Revista Colombiana de psiquiatria · 2024
Exploring risk factors for depression: a network analysis.
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Baños-Chaparro Jonatan
Аннотация
INTRODUCTION: Depression is a frequent psychological problem in the general population. There are no single conclusive causes for its development; on the contrary, it arises from the interaction of other emotional disorders. Determining risk factors is a primary objective to identify vulnerable individuals and optimize prevention.
OBJECTIVE: To analyze risk factors of the depression through network analysis in Peruvian adults from the general population.
METHODS: Cross-sectional study with a quantitative approach. A total of 567 Peruvian adults who answered several instruments assessing depressive symptoms, insomnia, suicidal ideation and anxiety participated. An undirected network model with all psychological variables and a predictive path diagram was estimated to identify risk factors for depression. Measures of centrality, precision and stability were also analyzed.
RESULTS: The network structure showed that depression, insomnia, suicidal ideation, and anxiety were mutually associated. In terms of expected influence and predictability, depression obtained the highest value, followed by anxiety. In the prediction plot, all psychological variables were directly connected with depression, with anxiety having the highest connection. The tests of accuracy and stability (CS = 0,75), were robust.
CONCLUSIONS: The results of the study suggest that problems with insomnia, suicidal ideation, and anxiety, are considerable risk factors for depression. Identifying and intervening early on those risk factors in adults in the general population could help to prevent the development of depressive symptoms.
OBJECTIVE: To analyze risk factors of the depression through network analysis in Peruvian adults from the general population.
METHODS: Cross-sectional study with a quantitative approach. A total of 567 Peruvian adults who answered several instruments assessing depressive symptoms, insomnia, suicidal ideation and anxiety participated. An undirected network model with all psychological variables and a predictive path diagram was estimated to identify risk factors for depression. Measures of centrality, precision and stability were also analyzed.
RESULTS: The network structure showed that depression, insomnia, suicidal ideation, and anxiety were mutually associated. In terms of expected influence and predictability, depression obtained the highest value, followed by anxiety. In the prediction plot, all psychological variables were directly connected with depression, with anxiety having the highest connection. The tests of accuracy and stability (CS = 0,75), were robust.
CONCLUSIONS: The results of the study suggest that problems with insomnia, suicidal ideation, and anxiety, are considerable risk factors for depression. Identifying and intervening early on those risk factors in adults in the general population could help to prevent the development of depressive symptoms.