Usability evaluation of mobile phone technologies for capturing cancer patient-reported outcomes and physical functions

Digital health(2023)

引用 0|浏览2
暂无评分
摘要
BackgroundBy eliminating the requirement for participants to make frequent visits to research sites, mobile phone applications ("apps") may help to decentralize clinical trials. Apps may also be an effective mechanism for capturing patient-reported outcomes and other endpoints, helping to optimize patient care during and outside of clinical trials. ObjectivesWe report on the usability of Digital BioMarkers for Clinical Impact (DigiBioMarC & TRADE; (DBM)), a novel smartphone-based app used by cancer patients in conjunction with a wearable device (Apple Watch & REG;). DBM is designed to collect patient-reported outcomes and record physical functions. MethodsIn a fully decentralized "bring-your-own-device" smartphone study, we enrolled 54 cancer patient and caregiver dyads from Kaiser Permanente Northern California (KPNC) from October 2020 through March 2021. Patients used the app for at least 28 days, completed weekly questionnaires about their symptoms, physical functions, and mood, and performed timed physical tasks. Usability was determined through a subset of the Mobile App Rating Scale (MARS), the full System Usability Scale (SUS), the Net Promoter Score (NPS), and semi-structured interviews. ResultsWe obtained usability survey data from 50 of 54 patients. Median responses to the selected MARS questions and the mean SUS scores indicated above average usability. The NPS from the semi-structured interviews at the end of the study was 24, indicating a favorable score. ConclusionsCancer patients reported above average usability for the DBM app. Qualitative analyses indicated that the app was easy to use and helpful. Future work will emphasize implementing further patient recommendations and evaluating the app's clinical efficacy in multiple settings.
更多
查看译文
关键词
BYOD,decentralized clinical trial,ePROs,wearable sensors,connected sensors,neoplasm,cancer,mHealth,patient-reported outcomes,mobile application,usability,smartphone
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要