Daniel_Burfoot comments on Let There Be Light - Less Wrong
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I'm going to second the recommendation of using psychometrics to further your self-awareness.
As the Wikipedia articles discuss, Myers-Briggs doesn't enjoy a great reputation among psychologists. Nevertheless, the INTP profile describes me, and probably a lot of people here, with freaky accuracy.
The Big Five is a great recommendation. It is very well respected in psychology, and I find especially useful for understanding disagreements with others. There is a big difference between how intelligent people who are low and high in openness view the world. Furthermore, differences in Agreeableness are a big source of interpersonal conflict.
I would stay away from this one. Gardner's notion of multiple intelligences has theoretical problems and does not enjoy empirical support.
For something scientifically validated on how people handle relationships, check out the concept of attachment style. Here's a quiz. I'm convinced that a lot of relationship problems are due to differences in attachment style, rather than one person being in the right and the other person being in the wrong.
Other individual differences that are useful for self-awareness, and understanding how others think differently:
Interests in people vs. things. Richard Lippa's research has shown that this dimension of interests is independent of the Big Five. See this section of his book for more on what the dimension is.
High sensitivity
Self-monitoring
Tangential and nit-picky but this claim bothers me, because I'm guessing when you say "scientifically validated" you mean that somebody did a frequentist analysis of a survey with N=245 and showed P<.05. To an LW reader, it may be obvious that there is a vast chasm between this kind of scientific evidence and the kind that justifies the laws of physics, but the distinction might be lost on the less savvy. Perhaps we should introduce a set of words capable of expressing the difference.
"The Cult of Statistical Significance" suggests that we're looking for tests that display power rather than significance.