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Testing the Physical Activity Self-Definition Model among low-active adults participating in a physical activity intervention
Affiliation:1. School of Kinesiology and Health Studies, Queen’s University, Kingston, Ontario, Canada;2. Faculty of Kinesiology and Recreation Management, University of Manitoba, Winnipeg, Manitoba, Canada;3. Institute of Cardiovascular Sciences, St. Boniface General Hospital Albrechtsen Research Centre, Winnipeg, Manitoba, Canada;4. Department of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada;5. Department of Kinesiology and Physical Education, McGill University, Montréal, Québec, Canada;6. School of Education and Human Development, University of Virginia, Charlottesville, Virginia, USA;1. Cricket Australia, National Cricket Centre, Brisbane, Qld, Australia;2. Queensland University of Technology, Brisbane, Qld, Australia;3. University of Canberra, Canberra, ACT, Australia;4. Faculty of Science Health and Education, University of the Sunshine Coast, Sippy Downs, Qld, Australia;1. University of Konstanz, Germany;2. Humboldt University of Berlin, Germany;3. University of Trier, Germany;1. Université des Antilles, Laboratoire “Adaptation Au Climat Tropical, Exercice & Santé”, Faculté des Sciences Du Sport de Pointe-à-Pitre, France;2. Université de Poitiers, Université de Tours, Centre National de La Recherche Scientifique, Centre de Recherches sur La Cognition et L’Apprentissage (UMR 7295), Poitiers, France;1. Department of Psychology, University of Portsmouth, PO1 2DT, UK;2. School of Sport, Health and Exercise Science, University of Portsmouth, PO1 2DT, UK
Abstract:Seeing oneself as a physically active person is one of the strongest predictors of physical activity behaviour and self-regulatory strategies. Determining whether and how physical activity self-perceptions can be stimulated may help low-active individuals who do not see themselves as a physically active person become more active. Cross-sectional research has tested the Physical Activity Self-Definition (PASD) model among active samples; longitudinal studies among low-active adults have yet to be done. The purpose of this study was to test the predictive power of the PASD model among low-active adults over a 16-week physical activity intervention. Participants completed surveys of validated questionnaires in-person at baseline (pre-intervention) and at 16-weeks (end of intervention) at one of two primary care facilities. The final sample included 119 low-active adults. Partial least squares-structural equation modeling indicated that the original model had small-medium predictive power (Q2 = 0.22; SRMR = 0.13 [0.05, 0.07]; RMSE = 1.13; MAE = 0.9; BIC = 1348.40). Two paths were added in the revised model (perceived wanting—PASD; perceived ability—perceived commitment), which explained an additional 4% and 5% of the variance in perceived commitment (R2 = 0.62 [0.48, 0.72]) and PASD (R2 = 0.74 [0.64, 0.80]; all p’s < 0.001), respectively. The revised model had medium predictive power (Q2 = 0.25; SRMR = 0.11 [0.05, 0.06]; RMSE = 1.1; MAE = 0.87; BIC = 1332.84) All path coefficients remained positive and significant at p ≤ .001. Among low-active adults, perceived wanting and perceived ability may be more salient when engaging in physical activity and regarding themselves as a physically active person. Findings may support practitioners and health care professionals in designing physical activity interventions to foster PASD among low-active adult populations.
Keywords:Physical activity  Exercise  Identity  Schema  Self-definition  Partial least squares-structural equation modeling  AVE"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd9876"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  average variance extracted  BIC"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd9876a"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Bayesian information criterion  CI"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd0045"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  confidence interval  ENCOURAGE"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd0055"  },"  $$"  :[{"  #name"  :"  text"  ,"  $$"  :[{"  #name"  :"  underline"  ,"  _"  :"  EN"  },{"  #name"  :"  __text__"  ,"  _"  :"  hancing Primary Care "  },{"  #name"  :"  underline"  ,"  _"  :"  COU"  },{"  #name"  :"  __text__"  ,"  _"  :"  nseling and "  },{"  #name"  :"  underline"  ,"  _"  :"  R"  },{"  #name"  :"  __text__"  ,"  _"  :"  eferrals to Community-Based Physical "  },{"  #name"  :"  underline"  ,"  _"  :"  A"  },{"  #name"  :"  __text__"  ,"  _"  :"  ctivity Opportunities for Sustained Lifestyle Chan"  },{"  #name"  :"  underline"  ,"  _"  :"  GE  HTMT"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd9876t"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  heterotrait-monotrait  MAE"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd9876as"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  mean absolute error  PACES"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd9876cc"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  physical activity enjoyment scale  PASD"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd0065"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  physical activity self-definition  PLS-SEM"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd98708"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  partial least squares-structural equation modeling  RMSE"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd0075"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  root mean squared error  SRMR"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd0065s"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  standardized root mean square residual  VIF"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  kwrd0065a"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  variance inflation factor
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