Table 3a.
Meta-Analyzed Semi-Partial Correlations Between Predictors and Depressed Mood
| Effect | k | N | r sp | 95% CI around rsp | t-statistic | τ2 | 95% CI around τ2 | Q | I 2 |
|---|---|---|---|---|---|---|---|---|---|
| Fixed Effects | |||||||||
| Pre-Test | 5 | 1950 | .56*** | [.53, .59] | 27.85 | ||||
| Gratitude (vs. Rumination) | 5 | 1950 | −.06* | [−.10, −.01] | −2.47 | ||||
| Distraction (vs. Rumination) | 5 | 1950 | −.08*** | [−.12, −.03] | −3.36 | ||||
| Depression (Centered) | 5 | 1950 | .07** | [.02, .11] | 2.90 | ||||
| Gratitude (vs. Rumination) × Depression | 5 | 1950 | −.04† | [−.08, .01] | −1.70 | ||||
| Distraction (vs. Rumination) × Depression | 5 | 1950 | −.05* | [−.10, −.01] | −2.28 | ||||
| Gratitude (vs. Distraction) | 5 | 1950 | .02 | [−.02, .07] | 0.90 | ||||
| Gratitude (vs. Distraction) × Depression | 5 | 1950 | .01 | [−.03, .05] | 0.56 | ||||
| Random Effects | |||||||||
| Pre-Test | 5 | 1950 | .56*** | [.48, .63] | 16.69 | 0.004 | [0.00, 0.06] | 10.69* | 62.60 |
| Gratitude (vs. Rumination) | 5 | 1950 | −.06* | [−.09, −.02] | −4.33 | 0.00 | [0.00, 0.004] | 1.30 | 0.00 |
| Distraction (vs. Rumination) | 5 | 1950 | −.08* | [−.13, −.02] | −3.84 | 0.00 | [0.00, 0.02] | 3.06 | 0.00 |
| Depression (Centered) | 5 | 1950 | .07** | [.03, .11] | 4.64 | 0.00 | [0.00, 0.01] | 1.56 | 0.00 |
| Gratitude (vs. Rumination) × Depression | 5 | 1950 | −.04 | [−.09, .02] | −1.94 | 0.00 | [0.00, 0.01] | 3.08 | 0.00 |
| Distraction (vs. Rumination) × Depression | 5 | 1950 | −.05* | [−.10, −.001] | −2.85 | 0.00 | [0.00, 0.01] | 2.57 | 0.00 |
| Gratitude (vs. Distraction) | 5 | 1950 | .02 | [−.01, .06] | 1.64 | 0.00 | [0.00, 0.004] | 1.21 | 0.00 |
| Gratitude (vs. Distraction) × Depression | 5 | 1950 | .01† | [−.002, .02] | 2.38 | 0.00 | [0.00, 0.00] | 0.22 | 0.00 |
Note. See Note under Table 2 for regression coding scheme. Per recommendations by Aloe and Becker (2012) we calculated semi-partial correlations for each predictor in each study and then calculated the fixed and random effects across the five studies by predictor using metacor within the meta package (inverse variance weighting is used for pooling; version 5.2–0; Schwarzer, 2022; Schwarzer et al., 2015) in R, version 4.1.3 (2022–03-10). In the random effects models, we used the restricted maximum likelihood estimator to calculate τ2 (Veroniki et al., 2016; Viechtbauer, 2005), the Q-profile method to calculate confidence intervals around τ2, and also applied a Knapp-Hartung adjustment (Knapp & Hartung, 2003). Indices of between-study heterogeneity (confidence intervals around τ2, Q [Cochran, 1954; Hoaglin, 2016], and I2 [Higgins & Thompson, 2002]) demonstrated minimal between-study variability on our predicted effects, so we did not move forward to explore our anticipated moderator (online vs. student sample). We consulted Harrer et al. (2021) for guidance in employing these meta-analytic procedures.
p < .10
p < .05
p < .01
p < .001