scholarly journals Revisiting the hierarchical structure of the 24 VIA character strengths: Three global dimensions may suffice to capture their essence

2021 ◽  
Author(s):  
Melanie Viola Partsch ◽  
Matthias Bluemke ◽  
Clemens M. Lechner
Keyword(s):  
Character Strengths ◽  
Self Regulation ◽  
Analytic Solutions ◽  
Character Trait ◽  
Analytic Structure ◽  
Levels Of Abstraction ◽  
Total N ◽  
Factor Analytic ◽  
The Hierarchical Structure ◽  
Trait Space

Peterson and Seligman's (2004) values-in-action (VIA) framework maps 24 character strengths onto six more abstract virtues through a theoretical classification. However, compared to other individual difference constructs, there is little consensus about the factor-analytic structure of the VIA trait space. Applying Horn’s parallel analysis, Goldberg’s Bass-ackwards approach, and cross-country congruency analysis, we scrutinize the factor-analytic solutions-hierarchy of the 24 VIA strengths with the aim to identify one or more useful global levels of abstraction (akin to the Big Five, HEXACO/Big Six, or personality metatraits). We assessed the 24 character strengths with the psychometrically refined IPIP-VIA-R inventory in two large and heterogeneous samples from Germany and UK (total N ≈ 2,000). Results suggested that three global dimensions suffice to capture the essence of character strengths: Level III recovered more than 50% of the total variation of the 24 character strengths in well-interpretable, global/general, cross-culturally replicable dimensions. We provisionally labeled them positivity, dependability, and mastery. Their superordinate Level-II-dimensions were reminiscent of the “Big Two” personality metatraits Dynamism and Social Self-Regulation. Our results advance the understanding of the VIA character trait space and may serve as a basis for developing scales to assess these global dimensions.

scholarly journals Revisiting the hierarchical structure of the 24 VIA character strengths: Three global dimensions may suffice to capture their essence

2021 ◽  
pp. 089020702110177
Author(s):  
Melanie V Partsch ◽  
Matthias Bluemke ◽  
Clemens M Lechner
Keyword(s):  
Character Strengths ◽  
Self Regulation ◽  
Analytic Solutions ◽  
Character Trait ◽  
Analytic Structure ◽  
Levels Of Abstraction ◽  
Total N ◽  
Factor Analytic ◽  
The Uk ◽  
Trait Space

The Values in Action (VIA) framework maps 24 character strengths onto six more abstract virtues through a theoretical classification. However, compared to other individual difference constructs, there is little consensus about the factor-analytic structure of the VIA trait space. Applying Horn’s parallel analysis, Goldberg’s Bass-ackwards approach, and cross-country congruency analysis, we scrutinize the factor-analytic solutions-hierarchy of the 24 VIA strengths with the aim to identify one or more useful global levels of abstraction (akin to the Big Five, HEXACO/Big Six, or personality metatraits). We assessed the 24 character strengths with the psychometrically refined IPIP-VIA-R inventory in two large and heterogeneous samples from Germany and the UK (total N ≈ 2,000). Results suggested that three global dimensions suffice to capture the essence of character strengths: Level III recovered more than 50% of the total variation of the 24 character strengths in well-interpretable, global/general, cross-culturally replicable dimensions. We provisionally labeled them positivity, dependability, and mastery. Their superordinate Level-II-dimensions were reminiscent of the “Big Two” personality metatraits Dynamism and Social Self-Regulation. Our results advance the understanding of the VIA character trait space and may serve as a basis for developing scales to assess these global dimensions.

scholarly journals Methods for estimating uncertainty in factor analytic solutions

2014 ◽  
Vol 7 (3) ◽  
pp. 781-797 ◽  
Author(s):  
P. Paatero ◽  
S. Eberly ◽  
S. G. Brown ◽  
G. A. Norris
Keyword(s):  
Environmental Protection Agency ◽  
Synthetic Data ◽  
Analytic Solutions ◽  
Data Sets ◽  
Random Errors ◽  
Data Set ◽  
Factor Analytic ◽  
Uncertainty Estimates ◽  
Multilinear Engine ◽  
Analytic Models

Abstract. The EPA PMF (Environmental Protection Agency positive matrix factorization) version 5.0 and the underlying multilinear engine-executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement of factor elements (BS-DISP). The goal of these methods is to capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. It is shown that the three methods complement each other: depending on characteristics of the data set, one method may provide better results than the other two. Results are presented using synthetic data sets, including interpretation of diagnostics, and recommendations are given for parameters to report when documenting uncertainty estimates from EPA PMF or ME-2 applications.

scholarly journals A Novel BrainHealth Index Prototype Improved by Telehealth-Delivered Training During COVID-19

2021 ◽  
Vol 9 ◽  
Author(s):  
Sandra Bond Chapman ◽  
Julie M. Fratantoni ◽  
Ian H. Robertson ◽  
Mark D'Esposito ◽  
Geoffrey S. F. Ling ◽  
...  
Keyword(s):  
Public Health ◽  
Social Engagement ◽  
Scale Up ◽  
Well Being ◽  
Ease Of Use ◽  
Strategy Training ◽  
Analytic Structure ◽  
Brain Health ◽  
Online Platform ◽  
Factor Analytic

Introduction: Brain health is neglected in public health, receiving attention after something goes wrong. Neuroplasticity research illustrates that preventive steps strengthen the brain's component systems; however, this information is not widely known. Actionable steps are needed to scale proven population-level interventions.Objectives: This pilot tested two main objectives: (1) the feasibility/ease of use of an online platform to measure brain health, deliver training, and offer virtual coaching to healthy adults and (2) to develop a data driven index of brain health. Methods: 180 participants, ages 18–87, enrolled in this 12-week pilot. Participants took a BrainHealth Index™ (BHI), a composite of assessments encompassing cognition, well-being, daily-life and social, pre-post training. Participants engaged in online training with three coaching sessions. We assessed changes in BHI, effects of training utilization and demographics, contributions of sub-domain measures to the BHI and development of a factor analytic structure of latent BrainHealth constructs.Results: The results indicated that 75% of participants showed at least a 5-point gain on their BHI which did not depend on age, education, or gender. The contribution to these gains were from all sub-domains, including stress, anxiety and resilience, even though training focused largely on cognition. Some individuals improved due to increased resilience and decreased anxiety, whereas others improved due to increased innovation and social engagement. Larger gains depended on module utilization, especially strategy training. An exploratory factor analytic solution to the correlation matrix of online assessments identified three latent constructs.Discussion/Conclusion: This pilot study demonstrated the efficacy of an online platform to assess changes on a composite BrainHealth Index and efficacy in delivering training modules and coaching. We found that adults, college age to late life, were motivated to learn about their brain and engage in virtual-training with coaching to improve their brain health. This effort intends to scale up to thousands, thus the pilot data, tested by an impending imaging pilot, will be utilized in ongoing machine learning (ML) algorithms to develop a precision brain health model. This pilot is a first step in scaling evidence-based brain health protocols to reach individuals and positively affect public health globally.

Reliability Generalization as a Seal of Quality of Substantive Meta-Analyses: The Case of the VIA Inventory of Strengths (VIA-IS) and Their Relationships to Life Satisfaction

2018 ◽  
Vol 122 (3) ◽  
pp. 1167-1188 ◽  
Author(s):  
Mercedes Ovejero Bruna ◽  
Andreea C. Brabete ◽  
Jesús M. Alvarado Izquierdo
Keyword(s):  
Life Satisfaction ◽  
Test Scores ◽  
Character Strengths ◽  
Meta Analysis ◽  
Self Regulation ◽  
Reliability Estimation ◽  
Assessment Instrument ◽  
Sample Type ◽  
Reliability Generalization ◽  
The Relationship

Reliable test scores are essential to interpret the results obtained in statistical analyses correctly. In this study, we used the Values in Action Inventory of Strengths (VIA-IS) as an example of a widely applied assessment instrument to analyze its metric quality in what is known as reliability generalization (RG). In addition, we conducted a meta-analysis of the correlations between character strengths and life satisfaction to examine the potential relationship between the reliability of test scores and the intensity of these correlations. The overall variability of alpha coefficients supports the argument that reliability is sample dependent. Indeed, there were statistically significant mean reliability differences for scores across the 24 scales, with the highest level of reliability observed for Creativity and the lowest for scores on Self-regulation. Significant moderators such as the standard deviation of the scores and the sample type contribute to understand the high variability observed in the reliability estimation. The second meta-analysis showed that Zest, Hope, Gratitude, Curiosity, and Love were the character strengths that were highly related to life satisfaction, while Modesty and Prudence were less related to life satisfaction. Furthermore, the high heterogeneity between samples might be an indicator of the relationship between the variability of reliability of character strengths' scores and the intensity of their correlations with life satisfaction. Those character strengths with high-potential RG are related or unrelated to life satisfaction, whereas character strengths with less-potential RG showed unstable correlation patterns. The results of both studies point out the role of the relationship between the reliability of test scores and substantive studies, such as Pearson's correlations meta-analysis.

scholarly journals Character Strengths in Children and Adolescents

2014 ◽  
Vol 30 (1) ◽  
pp. 57-64 ◽  
Author(s):  
Willibald Ruch ◽  
Marco Weber ◽  
Nansook Park ◽  
Christopher and Peterson†
Keyword(s):  
Children And Adolescents ◽  
Character Strengths ◽  
High Reliability ◽  
Gender Effects ◽  
Self Report ◽  
Parent Ratings ◽  
Total N ◽  
Self Reports ◽  
German Speaking ◽  
General Self Efficacy

The Values in Action Inventory of Strengths for Youth (VIA-Youth) is a self-report inventory assessing 24 character strengths among people 10–17 years of age. This paper describes the adaptation and initial validation of a German version of this measure utilizing several samples (in total N = 2,110 self-reports of participants aged 10–17 years, 56.5% girls; N = 219 parent-reports) from Germany and Switzerland. The 24 scales yielded high reliability and exhibited stability over 4 months. Self-reports and parent-ratings of strengths converged well. An oblique five-factor solution was found to represent the data well. There were small age effects, and small to medium gender effects (e.g., girls scored higher on beauty and kindness). Character strengths of hope, gratitude, love, and zest correlated positively with global life satisfaction. Furthermore, most of the strengths were strong predictors of general self-efficacy. Overall, the German VIA-Youth demonstrated good psychometric properties and promising evidence for validity. The German VIA-Youth is recommended for the assessment of character strengths in German-speaking children and adolescents.

Identifying sub-categories of social fears using an alternative factor analytic structure of the Social Phobia and Anxiety Inventory

2017 ◽  
Vol 251 ◽  
pp. 304-311 ◽  
Author(s):  
Georgia Panayiotou ◽  
Michalis P. Michaelides ◽  
Marios Theodorou ◽  
Klavdia Neophytou
Keyword(s):  
Social Phobia ◽  
Analytic Structure ◽  
Factor Analytic ◽  
The Social

Maximally correlated orthogonal composites and oblique factor analytic solutions

Psychometrika ◽  
1977 ◽  
Vol 42 (3) ◽  
pp. 439-442
Author(s):  
James M. Price ◽  
W. Alan Nicewander
Keyword(s):  
Analytic Solutions ◽  
Factor Analytic

scholarly journals Methods for estimating uncertainty in factor analytic solutions

2013 ◽  
Vol 6 (4) ◽  
pp. 7593-7631 ◽  
Author(s):  
P. Paatero ◽  
S. Eberly ◽  
S. G. Brown ◽  
G. A. Norris
Keyword(s):  
Synthetic Data ◽  
Analytic Solutions ◽  
The Other ◽  
Data Sets ◽  
Random Errors ◽  
Data Set ◽  
Factor Analytic ◽  
Uncertainty Estimates ◽  
Multilinear Engine ◽  
Analytic Models

Abstract. EPA PMF version 5.0 and the underlying multilinear engine executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement of factor elements (BS-DISP). The goal of these methods is to capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. It is shown that the three methods complement each other: depending on characteristics of the data set, one method may provide better results than the other two. Results are presented using synthetic data sets, including interpretation of diagnostics, and recommendations are given for parameters to report when documenting uncertainty estimates from EPA PMF or ME-2 applications.

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