The Influence of Negative Automatic Thoughts and Sleep Dysfunction on Depression Severity

Abstract

This study aimed to examine the predictive influence of negative automatic thoughts and sleep dysfunction on depression severity in a Brazilian adult population. A correlational descriptive design was employed involving 430 adult participants from Brazil, selected based on the Morgan and Krejcie sample size determination table. Participants completed the Beck Depression Inventory-II (BDI-II) for depression severity, the Automatic Thoughts Questionnaire (ATQ) for negative automatic thoughts, and the Pittsburgh Sleep Quality Index (PSQI) for sleep dysfunction. All instruments used were standardized, with confirmed validity and reliability in previous studies. Data were analyzed using IBM SPSS-27. Pearson correlation was used to assess bivariate relationships between variables, and multiple linear regression was performed to evaluate the joint predictive power of negative automatic thoughts and sleep dysfunction on depression severity. Pearson correlation analysis revealed a strong positive correlation between depression severity and negative automatic thoughts (r = .71, p < .01), and a moderate correlation with sleep dysfunction (r = .58, p < .01). Multiple regression analysis indicated that both predictors significantly contributed to the model (F(2, 427) = 262.41, p < .01), explaining 55% of the variance in depression scores (R² = .55). Negative automatic thoughts (β = .61, p < .01) had a stronger predictive effect than sleep dysfunction (β = .28, p < .01). The findings demonstrate that both negative automatic thoughts and sleep dysfunction are significant and independent predictors of depression severity, with cognitive distortions exerting a particularly strong influence. These results highlight the need for integrated interventions that simultaneously target maladaptive thought patterns and sleep disturbances to effectively mitigate depressive symptoms.