Open Access
Open access
volume 24 issue 4 pages 1101

Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST)

Valentino Šafran 1
Simon Lin 2, 3
Jama Nateqi 2, 3
Alistair G Martin 2
Urška Smrke 1
Umut Ariöz 1
Nejc Plohl 4
Matej Rojc 1
Dina Bēma 5
Marcela Chávez 6
Matej Horvat 7
Izidor Mlakar 1
2
 
Science Department, Symptoma GmbH, 1030 Vienna, Austria
6
 
Department of Information System Management, Centre Hospitalier Universitaire de Liège, 4000 Liège, Belgium
7
 
Department of Oncology, University Medical Centre Maribor, 2000 Maribor, Slovenia
Publication typeJournal Article
Publication date2024-02-08
scimago Q1
wos Q2
SJR0.764
CiteScore8.2
Impact factor3.5
ISSN14243210, 14248220
PubMed ID:  38400259
Biochemistry
Analytical Chemistry
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Instrumentation
Abstract

The importance and value of real-world data in healthcare cannot be overstated because it offers a valuable source of insights into patient experiences. Traditional patient-reported experience and outcomes measures (PREMs/PROMs) often fall short in addressing the complexities of these experiences due to subjectivity and their inability to precisely target the questions asked. In contrast, diary recordings offer a promising solution. They can provide a comprehensive picture of psychological well-being, encompassing both psychological and physiological symptoms. This study explores how using advanced digital technologies, i.e., automatic speech recognition and natural language processing, can efficiently capture patient insights in oncology settings. We introduce the MRAST framework, a simplified way to collect, structure, and understand patient data using questionnaires and diary recordings. The framework was validated in a prospective study with 81 colorectal and 85 breast cancer survivors, of whom 37 were male and 129 were female. Overall, the patients evaluated the solution as well made; they found it easy to use and integrate into their daily routine. The majority (75.3%) of the cancer survivors participating in the study were willing to engage in health monitoring activities using digital wearable devices daily for an extended period. Throughout the study, there was a noticeable increase in the number of participants who perceived the system as having excellent usability. Despite some negative feedback, 44.44% of patients still rated the app’s usability as above satisfactory (i.e., 7.9 on 1–10 scale) and the experience with diary recording as above satisfactory (i.e., 7.0 on 1–10 scale). Overall, these findings also underscore the significance of user testing and continuous improvement in enhancing the usability and user acceptance of solutions like the MRAST framework. Overall, the automated extraction of information from diaries represents a pivotal step toward a more patient-centered approach, where healthcare decisions are based on real-world experiences and tailored to individual needs. The potential usefulness of such data is enormous, as it enables better measurement of everyday experiences and opens new avenues for patient-centered care.

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GOST |
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GOST Copy
Šafran V. et al. Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST) // Sensors. 2024. Vol. 24. No. 4. p. 1101.
GOST all authors (up to 50) Copy
Šafran V., Lin S., Nateqi J., Martin A. G., Smrke U., Ariöz U., Plohl N., Rojc M., Bēma D., Chávez M., Horvat M., Mlakar I. Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST) // Sensors. 2024. Vol. 24. No. 4. p. 1101.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.3390/s24041101
UR - https://doi.org/10.3390/s24041101
TI - Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST)
T2 - Sensors
AU - Šafran, Valentino
AU - Lin, Simon
AU - Nateqi, Jama
AU - Martin, Alistair G
AU - Smrke, Urška
AU - Ariöz, Umut
AU - Plohl, Nejc
AU - Rojc, Matej
AU - Bēma, Dina
AU - Chávez, Marcela
AU - Horvat, Matej
AU - Mlakar, Izidor
PY - 2024
DA - 2024/02/08
PB - MDPI
SP - 1101
IS - 4
VL - 24
PMID - 38400259
SN - 1424-3210
SN - 1424-8220
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Šafran,
author = {Valentino Šafran and Simon Lin and Jama Nateqi and Alistair G Martin and Urška Smrke and Umut Ariöz and Nejc Plohl and Matej Rojc and Dina Bēma and Marcela Chávez and Matej Horvat and Izidor Mlakar},
title = {Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST)},
journal = {Sensors},
year = {2024},
volume = {24},
publisher = {MDPI},
month = {feb},
url = {https://doi.org/10.3390/s24041101},
number = {4},
pages = {1101},
doi = {10.3390/s24041101}
}
MLA
Cite this
MLA Copy
Šafran, Valentino, et al. “Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST).” Sensors, vol. 24, no. 4, Feb. 2024, p. 1101. https://doi.org/10.3390/s24041101.