these perceptions. This study validates a scalable method for real-time health equity monitoring and provides actionable evidence for interventions to build a more resilient healthcare infrastructure. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_10641 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Toward Equitable Access: Leveraging Crowdsourced Reviews to Investigate Public Perceptions of Health Resource Accessibility Xue, Zhaoqian Liu, Guanhong Zhang, Chong Wei, Kai Zeng, Qingcheng Hu, Songhua Hua, Wenyue Fan, Lizhou Zhang, Yongfeng Li, Lingyao Computation and Language Monitoring health resource disparities during public health crises is critical, yet traditional methods, like surveys, lack the requisite speed and spatial granularity. This study introduces a novel framework that leverages: 1) crowdsourced Google Maps reviews (2018-2021) and 2) advanced NLP (DeBERTa) to create a high-resolution, spatial-temporal index of public perception of health resource accessibility in the United States. We then employ Partial Least Squares (PLS) regression to link this perception index to a range of socioeconomic and demographic drivers. Our results quantify significant spatial-temporal shifts in perceived access, confirming that disparities peaked during the COVID-19 crisis and only partially recovered post-peak. We identify political affiliation, racial composition, and educational attainment as primary determinants of these perceptions. This study validates a scalable method for real-time health equity monitoring and provides actionable evidence for interventions to build a more resilient healthcare infrastructure. |
| title | Toward Equitable Access: Leveraging Crowdsourced Reviews to Investigate Public Perceptions of Health Resource Accessibility |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2502.10641 |