247 The Professional Counselor | Volume 13, Issue 3 individuals’ employment responses of “prefer not to answer” vs. “not employed (including students)” were not associated with depression category (p = .156) or anxiety category (p = .317). These results were interpreted as indicating that the ways in which individuals in the two time periods differed demographically did not have significant impact on the study’s dependent variables of interest. Therefore, binary logistic regressions were conducted with only time period as a predictor of each dependent variable. Relationship Between Time Period and Severity of Depression Symptoms Most individuals in the study were in the minimal depression range on the PHQ-9 as compared to the other four categories. Figure 1 shows the percentage of individuals falling into each of the five PHQ-9 categories during each of the two time periods. Figure 1 Percentages of Individuals Falling Into Each of the PHQ-9 Categories for Each of the Two Time Periods Across both time periods combined (August–September 2021 and January–February 2022), 51 individuals (34.23%) were mild or above in depression while 98 (65.77%) were in the minimal range. Binary logistic regression was used to test whether time period predicted severity of depression symptoms. Time period was entered as a predictor (1 = August–September 2021, 0 = January–February 2022) of depression (1 = mild or above, 0 = minimal depression). The overall binary logistic regression model was found to be statistically significant, χ2(1) = 14.46, p < .001, Cox & Snell R2 = .092, Nagelkerke R2 = .128. In the model, time period was found to be a significant predictor of depression, Wald χ2(1) = 12.17, B = 1.52, SE = .44, p < .001. The model estimated that the odds of being mild or above in
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