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Social well- being

GROUP 2 Dorota, Olga, Diana, Luis, Nikolas. Social well- being. Introduction. Our model aims at assessing social well-being Social well being was defined as: Having fulfilling and satisfactory relationships with others in society. Introduction. Our initial domains were:

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Social well- being

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  1. GROUP 2 Dorota, Olga, Diana, Luis, Nikolas Social well-being

  2. Introduction • Our model aims at assessing social well-being • Social well being was defined as: Having fulfilling and satisfactory relationships with others in society

  3. Introduction Our initial domains were: • Family & Friends • Community • Services • Work environment • Following some essential adaptations, our model has been transformed to its ultimate format…

  4. Formative indicators • Family & Friends • Social activities (SCLACT) • Living with a partner (LVGPTNA) • Enjoyable time spent with family (FMLENJ) • Community • Respect from other people (TRTRSP) • Help from others in local area (PPLAHLP) • Recognition received (RCNDSRV) • Closeness with people in your local area (FLCLPLA) • Discrimiation (DSCRGRP)

  5. Model specification REFLECTIVE FORMATIVE

  6. Model specification • In our model, social well-being is assessed through a formative model (followed by a reflective part) • Family & Friends – Community are the Formative components of our model • Services and work environment were left out due to data unavailability  impact on model‘s explanatory power • Social well-being is reflected on Happiness and Satisfaction with life (reflective part)

  7. Family & Friendsweights • Weights for: all countries except Austria • Errors were assumed to be 0 • Standardised weights CFI 0,999 >0,95 TLI 0,996 > 0,95 RMSEA 0,018 <0,050 SRMR 0,004< 0,050 • Highestimpact on Family & friendsisbyenjoyable time spentwiththem • Rational finding ! (-0,345) • Those not livingwith a partnerareexpectedtohave a negative influence

  8. Community weights • Weights for: all countries except Austria • Standardised weights • Errors were assumed to be zero (measurement error was estimated for Discrimination) CFI 0,999 >0,95 TLI 0,996 > 0,95 RMSEA 0,017 < 0,050 SRMR 0,003 < 0,050

  9. Social well-beingoverallweights • Weights for: all countries except Austria • Standardised weights • Correlation effects CFI 0,996 >0,95 TLI 0,973 > 0,95 RMSEA 0,032 <0,050 SRMR 0,007<0,050

  10. Adjusted model specification • Social well-being is reflected in another latent variable: General Satisfaction There is no impact on our model results through this alternative specification !

  11. Adjusted model specification

  12. Composite scoresandtheirquality • All formative indicators were standardised and then using factor loadings the composite scores were computed • Quality (formative) Quality = 1 - [var(error)/var(CS)] • Quality (reflective) Quality = cor(Latent CS, ObservedCS) = = Sum (Factor Loading x weight) / SD (ObservedCS)

  13. Composite scores • Family & Friends CSFAM=Zsclact x 0.515 - Zlvgptna x 0.345 + Zfmlenj x 0.728 • Community CSCOM=Ztrtrsp x 0.395 + Zpplahlp x 0.228 + Zrcndsrv x 0.607 + Zflclpla x 0.132 + Zdscrgrp x 0.192 • Social well-being CSSOCWEL = ZCSFAM x 0,267 + ZCSCOM x 0,316 • General satisfaction CSGENSATSF = ZHAPPY x 0,5 + ZLFSATSF x 0,5 Weights estimated through Solver (SD  min w1 + w2 = 1)

  14. Quality of Family & Friends • Quality obtained through SQP Now we can calculate error variance for CSFAM Var(error) = (0,515)2 x 0,3 + (-0,345) 2*0,4 + (0,728) 2*0,4 = 0,339 SD(CSFAM) = 1,065 Quality (CSFAM) = 1 – (0,339 / 1,0652) = 0,7

  15. Quality of Community • Quality obtained through SQP Now we can calculate error variance for CSCOM Var(error) = 0,3952 x 0,5 + 0,2282 x 0,4 + 0,6072 x 0,3 + 0,1322 x 0,1 + 0,1922 x 0,333 =0,223 SD(CSCOM) = 0,9885 Quality (CSCOM) = 1 – (0,223 / 0,98852) = 0,771

  16. Quality ofSocial Well-Being • Quality obtained through SQP Now we can calculate error variance for CSSOCWEL Var(error) = (0,267)2 x 0,3 + (0,316)2 x 0,229 = 0,044 Var(CSSOCWEL) = 0,224 Quality (CSSOCWEL) = 1 – (0,044 / 0,224) = 0,803

  17. Quality of General Satsifaction • This corresponds to the reflective component of our model • Quality = cor(Latent CS, ObservedCS) = = Sum (Factor Loading x weight) / SD (ObservedCS) • Quality = (0,825 x 0,5 + 0,835 x 0,5) / 0,92 = 0,902 This SD was calculated in SPSS by CSGENSAT

  18. Conclusions • Our models have a good fit (CFI, RMSEA, RMSR)  Family & Friends / Community / Social Well-Being • Quality of our CSs is satisfactory  Family & Friends / Community / Social Well-Being / General Satisfaction • Useful outcome: CS of Family & Friends (0,7) includes 30% of unexplained variance CS of Community (0,77) includes 23% of unexplained variance CS of Social Well-being (0,803) includes 20% of unexplained variance CS of General Satisfaction (0,902) includes 10% of unexplained variance

  19. Thankyou ! • Q &As time Hope your Social Well-being has increased throughout QMSS2 in Vienna. If not, see you in the next training event !

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