Positive versus negative mental health in emerging adulthood: a national cross-sectional survey

The dual continuum model suggests that positive mental health not only implies the absence of mental illness, but also constitutes an entity of its own. Measures that encompass both positive and negative mental health in young adults are rare. Thus, we assessed whether dimensions corresponding to positive and negative mental health could be identified in a sample of young individuals. Additionally, we explored how such dimensions were associated with potential health-related factors.

We obtained data from the Swedish National Public Health Survey 2004-2009 (23,394 women, 18,274 men, aged 16-29 years). We used exploratory factor analysis (EFA) to identify relevant factors revealed by the 12-item General Health Questionnaire (GHQ-12) and confirmatory factor analysis (CFA) to verify the factor structure. We tested the significance of the difference between effects of potential health-related factors on positive mental health (PMH) and negative mental health (NMH).

The EFA for the GHQ-12 revealed a two factor model with negative items that had high positive loadings on one factor and lower negative loadings on the other factor. The positive items had loading trends that were opposite those of the negative items. The fit of this model was supported by the CFA, which yielded a significantly better match than a unidimensional model. When we investigated the associations between GHQ-scores and potential predictors of health, we found that most potential predictors had significant and opposing effects on both PMH and NMH; with the strongest effects from suicidal ideation and perceived humiliation.

Our results could be seen to indicate that positive and negative mental health are distinct and complementary constructs. Still, the results of our factor analysis may specifically reflect the wording of the items. We conclude that the GHQ-12 is an appropriate tool for its original purpose, to detect "psychiatric morbidity". More refined measures, including predictors of health, are needed to assess PMH and validate the bidimensionality hypothesis.