Quantitative analysis of effect of Pilates exercises on psychological variables and academic achievement using fuzzy logic

Memmedova, Konul

doi:10.1007/s11135-017-0601-9

Cited by 10 publications

(5 citation statements)

References 12 publications

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“…Regarding social motives, we showed that Pilates was the least socially motivated PA. In general, Pilates is a frequently studied PA, and its benefits to health are well-documented (Memmedova, 2018). Despite our results, relatedness is considered an important factor for the maintenance of Pilates, following competence (Lee, 2018).…”

Section: Discussioncontrasting

confidence: 53%

Comparing Different Typologies of Physical Activities With a Focus on Motivation

et al. 2022

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There are numerous classifications of physical activities (PAs). However, they lack precise grouping criteria and tend to vary according to each author. Among other factors, the individual’s level of motivation is considered an important aspect of PA maintenance. In this study, we aimed to (1) compare several PAs according to intrinsic (Interest, Enjoyment, and Competence) and extrinsic (Appearance, Fitness/Health, and Social) motives and (2) analyze PAs with and without previous grouping to explore which PAs are more similar based on the different motivational subscales. We recruited 1,421 physically active Brazilian participants (mean age = 26.83, SD = 10.49). The participants stated which PA they practiced most frequently, and they answered the revised motivation for PA measure. The data were analyzed with multivariate general linear models and Kruskal–Wallis. We found that some PAs consistently differed from others regarding motivational subscales. For example, participants practicing Walking showed less Interest/Enjoyment and Competence motives than participants engaged in several other PAs. Pilates was highlighted by a particularly low level of Social motivation in comparison to other PAs. Furthermore, using the previously suggested categorization of PAs, we also showed consistent distinctions considering each motivational subscale. Specifically, one group of PA (categorized as more Complex, Team, Vigorous, Hybrid, and Combative) scored higher on intrinsic motivation, while the other group of activities (categorized as more Organized, Individual, Moderate, Strength, and Rhythmic) scored higher on Appearance and Fitness/Health motives. Our results thus provide initial evidence for possible new methods of grouping PA types that can improve maintenance behavior using motivation as a grouping factor.

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Section: Discussioncontrasting

confidence: 53%

Comparing Different Typologies of Physical Activities With a Focus on Motivation

et al. 2022

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“…For example, the personality can be measured by investigating the number of parties they attend, the number of friends they have, and whether they have good interpersonal relationships. Structural equation modeling can deal with the relationship between several variables at the same time and can reveal the degree of influence between the variables and is a widely used model in psychology and sociology [16]. Personality is a latent variable, and the number of friends, whether they party regularly, and whether they have good interpersonal relationships are the exogenous variables, also called observed variables.…”

Section: Fuzzy Qualitative Methods Design For Mental Healthmentioning

confidence: 99%

A Fuzzy Qualitative Simulation Study of College Student’s Mental Health Status

Deng

2022

Discrete Dynamics in Nature and Society

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The fuzzy qualitative approach used in this paper provides an in-depth study and analysis of the simulation of the mental health state of college students, which is continued from another perspective using structural equation modeling, in which sufficient conditions for the equation to satisfy local asymptotic stability, instability, and global attraction at the zero equilibrium point and sufficient conditions for the existence and instability of nonzero equilibrium points are discussed, respectively. In addition, the paper proves the boundedness of the solutions of the equation by mathematical induction and obtains sufficient conditions to ensure that the solutions are bounded. The intrinsic causes of college students’ psychological problems lie in the lack of social support in the family and outside the family and the influence of the overall social environment on college students. Finally, this paper puts forward some suggestions and countermeasures based on this research finding from three levels: family, school, and society, giving full play to the role of family support; schools should expand the main body of support, enrich the form of support, and provide comprehensive and multifaceted social support for college students. Finally, the simulation of the equation is carried out to verify the correctness of its conclusion. The rate of mental subhealth is 1.605 times that of college students admitted to ideal universities, which is consistent with our actual situation. At the level of condition guarantee, the hardware facilities, management system, and professional team of mental health education for college students are evaluated; from the specific content, the teaching work, educational activities, psychological counseling, and crisis intervention of mental health education for college students are evaluated; from the perspective of effect, the degree of goal achievement, social adaptation, and result satisfaction of the effect of mental health education for college students are evaluated. The final part analyzes and elaborates on the construction of evaluation indexes of mental health education for college students, the design of weight of guiding indexes, and the content and optimization path of the evaluation test. The results of the study show that personal ability and external pressure are important factors influencing college students’ mental health, and the influence of external pressure is greater. Logistic regression and structural equation modeling methods complement each other, and the findings of structural equation modeling are more comprehensive and integrated, while logistic regression illustrates the degree of each influencing factor.

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“…On this line, [36] compared Likert-type scale and three fuzzy conversion scales based on triangular, trapezoidal, and Gaussian fuzzy numbers, respectively. This type of fuzzy scaling has been widely applied, for instance, in measuring user experience [37], workers' motivation [38], teachers' beliefs about mathematics [39], students' perceptions about learning through a computer algebra system [40], motivation, attention and anxiety [41], job satisfaction [42], tourists' satisfaction [43,44,45], in evaluating healthcare services [46], educational services [47,48,49], and to develop methodologies for service quality analysis [50,51,52,53]. Instead, empirical-based fuzzy conversion methods transform crisp responses into fuzzy data using the information gathered directly from the empirical sample of responses.…”

Section: Currently Used Methods In Fuzzy Ratingmentioning

confidence: 99%

A psychometric modeling approach to fuzzy rating data

Calcagnì,

Cao,

Rubaltelli

et al. 2021

Preprint

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Modeling fuzziness and imprecision in human rating data is a crucial problem in many research areas, including applied statistics, behavioral, social, and health sciences. Because of the interplay between cognitive, affective, and contextual factors, the process of answering survey questions is a complex task, which can barely be captured by standard (crisp) rating responses.Fuzzy rating scales have progressively been adopted to overcome some of the limitations of standard rating scales, including their inability to disentangle decision uncertainty from individual responses. The aim of this article is to provide a novel fuzzy scaling procedure which uses Item Response Theory trees (IRTrees) as a psychometric model for the stage-wise latent response process. In so doing, fuzziness of rating data is modeled using the overall rater's pattern of responses instead of being computed using a single-item based approach. This offers a consistent system for interpreting fuzziness in terms of individual-based decision uncertainty. A simulation study and two empirical applications are adopted to assess the characteristics of the proposed model and provide converging results about its effectiveness in modeling fuzziness and imprecision in rating data.

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Quantitative analysis of effect of Pilates exercises on psychological variables and academic achievement using fuzzy logic

Cited by 10 publications

References 12 publications

Comparing Different Typologies of Physical Activities With a Focus on Motivation

Comparing Different Typologies of Physical Activities With a Focus on Motivation

A Fuzzy Qualitative Simulation Study of College Student’s Mental Health Status

A psychometric modeling approach to fuzzy rating data

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