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SeRUN(®) study: Development of running profiles using a mixed methods analysis

OBJECTIVE: To determine profiles of urban runners based on socio-demographic, health, motivational, training characteristics and running-related beliefs and behaviours. METHODS: Mixed, exploratory, sequential study with two stages: 1) quantitative, using an online survey; and 2) qualitative, using s...

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Detalles Bibliográficos
Autores principales: Besomi, Manuela, Leppe, Jaime, Di Silvestre, Maria Cristina, Setchell, Jenny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039021/
https://www.ncbi.nlm.nih.gov/pubmed/29990334
http://dx.doi.org/10.1371/journal.pone.0200389
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author Besomi, Manuela
Leppe, Jaime
Di Silvestre, Maria Cristina
Setchell, Jenny
author_facet Besomi, Manuela
Leppe, Jaime
Di Silvestre, Maria Cristina
Setchell, Jenny
author_sort Besomi, Manuela
collection PubMed
description OBJECTIVE: To determine profiles of urban runners based on socio-demographic, health, motivational, training characteristics and running-related beliefs and behaviours. METHODS: Mixed, exploratory, sequential study with two stages: 1) quantitative, using an online survey; and 2) qualitative, using semi-structured interviews with runners from the previous stage. Participants were recruited via: running routes commonly attended by runners, eight races, previous databases and social media networks. The survey collected information on six dimensions: (1) socio-demographic; (2) health; (3) motivations; (4) training characteristics; (5) running-related behaviour; and (6) beliefs and perceptions about health. Profiles were identified using a two-step hierarchical clustering analysis. Subsequently, 15 interviews were conducted with participating runners across each of the identified profiles. Qualitative analysis complemented the profiles characterization, explaining motivations to start and continue running, beliefs about risk factors and injury prevention, and the physical therapist’s role in rehabilitation. Statistical analysis from stage one was conducted using SPSS 22 with a confidence level of 5%. Qualitative data were analysed using thematic and content analyses. RESULTS: A total of 821 surveys were analysed (46% female), mean aged 36.6±10.0 years. Cluster analysis delineated four profiles (n = 752) according to years of running experience, weekly running volume and hours of weekly training. Profiles were named “Beginner” (n = 163); “Basic” (n = 164); “Middle” (n = 160) and “Advanced” (n = 265). Profiles were statistically different according to sex, age, years of running experience, training characteristics, previous injuries and use of technological devices (p<0.05). There were identified motivations to start and continue running. Beliefs about risk factors vary among stretching, footwear, training surface and overload. Runners identified the physical therapist as a specialist, involved in the rehabilitation process and showing empathy towards the patient. The identification of these profiles allows the generation of future prospective studies and clinical trials to evaluate risk and prognostic factors targeting specific populations of runners, with the ultimate aim of reducing running-related injury.
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spelling pubmed-60390212018-07-19 SeRUN(®) study: Development of running profiles using a mixed methods analysis Besomi, Manuela Leppe, Jaime Di Silvestre, Maria Cristina Setchell, Jenny PLoS One Research Article OBJECTIVE: To determine profiles of urban runners based on socio-demographic, health, motivational, training characteristics and running-related beliefs and behaviours. METHODS: Mixed, exploratory, sequential study with two stages: 1) quantitative, using an online survey; and 2) qualitative, using semi-structured interviews with runners from the previous stage. Participants were recruited via: running routes commonly attended by runners, eight races, previous databases and social media networks. The survey collected information on six dimensions: (1) socio-demographic; (2) health; (3) motivations; (4) training characteristics; (5) running-related behaviour; and (6) beliefs and perceptions about health. Profiles were identified using a two-step hierarchical clustering analysis. Subsequently, 15 interviews were conducted with participating runners across each of the identified profiles. Qualitative analysis complemented the profiles characterization, explaining motivations to start and continue running, beliefs about risk factors and injury prevention, and the physical therapist’s role in rehabilitation. Statistical analysis from stage one was conducted using SPSS 22 with a confidence level of 5%. Qualitative data were analysed using thematic and content analyses. RESULTS: A total of 821 surveys were analysed (46% female), mean aged 36.6±10.0 years. Cluster analysis delineated four profiles (n = 752) according to years of running experience, weekly running volume and hours of weekly training. Profiles were named “Beginner” (n = 163); “Basic” (n = 164); “Middle” (n = 160) and “Advanced” (n = 265). Profiles were statistically different according to sex, age, years of running experience, training characteristics, previous injuries and use of technological devices (p<0.05). There were identified motivations to start and continue running. Beliefs about risk factors vary among stretching, footwear, training surface and overload. Runners identified the physical therapist as a specialist, involved in the rehabilitation process and showing empathy towards the patient. The identification of these profiles allows the generation of future prospective studies and clinical trials to evaluate risk and prognostic factors targeting specific populations of runners, with the ultimate aim of reducing running-related injury. Public Library of Science 2018-07-10 /pmc/articles/PMC6039021/ /pubmed/29990334 http://dx.doi.org/10.1371/journal.pone.0200389 Text en © 2018 Besomi et al http://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/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Besomi, Manuela
Leppe, Jaime
Di Silvestre, Maria Cristina
Setchell, Jenny
SeRUN(®) study: Development of running profiles using a mixed methods analysis
title SeRUN(®) study: Development of running profiles using a mixed methods analysis
title_full SeRUN(®) study: Development of running profiles using a mixed methods analysis
title_fullStr SeRUN(®) study: Development of running profiles using a mixed methods analysis
title_full_unstemmed SeRUN(®) study: Development of running profiles using a mixed methods analysis
title_short SeRUN(®) study: Development of running profiles using a mixed methods analysis
title_sort serun(®) study: development of running profiles using a mixed methods analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039021/
https://www.ncbi.nlm.nih.gov/pubmed/29990334
http://dx.doi.org/10.1371/journal.pone.0200389
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