TY - JOUR
T1 - Co-design of a voice-based app to monitor long COVID symptoms with its end-users
T2 - A mixed-method study
AU - Fischer, Aurélie
AU - Aguayo, Gloria
AU - Pinker, India
AU - Oustric, Pauline
AU - Lachaise, Tom
AU - Wilmes, Paul
AU - Larché, Jérôme
AU - Benoy, Charles
AU - Fagherazzi, Guy
N1 - Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Luxembourg Government through the CoVaLux programme and funded by the Luxembourg National Research Fund, grant number 16954531.
Publisher Copyright:
© The Author(s) 2024.
PY - 2024/9/9
Y1 - 2024/9/9
N2 - Background: People living with Long COVID (PWLC), which is still a poorly understood disease, often face major issues accessing proper care and frequently feel abandoned by the healthcare system. PWLC frequently report impaired quality of life because of the medical burden, the variability and intensity of symptoms, and insecurity toward the future. These particular needs justify the development of innovative, minimally disruptive solutions to facilitate the monitoring of this complex and fluctuating disease. Voice-based interactions and vocal biomarkers are promising digital approaches for such health monitoring. Methods: Based on a mixed-method approach, this study describes the entire co-design process of Long COVID Companion, a voice-based digital health app to monitor Long COVID symptoms. Potential end-users of the app, both PWLC and healthcare professionals (HCP) were involved to (1) understand the unmet needs and expectations related to Long COVID care and management, (2) to assess the barriers and facilitators regarding a health monitoring app, (3) to define the app characteristics, including future potential use of vocal biomarkers and (4) to develop a first version of the app. Results: This study revealed high needs and expectations regarding a digital health app to monitor Long COVID symptoms and the readiness to use vocal biomarkers from end-users. The main expectations included improved care and daily life, and major concerns were linked to accessibility and data privacy. Long COVID Companion was developed as a web application and is composed of a health monitoring component that allows auto-evaluation of symptoms, global health, and scoring relevant symptoms and quality of life using standardized questionnaires. Conclusions: The Long COVID Companion app will address a major gap and provide day-to-day support for PWLC. However, further studies will be needed following its release, to evaluate its acceptability, usability and effectiveness.
AB - Background: People living with Long COVID (PWLC), which is still a poorly understood disease, often face major issues accessing proper care and frequently feel abandoned by the healthcare system. PWLC frequently report impaired quality of life because of the medical burden, the variability and intensity of symptoms, and insecurity toward the future. These particular needs justify the development of innovative, minimally disruptive solutions to facilitate the monitoring of this complex and fluctuating disease. Voice-based interactions and vocal biomarkers are promising digital approaches for such health monitoring. Methods: Based on a mixed-method approach, this study describes the entire co-design process of Long COVID Companion, a voice-based digital health app to monitor Long COVID symptoms. Potential end-users of the app, both PWLC and healthcare professionals (HCP) were involved to (1) understand the unmet needs and expectations related to Long COVID care and management, (2) to assess the barriers and facilitators regarding a health monitoring app, (3) to define the app characteristics, including future potential use of vocal biomarkers and (4) to develop a first version of the app. Results: This study revealed high needs and expectations regarding a digital health app to monitor Long COVID symptoms and the readiness to use vocal biomarkers from end-users. The main expectations included improved care and daily life, and major concerns were linked to accessibility and data privacy. Long COVID Companion was developed as a web application and is composed of a health monitoring component that allows auto-evaluation of symptoms, global health, and scoring relevant symptoms and quality of life using standardized questionnaires. Conclusions: The Long COVID Companion app will address a major gap and provide day-to-day support for PWLC. However, further studies will be needed following its release, to evaluate its acceptability, usability and effectiveness.
KW - digital health app
KW - Long COVID
KW - mixed methods
KW - remote symptom monitoring
KW - vocal biomarkers
UR - http://www.scopus.com/inward/record.url?scp=85203559092&partnerID=8YFLogxK
UR - https://pubmed.ncbi.nlm.nih.gov/39257875/
U2 - 10.1177/20552076241272671
DO - 10.1177/20552076241272671
M3 - Article
AN - SCOPUS:85203559092
SN - 2055-2076
VL - 10
JO - Digital Health
JF - Digital Health
M1 - 20552076241272671
ER -