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Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder
The use of remote measurement technologies (RMTs) across mobile health (mHealth) studies is becoming popular, given their potential for providing rich data on symptom change and indicators of future state in recurrent conditions such as major depressive disorder (MDD). Understanding recruitment into...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440458/ https://www.ncbi.nlm.nih.gov/pubmed/36057688 http://dx.doi.org/10.1038/s41746-022-00680-z |
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author | Oetzmann, Carolin White, Katie M. Ivan, Alina Julie, Jessica Leightley, Daniel Lavelle, Grace Lamers, Femke Siddi, Sara Annas, Peter Garcia, Sara Arranz Haro, Josep Maria Mohr, David C. Penninx, Brenda W. J. H. Simblett, Sara K. Wykes, Til Narayan, Vaibhav A. Hotopf, Matthew Matcham, Faith |
author_facet | Oetzmann, Carolin White, Katie M. Ivan, Alina Julie, Jessica Leightley, Daniel Lavelle, Grace Lamers, Femke Siddi, Sara Annas, Peter Garcia, Sara Arranz Haro, Josep Maria Mohr, David C. Penninx, Brenda W. J. H. Simblett, Sara K. Wykes, Til Narayan, Vaibhav A. Hotopf, Matthew Matcham, Faith |
author_sort | Oetzmann, Carolin |
collection | PubMed |
description | The use of remote measurement technologies (RMTs) across mobile health (mHealth) studies is becoming popular, given their potential for providing rich data on symptom change and indicators of future state in recurrent conditions such as major depressive disorder (MDD). Understanding recruitment into RMT research is fundamental for improving historically small sample sizes, reducing loss of statistical power, and ultimately producing results worthy of clinical implementation. There is a need for the standardisation of best practices for successful recruitment into RMT research. The current paper reviews lessons learned from recruitment into the Remote Assessment of Disease and Relapse- Major Depressive Disorder (RADAR-MDD) study, a large-scale, multi-site prospective cohort study using RMT to explore the clinical course of people with depression across the UK, the Netherlands, and Spain. More specifically, the paper reflects on key experiences from the UK site and consolidates these into four key recruitment strategies, alongside a review of barriers to recruitment. Finally, the strategies and barriers outlined are combined into a model of lessons learned. This work provides a foundation for future RMT study design, recruitment and evaluation. |
format | Online Article Text |
id | pubmed-9440458 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94404582022-09-05 Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder Oetzmann, Carolin White, Katie M. Ivan, Alina Julie, Jessica Leightley, Daniel Lavelle, Grace Lamers, Femke Siddi, Sara Annas, Peter Garcia, Sara Arranz Haro, Josep Maria Mohr, David C. Penninx, Brenda W. J. H. Simblett, Sara K. Wykes, Til Narayan, Vaibhav A. Hotopf, Matthew Matcham, Faith NPJ Digit Med Perspective The use of remote measurement technologies (RMTs) across mobile health (mHealth) studies is becoming popular, given their potential for providing rich data on symptom change and indicators of future state in recurrent conditions such as major depressive disorder (MDD). Understanding recruitment into RMT research is fundamental for improving historically small sample sizes, reducing loss of statistical power, and ultimately producing results worthy of clinical implementation. There is a need for the standardisation of best practices for successful recruitment into RMT research. The current paper reviews lessons learned from recruitment into the Remote Assessment of Disease and Relapse- Major Depressive Disorder (RADAR-MDD) study, a large-scale, multi-site prospective cohort study using RMT to explore the clinical course of people with depression across the UK, the Netherlands, and Spain. More specifically, the paper reflects on key experiences from the UK site and consolidates these into four key recruitment strategies, alongside a review of barriers to recruitment. Finally, the strategies and barriers outlined are combined into a model of lessons learned. This work provides a foundation for future RMT study design, recruitment and evaluation. Nature Publishing Group UK 2022-09-03 /pmc/articles/PMC9440458/ /pubmed/36057688 http://dx.doi.org/10.1038/s41746-022-00680-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Perspective Oetzmann, Carolin White, Katie M. Ivan, Alina Julie, Jessica Leightley, Daniel Lavelle, Grace Lamers, Femke Siddi, Sara Annas, Peter Garcia, Sara Arranz Haro, Josep Maria Mohr, David C. Penninx, Brenda W. J. H. Simblett, Sara K. Wykes, Til Narayan, Vaibhav A. Hotopf, Matthew Matcham, Faith Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder |
title | Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder |
title_full | Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder |
title_fullStr | Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder |
title_full_unstemmed | Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder |
title_short | Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder |
title_sort | lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440458/ https://www.ncbi.nlm.nih.gov/pubmed/36057688 http://dx.doi.org/10.1038/s41746-022-00680-z |
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