Examining the Role Ones’ Stage of Change Plays in Understanding the Relationship Between Motivation and Physical Activity

Abstract

Considerable research guided by the Self Determination Theory has demonstrated that people who are motivated by more self-determined reasons (e.g., enjoyment, core beliefs, or personally meaningful benefits) are more likely to be physical activity. However, far less is known about the role ones' stage of change (readiness for physical activity) plays in this relationship. The purpose of the present study was to (a) determine if the six forms of motivation and indices of physical activity varied across the stages of change, and (b) investigate if composite scores of self-determined and non-self-determined motivation were differentially related to physical activity indices depending on the stage of change of the individual. In total, 700 adults aged 18-65 (M age = 32.59; SD = 12.82) completed an online survey consisting of demographics, and assessments of stages of change, motivation, and physical activity. Results demonstrated that participants at more advanced stages of change reported significantly higher self-determined motives, moderate activity, vigorous activity, and frequency of physical activity, and lower amotivation, with introjected regulation peaking at the implementation phase. Moderation analyses indicated that stages of change moderated the relationship between self-determined motives and moderate to vigorous physical activity, as well as physical activity frequency, but did not moderate the relationship between non-self-determined motives and indices of physical activity. Findings suggested that participants' self-determined motives play a critical role in physical activity and becomes more important at more advanced stages of change, which is important to consider for program and intervention development.

Workflow assessing the effect of Achilles tendon rupture on gait function and metatarsal stress: Combined musculoskeletal modeling and finite element analysis

“…To understand the influence of unilateral ATR on foot internal biomechanics asymmetry, and further improve the effectiveness of rehabilitation and treatment. 46 A combined subject-specific musculoskeletal and foot-ankle complex finite element model was developed to provide potential information for the study purposes and clinical application. 47 The late stance phase of walking (60%-100%) was selected for the finite element analysis, the 60% of the stance phase was defined as initial push-off and the heel start to arise.…”

“…To understand the influence of unilateral ATR on foot internal biomechanics asymmetry, and further improve the effectiveness of rehabilitation and treatment. 46 A combined subject-specific musculoskeletal and foot-ankle complex finite element model was developed to provide potential information for the study purposes and clinical application. 47…”

Self-Serving Bias in Performance Goal Achievement Appraisals: Evidence From Long-Distance Runners

“…According to basic psychological needs theory, people have three fundamental psychological needs, namely autonomy (feeling a sense of choice about one’s behavior), competence (being able to bring about positive changes in desired outcomes), and relatedness (feeling accepted by one’s social milieu; Ntoumanis et al, 2021 ). The frustrations (and satisfactions) of these needs would impact one’s wellness and optimal functioning ( Ryan and Deci, 2019 ), resulting in amotivation, depression, and unhealthy behavior when frustrated ( Ng et al, 2013 ; Ntoumanis et al, 2021 ) and lower amotivation and adaptive behavior when satisfied ( Vansteenkiste et al, 2018 ; Ntoumanis et al, 2021 ; Pope et al, 2021 ). In the current study, runners who experienced performance failure were likely to encounter frustration in their self-determined motivations, such as competence and relatedness, because they failed to achieve their goals despite the significant amount of time and effort they put into the preparation for the event.…”

Gait Characteristics and Fatigue Profiles When Standing on Surfaces with Different Hardness: Gait Analysis and Machine Learning Algorithms

“…This may indicate that the gait characteristics of subjects standing on mats for 4 h are between fatigued and non-fatigued. Still, the degree of fatigue is lower than that of standing on the ground for 4 h [ 53 , 54 ].…”