Relationships Between Positive Human Traits and PERMA (Positive Emotion, Engagement, Relationships, Meaning, and Accomplishments) in Student Veterans With and Without Disabilities: A Canonical Correlation Analysis

2021 ◽  
Vol 35 (3) ◽  
pp. 238-247
Author(s):  
Emre Umucu ◽  
Beatrice Lee ◽  
Kanako Iwanaga ◽  
Kristin Kosyluk ◽  
John Blake ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Character Strengths ◽  
Well Being ◽  
Building Blocks ◽  
The United States ◽  
Student Veterans ◽  
The Core ◽  
Core Elements

PurposeWe explored the relationships between positive human traits and positive emotions, engagement, relationships, meaning, and achievement (PERMA) the core elements for Seligman's model of happiness and well-being.MethodTwo hundred and five student veterans (147 males and 58 females; 80 with service-related disability) were recruited from several colleges and universities across the United States. Participants completed positive human traits measures on resilience, hope, optimism, attachment, and coping, along with the PERMA Profiler that measures the five core elements of the well-being theory. Correlational techniques and canonical correlation analysis were computed to examine the canonical relationship between positive human traits and PERMA variables.ResultsOverall, the positive human traits set accounted for 37% of the variance in the PERMA set, whereas the PERMA set accounted for 51% of the variance in the positive human traits set.ConclusionsThe research findings suggest that human traits can be conceptualized as building blocks for PERMA, and PERMA are the core elements for happiness and well-being. Importantly, student veterans with disabilities had significantly lower resilience, secure attachment and PERMA scores. Positive psychology interventions to help student veterans, especially students with service-related disabilities, develop character strengths, and PERMA could improve college life adjustment and goal persistence of student veterans.

Trends in Snow Cover and Related Quantities at Weather Stations in the Conterminous United States

2015 ◽  
Vol 28 (19) ◽  
pp. 7518-7528 ◽  
Author(s):  
Noah Knowles
Keyword(s):  
United States ◽  
Correlation Analysis ◽  
Snow Cover ◽  
Canonical Correlation Analysis ◽  
Great Plains ◽  
Canonical Correlation ◽  
Snow Depth ◽  
The United States ◽  
Eastern Half ◽  
Precipitation Trends

Abstract Trend tests, linear regression, and canonical correlation analysis were used to quantify changes in National Weather Service Cooperative Observer (COOP) snow depth data and derived quantities, precipitation, snowfall, and temperature over the study period 1950–2010. Despite widespread warming, historical trends in snowfall and snow depth are generally mixed owing to competing influences of trends in precipitation. Trends toward later snow-cover onset in the western half of the conterminous United States and earlier onset in the eastern half and a widespread trend toward earlier final meltoff of snow cover combined to produce trends toward shorter snow seasons in the eastern half of the United States and in the west and longer snow seasons in the Great Plains and southern Rockies. The annual total number of days with snow cover exhibited a widespread decline. Monthly trend patterns show the dominant influence of temperature trends on occurrence of snow cover in the warmer snow-season months and a combination of temperature and precipitation trends in the colder months. A canonical correlation analysis indicated that most trends presented here took hold in the 1970s, consistent with the temporal pattern of global warming during the study period.

scholarly journals A Multidimensional Approach to Competitiveness, Innovation and Well-Being in the EU Using Canonical Correlation Analysis

2020 ◽  
Vol 12 (4) ◽  
pp. 5-21
Author(s):  
Ane-Mari Androniceanu ◽  
Jani Kinnunen ◽  
Irina Georgescu ◽  
Armenia Androniceanu
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Well Being ◽  
Eu Member States ◽  
Canonical Variates ◽  
Main Factors ◽  
The Uk ◽  
National Governments ◽  
The Eu

Achieving a competitive economy and a competitive market generally proceeds from the desire to meet economic and social objectives and it ensures a growing level of social welfare. The objectives of our research are to determine and highlight the bidirectional linear correlations among competitiveness, well-being and innovation and to analyze the main factors that influence these relations. Our research includes the EU member states and the UK using these countries’ specific indicators from the databases of EUROSTAT, the World Economic Forum and the United Nations from 2016-2018. We used Canonical Correlation Analysis to determine a set of canonical variates which represent linear combinations of the variables from each set. The contributions of our research show a direct and strong link among the three pillars of competitiveness, innovation and well-being. This analysis allowed us to identify and analyze the influence of innovation on the economic development and competitiveness of each EU country and on the well-being of its population. Governments and organizations that invest more in research in terms of innovation to increase the competitiveness of their products and services have shown a growing GDP and a higher level of population well-being. This research is representative at the European level and may influence the decisions of national governments and other institutions to encourage innovation through drivers such as R&D expenditures and human resources as the main factors generating economic growth and competitiveness, thus with a direct effect on GDP and on well-being.

scholarly journals Relationships Between the Coach-Created Motivational Climate and Athlete Engagement in Youth Sport

2015 ◽  
Vol 37 (2) ◽  
pp. 193-198 ◽  
Author(s):  
Thomas Curran ◽  
Andrew P. Hill ◽  
Howard K. Hall ◽  
Gareth E. Jowett
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Youth Sport ◽  
Well Being ◽  
Motivational Climate ◽  
Soccer Players ◽  
Positive Experiences ◽  
Coach Behaviors ◽  
A Performance

Youth sport is a source of well-being for adolescents, yet experiences vary and attrition can be high. We sought to better understand the coach behaviors that foster positive experiences in youth sport by examining relationships between the motivational climate and athlete engagement (viz., confidence, dedication, enthusiasm, and vigor). We reasoned that a mastery climate (emphasis on effort and learning) would correspond with higher engagement, whereas a performance climate (emphasis on ability and outcome) was expected to correspond with lower engagement. Two-hundred sixty adolescent soccer players completed measures of engagement and perceived coach motivational climate. All dimensions of engagement were positively predicted by a mastery climate. Furthermore, cognitive aspects of engagement were positively predicted by a performance climate. Canonical correlation analysis indicated that a composite of engagement was positively associated with a mastery climate. Results suggest that a mastery climate offers a means of promoting higher levels of overall engagement.

Analysis of Maximum Expiratory Flow Volume Curves Using Canonical Correlation Analysis

1985 ◽  
Vol 24 (02) ◽  
pp. 91-100 ◽  
Author(s):  
W. van Pelt ◽  
Ph. H. Quanjer ◽  
M. E. Wise ◽  
E. van der Burg ◽  
R. van der Lende
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Flow Volume ◽  
Non Linear ◽  
Maximum Expiratory Flow ◽  
Expiratory Flow ◽  
Relationship Of ◽  
The Relationship ◽  
Age And Sex

SummaryAs part of a population study on chronic lung disease in the Netherlands, an investigation is made of the relationship of both age and sex with indices describing the maximum expiratory flow-volume (MEFV) curve. To determine the relationship, non-linear canonical correlation was used as realized in the computer program CANALS, a combination of ordinary canonical correlation analysis (CCA) and non-linear transformations of the variables. This method enhances the generality of the relationship to be found and has the advantage of showing the relative importance of categories or ranges within a variable with respect to that relationship. The above is exemplified by describing the relationship of age and sex with variables concerning respiratory symptoms and smoking habits. The analysis of age and sex with MEFV curve indices shows that non-linear canonical correlation analysis is an efficient tool in analysing size and shape of the MEFV curve and can be used to derive parameters concerning the whole curve.

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