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Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let’s Move It trial

Background: Visualisations and readily-accessible web-based supplementary files can improve data reporting and transparency. In this paper, we make use of recent developments in software and psychological network analysis to describe the baseline cohort of a trial testing the Let’s Move It intervent...

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Autores principales: Heino, Matti T. J., Knittle, Keegan, Fried, Eiko, Sund, Reijo, Haukkala, Ari, Borodulin, Katja, Uutela, Antti, Araujo-Soares, Vera, Vasankari, Tommi, Hankonen, Nelli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Routledge 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114395/
https://www.ncbi.nlm.nih.gov/pubmed/34040851
http://dx.doi.org/10.1080/21642850.2019.1646136
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author Heino, Matti T. J.
Knittle, Keegan
Fried, Eiko
Sund, Reijo
Haukkala, Ari
Borodulin, Katja
Uutela, Antti
Araujo-Soares, Vera
Vasankari, Tommi
Hankonen, Nelli
author_facet Heino, Matti T. J.
Knittle, Keegan
Fried, Eiko
Sund, Reijo
Haukkala, Ari
Borodulin, Katja
Uutela, Antti
Araujo-Soares, Vera
Vasankari, Tommi
Hankonen, Nelli
author_sort Heino, Matti T. J.
collection PubMed
description Background: Visualisations and readily-accessible web-based supplementary files can improve data reporting and transparency. In this paper, we make use of recent developments in software and psychological network analysis to describe the baseline cohort of a trial testing the Let’s Move It intervention, which aimed to increase physical activity (PA) and reduce sedentary behaviours (SB) among vocational school students. Methods: At baseline, 1166 adolescents, distributed across 6 school clusters and four educational tracks, completed measures of PA and SB, theoretical predictors of these behaviours, and body composition. Within a comprehensive website supplement, which includes all code and analyses, data were tabulated and visualised, and network analyses explored relations between predictor variables and outcomes. Results: Average daily moderate-to-vigorous PA was 65 min (CI95: 57min–73 min), and SB 8h44 min (CI95: 8h04min–9h24 min), with 25.8 (CI95: 23.5–28.0) interruptions to sitting. Cluster randomisation appeared to result in balanced distributions for baseline characteristics between intervention and control groups, but differences emerged across the four educational tracks. Self-reported behaviour change technique (BCT) use was low for many but not all techniques. A network analysis revealed direct relationships between PA and behavioural experiments, planning and autonomous motivation, and several BCTs were connected to PA via autonomous motivation. Visualisation uncovered a case of Simpson’s paradox. Conclusions: Data-visualisation and data exploration techniques (e.g. network analysis) can help reveal the dynamics involved in complex multi-causal systems – a challenging task with traditional data presentations. The benefits of presenting complex data visually should encourage researchers to publish extensive analyses and descriptions as website supplements, which would increase the speed and quality of scientific communication, as well as help to address the crisis of reduced confidence in research findings. We hope that this example will serve as a template for other investigators to improve upon in the future.
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spelling pubmed-81143952021-05-25 Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let’s Move It trial Heino, Matti T. J. Knittle, Keegan Fried, Eiko Sund, Reijo Haukkala, Ari Borodulin, Katja Uutela, Antti Araujo-Soares, Vera Vasankari, Tommi Hankonen, Nelli Health Psychol Behav Med Articles Background: Visualisations and readily-accessible web-based supplementary files can improve data reporting and transparency. In this paper, we make use of recent developments in software and psychological network analysis to describe the baseline cohort of a trial testing the Let’s Move It intervention, which aimed to increase physical activity (PA) and reduce sedentary behaviours (SB) among vocational school students. Methods: At baseline, 1166 adolescents, distributed across 6 school clusters and four educational tracks, completed measures of PA and SB, theoretical predictors of these behaviours, and body composition. Within a comprehensive website supplement, which includes all code and analyses, data were tabulated and visualised, and network analyses explored relations between predictor variables and outcomes. Results: Average daily moderate-to-vigorous PA was 65 min (CI95: 57min–73 min), and SB 8h44 min (CI95: 8h04min–9h24 min), with 25.8 (CI95: 23.5–28.0) interruptions to sitting. Cluster randomisation appeared to result in balanced distributions for baseline characteristics between intervention and control groups, but differences emerged across the four educational tracks. Self-reported behaviour change technique (BCT) use was low for many but not all techniques. A network analysis revealed direct relationships between PA and behavioural experiments, planning and autonomous motivation, and several BCTs were connected to PA via autonomous motivation. Visualisation uncovered a case of Simpson’s paradox. Conclusions: Data-visualisation and data exploration techniques (e.g. network analysis) can help reveal the dynamics involved in complex multi-causal systems – a challenging task with traditional data presentations. The benefits of presenting complex data visually should encourage researchers to publish extensive analyses and descriptions as website supplements, which would increase the speed and quality of scientific communication, as well as help to address the crisis of reduced confidence in research findings. We hope that this example will serve as a template for other investigators to improve upon in the future. Routledge 2019-07-25 /pmc/articles/PMC8114395/ /pubmed/34040851 http://dx.doi.org/10.1080/21642850.2019.1646136 Text en © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Heino, Matti T. J.
Knittle, Keegan
Fried, Eiko
Sund, Reijo
Haukkala, Ari
Borodulin, Katja
Uutela, Antti
Araujo-Soares, Vera
Vasankari, Tommi
Hankonen, Nelli
Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let’s Move It trial
title Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let’s Move It trial
title_full Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let’s Move It trial
title_fullStr Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let’s Move It trial
title_full_unstemmed Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let’s Move It trial
title_short Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the Let’s Move It trial
title_sort visualisation and network analysis of physical activity and its determinants: demonstrating opportunities in analysing baseline associations in the let’s move it trial
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114395/
https://www.ncbi.nlm.nih.gov/pubmed/34040851
http://dx.doi.org/10.1080/21642850.2019.1646136
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