Overall there were no statistical differences in life satisfaction between Spanish and English adolescents (means of 7.15 and 6.99 respectively) (t = 2.533, p > 0.01, Cohen's d 0.09)
Table shows the frequency distributions of all independent variables of interest for Spain and England. No statistical differences in the patterns of distribution between the 2 countries were found for gender, sense of family belonging (SSB), school autonomy and control (SAC), school social support (SSS) or peer social support (PSS). Differences were observed however, for family autonomy and control (FAC), family social support (FSS) and sense of belonging both at school (SSB) and in the neighbourhood (NSB). The largest differences were found for FAC (X2 = 194.044, p = < 0.001, V = 0.244) and FAS (X2 = 287.48, p = < 0.001, V = 0.282. For example, for FAC the distribution in England ranged from 69% to 3% compared to 46% and 10% for Spanish counterparts. Spanish respondents were much more likely to report that they lived in a family with low affluence (27.9%) compared with 6.6% in England).
Differences were also observed for FSS (,X2 = 37.324. p = < 0.001, V = 0.108) SSB and NSB (X2 = 130.558, p = < 0.001, 0056 = 0.0.190; X2 = 93.212, p = < 0.001, V = 0.168 respectively). In this regard Spanish respondents were more likely to report consistently higher levels across these attributes.
Tables 3 summarises the associations found between individual candidate assets and life satisfaction in each of the countries and all relationships were found to be significant. However, the magnitude of difference between countries was most marked for FAC (in the case of England, the effect size is much greater -Cohen's d = 1.34 than in Spain -Cohen's d = 0.82), which had a greater impact on life satisfaction in England. Mean values of life satisfaction in England range from 7.38 (high FAC) to 5.12 (low FAC) compared to the 7.51 (high FAC) to 6.23 (low FAC) in Spain.
Gender was significantly related to life satisfaction in both countries but family affluence only in England.
General Linear Modelling (GLM)
Table shows the results of the GLM and highlights that taken together the candidate assets included in the model explained 20% and 19% of the variance in life satisfaction in Spain and England respectively. For the purposes of this analysis candidate assets with partial eta squared estimates > 0.01 were considered to be important influences on life satisfaction.
Observing the models produced for both countries, 3 measures of social capital and 2 measures of social support were found to be important. However, the relative importance of these factors within each country differed. In Spain, FSS and SSB explained the largest amount of variance (F = 20.43 p < .0.001; partial η2 = .031 and F = 18.33 p < .0.001; partial η2 = .028 respectively). FAC and SSS explained less of the variance (1% each) but were still significant in the model. In England, whilst similar social capital and social support factors were shown to be important, a somewhat different configuration was observed. In this case, the candidate asset displaying the largest proportion of variance was FAC (F = 19.32, p < .0.001; partial η2 = .027) followed by FSS and SSB (each explaining 3%) and then SSB (1%). Family affluence (FAS) was also highlighted as significant in England.
The decision trees (Figures and ) show how each of the independent variables interact to predict life satisfaction. All independent variables found to be significantly related to life satisfaction during bivariate analysis in the respective countries were included in this part of the analysis.
Each tree generated 3 levels, a different constellation of factors was observed for each country. In England, the optimum configuration of factors consisted of FAC (p = < 0.000, F = 36.272), SSB (p = < 0.000, F 29.442) and FSS (p = < 0.000, F 21.043). High levels of these potential assets reinforced the possibilities for improved life satisfaction from a base mean of 7.08 to 7.9. In contrast in Spain the maximum mean value of life satisfaction was achieved with high levels of FSS (p = < 0.000, F 61.329), SSS (p = < 0.000, F 30.466) and NSB (p = < 0.000, F 11.174), rising from 7.17 to 8.20.
Figures and also illustrate how decision trees can help to highlight assets that might be important when others at higher node levels are absent. For example, in Spain even those with medium levels of FSS (mean life satisfaction lower than mean for node 0), but have higher levels of school sense of belonging (SSS) can see observed improvements in life satisfaction.