A Causal Relationship Model for Depression in Several Age Groups

Abstract

               Depression disorder is still a major global mental health problems. One way to reduce the number of patients with depression disorder is a prevention of the onset of depression in individuals which is an early symptom of depression disorder. Preventing or treating existing depression requires knowing the causal factors of depression to which be used for planning to address depression problems. Nowadays, a structural equation modelling is an advanced analytical statistic that is suitable for studying causal factors. The knowledges presented in this article is a synthesis of a causal relationship model for depression using a structural equation model. The structural model was synthesized by the analysis of causal factors for depression from theoretical explanation and research confirmation. The measurement models of latent variables were synthesized from the analysis of their definitions and measurements. The synthesized causal relationship model for depression consisted of 10 causal latent variables including cognitive   distortions, dysfunctional attitudes, negative automatic thoughts, negative life events, stress, self-esteems, positive effects, adversity quotients, family relationships, and social supports. These factors have positive and negative direct effects to depression and indirect effects as well. The measurement model of these factors consisted of a total of 23 observed variables. The latent depression variable was measured with four observed variables. The synthesized causal relationship model for depression is a conceptual model which can be used as a research conceptual framework.