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Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain

Smartphone-based ecological momentary assessment (EMA) methods are widely used for data collection and monitoring in healthcare but their uptake clinically has been limited. Low back pain, a condition with limited effective treatments, has the potential to benefit from EMA. This study aimed to (i) d...

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Autores principales: Kaur, Ekjyot, Delir Haghighi, Pari, Cicuttini, Flavia M., Urquhart, Donna M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503545/
https://www.ncbi.nlm.nih.gov/pubmed/36146442
http://dx.doi.org/10.3390/s22187095
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author Kaur, Ekjyot
Delir Haghighi, Pari
Cicuttini, Flavia M.
Urquhart, Donna M.
author_facet Kaur, Ekjyot
Delir Haghighi, Pari
Cicuttini, Flavia M.
Urquhart, Donna M.
author_sort Kaur, Ekjyot
collection PubMed
description Smartphone-based ecological momentary assessment (EMA) methods are widely used for data collection and monitoring in healthcare but their uptake clinically has been limited. Low back pain, a condition with limited effective treatments, has the potential to benefit from EMA. This study aimed to (i) determine the feasibility of collecting pain and function data using smartphone-based EMA, (ii) examine pain data collected using EMA compared to traditional methods, (iii) characterize individuals’ progress in relation to pain and function, and (iv) investigate the appropriation of the method. Our results showed that an individual’s ‘pain intensity index’ provided a measure of the burden of their low back pain, which differed from but complemented traditional ‘change in pain intensity’ measures. We found significant variations in the pain and function over the course of an individual’s back pain that was not captured by the cohort’s mean scores, the approach currently used as the gold standard in clinical trials. The EMA method was highly acceptable to the participants, and the Model of Technology Appropriation provided information on technology adoption. This study highlights the potential of the smartphone-based EMA method for enhancing the collection of outcome data and providing a personalized approach to the management of low back pain.
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spelling pubmed-95035452022-09-24 Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain Kaur, Ekjyot Delir Haghighi, Pari Cicuttini, Flavia M. Urquhart, Donna M. Sensors (Basel) Article Smartphone-based ecological momentary assessment (EMA) methods are widely used for data collection and monitoring in healthcare but their uptake clinically has been limited. Low back pain, a condition with limited effective treatments, has the potential to benefit from EMA. This study aimed to (i) determine the feasibility of collecting pain and function data using smartphone-based EMA, (ii) examine pain data collected using EMA compared to traditional methods, (iii) characterize individuals’ progress in relation to pain and function, and (iv) investigate the appropriation of the method. Our results showed that an individual’s ‘pain intensity index’ provided a measure of the burden of their low back pain, which differed from but complemented traditional ‘change in pain intensity’ measures. We found significant variations in the pain and function over the course of an individual’s back pain that was not captured by the cohort’s mean scores, the approach currently used as the gold standard in clinical trials. The EMA method was highly acceptable to the participants, and the Model of Technology Appropriation provided information on technology adoption. This study highlights the potential of the smartphone-based EMA method for enhancing the collection of outcome data and providing a personalized approach to the management of low back pain. MDPI 2022-09-19 /pmc/articles/PMC9503545/ /pubmed/36146442 http://dx.doi.org/10.3390/s22187095 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 Article
Kaur, Ekjyot
Delir Haghighi, Pari
Cicuttini, Flavia M.
Urquhart, Donna M.
Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain
title Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain
title_full Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain
title_fullStr Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain
title_full_unstemmed Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain
title_short Smartphone-Based Ecological Momentary Assessment for Collecting Pain and Function Data for Those with Low Back Pain
title_sort smartphone-based ecological momentary assessment for collecting pain and function data for those with low back pain
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503545/
https://www.ncbi.nlm.nih.gov/pubmed/36146442
http://dx.doi.org/10.3390/s22187095
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