– A public health approach for promoting mental health has become a major health policy agenda of many governments. Despite this worldwide attention on research addressing population mental health and general wellbeing, very little is heard on positive mental health from the low-and middle-income countries. This paper aims to present an attempt to develop a model of positive mental health among young people. This could be used for integrating the concept of positive mental health (PMH) into public health interventions.
– The study was conducted in the state of Kerala, India. The paper administered the “Achutha Menon Centre Positive Mental health Scale” to a sample of 453 (230 men and 223 women) in the age group 18-24, along with an interview schedule exploring the relationship of PMH with many explanatory variables such as sex, beliefs, religion, education, employment and social capital. The paper developed an input path model through a series of multiple regressions explaining the levels of PMH in the community, which was then tested statistically (using AMOS version 7.0). The input model was created by identifying the determinants and correlates of PMH based on their predictive power on the outcome variable, the PMH score. The input diagram was used to test the model fit of the data.
– The path model (Figure 1) clearly specified the determinants of PMH. Among them, the variables that have a direct determinant effect on PMH are: quality of home learning environment, employment status, education status, marital status, self-perception on possession of skills, happiness with life, membership in social organizations and socializing capability.
– In this study, path model is used to confirm relationships among observed and latent variables. The path diagram assesses the comparative strength of the correlations between the variables and does not test the directionality. Or, the model itself cannot prove causation.
– Determinants of PMH those are amenable to interventions as well as those which help in recognizing characteristic groups for intervention could help to plan future intervention programs.
– Original paper based on primary data collected through a cross-sectional survey.
