Abstract

The dual-factor approach to mental health was employed to explore levels and interrelations of protective factors associated with resilience in a dataset of 30,841 schoolchildren aged 11-14 in England. ANOVA was used to contrast levels of protective factors between groups (combinations of higher/lower psychopathology and higher/lower wellbeing) and network analysis to explore protective factor interrelations. Levels of protective factors tended to be highest for those who had higher wellbeing and lower psychopathology (termed 'complete mental health'). Those with lower levels of protective factors were split between two subpopulations: having lower wellbeing and higher psychopathology (termed 'troubled'), and having lower wellbeing and lower psychopathology (termed 'vulnerable'). Analysis of the protective factor networks revealed that the four subpopulations of the model were distinguished by both their overall structure and individual node connectivity (the 'complete mental health' subpopulation demonstrated the greatest connectivity), though two were similar: those with higher wellbeing and higher psychopathology (termed 'symptomatic but content') and lower wellbeing and higher psychopathology ('troubled'). The results indicate that while 'vulnerable' and 'symptomatic but content' may be hard to discriminate conceptually, the former may reflect a lower capacity to cope during periods of adversity (i.e., show resilience). Overall, the results encourage a holistic approach to mental health screening, particularly as children with lower wellbeing had lower levels of the protective factors, regardless of their level of psychopathology. Moreover, interventions to improve protective factors associated with positive development in stressed environments may therefore have a greater impact on improving wellbeing than decreasing symptoms of psychopathology.

Full Text
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