Interpreting Mediation results

#1
Hello,

I have a few questions regarding interpretation of my results for Mediation using Hayes' Process macro. The key point for finding significance is to see that the Class Interval does not include zero. However, in my mediation model, although the indirect effect CI doesn't include zero, the initial Models's CI (for bcope_ma, under Duration) includes zero. Should I still count my indirect effects as significant even though initial model for mediation is not significant?

I'm trying to see is duration in a new country effects a person's quality of life which is mediated by their coping ability. Results pasted below. Please Help! Thanks in advance!

Model = 4
Y = qoltot
X = duration
M = bcope_ma

Sample size
70

**************************************************************************
Outcome: bcope_ma

Model Summary
R R-sq F df1 df2 p
.1830 .0335 2.3550 1.0000 68.0000 .1295

Model
coeff se t p LLCI ULCI
constant 22.5169 1.3151 17.1223 .0000 19.8927 25.1411
duration -.0388 .0253 -1.5346 .1295 -.0893 .0117

**************************************************************************
Outcome: qoltot

Model Summary
R R-sq F df1 df2 p
.3234 .1046 3.9140 2.0000 67.0000 .0247

Model
coeff se t p LLCI ULCI
constant 91.2951 9.5536 9.5560 .0000 72.2258 110.3643
bcope_ma -1.0460 .3823 -2.7364 .0079 -1.8091 -.2830
duration .0059 .0811 .0725 .9425 -.1559 .1677

************************** TOTAL EFFECT MODEL ****************************
Outcome: qoltot

Model Summary
R R-sq F df1 df2 p
.0674 .0045 .3102 1.0000 68.0000 .5794

Model
coeff se t p LLCI ULCI
constant 67.7413 4.3387 15.6134 .0000 59.0836 76.3990
duration .0465 .0834 .5570 .5794 -.1200 .2129

***************** TOTAL, DIRECT, AND INDIRECT EFFECTS ********************

Total effect of X on Y
Effect SE t p LLCI ULCI
.0465 .0834 .5570 .5794 -.1200 .2129

Direct effect of X on Y
Effect SE t p LLCI ULCI
.0059 .0811 .0725 .9425 -.1559 .1677

Indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0406 .0311 .0009 .1240

Partially standardized indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0022 .0016 .0000 .0068

Completely standardized indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0589 .0411 .0017 .1650

Ratio of indirect to total effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .8736 149.0933 .1603 53.5001

Ratio of indirect to direct effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma 6.9093 17.9156 3.4423 275.8767

R-squared mediation effect size (R-sq_med)
Effect Boot SE BootLLCI BootULCI
bcope_ma .0045 .0173 -.0184 .0543

Preacher and Kelley (2011) Kappa-squared
Effect Boot SE BootLLCI BootULCI
bcope_ma .0601 .0401 .0066 .1692

Normal theory tests for indirect effect
Effect se Z p
.0406 .0318 1.2753 .2022

******************** ANALYSIS NOTES AND WARNINGS *************************

Number of bootstrap samples for bias corrected bootstrap confidence intervals: 1000

Level of confidence for all confidence intervals in output: 95.00

NOTE: Some cases were deleted due to missing data. The number of such cases was: 33