Personality x Situation Interactions: A Cautionary Note

Abstract: No robust and reliable interaction effects of the Big Five personality traits and unemployment on life-satisfaction in the German Socio-Economic Panel.

With the exception of late Walter Mischel, Lee Ross, and Dick Nisbett, we are all interactionists (ok, maybe Costa & Mcrae are guilty of dispositionism). As Lewin told every body in 1934, behaviour is a function of the person and the situation, and the a priori probability that the interaction effect between the two is zero (the nil-hypothesis is false) is pretty much zero. So, our journals should be filled with examples of personality x situation interactions. Right? But they are not. Every once in a while when I try to update my lecture notes and look for good examples of a personality x situation interaction I can’t find good examples. One reason is of course the long history of studying situations and traits separately. However, experience sampling studies emerged in the 1980s and the data are ideally suited to look for interaction effects. Another problem is that interaction effects can be difficult to demonstrate because you need large samples to get significant results.

This time I had a solution to my problems. I have access to the German Socio-Economic Panel (SOEP) data. The SOEP has a large sample (N > 10,000), measured the Big Five four times over a 12-year period and many measures of situations like marriage, child birth, or unemployment. So, I could just run an analysis and find a personality x situation interaction. After all, in large samples, you always get p < .05. Right? If you think so, you might be interested to read on and find out what happened.

The Big Five were measure the first time in 2005 (wave v). I picked unemployment and neuroticism as predictors because it is well-known that neuroticism is a personality predictor of life-satisfaction and unemployment is a situational predictor of life-satisfaction. It also made sense that neurotic people might respond more strongly to a negative life-event. However, contrary to these expectations, the interaction was far from significant (p = .5), while the main effects of unemployment (-1.5) and neuroticism (-.5) were highly significant. The effect of unemployment is equivalent to a change by three standard deviations in neuroticism.

Undeterred, I looked for interactions with the other Big Five dimensions. Surely, I would find an explanation for the interaction when I found one. To make things simple, I added all five interactions to the model and, hooray, a significant interaction with conscientiousness popped up, p = .02.

Was I the first to discover this? I quickly checked for articles and of course somebody else had beat me to the punch. There it was. In 2010, Boyce, Wood, and Brown had used the SOEP data to show that conscientious people respond more strongly to the loss of a job.

Five years later, a follow-up article came to the same conclusion.

A bit skeptical of p-values that are just below .02, I examined whether the interaction effect can be replicated. I ran the same analysis as I did with the 2005 data in 2009.

The effect size was cut in half and the p-value was no longer significant, p = .25. However, the results did replicate that none of the other four Big Five dimensions moderated the effect of unemployment.

So, what about the 2013 wave? Again not significant, although the effect size is again negative.

And what happened in 2017? A significant effect, hooray again, but this time the effect is positive.

Maybe the analyses are just not powerful enough. To increase power, we can include prior life-satisfaction as a predictor variable to control for some of the stable trait variance in life-satisfaction judgments. We are now only trying to predict changes in life-satisfaction in response to unemployment. In addition, we can include prior unemployment to make sure that the effect of unemployment is not due to some stable third variable.

We see that it is current unemployment that has a negative effect on life-satisfaction. Prior unemployment actually has a positive effect, suggesting some adaptation to long-term unemployment. Most important, the interaction between conscientiousness and current unemployment is not significant, p = .68.

The interaction was also non-significant in 2013, p = .69.

And there was no significant interaction in 2017, p = .38.

I am sure that I am not the first to look at this, especially given two published articles that reported a significant interaction. However, I suspect that nobody thought about sharing these results because the norm in psychology is still to report significant results. However, the key finding here appears to be that the Big Five traits do not systematically interact with a situation in explaining an important outcome.

So, I am still looking for a good demonstration of a personality x situation interaction that I can use for my lecture in the fall. Meanwhile, I know better than to use the published studies as an example.

2 thoughts on “Personality x Situation Interactions: A Cautionary Note

  1. Hi! I am a big fan of your webpage. I have two thoughts for you: The first is how unemployment was coded. Is it a binary variable or does it contain information on the duration of unemployment? Being unemployed for a week or for over one year has definitely a different impact on well-being. If there is information on the duration of unemployment, Heckman models could help in the search for interactions.

    My second though is the usual profile of unemployed people. Is there a typical profile of the unemployed, perhaps there are several? If specific profiles are more prone to be unemployed, the interaction could easily disappear, because unemployment already contains the extra information provided by the personality dimension.

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    1. It was coded, currently unemployed.
      There is a strong effect of unemployment, so this is not the problem.
      I also think there are moderates, but they don’t seem to be captured by the Big Five items.
      I agree that these analyses are not conclusive, but a strong effect should pop out in these analyses.

      Like

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