Table 5.
Direct and bootstrapped indirect effects in the mediational models.
| Main outcomea and mediatorsb (R2)c, and direct effects | Indirect effects | |||||||||
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Pathd | Coefficiente | P valuef | Path | Coefficientg | 95% CIh | ||||
| Composite (0.57) | ||||||||||
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Positive affect (0.16) | a × b | –0.15 | –0.28 to –0.03 | ||||||
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ai | 0.76 | .001 |
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bj | –0.19 | .03 |
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c′k | –0.57 | .001 |
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cl | –0.42 | .01 |
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| Composite (0.55) | ||||||||||
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Negative affect (0.15) | a × b | –0.14 | –0.28 to –0.02 | ||||||
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a | –0.60 | .007 |
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b | 0.22 | .007 |
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c′ | –0.56 | .001 |
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c | –0.42 | .009 |
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| Composite (0.58) | ||||||||||
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Openness to the future (0.12) | a × b | –0.06 | –0.18 to 0.01 | ||||||
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a | –0.15 | .07 |
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b | 0.37 | .10 |
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c′ | –0.54 | .001 |
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c | –0.48 | .003 |
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aThe dependent variable (main outcome) is the composite score at 3-month follow-up.
bThe potential mediators, highlighted in italics (positive affect, negative affect, and openness to the future), were based on pre-post change scores.
cR2: variance explained by regression models.
dPath coefficients are (standardized) ordinary least squares–based regression coefficients.
eCoefficient: (standardized) slope.
fP value related to t test.
gThe product of “ab” is the bootstrapped indirect effect using 10,000 samples.
hIt is the 95% CI of the bootstrapped indirect effect using 10,000 samples.
ia: the direct path between the independent variable and the mediator.
jb: the direct path between the mediator and the outcome.
kc′: total effects.
lc: direct effect of the independent variable on the dependent variable after adjustment for mediating effects.