参与者人口统计信息
糖尿病视网膜病变研究中8名参与者的人口统计表格数据，用于分析筛查依从性因素。
基本信息
资源简介
参与者人口统计信息
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集，收录 1 个文件、合计 5.63 KB，主题涵盖 participant populations aligned、grounded theory techniques、facilitators among individuals、conducted analyses using、collected demographic data，可用于统计建模、特征工程与队列分析，CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Participant demographic information.》。源站首次发布：2026-04-02。
【数据内容】
源站原始描述：To validate and expand upon a framework of diabetic retinopathy (DR) screening adherence by examining barriers and facilitators among individuals with severe DR and those under-adherent to screening. From March 2021 to February 2022, we conducted eight remote semi-structured interviews with adults with diabetes across two participant populations: (1) participants with severe DR who had undergone procedures (n = 4) and (2) participants under-adherent to screening, defined as no eye exam in >1 yea…
【数据结构与技术规格】
文件数 1 个，合计 5.63 KB。Table 2.xls：application/vnd.ms-excel，5.63 KB。数据集 DOI：10.1371/journal.pgph.0006230.t002。
【主题与分类】
源站学科分类：Medicine、Biotechnology、Sociology、Biological Sciences not elsewhere classified、Science Policy。主题标签：participant populations aligned、grounded theory techniques、facilitators among individuals、conducted analyses using、collected demographic data、yale eye center、identify recurring themes、participants identified lack、improve patient education、address structural barriers。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面：https://plos.figshare.com/articles/dataset/_p_Participant_demographic_information_p_/31929899
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Fu, Julia; Andoh, Joana; Fairless, Elizabeth; Weiss, June; Norcott, Althea; Nwanyanwu, Kristen (2026). Participant demographic information.. PLOS Global Public Health. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：<p>Participant demographic information.</p>
- DOI：10.1371/journal.pgph.0006230.t002
- 发布日期：2026-04-02
- 文件数：1 个
- 文件总体积：5.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/_p_Participant_demographic_information_p_/31929899
命令行下载
curl -L -o "Table 2.xls" "https://ndownloader.figshare.com/files/63414626"
文件清单
Table 2.xls（5.63 KB）
文件总体积 5.63 KB（源站 API 实测）。
数据说明
To validate and expand upon a framework of diabetic retinopathy (DR) screening adherence by examining barriers and facilitators among individuals with severe DR and those under-adherent to screening. From March 2021 to February 2022, we conducted eight remote semi-structured interviews with adults with diabetes across two participant populations: (1) participants with severe DR who had undergone procedures (n = 4) and (2) participants under-adherent to screening, defined as no eye exam in >1 year (n = 4). We recruited participants from the Yale Eye Center and community referrals. During the interviews, we collected demographic data and presented participants with a DR screening adherence framework previously developed by our group. We transcribed all interviews and conducted analyses using a hybrid deductive-inductive analytic approach informed by grounded theory techniques to identify recurring themes. Themes across both participant populations aligned with the existing framework, including vision status, emotional context, competing concerns, resource availability, cues to action, knowledge-creating experiences, and in-clinic experiences. The patient-doctor relationship emerged as a sub-theme of in-clinic experiences, highlighting the role of trust and communication in supporting sustained eye care engagement. At the individual level, participants with stable vision often perceived no need for screening. At the institutional and structural level, participants identified lack of insurance and transportation as significant barriers. These findings support the robustness of the DR screening adherence framework across varying levels of disease severity and engagement. Interventions that improve patient education, address structural barriers, and strengthen patient-doctor relationships may enhance screening adherence among populations at high risk for vision loss.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pgph.0006230.t002（source: https://plos.figshare.com/articles/dataset/_p_Participant_demographic_information_p_/31929899）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
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