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

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  • Manuela Besomi
  • Jaime Leppe
  • Maria Cristina Di Silvestre
  • Jenny Setchell

Abstract

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

Suggested Citation

  • Manuela Besomi & Jaime Leppe & Maria Cristina Di Silvestre & Jenny Setchell, 2018. "SeRUN® study: Development of running profiles using a mixed methods analysis," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
  • Handle: RePEc:plo:pone00:0200389
    DOI: 10.1371/journal.pone.0200389
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    Cited by:

    1. Eric C Honert & Maurice Mohr & Wing-Kai Lam & Sandro Nigg, 2020. "Shoe feature recommendations for different running levels: A Delphi study," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-17, July.

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