自动胰岛素输注期间向免校准传感器与远程监测过渡的用户体验:一项定性研究 Table_1

一项关于1型糖尿病患者使用自动胰岛素输注期间过渡到免校准传感器和远程监测的用户体验定性研究结果表。

NIAID Data Ecosystem
浏览 12
表格type 1 diabetes mellituscontinuous glucose monitoringinterviewpatient satisfactionremote monitoring
Table_1_User experiences during the transition to calibration-free sensors with remote monitoring while using automated insulin delivery - a qualitative study.docx

基本信息

模态
表格
大小
0.000016813 GB
许可
CC BY 4.0
创建/更新时间
2026-10-10
版本
v1

资源简介

自动胰岛素输注期间向免校准传感器与远程监测过渡的用户体验:一项定性研究 Table_1

【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 16.81 KB,主题涵盖 type 1 diabetes mellitus、continuous glucose monitoring、interview、patient satisfaction、remote monitoring,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《Table_1_User experiences during the transition to calibration-free sensors with remote monitoring while using automated insulin delivery - a qualitative study.docx》。配套论文《Improved Glycemic Outcomes With Medtronic MiniMed Advanced Hybrid Closed-Loop Delivery: Results From a Randomized Crossover Trial Comparing Automated Insulin Delivery With Predictive Low Glucose Suspend in People With Type 1 Diabetes》发表于 Diabetes Care(2021),DOI:10.2337/dc20-2250。源站首次发布:2023-08-24。

【数据内容】

源站原始描述:IntroductionTo evaluate the experiences of patients with type 1 diabetes following transition from a calibration-requiring to a calibration-free sensor and remote monitoring in the context of using automated insulin delivery (AID). Research design and methodsFifteen participants aged 7–65 years with type 1 diabetes participating in a longitudinal study used a Medtronic® advanced hybrid closed loop (AHCL) device with initially calibration-requiring then calibration-free sensors. Qualitative inter…

【数据结构与技术规格】

文件数 1 个,合计 16.81 KB。Table_1_User experiences during the transition to calibration-free sensors with remote monitoring while using automated insulin delivery - a qualitati.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,16.81 KB。数据集 DOI:10.3389/fendo.2023.1214975.s001。

【主题与分类】

源站学科分类:Reproduction、Cell Metabolism、Endocrinology。主题标签:type 1 diabetes mellitus、continuous glucose monitoring、interview、patient satisfaction、remote monitoring。

【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://frontiersin.figshare.com/articles/dataset/Table_1_User_experiences_during_the_transition_to_calibration-free_sensors_with_remote_monitoring_while_using_automated_insulin_delivery_-_a_qualitative_study_docx/24023742

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Sehgal, Shekhar; De Bock, Martin; Jones, Shirley; Frewen, Carla; Wheeler, Benjamin J. (2023). Table_1_User experiences during the transition to calibration-free sensors with remote monitoring while using automated insulin delivery - a qualitative study.docx. Frontiers. Dataset

官方服务

专家保障全链路合规授权与标注交付

陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

帮我联系

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)

命令行下载

curl -L -o "Table_1_User experiences during the transition to calibration-free sensors with remote monitoring while using automated insulin delivery - a qualitati.docx" "https://ndownloader.figshare.com/files/42125106"

文件清单

  • Table_1_User experiences during the transition to calibration-free sensors with remote monitoring while using automated insulin delivery - a qualitati.docx(16.81 KB)

文件总体积 16.81 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

IntroductionTo evaluate the experiences of patients with type 1 diabetes following transition from a calibration-requiring to a calibration-free sensor and remote monitoring in the context of using automated insulin delivery (AID).
Research design and methodsFifteen participants aged 7–65 years with type 1 diabetes participating in a longitudinal study used a Medtronic® advanced hybrid closed loop (AHCL) device with initially calibration-requiring then calibration-free sensors. Qualitative interviews were conducted ≥20 weeks following use of the calibration-requiring and ≥4 weeks after use of the calibration-free sensors/remote monitoring. Thematic analysis was used to identify key themes and subthemes.
ResultsAt baseline, mean diabetes duration was 14.5 years ( ± 10.9), mean Hba1c 54.8 mmol/mol ( ± 10.2) (7.2 ± 0.9%) and Time in range 75.4% ( ± 11.6). Participants reported a progressive improvement in digital and lifestyle integration, and device trust following transition to calibration-free sensors with remote monitoring potential. They also reported a reduced need for capillary glucose, increased device satisfaction and trust, and reduced burden of diabetes care. Negative aspects reported included periodic early sensor loss, and for some, impaired integration with mobile devices.
ConclusionTransitioning to calibration-free sensors with remote monitoring while using AHCL was associated with better user experience, including perceptions of improved quality of life and a reduced burden of diabetes care. Appropriate expectation setting, training, and ongoing support allow for the optimal user experience while using AHCL.
Clinical trial registrationhttps://www.anzctr.org.au, identifier ACTRN12621000360819

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fendo.2023.1214975.s001(source: https://frontiersin.figshare.com/articles/dataset/Table_1_User_experiences_during_the_transition_to_calibration-free_sensors_with_remote_monitoring_while_using_automated_insulin_delivery_-_a_qualitative_study_docx/24023742)。

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。

⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。

获取专属数据定制方案