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Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol

SIMPLE SUMMARY: Adolescent and young adult (AYA) patients diagnosed with cancer are at a higher risk of psychological distress, which requires regular monitoring throughout their cancer journeys. Paper-and-pencil or digital surveys for psychological stress are often cumbersome to complete during a p...

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Autores principales: Zhang, Anao, Kamat, Aarti, Acquati, Chiara, Aratow, Michael, Kim, Johnny S., DuVall, Adam S., Walling, Emily
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8870320/
https://www.ncbi.nlm.nih.gov/pubmed/35205663
http://dx.doi.org/10.3390/cancers14040914
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author Zhang, Anao
Kamat, Aarti
Acquati, Chiara
Aratow, Michael
Kim, Johnny S.
DuVall, Adam S.
Walling, Emily
author_facet Zhang, Anao
Kamat, Aarti
Acquati, Chiara
Aratow, Michael
Kim, Johnny S.
DuVall, Adam S.
Walling, Emily
author_sort Zhang, Anao
collection PubMed
description SIMPLE SUMMARY: Adolescent and young adult (AYA) patients diagnosed with cancer are at a higher risk of psychological distress, which requires regular monitoring throughout their cancer journeys. Paper-and-pencil or digital surveys for psychological stress are often cumbersome to complete during a patient’s visit, and many patients find completing the same survey multiple times repetitive and boring. Recent advances in mobile technology and speech science have enabled flexible and engaging ways of monitoring psychological distress. This paper describes the scientific process we will use to evaluate an artificial intelligence (AI)-enabled mobile app to monitor depression and anxiety among AYAs diagnosed with cancer. ABSTRACT: Adolescents and young adults (AYAs) diagnosed with cancer are an age-defined population, with studies reporting up to 45% of the population experiencing psychological distress. Although it is essential to screen and monitor for psychological distress throughout AYAs’ cancer journeys, many cancer centers fail to effectively implement distress screening protocols largely due to busy clinical workflow and survey fatigue. Recent advances in mobile technology and speech science have enabled flexible and engaging methods to monitor psychological distress. However, patient-centered research focusing on these methods’ feasibility and acceptability remains lacking. Therefore, in this project, we aim to evaluate the feasibility and acceptability of an artificial intelligence (AI)-enabled and speech-based mobile application to monitor psychological distress among AYAs diagnosed with cancer. We use a single-arm prospective cohort design with a stratified sampling strategy. We aim to recruit 60 AYAs diagnosed with cancer and to monitor their psychological distress using an AI-enabled speech-based distress monitoring tool over a 6 month period. The primary feasibility endpoint of this study is defined by the number of participants completing four out of six monthly distress assessments, and the acceptability endpoint is defined both quantitatively using the acceptability of intervention measure and qualitatively using semi-structured interviews.
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spelling pubmed-88703202022-02-25 Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol Zhang, Anao Kamat, Aarti Acquati, Chiara Aratow, Michael Kim, Johnny S. DuVall, Adam S. Walling, Emily Cancers (Basel) Study Protocol SIMPLE SUMMARY: Adolescent and young adult (AYA) patients diagnosed with cancer are at a higher risk of psychological distress, which requires regular monitoring throughout their cancer journeys. Paper-and-pencil or digital surveys for psychological stress are often cumbersome to complete during a patient’s visit, and many patients find completing the same survey multiple times repetitive and boring. Recent advances in mobile technology and speech science have enabled flexible and engaging ways of monitoring psychological distress. This paper describes the scientific process we will use to evaluate an artificial intelligence (AI)-enabled mobile app to monitor depression and anxiety among AYAs diagnosed with cancer. ABSTRACT: Adolescents and young adults (AYAs) diagnosed with cancer are an age-defined population, with studies reporting up to 45% of the population experiencing psychological distress. Although it is essential to screen and monitor for psychological distress throughout AYAs’ cancer journeys, many cancer centers fail to effectively implement distress screening protocols largely due to busy clinical workflow and survey fatigue. Recent advances in mobile technology and speech science have enabled flexible and engaging methods to monitor psychological distress. However, patient-centered research focusing on these methods’ feasibility and acceptability remains lacking. Therefore, in this project, we aim to evaluate the feasibility and acceptability of an artificial intelligence (AI)-enabled and speech-based mobile application to monitor psychological distress among AYAs diagnosed with cancer. We use a single-arm prospective cohort design with a stratified sampling strategy. We aim to recruit 60 AYAs diagnosed with cancer and to monitor their psychological distress using an AI-enabled speech-based distress monitoring tool over a 6 month period. The primary feasibility endpoint of this study is defined by the number of participants completing four out of six monthly distress assessments, and the acceptability endpoint is defined both quantitatively using the acceptability of intervention measure and qualitatively using semi-structured interviews. MDPI 2022-02-12 /pmc/articles/PMC8870320/ /pubmed/35205663 http://dx.doi.org/10.3390/cancers14040914 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Study Protocol
Zhang, Anao
Kamat, Aarti
Acquati, Chiara
Aratow, Michael
Kim, Johnny S.
DuVall, Adam S.
Walling, Emily
Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol
title Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol
title_full Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol
title_fullStr Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol
title_full_unstemmed Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol
title_short Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol
title_sort evaluating the feasibility and acceptability of an artificial-intelligence-enabled and speech-based distress screening mobile app for adolescents and young adults diagnosed with cancer: a study protocol
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8870320/
https://www.ncbi.nlm.nih.gov/pubmed/35205663
http://dx.doi.org/10.3390/cancers14040914
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