Perceived Behavioral Control over Child Physical Activity Support Measure

2016 ◽  
Author(s):  
Ryan E. Rhodes ◽  
John C. Spence ◽  
Tanya Berry ◽  
Sameer Deshpande ◽  
Guy Faulkner ◽  
...  
Keyword(s):  
Physical Activity ◽  
Behavioral Control ◽  
Perceived Behavioral Control ◽  
Child Physical Activity ◽  
Support Measure

Gender differences for theory-based determinants of muscle-strengthening physical activity in college-aged students: a moderation analysis

2019 ◽  
Vol 10 (3) ◽  
pp. 781-791 ◽  
Author(s):  
Grace Fairchild Saidi ◽  
Paul Branscum
Keyword(s):  
Physical Activity ◽  
Gender Differences ◽  
Reasoned Action ◽  
Behavioral Control ◽  
Perceived Behavioral Control ◽  
Reasoned Action Approach ◽  
Muscle Strengthening ◽  
Perceived Norms ◽  
Motivational Interventions ◽  
The Relationship

Abstract Researchers and practitioners have primarily focused on understanding and promoting aerobic forms of physical activity (PA), while leaving muscle-strengthening forms of PA less understood. There are also stark gender disparities for muscle-strengthening PA but not aerobic PA. The purpose of this study was to apply the reasoned action approach (RAA) toward understanding theory-based determinants of muscle-strengthening PA and to explore gender differences. Female (n = 272) and male (n = 120) college students completed a valid and reliable survey evaluating their participation in muscle-strengthening PA and the constructs of the RAA (intentions, attitudes, perceived norms, and perceived behavioral control [PBC]). Results showed that attitudes, perceived norms, and PBC explained a substantial amount of the variance of intentions for both female (53.8%) and male (54.7%) participants; however, when predicting participation in muscle-strengthening PA, PBC moderated the relationship between intentions and muscle-strengthening PA participation for female participants but not for male participants. Results from this study showed that for women, implementational processes are likely needed for public health interventions to promote muscle-strengthening PA to build capability, skills, and self-efficacy, while for men, motivational interventions are warranted to create favorable attitudes.

Predicting Physical Activity Intention and Behavior in School-Age Children

2008 ◽  
Vol 20 (3) ◽  
pp. 342-356 ◽  
Author(s):  
Louise Foley ◽  
Harry Prapavessis ◽  
Ralph Maddison ◽  
Shauna Burke ◽  
Erin McGowan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Self Efficacy ◽  
Behavioral Control ◽  
Integrated Model ◽  
School Age Children ◽  
Perceived Behavioral Control ◽  
School Aged Children ◽  
Efficacy Measures ◽  
Objectively Measured ◽  
And Behavior

Two studies were conducted to predict physical activity in school-aged children. Study 1 tested the utility of an integrated model in predicting physical activity (PA) intention and behavior—the theory of planned behavior (TPB) and self-efficacy theory. Six hundred and forty-five New Zealand children (aged 11–13 years) completed measures corresponding to the integrated model and a self-reported measure of PA one week later. Perceived behavioral control (PBC) and subjective norm were the two strongest predictors of intentions. Task efficacy and barrier efficacy were the two strongest predictors of PA. A second study (Study 2) was conducted to determine whether the self-efficacy measures could discriminate objectively measured PA levels. Sixty-seven Canadian children (aged 11–13 years) completed task and barrier self-efficacy measures. The following week, children classified as ‘high’ (n = 11) and ‘lower’ (n = 7) for both task and barrier efficacy wore an Actical® monitor for seven consecutive days to provide activity-related energy expenditure (AEE) data. Results showed that children with high efficacy expended significantly greater AEE than their lower efficacious counterparts. Findings from these two studies provide support for the use of self-efficacy interventions as a potentially useful means of increasing PA levels among school-aged children.

The Theory of Planned Behavior and Physical Activity Change: Outcomes of the Aging Well and Healthily Intervention Program for Older Adults

2017 ◽  
Vol 25 (3) ◽  
pp. 438-445 ◽  
Author(s):  
Elske Stolte ◽  
Marijke Hopman-Rock ◽  
Marja J. Aartsen ◽  
Theo G. van Tilburg ◽  
Astrid Chorus
Keyword(s):  
Physical Activity ◽  
Theory Of Planned Behavior ◽  
Planned Behavior ◽  
Structural Equation ◽  
Intervention Program ◽  
Behavioral Control ◽  
Subjective Norm ◽  
Equation Modeling ◽  
Perceived Behavioral Control ◽  
Aging Well

The predictive value of the Theory of Planned Behavior (TPB) on intention and physical activity (PA) over time was examined. Data from the Aging Well and Healthily intervention program (targeting perceived behavioral control and attitude, not subjective norm) were analyzed, including pretest (T0), posttest (T1, except subjective norm) and 4–6 months follow-up (T2, PA outcomes only) (N = 387, M age 72 years). Structural equation modeling was used to test a TPB model. PA was measured subjectively using the Voorrips sports subscale (T0 and T2), items measured perceived increase in PA (T1), and adherence to exercises (T1 and T2). Model fit was good. The TPB explained variation in intention well (R2 .54–.60) and some PA behavior (R2 .13–.16). The intervention successfully got participants to exercise independent of the measured TPB concepts. More TPB studies in the context of interventions are needed.

scholarly journals Psychosocial Variables Related to Weight-Related Self-Stigma in Physical Activity among Young Adults across Weight Status

2019 ◽  
Vol 17 (1) ◽  
pp. 64 ◽  
Author(s):  
Xavier C. C. Fung ◽  
Amir H. Pakpour ◽  
Ya-Ke Wu ◽  
Chia-Wei Fan ◽  
Chung-Ying Lin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Young Adults ◽  
Structural Equation ◽  
Weight Status ◽  
Healthy Lifestyle ◽  
Behavioral Control ◽  
Healthcare Providers ◽  
Model Fit ◽  
Equation Modeling ◽  
Perceived Behavioral Control

A healthy lifestyle with sufficient physical activity (PA) can contribute to weight management. Yet, many people do not maintain a healthy lifestyle. To explain PA, we propose a model that incorporates the Theory of Planned Behavior (TPB) with weight-related self-stigma. We recruited 325 young adults to complete questionnaires regarding their physical activities, weight-related self-stigma, and TPB factors. We used structural equation modeling to examine the model fit and the path invariance across weight groups. The model showed excellent model fit, but path invariance was not supported. Weight-related self-stigma significantly explained the perceived behavioral control, behavioral intention, and engagement of PA. People without overweight and people with overweight have different considerations for PA. Weight-related self-stigma is important for PA as well. To promote a healthy lifestyle, healthcare providers should provide different suggestions or interventions that suit their patients’ weight-related concerns.

Prediction of Physical Activity Intention from Social Psychological Variables: Results from the Campbell's Survey of Weil-Being

1994 ◽  
Vol 16 (1) ◽  
pp. 56-69 ◽  
Author(s):  
Leonard M. Waekel ◽  
W. Kerry Mummery ◽  
Thomas Stephens ◽  
Cora L. Craig
Keyword(s):  
Physical Activity ◽  
Theory Of Planned Behavior ◽  
Planned Behavior ◽  
Reasoned Action ◽  
Behavioral Control ◽  
Perceived Behavioral Control ◽  
Social Psychological ◽  
Psychological Variables ◽  
Behavior Intention ◽  
Relative Utility

The purpose of the study was to investigate the utility of various social-psychological variables for predicting intentions to engage in physical activity within a national population. More specifically, attitude, perceived behavioral control, and perceived social support measures were utilized to provide modified operationalizations of the theories of planned behavior and reasoned action in order to assess their relative utility for predicting physical activity intentions. Data from the Campbell's Survey of the Weil-Being of Canadians enabled the assessment of the predictive efficacy of the two models in the overall population, as well as in various population subgroups. The theory of planned behavior was found to account for a substantially greater percentage of the behavior intention variance (31%) than did the theory of reasoned action (15%). Further, the study provides some support for the utility of the theory of planned behavior for understanding the activity intentions of different population groups.

Applying the Theory of Planned Behavior to Physical Activity: The Moderating Role of Mental Toughness

2015 ◽  
Vol 37 (5) ◽  
pp. 514-522 ◽  
Author(s):  
Thomas E. Hannan ◽  
Robyn L. Moffitt ◽  
David L. Neumann ◽  
Patrick R. Thomas
Keyword(s):  
Physical Activity ◽  
Theory Of Planned Behavior ◽  
Planned Behavior ◽  
Behavioral Control ◽  
Physical Activity Behavior ◽  
Mental Toughness ◽  
Future Research ◽  
Perceived Behavioral Control ◽  
Moderation Effect ◽  
Toughness Index

This study explored whether mental toughness, the capacity to maintain performance under pressure, moderated the relation between physical activity intentions and subsequent behavior. Participants (N = 117) completed the Mental Toughness Index and a theory of planned behavior questionnaire. Seven days later, physical activity was assessed using the International Physical Activity Questionnaire. Attitudes, subjective norms, and perceived behavioral control explained substantial variance (63.1%) in physical activity intentions. Intentions also significantly predicted physical activity behavior. The simple slopes analyses for the moderation effect revealed a nonsignificant intention–behavior relation at low levels of mental toughness. However, intentions were significantly and positively related to physical activity when mental toughness was moderate or high, suggesting that the development of a mentally tough mindset may reduce the gap between behavior and physical activity intention. Future research is needed to confirm these findings and apply them in the design of mental toughness interventions to facilitate physical activity engagement.

Predicting Decisional Determinants of Physical Activity Among Older Adults: An Integrated Behavior Approach

2021 ◽  
pp. 089826432110490
Author(s):  
Christian E. Preissner ◽  
Kathleen Charles ◽  
Bärbel Knäuper ◽  
Navin Kaushal
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Structural Equation ◽  
Social Cognitive ◽  
Behavioral Control ◽  
Autonomous Motivation ◽  
Perceived Behavioral Control ◽  
Behavioral Determinants ◽  
Past Behavior ◽  
Cognitive Determinants

Objectives The present study applied the Integrated Behavior Change Model to investigate how behavioral decisions are predicted, namely, intention, planning, and habits, with respect to physical activity. Methods: Participants were older adults (ages 65+) residing in the U.S. ( N = 667) who completed online measures of behavioral determinants (autonomous motivation, perceived behavioral control, subjective norms, attitudes, intention, habit, and consistency), in addition to past behavior. Results: A structural equation model revealed that intention was predicted by past behavior and social-cognitive determinants. Social cognitive determinants mediated between past behavior and habit, as well as between autonomous motivation and habit. Intention mediated between past behavior and planning. Discussion: This study highlights the importance of multiple processes (social cognitive, habit/automatic, and post-intentional/planning) that formulate physical activity intentions. Mediation pathways revealed the importance of autonomous motivation for establishing intentions and habit. Facilitating these processes among older adults could be effective for promoting physical activity.

scholarly journals Using Theory of Planned Behavior to Predict the Physical Activity of Children: Probing Gender Differences

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Lijuan Wang ◽  
Lin Wang
Keyword(s):  
Physical Activity ◽  
Gender Differences ◽  
Theory Of Planned Behavior ◽  
Planned Behavior ◽  
Primary Schools ◽  
Leisure Time ◽  
Behavioral Control ◽  
Vigorous Physical Activity ◽  
Primary Objective ◽  
Perceived Behavioral Control

Objectives. The primary objective of this study was to use the theory of planned behavior (TPB) to examine the association between TPB variables and the moderate-to-vigorous physical activity (MVPA) of children in Shanghai, China. Gender differences were also explored.Methods. The participants were 353 children (180 boys and 173 girls) aged 9 to 13 years from three primary schools in Shanghai. Accelerometers were used to measure the MVPA duration of the children. Questionnaires that focused on attitude, subjective norms, and perceived behavioral control (PBC) related to MVPA engagement were completed by the participants.Results. Regression analyses revealed that intention, and not PBC, accounted for 9% of the variance in MVPA. Meanwhile, attitude and PBC explained 33% of the variance in intentions to engage in MVPA. In terms of gender differences, TPB performed better in the physical activity (PA) domain for boys than for girls. Furthermore, attitude and PBC were significantly associated with intention among boys, whereas only PBC was significantly related to intention among girls.Conclusion. Practitioners should consider tailoring intervention to address gender differences to increase leisure-time PA participation of children.

scholarly journals Does Motivation in Physical Education Have an Impact on Out-of-School Physical Activity over Time? A Longitudinal Approach

2020 ◽  
Vol 17 (19) ◽  
pp. 7258 ◽  
Author(s):  
Djenna Hutmacher ◽  
Melanie Eckelt ◽  
Andreas Bund ◽  
Georges Steffgen
Keyword(s):  
Physical Activity ◽  
Physical Education ◽  
Behavioral Control ◽  
Longitudinal Design ◽  
Autonomous Motivation ◽  
Perceived Behavioral Control ◽  
Mixed Effect ◽  
Motivational Regulation ◽  
The Impact ◽  
Out Of School

Previous research based on the trans-contextual model proposes that autonomous motivation in physical education (PE) is transferable to an out-of-school leisure-time (LT) context. However, only cross-sectional and unidirectional analyses have been conducted. The present study used a longitudinal design assessing N = 1681 students (M = 14.68 years) on two occasions, measuring the following constructs: perceived need for support in PE, motivational regulation during PE and LT, attitude, subjective norm, perceived behavioral control, intention, and physical activity behavior. Findings based on mixed effect models revealed that autonomy, competence, and relatedness support of the PE teacher were positively related to autonomous motivation. Moreover, similar motivational regulation types were found to significantly cross-lag across contexts. Through longitudinal mediation analyses, further support for the impact of autonomous motivation on physical activity, mediated by intention, attitude, and perceived behavioral control, was found. Suggestions for educational stakeholders regarding how to promote students’ autonomous motivation are provided.

scholarly journals Lifestyle E-Coaching for Physical Activity Level Improvement: Short-Term and Long-Term Effectivity in Low Socioeconomic Status Groups

2019 ◽  
Vol 16 (22) ◽  
pp. 4427 ◽  
Author(s):  
Hanne Spelt ◽  
Thomas Tsiampalis ◽  
Pania Karnaki ◽  
Matina Kouvari ◽  
Dina Zota ◽  
...  
Keyword(s):  
Physical Activity ◽  
Socioeconomic Status ◽  
Low Socioeconomic Status ◽  
Behavioral Control ◽  
Cost Effective ◽  
Activity Level ◽  
Control Group ◽  
Perceived Behavioral Control ◽  
Low Ses ◽  
Activity Levels

E-coaching applications can improve people’s lifestyles; however, their impact on people from a lower socioeconomic status (low SES) is unknown. This study investigated the effectiveness of a lifestyle e-coaching application in encouraging people facing low SES disadvantages to engage in a more active lifestyle over a course of 19 weeks. In this bicountry study, 95 people with low activity level (GR: 50, NL: 45) used a mobile application linked to a wearable activity tracker. At the start and after 6 and 19 weeks, self-reported physical activity levels, attitudes, and intention towards increasing activity levels, perceived behavioral control, and wellbeing were measured. Results indicated that participants using the lifestyle e-coaching application reported significantly more often an increase in activity levels than a parallel control group. Additionally, the people using the application also more often reported increased levels of wellbeing and perceived behavioral control. Therefore, lifestyle e-coaching applications could be a cost-effective solution for promoting healthier lifestyles in low-SES populations.

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