Visualisation and network analysis of physical activity and its determinants: Demonstrating opportunities in analysing baseline associations in the let's move it trial

被引:11
|
作者
Heino, Matti T. J. [1 ]
Knittle, Keegan [1 ]
Fried, Eiko [2 ]
Sund, Reijo [3 ]
Haukkala, Ari [1 ]
Borodulin, Katja [1 ]
Uutela, Antti [1 ]
Araujo-Soares, Vera [4 ]
Vasankari, Tommi [5 ]
Hankonen, Nelli [1 ]
机构
[1] Univ Helsinki, Fac Social Sci, POB 54, FIN-00014 Helsinki, Finland
[2] Leiden Univ, Dept Clin Psychol, Leiden, Netherlands
[3] Univ Eastern Finland, Fac Hlth Sci, Kuopio, Finland
[4] Newcastle Univ, Med Fac, Inst Hlth & Soc, Newcastle Upon Tyne, Tyne & Wear, England
[5] UKK Inst Hlth Promot Res, Tampere, Finland
来源
基金
芬兰科学院;
关键词
Exercise; physical activity; school-based intervention; behaviour change; sedentary behaviour; SEDENTARY BEHAVIOR; INTERVENTIONS; HYPOTHESIS; ATTITUDES; MODELS; TIME;
D O I
10.1080/21642850.2019.1646136
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
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: 57 min-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.
引用
收藏
页码:269 / 289
页数:21
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