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Why we only remember the good parts of vacations and forget the bad?

Wed 26 Feb 2025
Published 1 year ago.
Updated 2 weeks ago.
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Why we only remember the good parts of vacations and forget the bad?

Ever look back on a vacation and think it was all perfect sunshine and smooth sailing? That’s Rosy Retrospection at work! It’s a cognitive bias—a common mental pitfall that can impede critical thinking and decision-making.

To make sense of a complicated world, our brains simplify things. We tend to focus on the highlights, like breathtaking views or delicious meals, and forget the minor annoyances—lost luggage, sunburn, or long lines. This is also partly due to how memories are stored: positive emotions are linked to stronger memories, making happy moments more likely to stick.

This phenomenon applies to relationships as well, such as “the one that got away.” Often, we reminisce about these relationships by focusing only on the peak moments, forgetting the reasons why they ended, which can color our memories more positively than reality. Just remember, real life isn’t all sunshine and rainbows.

However, Rosy Retrospection isn’t always bad. Reminiscing for fun and enjoyment can leave you with a positive outlook and enjoyable memories. Just be mindful of this bias when planning to repeat an experience, whether it’s a relationship, job, or idealizing “the good old days.”

Rosy retrospection is a cognitive bias. Mastering it and making it a conscious part of your thinking abilities only requires awareness. Cognitive biases are one of the Four Mind Traps covered in the TST Framework.

— map / TST —

Deep-Dive Article: 4 Mind Traps: Fallacies, Biases, Heuristics, and Stereotypes
Michael Alan Prestwood
Author & Natural Philosopher
Prestwood writes on science-first philosophy, with particular attention to the convergence of disciplines. Drawing on his TST Framework, his work emphasizes rational inquiry grounded in empirical observation while engaging questions at the edges of established knowledge. With TouchstoneTruth positioned as a living touchstone, this work aims to contribute reliable, evolving analysis in an emerging AI era where the credibility of information is increasingly contested.
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