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formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R

Open-source software improves the reproducibility of scientific research. Because existing open-source tools often do not offer dedicated support for longitudinal data collection on phones and computers, we built formr, a study framework that enables researchers to conduct both simple surveys and mo...

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Detalles Bibliográficos
Autores principales: Arslan, Ruben C., Walther, Matthias P., Tata, Cyril S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005096/
https://www.ncbi.nlm.nih.gov/pubmed/30937847
http://dx.doi.org/10.3758/s13428-019-01236-y
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author Arslan, Ruben C.
Walther, Matthias P.
Tata, Cyril S.
author_facet Arslan, Ruben C.
Walther, Matthias P.
Tata, Cyril S.
author_sort Arslan, Ruben C.
collection PubMed
description Open-source software improves the reproducibility of scientific research. Because existing open-source tools often do not offer dedicated support for longitudinal data collection on phones and computers, we built formr, a study framework that enables researchers to conduct both simple surveys and more intricate studies. With automated email and text message reminders that can be sent according to any schedule, longitudinal and experience-sampling studies become easy to implement. By integrating a web-based application programming interface for the statistical programming language R via OpenCPU, formr allows researchers to use a familiar programming language to enable complex features. These can range from adaptive testing, to graphical and interactive feedback, to integration with non-survey data sources such as self-trackers or online social network data. Here we showcase three studies created in formr: a study of couples with dyadic feedback; a longitudinal study over months, which included social networks and peer and partner ratings; and a diary study with daily invitations sent out by text message and email and extensive feedback on intraindividual patterns.
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spelling pubmed-70050962020-02-25 formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R Arslan, Ruben C. Walther, Matthias P. Tata, Cyril S. Behav Res Methods Article Open-source software improves the reproducibility of scientific research. Because existing open-source tools often do not offer dedicated support for longitudinal data collection on phones and computers, we built formr, a study framework that enables researchers to conduct both simple surveys and more intricate studies. With automated email and text message reminders that can be sent according to any schedule, longitudinal and experience-sampling studies become easy to implement. By integrating a web-based application programming interface for the statistical programming language R via OpenCPU, formr allows researchers to use a familiar programming language to enable complex features. These can range from adaptive testing, to graphical and interactive feedback, to integration with non-survey data sources such as self-trackers or online social network data. Here we showcase three studies created in formr: a study of couples with dyadic feedback; a longitudinal study over months, which included social networks and peer and partner ratings; and a diary study with daily invitations sent out by text message and email and extensive feedback on intraindividual patterns. Springer US 2019-04-01 2020 /pmc/articles/PMC7005096/ /pubmed/30937847 http://dx.doi.org/10.3758/s13428-019-01236-y Text en © The Author(s) 2019 Open Access This 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.
spellingShingle Article
Arslan, Ruben C.
Walther, Matthias P.
Tata, Cyril S.
formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R
title formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R
title_full formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R
title_fullStr formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R
title_full_unstemmed formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R
title_short formr: A study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using R
title_sort formr: a study framework allowing for automated feedback generation and complex longitudinal experience-sampling studies using r
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005096/
https://www.ncbi.nlm.nih.gov/pubmed/30937847
http://dx.doi.org/10.3758/s13428-019-01236-y
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