scholarly journals The Predictive Five: A supervised learning approach to personality psychology

2020 ◽  
Author(s):  
Gal Ben-Yosef ◽  
michael gilead ◽  
Jonathan Rosenblatt
Keyword(s):  
Dimensionality Reduction ◽  
Predictive Accuracy ◽  
Factor Model ◽  
Five Factor Model ◽  
Well Being ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Good Test ◽  
Human Personality ◽  
Novel Approach

In the current study, we set out to examine the viability of a novel approach to modeling human personality. Current research in psychology suggests that people’s personalities can be effectively described using five broad dimensions (the Five-Factor Model; FFM); however, the FFM has been criticized for its relatively limited predictive ability. We propose a novel approach to modeling human personality that is based on the maximization of the model’s predictive accuracy. Unlike the FFM, which performs unsupervised dimensionality reduction, we utilized supervised machine learning techniques for dimensionality reduction of questionnaire data, using numerous psychologically meaningful outcomes as data labels (e.g., intelligence, well-being, sociability). The results showed that our five dimensional personality summary, which we term the Predictive Five (PF), provides predictive performance that is superior to the FFM in independent validation datasets, and on a new set of outcome variables selected by an independent group of psychologists. Furthermore, we examine the between-participants’ replicability of the PF representation and show that the PF has good test-retest reliability, and as such provides an important addition to the psychologists' toolbox. The approach described herein has the promise of providing an interpretable low-dimensional personality representation, which is also predictive of behaviour.

scholarly journals The Predictive Five: a Supervised Learning Approach to Personality Psychology

2022 ◽  
Author(s):  
Michael Gilead ◽  
Gal Lavi ◽  
Jonathan Rosenblatt
Keyword(s):  
Dimensionality Reduction ◽  
Predictive Accuracy ◽  
Factor Model ◽  
Five Factor Model ◽  
Predictive Performance ◽  
Well Being ◽  
Supervised Machine Learning ◽  
Personality Psychology ◽  
Human Personality ◽  
Novel Approach

Abstract In the current study, we set out to examine the viability of a novel approach to modeling human personality. Research in psychology suggests that people’s personalities can be effectively described using five broad dimensions (the Five-Factor Model; FFM); however, the FFM potentially leaves room for improved predictive accuracy. We propose a novel approach to modeling human personality that is based on the maximization of the model’s predictive accuracy. Unlike the FFM, which performs unsupervised dimensionality reduction, we utilized a supervised machine learning technique for dimensionality reduction of questionnaire data, using numerous psychologically meaningful outcomes as data labels (e.g., intelligence, well-being, sociability). The results showed that our five-dimensional personality summary, which we term the “Predictive Five” (PF), provides predictive performance that is better than the FFM on two independent validation datasets, and on a new set of outcome variables selected by an independent group of psychologists. The approach described herein has the promise of eventually providing an interpretable, low-dimensional personality representation, which is also highly predictive of behavior.

Factorial Invariance of Child Self-Report Across English and Spanish Language Groups in a Hispanic Population Utilizing the PedsQL™ 4.0 Generic Core Scales

2010 ◽  
Vol 26 (3) ◽  
pp. 194-202 ◽  
Author(s):  
Daniel A. Newman ◽  
Christine A. Limbers ◽  
James W. Varni
Keyword(s):  
Health Care Services ◽  
Factor Model ◽  
Five Factor Model ◽  
Well Being ◽  
Factorial Invariance ◽  
Spanish Language ◽  
Self Report ◽  
Hispanic Population ◽  
Language Groups ◽  
Related Quality

The measurement of health-related quality of life (HRQOL) in children has witnessed significant international growth over the past decade in an effort to improve pediatric health and well-being, and to determine the value of health-care services. In order to compare international HRQOL research findings across language groups, it is important to demonstrate factorial invariance, i.e., that the items have an equivalent meaning across the language groups studied. This study examined the factorial invariance of child self-reported HRQOL across English- and Spanish-language groups in a Hispanic population of 2,899 children ages 8–18 utilizing the 23-item PedsQL™ 4.0 Generic Core Scales. Multigroup confirmatory factor analysis (CFA) was performed specifying a five-factor model across language groups. The findings support an equivalent 5-factor structure across English- and Spanish-language groups. Based on these data, it can be concluded that children across the two languages studied interpreted the instrument in a similar manner. The multigroup CFA statistical methods utilized in the present study have important implications for cross-cultural assessment research in children in which different language groups are compared.

scholarly journals Sustainable Development Goals and Investment Strategies: The Profitability of Using Five-Factor Fama-French Alphas

2020 ◽  
Vol 12 (5) ◽  
pp. 1842 ◽  
Author(s):  
José Luis Miralles-Quirós ◽  
María Mar Miralles-Quirós ◽  
José Manuel Nogueira
Keyword(s):  
Sustainable Development ◽  
Sustainable Development Goals ◽  
Factor Model ◽  
Five Factor Model ◽  
Well Being ◽  
Good Health ◽  
Investment Strategy ◽  
Investment Strategies ◽  
Responsible Investment ◽  
Development Goals

This study focuses on assets related to Sustainable Development Goals (SDGs), which are the most recent aspect of the Socially Responsible Investment framework and have caught the attention of investors due to their investment opportunities as well as the global challenges that can be achieved. The profitability of developing an investment strategy is shown based on the value of the alphas obtained from the estimation of the Fama-French five-factor model when compared to an equally weighted portfolio, even when transaction costs are taken into consideration. In addition, it is proven that investors should focus their investments on two main SDGs: Good health and well-being (Goal 3) and Industry, innovation and infrastructure (Goal 9).

The Five-Factor Model of Personality, Subjective Well-Being, and Social Adaptation: Generalizability to the Spanish Context

2005 ◽  
Vol 96 (3) ◽  
pp. 863-866 ◽  
Author(s):  
Victor M. Ruiz
Keyword(s):  
General Population ◽  
Undergraduate Students ◽  
Factor Model ◽  
Five Factor Model ◽  
Well Being ◽  
Social Adaptation ◽  
Subjective Well Being ◽  
Clear Pattern ◽  
Population Analyses ◽  
Five Factors

The relationships between the five-factor model of personality, subjective well-being, and social adaptation were examined in two Spanish groups, one of 112 undergraduate students and one of 177 participants from the general population. Analyses showed a clear pattern of low but positive associations among scores on well-being, social adaptation, and four of the five factors of personality (Extraversion, Agreeableness, Conscientiousness, and Emotional Stability), very similar to those obtained by previous research in the American context.

scholarly journals Does Personality Similarity in Bottlenose Dolphin Pairs Influence Dyadic Bond Characteristics?

2017 ◽  
Vol 30 ◽  
Author(s):  
Kelsey R. Moreno ◽  
Lauren Highfill ◽  
Stan A. Kuczaj II
Keyword(s):  
Factor Model ◽  
Five Factor Model ◽  
Well Being ◽  
Social Structures ◽  
Life History Strategies ◽  
Personality Factor ◽  
Naturalistic Environment ◽  
Animal Care ◽  
Captive Animal ◽  
Bond Characteristics

Social structures are critical to the success of many species and have repercussions on health, well-being, and adaptation, yet little is known about the factors which shape these structures aside from ecology and life history strategies. Dyadic bonds are the basis of all social structures; however, mechanisms for formations of specific bonds or patterns in which individuals form which types of bonds have yet to be demonstrated. There is a variety of evidence indicating personality may be a factor in shaping bonds, but this relationship has not been explored with respect to bond components and is yet to be demonstrated in dolphins. This study utilizes a captive population in a naturalistic environment to test for correlation between similarity within the dyad along each personality factor and the strength of the dyad’s bond characteristics. Personality was assessed using a Five Factor Model questionnaire. Dyadic bond strength and characteristic qualities were determined through an exploratory factor analysis to group behaviors recorded via underwater opportunistic focal-follow video. Discovered bond components differed from previous studies and were termed affiliative support, sociosexual, and conflict play. Individuals who differed in Extraversion and Neuroticism displayed greater levels of bonding. This study expands our understanding of the formation of bonds between individuals and the evolution of social structure. Furthermore, it better equips us for making informed environmental policy decisions and improving captive animal care.

scholarly journals Personality Traits in Australian Business Graduates and Implications for Organizational Effectiveness

2014 ◽  
Vol 28 (2) ◽  
pp. 113-126 ◽  
Author(s):  
Denise Jackson
Keyword(s):  
Personality Traits ◽  
Organizational Performance ◽  
Factor Model ◽  
Five Factor Model ◽  
Well Being ◽  
Background Characteristics ◽  
Business Graduates ◽  
Robust Model ◽  
And Performance ◽  
Demographic Background

The Five-Factor model is widely accepted as a robust model of personality that influences workplace behaviour and performance. Given evidence of persistent skills gaps in Australia, it is important to explore personality traits in business graduates to understand whether they have the necessary characteristics to enable the country to perform successfully nationally and to compete on a global level, particularly during periods of economic uncertainty. This study examines personality traits in 674 Australian business graduates, using the Ten-Item Personality Inventory (TIPI), and variations in traits across demographic/background characteristics. The results indicate that graduates are relatively high in extroversion, conscientiousness and emotional stability and low in openness and agreeableness. Some gender differences were apparent. The findings are largely positive for organizational performance, but raise concern for organizational well-being, effective leadership and innovativeness. There is some alignment between the findings and documented deficiencies in graduate performance, highlighting areas for intervention. Strategies for managing typical traits in business graduates and their potential impact on prevalent skills gaps are discussed for both professional and education practitioners.

scholarly journals Incremental Criterion Prediction of Personality Facets over Factors: Obtaining Unbiased Estimates and Confidence Intervals

2017 ◽  
Author(s):  
Jeromy Anglim ◽  
Sharon L. Grant
Keyword(s):  
Confidence Intervals ◽  
Regression Models ◽  
Factor Model ◽  
Five Factor Model ◽  
Well Being ◽  
R Package ◽  
Alternative Methods ◽  
Personality Facets ◽  
Unbiased Estimates ◽  
Level Analysis

Many researchers have argued that higher order models of personality such as the Five Factor Model are insufficient, and that facet-level analysis is required to better understand criteria such as well-being, job performance, and personality disorders. However, common methods in the extant literature used to estimate the incremental prediction of facets over factors have several shortcomings. This paper delineates these shortcomings by evaluating alternative methods using statistical theory, simulation, and an empirical example. We recommend using differences between Olkin-Pratt adjusted r-squared for factor versus facet regression models to estimate the incremental prediction of facets and present a method for obtaining confidence intervals for such estimates using double adjusted-r-squared bootstrapping. We also provide an R package that implements the proposed methods.

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