Intrinsic goals for leisure-time physical activity predict children's daily step counts through autonomous motivation

Abstract

Objectives: The present study tested a motivational sequence in which children's goals for leisure-time sport and physical activity (PA) from Goal Content Theory predicted pedometerdetermined PA through behavioural regulation constructs from Self-Determination Theory. Design:Quantitative cross-sectional study.Method: A sample of 1,272 Flemish (Dutch speaking part of Belgium) sixth graders (M age = 11.42 years) filled in a questionnaire on PA goal content, behavioural regulations and pubertal status. Children's height and weight were measured to assess Body Mass Index (BMI). To measure daily PA behaviour, participants wore a pedometer for seven consecutive days.Structural equation modelling was performed to test the proposed motivational sequence and to examine the mediation effect of behavioural regulations towards leisure-time sport and PA on the relation between PA goal content and daily step counts.Results: A structural equation model supported the hypothesized sequence in which intrinsic goals for leisure-time sport and PA predicted children's daily step counts through autonomous motivation towards leisure-time sport and PA. Multi-sample invariance testing revealed that the proposed model was largely invariant across BMI groups, pubertal status and gender. Conclusion:The findings highlight the importance of emphasizing intrinsic goals for participation in leisure-time sport and PA in children aged 10-12 years. By stimulating children to participate in PA and sports by referring to intrinsic goals, children are more likely to enjoy PA, which in turn might increase the likelihood of a regular and long-term PA engagement.

Associations between Physical Activity Motives and Trends in Moderate-to-Vigorous Physical Activity Among Adolescents Over Five Years.

“…Our results suggests that social motives were not associated with MVPA for both sexes. Previous investigations on this relationships have not been consistent with some showing that greater social motives were related to more PA, [35,36] others indicated it was associated to less PA, [31] and some, like our study suggested it was not related to PA. [32,38] Our results are similar to the only other longitudinal study that examined the relationship of the five motives with objectively measured PA. [32] A recent systematic review of qualitative studies on barriers and facilitators of PA behavior in adolescents suggests that friendships have an influence on PA behavior. [61] However, researchers have found that youth tend to be friends with peers that accumulate similar levels of PA. [62] This might suggest that social motives are not helpful in the initiation of PA behavior, as youth choose friends that share certain behaviors, and not because these friends are going to make them start something new.…”

“…Still, boys rated appearance motives higher than girls, but after turning 12 years old, the increase in the rating of this motive was more pronounced for girls than for boys. Previous cross-sectional publications have been inconsistent in their findings in relation to how appearance motives may relate to MVPA [31,36] and a longitudinal study with two measurement points found no association between appearance motives and MVPA. [32] Collectively, this suggests that perceived and experienced social pressures to achieve a specific physique by both girls and boys do not lead to increased PA. [63][64][65] It is therefore recommended that interventions do not foster appearance motives as a tool to increase PA.…”

An application of goal content theory to examine how desired exercise outcomes impact fitness technology feature set selection

“…Designers of future generations of fitness technologies may also want to consider expanding the DMFs to include features that provide insightful analytics on progress towards body‐focused goals, as well as advancing the presentations of the common fitness and health analytics (Epstein, Caraway, et al, ). Motivation research in the exercise context recommends emphasizing intrinsic goals to exercisers with extrinsic goals in an attempt to switch their focus (Sebire et al, ; Seghers, Vissers, Rutten, Decroos, & Boen, ), an intervention that fitness technologies could assist.…”

Statistical methods to model and evaluate physical activity programs, using step counts: A systematic review

“…Thirteen articles included in the review used more than one statistical modeling technique in analysing the step counts [ 4 , 13 , 27 – 37 ]. It was noted that 60% of the articles used general linear models, while 24% of the articles used generalized linear models, 10% of the articles used multilevel modeling, 4% used structural equation modeling and 2% of the articles used generalized estimating equations.…”

“…In this category, most of the studies (80%) are cross sectional while only two studies that used structural equation models, have longitudinal designs. The four studies which used structural equation models relate to school-based activity programs [ 37 , 60 – 62 ].…”