An Examination of Dweck's Psychological Needs Model in Relation to Exercise-Related Well-Being.

identity meaning optimal predictability physical activity psychological need satisfaction subjective vitality

Journal

Journal of sport & exercise psychology
ISSN: 1543-2904
Titre abrégé: J Sport Exerc Psychol
Pays: United States
ID NLM: 8809258

Informations de publication

Date de publication:
21 Jun 2021
Historique:
received: 25 01 2021
revised: 20 03 2021
accepted: 31 03 2021
pubmed: 23 6 2021
medline: 15 12 2021
entrez: 22 6 2021
Statut: epublish

Résumé

This two-part study examined Dweck's psychological needs model in relation to exercise-related well-being and particularly focused on the basic need for optimal predictability and compound needs for identity and meaning. In Part 1 (N = 559), using exploratory factor analysis, scores derived from items assessing optimal predictability (prediction of affect and instrumental utility in exercise) were empirically distinct from scores derived from items assessing competence, relatedness, and autonomy. In Part 2, participants from Part 1 (N = 403) completed measures of exercise-related well-being 4 weeks after baseline assessment. Prediction of affect was the most consistent predictor of subsequent exercise-related well-being. An implication of these findings is that optimal predictability (primarily prediction of affect) represents a unique experience that may be necessary for thriving in the context of exercise. Prediction of affect should be targeted in experimental designs to further understand its relationship with exercise-related well-being.

Identifiants

pubmed: 34157674
doi: 10.1123/jsep.2021-0026
pii: jsep.2021-0026
doi:
pii:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

323-334

Commentaires et corrections

Type : ErratumIn

Auteurs

Colin M Wierts (CM)

University of British Columbia.

Bruno D Zumbo (BD)

University of British Columbia.

Ryan E Rhodes (RE)

University of Victoria.

Guy Faulkner (G)

University of British Columbia.

Mark R Beauchamp (MR)

University of British Columbia.

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Classifications MeSH