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Significant predictors of self-esteem during adolescence

Significant predictors of self-esteem during adolescence. Gyöngyi Kökönyei, Ágnes Balogh. Self-esteem/definitions. Dynamic and changing construct G lobal and domain-specific William James (1 8 83) viewed self - esteem as the ratio of one’s successes to one’s p re t ensions.

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Significant predictors of self-esteem during adolescence

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  1. Significant predictors of self-esteem during adolescence Gyöngyi Kökönyei, Ágnes Balogh

  2. Self-esteem/definitions • Dynamic and changing construct • Global and domain-specific • William James (1883) viewed self-esteemas the ratio of one’s successes to one’s pretensions. • Rosenberg (1979, p. 31) referred to self-esteem as a “positive or negative evaluation of the self.”

  3. Self-concept during adolescence • Main task: to establish identity (Erikson, 1962) and to restructure self-concept • The source of self-esteem • Essential component of mental health

  4. Sources of self-esteem These processes develop synergistically • Self-definition • Interpersonal relatedness • Family relationships (attachment, approval, loving) • Teachers opinion and approval • Social acceptance by peer (classmates and friends) • Physical attractiveness

  5. Changes in self-esteem by sex Baldwin and Hoffmann, 2002

  6. Women/girls Collectivist Ensembled Connected Men/boys Individualist Independent Autonomous Gender differences in self-schemas Do women and men have different self-concept? Do women and men (girls and boys) have different origins of self-esteem?

  7. Sources of self-esteem • Family relationships (approval, loving) • Teachers opinion and approval • Physical attractiveness • Social acceptance by peer Do the sources have higher impact on girls’ self-esteem?

  8. Method • Sample: Hungarian national sample of Health-Behaviour in School-aged Children study 2001/02 (age: 13-17, N=4539, male: 45%). • Rosenberg Self-esteem Scale (Cronbach-alpha=0.83) • Gender and grade differences (t test and (M)ANOVA • Step-wise linear regression with dummy variables

  9. Gender differences in 7-11 grade students **p<0.01

  10. Two-way variance analyses Significant main effects and significant interaction (explained variance 4,3%)

  11. Body Image Index Family variables: Care, Overprotection, Communication Monitoring Communication with friends (talking about bothering things) Classmates Teachers FAS Self-esteem Model Predictors Dependent variable

  12. Body image (betai) Body image_indicator (betai1) Model with indicators for girls (an example)

  13. Body Image Index Body Image Index_D FamilyOverprotection Family Overprotection_D Family Communication Family Communication_D Communication with friends Communication with friends _D Classmates Classmates_D FAS FAS_D Self-esteem Model Predictors Dependent variable

  14. Results /7th grade students Family overprotection for boys: -0.19 Family overprotection for girls (-0,19+ -0,07): -0.26

  15. Results /9th grade students Family overprotection and FAS have impact on self-esteem only among girls

  16. Results /11th grade students Scale of classmates has impact on self-esteem only among girls Family overprotection for boys: -0,41 Family overprotection for girls: (-0.41+0.21): -0.20

  17. Discussion I. • Body Image is as strong predictor among girls as among boys. Results do not support the hypothetical difference. • Communication with family member seems to be one of the most robust predictors independently of sex and age (grade)

  18. Discussion II.Gender differences • The most robust result suggests that family overprotection has higher negative impact among girls in 7th and 9th grade, but in 11th grade its negative impact is higher among boys. • Overprotection means physical and psychological restriction • autonomy restriction (?) • Lack of social skills (?)

  19. Discussion III.Gender differences • Influence of classmates’acceptance has higher only among 11th grade girls

  20. Future direction • To develop factors including parental monitoring and attachment (care) as well. • To include teachers’ scale and school items as well • To compare value of betas for the same predictors in different grade (age) groups • To develop path analyses

  21. Thank you!

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