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Adolescent Wellbeing and Connectedness to School, Family, Peers, and Community over Time

Adolescent Wellbeing and Connectedness to School, Family, Peers, and Community over Time. Paul E. Jose & Jan Pryor Victoria University of Wellington, Roy McKenzie Centre for the Study of Families SASP Conference Wellington, NZ March 29, 2008. Thank you.

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Adolescent Wellbeing and Connectedness to School, Family, Peers, and Community over Time

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  1. Adolescent Wellbeing and Connectedness to School, Family, Peers, and Community over Time Paul E. Jose & Jan Pryor Victoria University of Wellington, Roy McKenzie Centre for the Study of Families SASP Conference Wellington, NZ March 29, 2008

  2. Thank you • To the FRST Foundation for their financial support • To the YCP research team: Bill Siddells, Jo Kleeb, Carla Crespo, our Maori Research group, and all of the research staff • To the respondents, their families, their schools, and their principals

  3. Rationale for the study • Western society has tended to emphasise the “individuation” of its adolescents, i.e., their development of self and separation from their family of origin. Is healthy development during adolescence simply a case of e separation? • We are interested in striking a more balanced note: we believe that this individuation occurs within a matrix of connections: • Family • Peer group • School • Community

  4. Development over time • Probably the strength of these connections vary over time (and possibly by age, gender, and ethnicity) • We expect that over time, connectedness will go down for: • Family • School • And we would expect that general adjustment would go down as well: • Wellbeing (a combination of 4 related constructs) • And we expect that over time, connectedness will go up for: • Peers • Community -------------------------------------------------------------- • What is the association between connectedness and wellbeing over time?

  5. Basic hypothesis Connectedness Wellbeing If one were to assess these two general constructs at one point in time, one would probably find that they were positively associated, but we would not know which one caused the other or if they exist in a bidirectional relationship (shown on next slide.

  6. A bidirectional relationship? Time 1 Time 2 Connectedness Connectedness Wellbeing Wellbeing

  7. Measures Connectedness: • Family connectedness: family cohesion subscale of the FACES scale, 5 items (a = .88) • School connectedness: 5 items (a = .80) • Peer connectedness: 3 items (a = .78) • Community connectedness: 4 items (a = .70) Wellbeing: • Life satisfaction : 3 items measuring (a = .71) • Positive affect: 3 items measuring (a = .69) • Confidence: 4 items measuring (a = .79) • Aspirations: 4 items measuring (a = .74)

  8. Characteristics of the sample • About 1,400 adolescents gave us complete data at both time points • About equal numbers of males and females • Focused on ENZ (935) and Maori (460) respondents, i.e., left out Pacific and Other • About equal numbers of three cohorts (10-11, 12-13, and 14-15 year-olds)

  9. Procedure • Administered a large survey (over 250 questions) via laptop to the adolescents in their schools • Period of time between T1 and T2 was about one year (we are collecting T3 now) • Obtained data from parents and principals as well. Also, an in-depth qualitative study by NZCER. Much more to come . . .

  10. Mean group differences over time? • Yes, a repeated measures MANOVA indicated that the following measures went DOWN over one year: • Family connectedness • Peer connectedness (against prediction) • School connectedness • Well-being • One measure did not change: • Community connectedness (against prediction) ------------------------------------------------------------ • Now let’s consider the question of whether WB and Conn affect each other through time.

  11. The model R2 1 Family Family Connect- ness T1 Connect- ness T2 Friends 2 Friends 4 School School Comm. Comm. 3 Aspir. Aspir. Wellbeing T1 Wellbeing T2 Confid. Confid. PosAff PosAff Life sat Life sat

  12. A good fitting model • Chi-square = 339.6, df = 91, p < .001, ratio = 3.73 • RMR = .017; GFI = .98; AGFI = .96; NFI = .97 • RMSEA = .041, Critical N = 607

  13. The answers R2 Family Family .59 .63 .47 .47 Connect- ness T1 Connect- ness T2 Friends .74*** Friends .55 .74 .69 School School .43 .34 Comm. Comm. .21*** .69 Aspir. Aspir. .64 Wellbeing T1 Wellbeing T2 .47*** .78 .82 Confid. Confid. .43 .50 .47 .76 PosAff PosAff .75 Life sat Life sat WB1 => Conn2 beta = .01, p = .89

  14. Important points • All indicators load well on their respective constructs (community lowest for connectedness) • Stabilities of WB and Conn are reasonable, although Conn is more stable. Still, it is probably somewhat modifiable. • Most important: Wellbeing T1 does NOT predict Connectedness T2, i.e., doesn’t seem to be reciprocal (at this level), but Conn T1 does predict WB T2. Confirms our basic hypothesis. • Amount of variance explained in the two outcomes are reasonable: not too high, not too low.

  15. Conclusions • It seems that wellbeing as well as most aspects of connectedness diminish over one year (separation?). Third year of data will give us a clearer sense of change over time. • But it also seems that a general sense of connectedness is predictive of an improved sense of wellbeing one year later. • Those youth who are well connected report greater levels of aspiration, confidence, life satisfaction, and positive affect one year later. • Implication? Social policy should be devoted to enhancing connections in youth of this age • Wellbeing T1 did not predict Conn T2! Reminds me of efforts in the U.S. of trying to boost grades by improving self-esteem. It matters where and how we design interventions.

  16. Future directions • If we examine specific aspects of connectedness, will we find the same patterns? • I think that we’ll see a fairly complicated picture: • evidence of WB1 predicting SchlConn2; • also aspects of connectedness affect each other over time (e.g., FamConn1 predicts SchlConn2) • Do connectedness and wellbeing predict outcomes that we care about: school performance, delinquency, weight control, sleep, involvement with cultural activities, ethnic identity, and so forth? • We may find that some separation is healthy against a backdrop of general connectedness. What about individuals who increase in connectedness? • Differences by age, gender, ethnicity, socio-economic status? Thus far: biggest differences by age.

  17. Thank you for listening • Check out our web-site: http://www.vuw.ac.nz/youthconnectedness/ • Write to myself: paul.jose@vuw.ac.nz • Or Jan Pryor: jan.pryor@vuw.ac.nz ----------------------------------------------------------- Does anyone have a few dollars to continue this project?

  18. Stability coefficients over one year .54*** Family Conn 1 Family Conn 2 strongest .33*** Peer Conn 1 Peer Conn 2 weakest .42*** School Conn 1 School Conn 2 .48*** Comm. Conn 1 Comm. Conn 2 .40*** Well- Being 1 Well- Being 2

  19. Cross-lag coefficients over one year R2 Family Conn 1 Family Conn 2 .40 Peer Conn 1 Peer Conn 2 .18 School Conn 1 School Conn 2 .33 Comm. Conn 1 Comm. Conn 2 .27 Well- Being 1 Well- Being 2 .29 Bold: b > .10; light: b > .05

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