Physical activity and social support mediate the relationship between chronic diseases and positive mental health in a national sample of community-dwelling Canadians 65+: A Structural Equation Analysis

2021 ◽  
Author(s):  
Guang Yang ◽  
Carl D'Arcy
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Social Support ◽  
Chronic Diseases ◽  
Structural Equation ◽  
National Sample ◽  
Community Dwelling ◽  
Structural Equation Analysis ◽  
Equation Analysis ◽  
The Relationship

The relation of acculturation to latinas’ perceived neighborhood safety and physical activity: A structural equation analysis

2007 ◽  
Vol 34 (3) ◽  
pp. 295-303 ◽  
Author(s):  
Latrice C. Pichon ◽  
Elva M. Arredondo ◽  
Scott Roesch ◽  
James F. Sallis ◽  
Guadalupe X. Ayala ◽  
...  
Keyword(s):  
Physical Activity ◽  
Structural Equation ◽  
Neighborhood Safety ◽  
Structural Equation Analysis ◽  
Equation Analysis ◽  
Perceived Neighborhood Safety

scholarly journals Physical Activity in Natural Environments Is Associated With Motivational Climate and the Prevention of Harmful Habits: Structural Equation Analysis

2019 ◽  
Vol 10 ◽  
Author(s):  
Manuel Castro-Sánchez ◽  
Félix Zurita-Ortega ◽  
José Antonio Pérez-Turpin ◽  
Javier Cachón-Zagalaz ◽  
Cristian Cofre-Bolados ◽  
...  
Keyword(s):  
Physical Activity ◽  
Structural Equation ◽  
Motivational Climate ◽  
Natural Environments ◽  
Structural Equation Analysis ◽  
Equation Analysis

International Tourists Service Quality Perception And Behavioral Loyalty Toward Medical Tourism In Bangkok Metropolitan Area

2011 ◽  
Vol 27 (6) ◽  
pp. 1 ◽  
Author(s):  
Aurathai Lertwannawit ◽  
Nak Gulid
Keyword(s):  
Service Quality ◽  
Metropolitan Area ◽  
Structural Equation ◽  
Medical Tourism ◽  
Brand Trust ◽  
Positive Relationships ◽  
Behavioral Loyalty ◽  
Structural Equation Analysis ◽  
Equation Analysis ◽  
The Relationship

This research assesses the relationship between service quality, value, satisfaction, and brand trust on the behavioral loyalty of international tourists acting as medical tourists toward private hospital medical services in the Bangkok Metropolitan area. A quantitative study was performed using 400 international tourists who use medical service from private hospitals in Thailand. Structural equation analysis is used to test the hypotheses. The results indicate that there are significant positive relationships between service quality and value (H1), satisfaction (H2), and brand trust (H3). Value (H4), satisfaction (H5), and brand trust (H6) have significant positive relationships with behavioral loyalty. Service quality has an indirect effect on behavioral loyalty by having value, satisfaction, and brand trust function as mediators. Finally, nationality has no moderating effect on the relationship between service quality and value (H7), satisfaction (H8), and brand trust (H9).

Physical activity prescription among Mexican physicians: a structural equation analysis of the theory of planned behaviour

2015 ◽  
Vol 69 (3) ◽  
pp. 375-383 ◽  
Author(s):  
K. I. Galaviz ◽  
E. Jauregui-Ulloa ◽  
L. R. Fabrigar ◽  
A. Latimer-Cheung ◽  
J. Lopez y Taylor ◽  
...  
Keyword(s):  
Physical Activity ◽  
Structural Equation ◽  
Theory Of Planned Behaviour ◽  
Planned Behaviour ◽  
Structural Equation Analysis ◽  
Equation Analysis

The Association of Social Support and Leisure Time Physical Activity With Mental Health Among Individuals With Cancer

2020 ◽  
pp. 089011712096132
Author(s):  
Jaehyun Kim ◽  
Junhyoung Kim ◽  
Ronald D. Williams ◽  
Areum Han
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Social Support ◽  
Emotional Support ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
Mediating Effect ◽  
Cross Sectional ◽  
Tangible Support ◽  
The Relationship

Purpose: This study examined the relationship among social support, leisure time physical activity (LTPA), and mental health among people with cancer. Design: Cross-sectional study. Setting and participants: Using the 2017 Health Information National Trends Survey, we extracted data of 504 respondents who had been diagnosed with any of the 22 types of cancer listed in the survey questionnaire. Measures: As independent variables, we assessed 3 different types of support: emotional, informational, and tangible support. As mediating and outcome variables, we measured LTPA and mental health, respectively. Analysis: Using AMOS version 22, a path analysis was conducted to measure model fit. A mediation test was then conducted using bootstrapping procedures. Results: The hypothesized model provided an acceptable fit to the data. Specifically, emotional support ( b = .15, p = .005), informational support ( b = .13, p = .008), tangible support ( b = .12, p = .010), and LTPA ( b = .14, p = .001) were significantly associated with mental health. We revealed a significant mediating effect of LPTA on the relationship between emotional support and mental health (Estimate = .037, 95% CI = .001–.098, p < .05). Conclusion: Social support and LTPA played a significant role in promoting mental health among people with cancer. In particular, the results confirmed that individuals with cancer who reported receiving emotional support tended to engage in LTPA and thus reported better mental health.

scholarly journals The Fundraising Disadvantages Confronting American Political Parties

The Forum ◽  
2015 ◽  
Vol 13 (2) ◽  
Author(s):  
Anne Baker
Keyword(s):  
Political Parties ◽  
Interest Groups ◽  
Democratic Party ◽  
Structural Equation ◽  
Finance Reform ◽  
Structural Equation Analysis ◽  
Equation Analysis ◽  
The Supreme Court ◽  
Relationship Of ◽  
The Relationship

AbstractIn the wake of the Bi-Partisan Campaign Finance Reform Act of 2002 and subsequent rulings by the Supreme Court, American political parties face greater regulation than interest groups in terms of their ability to finance federal elections. While parties continue to be constrained by contribution limits, nearly all interest groups can now raise and spend money in unlimited amounts to influence elections. Further, many new groups formed to take advantage of these legal changes. Few studies address the ramifications of these developments for political parties’ fundraising capabilities. To see whether these disadvantages hamper party fundraising, I examine parties’ direct fundraising costs overtime and I use structural equation analysis to investigate the giving habits of party donors overtime. I find the fundraising cost of each dollar raised has risen and habitual party donors provide significant support to Super PACs. Habitual party donors have also become less consistent givers in the Democratic Party. I discuss the relationship of these findings to changes in party fundraising tactics and their implications for future efforts by the parties to maintain their revenue streams.

The Validation Process for Tier-III Variables and Fitness of the Model

2013 ◽  
pp. 238-254
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Theoretical Models ◽  
Parameter Estimates ◽  
Analysis Model ◽  
Validation Process ◽  
Structural Equation Analysis ◽  
Equation Analysis ◽  
Proposed Model ◽  
The Relationship

The validation of the model is dependent on the strength of the relationships established through variables, and Tier-III influencers are designed to ensure the validation process at a macro level. Tier-III influencers of the model help us understand the relations between variables matching (fitting) the data (Tier-I and II) and the way they influence the appropriateness of the model. Tier-III influencers characterize theoretical testing of the model and are mostly based on theory-driven search for the important antecedents of one or more focal variables. Tier-III influencers help us understand the relationship among the variables governing the outcome of the proposed model. It is agreed that the process of testing or validating theoretical models with survey data is addressed by first determining the adequacy of the measures of the unobserved variables in the model and then determining the reasonableness or adequacy of the hypothesized model. Measurements of Tier-III use conceptual definitions of the unobserved or latent variables, along with observed variables or items that measure these unobserved or latent variables. This chapter discusses model-to-data fit and parameter estimates by utilizing structural equation analysis. Model adequacy is determined by using hypotheses and model-to-data fit and parameter estimates from structural models.

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