参与者资格标准
该数据集提供一项关于中风康复设施物理环境影响的研究的参与者资格标准。

基本信息
资源简介
参与者资格标准
【数据集背景】
本数据集源站标题为《Participant eligibility criteria.》。源站首次发布:2023-06-09。
【数据内容】
源站原始描述:Hospital design can impact patient outcomes, but there is very little healthcare design evidence specific to stroke rehabilitation facilities. Our aim was to explore, from the patient perspective, the role of the physical environment in factors crucial to stroke recovery, namely, stroke survivor activity (physical, cognitive, social), sleep, emotional well-being, and safety. We conducted a mixed-methods multiple-case study at two inpatient rehabilitation facilities in Victoria, Australia, (n = 2…
【数据结构与技术规格】
文件数 1 个,合计 5.63 KB。Table 1.xls:application/vnd.ms-excel,5.63 KB。数据集 DOI:10.1371/journal.pone.0280690.t001。
【主题与分类】
源站学科分类:Medicine、Biotechnology、Environmental Sciences not elsewhere classified、Biological Sciences not elsewhere classified、Science Policy。主题标签:using “ walk、social ), sleep、privacy without isolation、stroke survivors spent、stroke survivor activity、stroke rehabilitation facilities、new conceptual model、impact patient outcomes、div >< p、based design principles。
【适用方向】
文本类数据可用于医学自然语言处理,如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/Participant_eligibility_criteria_/23468775
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Lipson-Smith, Ruby; Zeeman, Heidi; Muns, Leanne; Jeddi, Faraz; Simondson, Janine; Bernhardt, Julie (2023). Participant eligibility criteria.. PLOS ONE. Dataset
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:Participant eligibility criteria.
- DOI:10.1371/journal.pone.0280690.t001
- 发布日期:2023-06-09
- 文件数:1 个
- 文件总体积:5.63 KB
- 源站页面:https://plos.figshare.com/articles/dataset/Participant_eligibility_criteria_/23468775
命令行下载
curl -L -o "Table 1.xls" "https://ndownloader.figshare.com/files/41177496"
文件清单
Table 1.xls(5.63 KB)
文件总体积 5.63 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
Hospital design can impact patient outcomes, but there is very little healthcare design evidence specific to stroke rehabilitation facilities. Our aim was to explore, from the patient perspective, the role of the physical environment in factors crucial to stroke recovery, namely, stroke survivor activity (physical, cognitive, social), sleep, emotional well-being, and safety. We conducted a mixed-methods multiple-case study at two inpatient rehabilitation facilities in Victoria, Australia, (n = 20 at Case 1, n = 16 at Case 2) using “walk-through” semi-structured interviews, behavioural mapping, questionnaires, and retrospective audit. Four interrelated themes emerged: 1) entrapment and escape; 2) power, dependency, and identity in an institutional environment; 3) the rehabilitation facility is a shared space; and 4) the environment should be legible and patient-centred. Quantitative data revealed patterns in patient activity; stroke survivors spent over 75% of their time in bedrooms and were often inactive. Convergent mixed methods analysis was used to generate a new conceptual model of the role of the physical environment in stroke survivors’ behaviour and well-being, highlighting the importance of variety and interest, privacy without isolation, and patient-centred design. This model can be used by designers, healthcare providers, and policy makers to inform the design of rehabilitation environments.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0280690.t001(source: https://plos.figshare.com/articles/dataset/Participant_eligibility_criteria_/23468775)。
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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