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Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain

BACKGROUND: Mobile technology has opened opportunities within health care and research to allow for frequent monitoring of patients. This has given rise to detailed longitudinal information and new insights concerning behaviour and development of conditions over time. Responding to frequent question...

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Autores principales: Axén, Iben, Bodin, Lennart
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5020455/
https://www.ncbi.nlm.nih.gov/pubmed/27619804
http://dx.doi.org/10.1186/s12874-016-0221-4
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author Axén, Iben
Bodin, Lennart
author_facet Axén, Iben
Bodin, Lennart
author_sort Axén, Iben
collection PubMed
description BACKGROUND: Mobile technology has opened opportunities within health care and research to allow for frequent monitoring of patients. This has given rise to detailed longitudinal information and new insights concerning behaviour and development of conditions over time. Responding to frequent questionnaires delivered through mobile technology has also shown good compliance, far exceeding that of traditional paper questionnaires. However, to optimize compliance, the burden on the subjects should be kept at a minimum. In this study, the effect of using fewer data points compared to the full data set was examined, assuming that fewer measurements would lead to better compliance. METHOD: Weekly text-message responses for 6 months from subjects recovering from an episode of low back pain (LBP) were available for this secondary analysis. Most subjects showed a trajectory with an initial improvement and a steady state thereafter. The data were originally used to subgroup (cluster) patients according to their pain trajectory. The resulting 4-cluster solution was compared with clusters obtained from five datasets with fewer data-points using Kappa agreement as well as inspection of estimated pain trajectories. Further, the relative risk of experiencing a day with bothersome pain was compared week by week to show the effects of discarding some weekly data. RESULTS: One hundred twenty-nine subjects were included in this analysis. Using data from every other weekly measure had the highest agreement with the clusters from the full dataset, weighted Kappa = 0.823. However, the visual description of pain trajectories favoured using the first 18 weekly measurements to fully capture the phases of improvement and steady-state. The weekly relative risks were influenced by the pain trajectories and 18 weeks or every other weekly measure were the optimal designs, next to the full data set. CONCLUSIONS: A population recovering from an episode of LBP could be described using every other weekly measurement, an option which requires fewer weekly measures than measuring weekly for 18 weeks. However a higher measuring frequency might be needed in the beginning of a clinical course to fully map the pain trajectories.
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spelling pubmed-50204552016-09-14 Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain Axén, Iben Bodin, Lennart BMC Med Res Methodol Research Article BACKGROUND: Mobile technology has opened opportunities within health care and research to allow for frequent monitoring of patients. This has given rise to detailed longitudinal information and new insights concerning behaviour and development of conditions over time. Responding to frequent questionnaires delivered through mobile technology has also shown good compliance, far exceeding that of traditional paper questionnaires. However, to optimize compliance, the burden on the subjects should be kept at a minimum. In this study, the effect of using fewer data points compared to the full data set was examined, assuming that fewer measurements would lead to better compliance. METHOD: Weekly text-message responses for 6 months from subjects recovering from an episode of low back pain (LBP) were available for this secondary analysis. Most subjects showed a trajectory with an initial improvement and a steady state thereafter. The data were originally used to subgroup (cluster) patients according to their pain trajectory. The resulting 4-cluster solution was compared with clusters obtained from five datasets with fewer data-points using Kappa agreement as well as inspection of estimated pain trajectories. Further, the relative risk of experiencing a day with bothersome pain was compared week by week to show the effects of discarding some weekly data. RESULTS: One hundred twenty-nine subjects were included in this analysis. Using data from every other weekly measure had the highest agreement with the clusters from the full dataset, weighted Kappa = 0.823. However, the visual description of pain trajectories favoured using the first 18 weekly measurements to fully capture the phases of improvement and steady-state. The weekly relative risks were influenced by the pain trajectories and 18 weeks or every other weekly measure were the optimal designs, next to the full data set. CONCLUSIONS: A population recovering from an episode of LBP could be described using every other weekly measurement, an option which requires fewer weekly measures than measuring weekly for 18 weeks. However a higher measuring frequency might be needed in the beginning of a clinical course to fully map the pain trajectories. BioMed Central 2016-09-13 /pmc/articles/PMC5020455/ /pubmed/27619804 http://dx.doi.org/10.1186/s12874-016-0221-4 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Axén, Iben
Bodin, Lennart
Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain
title Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain
title_full Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain
title_fullStr Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain
title_full_unstemmed Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain
title_short Searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (SMS) to collect repeated measures among patients with low back pain
title_sort searching for the optimal measuring frequency in longitudinal studies -- an example utilizing short message service (sms) to collect repeated measures among patients with low back pain
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5020455/
https://www.ncbi.nlm.nih.gov/pubmed/27619804
http://dx.doi.org/10.1186/s12874-016-0221-4
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