High Levels of Anxiety as Determinants of Stress in University Students: A Cross-Sectional Study Conducted at a Brazilian University
Description
Objective: The study aimed to verify the correlation between anxiety and stress levels in undergraduate students at a Brazilian university. Method: A cross-sectional observational study with a quantitative approach was conducted. The sample consisted of 688 undergraduate students from a Brazilian public university. The instruments used for data collection were the Beck Anxiety Inventory (BAI) to measure anxiety levels and the Lipp Stress Symptom Inventory (LSSI) to assess stress levels. Statistical analyses included non-parametric tests, such as Pearson's Chi-square, Fisher's exact test, and the Mann-Whitney U test, as well as Spearman's correlation. Results: Younger participants, females, those without a partner, and those with lower income levels showed higher levels of anxiety. We found a strong correlation between anxiety and stress. Students with higher levels of anxiety also had higher scores in all stages of stress, particularly in the resistance and exhaustion stages. Physical and psychological stress symptoms were also more intense among those with higher anxiety. Conclusion: There was a significant correlation between anxiety and stress in university students, with important implications for the mental health of this population.
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A sociodemographic questionnaire was used, targeting university students with questions related to aspects such as age group, gender, sexual orientation, skin color, marital status, whether they lived with others, education level, employment status, and income (calculated in minimum wages). This questionnaire was developed by the researchers themselves, and the studied aspects were transformed into categorical variables for sample characterization. The Beck Anxiety Inventory was used to measure the participants' anxiety levels. It consists of Likert scale questions addressing the intensity of somatic symptoms related to anxiety, such as tremors, palpitations, and fears, among others. The final score classifies the individual into levels of anxiety: "Minimal" (0-7 points), "Mild" (8-15 points), "Moderate" (16-25 points), or "Severe" (26-63 points) . For this research's analyses, we created a re-categorized variable as "Minimal/Mild" and "Moderate/Severe," used to divide the sample into both groups for comparison. We also used the scalar variable of the total score to include correlation analysis. The Lipp Stress Symptom Inventory (LSSI) was used to measure stress levels. It covers variables related to physical and psychological symptoms experienced by participants in the last 24 hours or the last week. For each symptom marked, the participant accumulates 1 point. A total of 53 symptoms are listed, including tachycardia, appetite changes, insomnia, sudden enthusiasm, memory problems, nausea, and diarrhea. The sum of this score assesses the individual in three stages: "alarm stage," "resistance stage," and "exhaustion stage" . For our study, we used as categorical variables the classification of individuals into each of the three stages, as well as the scalar variables of their individual and total scores. All instruments were translated and validated into Portuguese, the native language of the study participants. The collected data were tabulated in spreadsheets using Microsoft® Excel version 2016 and analyzed using the Statistical Package for the Social Sciences, version 20.0. The data were organized and presented in tables. The Kolmogorov-Smirnov normality test was conducted, identifying the non-normal distribution of the variables of interest in the sample. Therefore, non-parametric tests were performed, including Pearson's Chi-square and Fisher's exact test for the analysis of associations between categorical variables, and the Mann-Whitney U test for scalar variables. Scalar data were represented as percentiles (25, 50, and 75), as well as their respective means and Standard Deviations (SD). To verify the correlation between anxiety (BAI) and stress (LSSI), we used Spearman's Rho (r) test, adopting the following parameters to measure its strength: r < 0.29 (weak); 0.29 ≤ r ≤ 0.49 (moderate); r > 0.50 (strong). For all analyses, a 95% confidence interval was considered, and the level of significance was determined when the p-value < 0.05.