TABLE 2.
Associations of overall suffering (Wave 2) with subsequent anxiety symptoms, depression symptoms, and facets of well‐being assessed 1 month later (Wave 3)
| Overall suffering | ||
|---|---|---|
| Outcome | β [95% CI] | E‐values a [EE b , LCI c ] |
| Psychological distress | ||
| Anxiety symptoms | 0.22 [0.12, 0.32]*** | [1.74, 1.48] |
| Depression symptoms | 0.25 [0.16, 0.35]*** | [1.83, 1.57] |
| Well‐being | ||
| Life satisfaction | −0.21 [−0.30, −0.12]*** | [1.71, 1.47] |
| Happiness | −0.26 [−0.35, −0.17]*** | [1.84, 1.61] |
| Physical health | −0.13 [−0.23, −0.03]* | [1.50, 1.22] |
| Mental health | −0.19 [−0.28, −0.11]*** | [1.67, 1.44] |
| Meaning in life | −0.14 [−0.22, −0.05]*** | [1.52, 1.27] |
| Sense of purpose | −0.14 [−0.23, −0.05]*** | [1.53, 1.28] |
| Promote good | −0.10 [−0.20, −0.01]* | [1.43, 1.08] |
| Delayed gratification | −0.10 [−0.20, −0.01]* | [1.42, 1.08] |
| Content with relationships | −0.09 [−0.17, 0.00] | [1.38, 1.00] |
| Satisfying relationships | −0.07 [−0.16, 0.01] | [1.34, 1.00] |
Note: n = 594 for all analyses. In separate models, ordinary least squares regressions were used to regress each outcome on overall suffering. Regression models estimate the mean change (β) in the standardized scores of each outcome with the change in overall suffering. Overall suffering and each outcome were continuous and standardized (M = 0, SD = 1). All models adjusted for prior values of age, gender, ethnic status, marital status, educational attainment, religious status, dimensions of religious orientation (i.e., intrinsic, extrinsic, and quest), frequency of religious service attendance, financial and material stability assessed in Wave 1, prior values of overall suffering assessed in Wave 1, and prior values of all outcomes (i.e., anxiety symptoms, depression symptoms, and each facet of well‐being) assessed in Wave 1.
Abbreviations: β, standardized effect size; CI, confidence interval; EE, E‐value for the effect estimate; LCI, E‐value for the limit of the confidence interval.
The formula for calculating E‐values can be found in VanderWeele and Ding (2017).
E‐values for effect estimates are the minimum strength of association that an unmeasured confounder would need to have with both the exposure and the outcome variable to fully explain away the observed effect, after accounting for the measured covariates.
E‐values for the limit of the 95% CI closest to the null denote the minimum strength of association that an unmeasured confounder would need to have with both the exposure and the outcome variable to shift the confidence interval to include the null value, after accounting for the measured covariates.
*p < 0.05 before Bonferroni correction, ***p < 0.05 after Bonferroni correction (the p‐value cutoff for Bonferroni correction was 0.05/12 = 0.004 for each outcome).