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Exploring the Relationship Between Factors of Emotional and General Intelligence and the Success of Foster Care Alumni

Exploring the Relationship Between Factors of Emotional and General Intelligence and the Success of Foster Care Alumni. Quality of Life Applied Research Grant June 10, 2008 Tom Kennedy, Ph.D. – FSEHS Alex Edmonds, Ph.D. – FSEHS Nicole Englebert , B.S. – CPS

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Exploring the Relationship Between Factors of Emotional and General Intelligence and the Success of Foster Care Alumni

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  1. Exploring the Relationship Between Factors of Emotional and General Intelligence and the Success of Foster Care Alumni Quality of Life Applied Research Grant June 10, 2008 Tom Kennedy, Ph.D. – FSEHS Alex Edmonds, Ph.D. – FSEHS Nicole Englebert, B.S. – CPS Marjory Bruszer, CEO – SOS Children’s Villages

  2. Introduction • It is well documented that foster care children often experience more adversity than non-foster care children as they move into young adulthood and “age out” of the foster care system. • According to the Child Welfare League of America (2005), approximately 20,000 to 25,000 adolescents “age out” of the foster care system each year, of these children, 25% end up homeless, 56% become unemployed, and 27% of the young men end up in jail.

  3. Introduction • A recent survey (Miller, 2008) designed to measure the success of Florida’s efforts to prepare older foster children (age 13 to 23) for adulthood revealed that: • (a) at least one in four former foster kids are homeless in Sarasota • (b) fewer than one in 10 foster children age 17 are performing at grade level in St. Augustine • (c) fewer than one in four 17-year-old foster kids passed Florida's high-stakes standardized assessment test in Miami, Tampa and Daytona Beach • In Broward County specifically, the school board reported that children in foster care scored lower on school-wide exams than children not in foster care (The School of Broward County, 2007).

  4. Introduction • “The little research that exists on outcomes for youth who have grown up in foster care indicates that resilience is not a common phenomenon within this population.” (Hines, Merdinger & Wyatt, 2005) • Clearly, there is a significant need to better understand the factors that affect the success of foster care children as they “age out” of the system. • By gaining a better understanding of factors that both predict success and are amenable to change, it may be possible to tailor early interventions that increase quality of life.

  5. Introduction • It is theorized that a model constructed of variables from two general domains (emotional intelligence and general intelligence) will accurately predict the success of foster care alumni.

  6. Introduction • Impetus for this research: • Gain a better understanding of factors that affect the success of young adults in Broward who have “aged out” of the foster care system. • No published study to date has explored variables from the area of general and emotional intelligence to predict the success of foster care alumni. This study has the potential to both add to the existing literature, and lead to improved preventative interventions.

  7. Research Question 1 To what extent can success be reliably predicted from variables selected from the domain of emotional and general intelligence?

  8. Research Question 2 If success can be predicted accurately, which variables are central in the prediction of that status? Does the inclusion of a particular variable increase or decrease the probability of the specific outcome?

  9. Research Question 3 How well does the model classify cases for which the outcome is unknown? In other words, how many successful participants are classified accurately and how many unsuccessful participants are correctly classified?

  10. Predictor Variables (IV’s) 1) Emotional Intelligence (EI) 2) General Intelligence (IQ)

  11. Emotional Intelligence Exercise

  12. Emotional Intelligence • Ability Based Models • EI is an ability involving cognitive • processing of emotional information • Measurements: Performance Tests • -Mayer Salovey Caruso Emotional Intelligence Test (MSCEIT) • Mayer, Salovey, Caruso • 1) Perception • 2) Utilization • 3) Understanding • 4) Regulation • Mixed Models/Trait EI Models • - EI is a dispositional tendency • - Measurements: self-report questionnaires • Baron Emotional Quotient Inventory (EQ-i) • Widely used • - Goleman • Self awareness • Self-regulation • Motivation • Empathy • Social skills 2 types of theories/models (Austin et al., 2005; Extremera, Fernandez-Berrocal, 2005; Petrides, Frederickson, & Furnham, 2004; Zeidner, Mathews, Roberts, & MacCann, 2003)

  13. The Trait EI Model • What is Emotional Intelligence (EI) • interrelated emotional, and social competencies, skills, and facilitators • Determine how one understands, expresses him or herself, understands others, and relates with them • Emotional Intelligence (Interpersonal and intrapersonal components) • Self-awareness • Emotional understanding • Self-regulation • Social awareness • Social influence • Emotion expression • Influences one’s coping with environmental demands • Associated with a range of outcomes relating to one’s quality of life (Austin, Saklofske, & Egan, 2005; Baron, 2007; Kunnanatt, 2004; Zeidner et al., 2003)

  14. What does it mean to be emotionally intelligent? • “Personally and socially desirable transactional outcomes” • Capable of correctly understanding: • Self emotion • Other’s emotions • Rules • Beliefs • Evaluate situations and express feelings accordingly • Are more able to resist peer pressure in connection to risky health behaviors • related to willingness to seek help for personal-emotional problems, depression, and suicidal ideation (Austin et al., 2005; Bar-On, 2007; Kunnanat, 2004; Matthews, Zeidner, & Roberts, 2007)

  15. EI: a separate construct • Is EI distinct from general intelligence and the personality domain? • EI is generally seen as learnable whereas traditional intelligence is not • EI correlation with the WAIS intelligence test: r= .12 • Incremental Validity of EI • EI may explain a variance in happiness beyond other personality traits (Austin et al., 2005; Chamorro-Premuzic, Bennett, & Furnham, 2007; Zeidner et al., 2003)

  16. EI Research Findings • Positive associations: • Life satisfaction • Happiness • Life and business success • General well being • Social Network Size and Quality • Scholastic achievement • Parental warmth • Positive peer and family relations • Negative associations: • Depression • Loneliness • Psychological distress • Smoking and alcohol consumption in adolescents • Deviant Behavior in children • Alexithymia (difficulty identifying feelings, difficulty describing feelings, and externally oriented thinking) (Austin et al., 2005; Bar-On, Maree, & Elias, 2007; Bastian, Burns, Nettelbeck, 2005; Bradberry & Greaves, 2005; Derksen, Kramer, & Katzko, 2002; Petrides et al., 2004)

  17. Foster Care Children • 80% have significant mental health problems • Behavior and adaptive functioning problems • Emotional and behavioral disturbances • Coping difficulties • Inadequate care • Well-being issues • At risk for difficulties into adulthood (Kerker & Dore, 2006; Taussig, 2002)

  18. Risk Factors for Foster Care Youth • Histories of • Domestic violence • Criminal involvement • Mental illness • Drug and/or alcohol abuse • Genetic predisposition for mental health problems • In utero drug and/or alcohol exposure • Brain development • Negative impact of Trauma • Deficits in empathy and emotional connection between parents and infant (Bar-On et al., 2007; Bradberry & Greaves, 2005; Kerker & Dore, 2006; Taussig, 2002; Zeidner et al., 2003)

  19. Risk Factors Environmental Factors • Influenced by: • Role models • Significant life situations • Experiences • May be vulnerable to Emotional Intelligence deficits because many encounter: • Abuse/neglect • Domestic violence • Placement in multiple foster homes • Inconsistent care • Removal from the biological home (Bar-On et al., 2007; Bradberry & Greaves, 2005; Kerker & Dore, 2006; Taussig, 2002; Zeidner et al., 2003)

  20. Risk Factors • Foster children often: • Internalize negative messages from experiences • Lack good parenting • Have repeated separations which may lead to stress and emotional problems • Have fewer friends and social networks • Foster children with High EI- may react to stress differently (Bar-On et al., 2007; Bradberry & Greaves, 2005; Fong, Schwab, & Armour, 2006; Zeidner et al., 2003)

  21. Emotional Intelligence Interventions • Emotional intelligence • Identified as changing with age and is considered a dynamic construct • Generally accepted as learnable • Interventions • Have been used in human resource settings • What about with foster care youth? • May reduce future risk as they “age out” of the system • May increase success (Bar-On, 2007; Derksen et al., 2002; Kunnanatt, 2004; Zeidner et al., 2003 )

  22. Emotional Intelligence Measures • May identify: • At risk foster care children • Foster children who tend to be more happy, successful, and satisfied with life • A need for training programs (Austin et al., 2005; Chamorro-Prezmuzic et al., 2006; Dulewicz et al., 2003; Kunnanatt, 2004; Petrides et al., 2004; Zeidner et al., 2003)

  23. Bar-On Emotional Quotient Inventory (EQ-i) • Non-cognitive Model • Assesses personal and social applications • Five Composite Scales: • Intrapersonal • Interpersonal • Adaptability • General Mood • Stress Management • Internal consistency reliability = 0.97 (Austin et al., 2005; Baron, 2007; Conte, 2005; Kunnanatt, 2004)

  24. General Intelligence • For the purposes of this study, general intelligence (IQ) will be measured by the KaufmanBrief Intelligence Test (K-BIT). • The K-BIT was created to address the need for a brief, self-contained, reliable, valid, and adequately normed test of both verbal and nonverbal ability.

  25. General Intelligence(K-BIT) • The test is divided into a measure of verbal or crystallized thinking (Expressive Vocabulary and Definitions), and one of nonverbal or fluid thinking (Matrices). • An overall IQ is provided through the K-BIT IQ Composite.

  26. General Intelligence • Advocates for IQ assert that “it is the most effective predictor known of individual performance at school and on the job” • Researchers claim that “g” can predict not finishing high school and being unemployed. • What we “think” we know (when factors such as SES are controlled for) • IQ accounts for about 25% of the variance in schooling outcome. • IQ accounts for 15% of the variance in an individuals income. • Differences in intelligence account for anywhere from 4% to 30% of the variance in job-performance ratings • People who demonstrate delinquent behavior score 8 points lower on IQ tests than do non-delinquents

  27. General Intelligence • According to a study conducted at Yale University on the predictive value of IQ, the authors conclude with… • IQ is a relative good predictor of many kinds of childhood and adult outcomes, although many other factors contribute to these outcomes as well • Broader test of intelligence such as those being proposed and explored (e.g., Gardner and Stenberg) offer possibilities for increasing levels of prediction • IQ is a better predictor of more academic performances than of less academic performances

  28. General Intelligence • A study published last year in the journal of Science, found that the severe cognitive impairment that results from profound neglect can be significantly reversed through placing children in foster-home settings, particularly if placed before age 2. • Even among the youngest children placed in foster care, children with histories of institutionalization still have IQ’s that are nearly 10 points below that of never institutionalized children

  29. Criterion Variables (DV’s) • Subjective well being is used as an indicator of life satisfaction, preponderance and intensity of positive, happy emotions and absence of negative affect in one’s life • SWB is based on how and why we view our lives as a satisfying, happy experience (Deiner & Emmons, 1984; Bryant & Veroff, 1982; Emmons et al., 1985)

  30. Criterion Variables (DV’s) Subjective Well Being • Literature suggests that individuals “make” their own standard for what constitutes a satisfying life and then compare the experiences of their own life to that standard (Pavot, Deiner, Colvin & Sandvik, 1991)

  31. Criterion Variables (DV’s) • The QLQ is a measure of subjective well being (Evans & Cope, 1989). The measure includes 15 subscales and an overall summative scale. • Material Well-Being, Physical Well-Being, Personal Growth, Marital Relations, Parent-Child Relations, Extended Family Relations, Extramarital Relations, Altruistic Behavior, Political Behavior, Job Characteristics, Occupational Relations, Job Satisfiers, Creative/Aesthetic Behavior, Sports Activity, Vacation Behavior, Social Desirability, Total Quality of Life.

  32. Criterion Variables (DV’s) • Although subjective well being is conceptualized as a global index of success, additional factors will be considered and factored into the construct of “success.”

  33. Criterion Variables (DV’s)Descriptive • Job Status • Secondary Education History • Legal History • Job Status • ?

  34. Present Study • The purpose is to determine how accurately factors of general and emotional intelligence can predict success in a sample of male and female foster care alumni. • Additional comparisons will be made relative to demographic variables such as years in the foster care system, ethnicity and gender.

  35. Procedures and Methodology • Participants • N=50 • Both male and females • All have aged out of SOS Children’s Villages • English speaking • Live is South Florida

  36. Procedures and Methodology • Measures • IV’s • Kaufman Brief Intelligence Test (K-BIT) • Bar-On’s Emotional Quotient Inventory (EQ-i) • DV’s • The Quality of Life Questionnaire (QLQ) • Semi-Structured Interview (at least 4 descriptive variables)

  37. Procedures and Methodology • Design and Data Analysis • First, a correlation analysis will be conducted to find those variables that demonstrate the strongest correlation with predicted success. • These variables will then be explored via logistic regression.

  38. Procedures and Methodology • Design and Data Analysis • Logistic Regression • To examine the effects of continuous predictors (IQ and EI) on a binary dependent variable (successful versus unsuccessful) • The purpose of LR is to classify individuals into groups, thus, LR produces a regression equation that accurately predicts the probability of whether an individual will fall into one category (e.g., successful) or the other (e.g., unsuccessful).

  39. Procedures and Methodology • Design and Data Analysis • Hosmer and Lemeshow (2000) stress that the use of LR is to find the “best fitting and most parsimonious, yet biologically reasonable model to describe the relationship between an outcome (dependent or response) variable and a set of independent (predictor or explanatory) variables (p.1).”

  40. Results • Odds Ratio {Exp(B)} • An interpretation of the logit coefficient. • The odds ratio is the probability of the event divided by the probability of the nonevent.

  41. Results • For example, if expB =2, then a one unit change in the predictor variables (IQ and EI) would make the event twice as likely (.67/.33) to occur. • Odds ratios equal to 1 mean that there is a 50/50 chance that the event will occur with a one unit change in the independent variable.

  42. Example Results(Classification Table)

  43. References • Austin, E. J., Saklofske, D. H., & Egan, V. (2005). Personality, well-being and health correlates of trait emotional intelligence. Personality and Individual Differences, 38, 547-558. • Bar-On, R. (2007). Providing Information and Fostering Discussion on Emotional Intelligence. Retrieved March 9, 2008, from www.reuvenbaron.org/ • Bar-On, R. Maree, J.G., & Elias, M. J. (Eds.). (2007). Education People to be Emotionally Intelligent. Westport, Connecticut: Praeger. • Bastian, V. A., Burns, N. R., & Nettelbeck, T. (2005). Emotional Intelligence predicts life skills, but not as well as personality and cognitive abilities. Personality and Individual Differences, 39, 1135-1145. • Bradberry, T., & Greaves, J. (2005). The Emotional Intelligence Quick Book: Everything You Need To Know To Put Your EQ To Work. New York: Fireside. • Chamorro-Premuzic, T., Bennett, E., & Furnham, A. (2006). The happy personality: Mediational • role of trait emotional intelligence. Personality and Individual Differences, 42, 1633-1639. • Derksen, J., Kramer, I., & Katzko, M. (2002). Does a self-report measure for emotional intelligence assess something different than general intelligence? Personality and Individual Differences, 32, 37-48. • Dulewicz, V., Higgs, M., & Slaski, M. (2003). Measuring emotional intelligence: content, construct and criterion-related validity. Journal of Managerial Psychology, 18(5), 405-420. • Extremera, N. & Fernandez-Berrocal, P.(2005). Perceived emotional intelligence and life satisfaction: Predictive and incremental validity using the Trait Meta-Mood Scale. Personality and Individual Differences, 39, 937-948. • Fong, R., Schwab, J., &Armour , M. (2006). Continuity of activities and child well-being for foster care youth. Children and Youth Services Review, 28, 1359-1374. • Kerker, B. D., & Dore, M. M. (2006). Mental Health Needs and Treatment of Foster Youth: Barriers and Opportunities. American Journal of Orthopsychiatry, 76(1), 138-147. • Kunnanatt, J. T. (2004). Emotional Intelligence: The New Science of Interpersonal Effectiveness. Human Resource Development Quarterly, 15(4), 489-495. • Matthews, G., Zeidner, M., & Roberts, R. D. (Eds.). (2007). The Science of Emotional Intelligence: Knowns and Unknowns. New York: Oxford University Press. • Petrides, K. V., Frederickson, N., & Furnham, A. (2004). The role of trait emotional intelligence in academic performance and deviant behavior at school. Personality and Individual Differences, 36, 277-293. • Taussig, H. N. (2002). Risk behaviors in maltreated youth placed in foster care: a longitudinal • study of protective and vulnerability factors. Child Abuse & Neglect, 26, 1179-1199. • Zeidner, M. Matthews, G., Roberts, R. D., & MacCann, C.(2003). Development of Emotional Intelligence: Towards a Multi-Level Investment Model. Human Development, 46, 69-96.

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