I conducted a simple mediation analysis using process macro in SPSS. Both indirect and direct effects are significant and negative. The total effect is also significant and negative. (X- Academic procrastination, Y- Perceived Academic Performance, and M or mediator- Academic Anxiety)
Total effect of X on Y = -0.411
Direct effect of X on Y = -0.341
Indirect effect of X on Y = -0.06 (weak but significant).
How do I interpret the same to make theoretical sense?
To interpret the results, I would look at all the direct effects (path/regression slope coefficients) first, including X --> M and M --> Y. I would assume that the direct effect X (procrastination) --> M (anxiety) should be positive (the higher the level of procrastination, the higher the anxiety level). I would further assume that the path M (anxiety) --> Y (academic performance) is negative (the higher the anxiety, the lower the performance). This would explain the negative indirect effect (since the indirect effect is equal to the product of the two direct effects X --> M and M --> Y).
The negative direct effect X --> Y appears to make sense (the higher the level of procrastination, the lower the performance).
Hi,
to add a thought. Doesn't it make more sense that anxiety causes procrastination? In addition both could form a feedback loop in which case, your model would not be able to identify both or a single effect. Don't you have any instrumental variables to strengthen the model? A simple partial mediation model is not a strong support for the mediation process.
Best,
Holger
It is a credible point. But in this study, I have considered only these three variables.
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