儿童青少年精神科咨询项目诊所数据集（数据表1）

数据集获取（Figshare）

• 源站标题：Data Sheet 1_A comparison of floating catchment area parameters with applications to a dataset of clinics enrolled in a statewide child and adolescent psychiatric consultation program.pdf
• DOI：10.3389/fpubh.2025.1498819.s001
• 发布日期：2025-02-20
• 文件数：1 个
• 文件总体积：292.91 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_A_comparison_of_floating_catchment_area_parameters_with_applications_to_a_dataset_of_clinics_enrolled_in_a_statewide_child_and_adolescent_psychiatric_consultation_program_pdf/28448990

命令行下载

curl -L -o "Data Sheet 1_A comparison of floating catchment area parameters with applications to a dataset of clinics enrolled in a statewide child and adolescent.pdf" "https://ndownloader.figshare.com/files/52483406"

文件清单

• Data Sheet 1_A comparison of floating catchment area parameters with applications to a dataset of clinics enrolled in a statewide child and adolescent.pdf（292.91 KB）

文件总体积 292.91 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

IntroductionHealthcare resources are often crucial but limited, requiring careful consideration and informed allocation based on population needs and potential healthcare access. In resource allocation settings, availability and accessibility of resources should be examined simultaneously. The two-step floating catchment area (2SFCA) method has been previously used to evaluate spatial accessibility to healthcare resources and services, and to address health-related disparities. The 2SFCA methods have regained significant popularity during the COVID-19 pandemic, as their application proved crucial in addressing priority public health data analysis, modeling, and accessibility challenges. However, comprehensive comparisons of the 2SFCA method input parameters in the context of public health concerns in Texas are lacking. Our study aims to (a) perform a comparative analysis of 2SFCA input parameters on patterns of spatial accessibility and (b) identify a 2SFCA method to guide evaluation of equitable allocation of scarce mental health resources for children and adolescents in Texas.
MethodsWe used the Texas Child Psychiatry Access Network (CPAN) data to assess county-level, regional patterns in access to pediatric psychiatric care, and to identify areas to expand CPAN to mitigate access-related disparities. Using the 2SFCA method, we further compared accessibility patterns across two kernel density distance decay functions for 10 catchment area specifications.
ResultsAs expected, spatial accessibility measures, such as the spatial accessibility ratio (SPAR), are sensitive to input parameters, particularly the catchment area. However, across all catchment area thresholds, two clusters of counties in southern and central Texas had particularly low accessibility, highlighting the opportunity for expanding the provider network in these areas.
DiscussionIdentifying areas with low accessibility can help public health initiatives prioritize regions in need of improved services and resources. The incorporation of additional data on supply capacity and care-seeking behavior would aid in the refinement of estimates for spatial accessibility at the regional level and within la

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fpubh.2025.1498819.s001（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_A_comparison_of_floating_catchment_area_parameters_with_applications_to_a_dataset_of_clinics_enrolled_in_a_statewide_child_and_adolescent_psychiatric_consultation_program_pdf/28448990）。