文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

User-Centred Design and Development of a Smartphone Application () for Digital Phenotyping in Ophthalmology.

作者信息

Devraj Kishan, Jones Lee, Higgins Bethany, Thomas Peter B M, Moosajee Mariya

机构信息

Institute of Ophthalmology, University College London, London EC1V 9EL, UK.

Moorfields Eye Hospital NHS Foundation Trust, London EC1V 2PD, UK.

出版信息

Healthcare (Basel). 2024 Dec 18;12(24):2550. doi: 10.3390/healthcare12242550.


DOI:10.3390/healthcare12242550
PMID:39765977
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11675816/
Abstract

BACKGROUND: Visual impairment can significantly impact an individual's daily activities. Patients require regular monitoring, typically occurring within hospital eye services. Capacity constraints have necessitated innovative solutions to improve patient care. Existing digital solutions rely on task-based digital home monitoring such as visual acuity testing. These require active involvement from patients and do not typically offer an indication of quality of life. Digital phenotyping refers to the use of personal digital devices to quantify passive behaviour for detecting clinically significant changes in vision and act as biomarkers for disease. Its uniqueness lies in the ability to detect changes passively. The objective was to co-design an accessible smartphone app () for the purposes of digital phenotyping in people with sight impairment. METHODS: Development of included stakeholder consultations following principles of user-centred design. Apple iOS software frameworks (HealthKit, ResearchKit, and SensorKit) and a SwiftUI developer toolkit were used to enable the collection of active and passive data streams. Accessibility and usability were assessed using the System Usability Scale (SUS) and feedback following a 3-month pilot study. Consultations with patients informed the design of , including preferred survey scheduling and the relevancy of patient support resources. RESULTS: Twenty visually impaired participants (mean age 42 ± 19 years) were recruited to the pilot study. The average score on the SUS was 76.8 (±8.9), indicating good usability. There was a statistically significant moderate negative correlation between SUS scores and visual acuity in both the better (r = -0.494; ≤ 0.001) and worse eye (r = -0.421; ≤ 0.001). CONCLUSIONS: offers promising potential for collecting patient-generated health data for the purposes of digital phenotyping in patients with eye disease. Through further testing and validation, this novel approach to patient care may ultimately provide opportunities for remote monitoring in ophthalmology.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ae/11675816/278dfe0612d3/healthcare-12-02550-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ae/11675816/9b3005524ed7/healthcare-12-02550-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ae/11675816/363a0b2944b9/healthcare-12-02550-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ae/11675816/278dfe0612d3/healthcare-12-02550-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ae/11675816/9b3005524ed7/healthcare-12-02550-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ae/11675816/363a0b2944b9/healthcare-12-02550-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ae/11675816/278dfe0612d3/healthcare-12-02550-g003.jpg

相似文献

[1]
User-Centred Design and Development of a Smartphone Application () for Digital Phenotyping in Ophthalmology.

Healthcare (Basel). 2024-12-18

[2]
Designing Survey-Based Mobile Interfaces for Rural Patients With Cancer Using Apple's ResearchKit and CareKit: Usability Study.

JMIR Form Res. 2024-9-26

[3]
Exploring the Potential of Apple SensorKit and Digital Phenotyping Data as New Digital Biomarkers for Mental Health Research.

Digit Biomark. 2023-8-25

[4]
Digital Phenotyping for Monitoring and Disease Trajectory Prediction of Patients With Cancer: Protocol for a Prospective Observational Cohort Study.

JMIR Res Protoc. 2023-10-10

[5]
Development of a Digital Patient Assistant for the Management of Cyclic Vomiting Syndrome: Patient-Centric Design Study.

JMIR Form Res. 2024-6-6

[6]
Home-monitoring for neovascular age-related macular degeneration in older adults within the UK: the MONARCH diagnostic accuracy study.

Health Technol Assess. 2024-7

[7]
Digital Phenotyping of Mental and Physical Conditions: Remote Monitoring of Patients Through RADAR-Base Platform.

JMIR Ment Health. 2024-10-23

[8]
Cross-Platform Ecological Momentary Assessment App (JTrack-EMA+): Development and Usability Study.

J Med Internet Res. 2025-1-28

[9]
Usability of smartphone apps as reading aids for low vision patients.

Disabil Rehabil Assist Technol. 2022-10

[10]
Personalized Smartphone-Enabled Assessment of Blood Pressure and Its Treatment During the SARS-CoV-2 COVID-19 Pandemic in Patients From the CURE-19 Study: Longitudinal Observational Study.

JMIR Mhealth Uhealth. 2024-12-3

引用本文的文献

[1]
Challenges and standardisation strategies for sensor-based data collection for digital phenotyping.

Commun Med (Lond). 2025-8-19

本文引用的文献

[1]
Leveraging foundation and large language models in medical artificial intelligence.

Chin Med J (Engl). 2024-11-5

[2]
Large language models approach expert-level clinical knowledge and reasoning in ophthalmology: A head-to-head cross-sectional study.

PLOS Digit Health. 2024-4-17

[3]
Assessment of a Large Language Model's Responses to Questions and Cases About Glaucoma and Retina Management.

JAMA Ophthalmol. 2024-4-1

[4]
Multimodal digital phenotyping of diet, physical activity, and glycemia in Hispanic/Latino adults with or at risk of type 2 diabetes.

NPJ Digit Med. 2024-1-11

[5]
'It would help people to help me': Acceptability of digital phenotyping among young people with visual impairment and their families.

Digit Health. 2024-1-5

[6]
Review of emerging trends and projection of future developments in large language models research in ophthalmology.

Br J Ophthalmol. 2024-9-20

[7]
Exploring the Potential of Apple SensorKit and Digital Phenotyping Data as New Digital Biomarkers for Mental Health Research.

Digit Biomark. 2023-8-25

[8]
Digital health for all: How digital health could reduce inequality and increase universal health coverage.

Digit Health. 2023-7-7

[9]
Sources of bias in artificial intelligence that perpetuate healthcare disparities-A global review.

PLOS Digit Health. 2022-3-31

[10]
Relapse prediction in schizophrenia with smartphone digital phenotyping during COVID-19: a prospective, three-site, two-country, longitudinal study.

Schizophrenia (Heidelb). 2023-1-27

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索