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Are people happier when their personality matches their region?

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Swiss adults whose pattern of Big Five traits resembled their canton's typical profile reported higher wellbeing, but other ways of measuring 'fit' gave null or even opposite results.

Source

Regional Cultures and the Psychological Geography of Switzerland: Person-Environment-Fit in Personality Predicts Subjective Wellbeing

Götz FM, Ebert T, Rentfrow PJ · Frontiers in psychology · 2018

doi.org/10.3389/fpsyg.2018.00517Read the full paper ↗20 citationscc by

Study at a glance

Design
Cohort — Secondary analysis of Swiss Household Panel waves 11-17 (2009-2015): Big Five measured once, canton-level personality profiles aggregated, and three-level models (years within persons within cantons) predicting annual wellbeing from person-canton fit.
N
N=7767 · 7,767 adult panel members with Big Five data were used for mapping; multilevel models used a 2012 base year and excluded six cantons with fewer than 50 respondents, so model Ns are somewhat smaller (reported in tables not included in the text).
Population
Nationally representative adult residents of Switzerland (mean age 46.8) in the Swiss Household Panel.
Outcome
Life satisfaction, satisfaction with personal relationships, positive affect and negative affect (single 0-10 items), predicted by shape, elevation and scatter fit indices.

Structured fields used in claim comparison tables when every cited study has a complete layer.

What they did

Using the Swiss Household Panel, the researchers averaged the Big Five personality scores of residents in each canton to build regional personality profiles and mapped them. They then computed how well each adult's own profile fitted their canton's in three ways: shape (correlation between profiles), elevation (difference in average level) and scatter (difference in variability). Multilevel models tested whether these fit indices predicted life satisfaction, relationship satisfaction, positive affect and negative affect across yearly panel waves.

What they found

Personality varied by region, with a clear split for extraversion and neuroticism: French- and Italian-speaking cantons were higher in neuroticism and lower in extraversion than the German-speaking east. Shape similarity consistently predicted higher life satisfaction, relationship satisfaction and positive affect and lower negative affect, and this survived robustness checks. Elevation mostly had no effect, and scatter predicted better wellbeing, the opposite of what fit theory predicts. Only a tiny share of the variance in wellbeing (at most 1.97%) sat at the canton level.

The limits

What it doesn't show

The data are correlational, so fit cannot be shown to cause wellbeing; people may also choose where to live. Personality was measured only once with a 10-item scale whose inter-item correlations were low (as low as 0.08 for agreeableness), and wellbeing was measured with single items. Cantons may be too coarse to capture people's actual local culture, residential moves were not modelled, and the authors' 'complementary fit' explanation for the scatter result is post hoc and preliminary.

Key terms

Person-environment fit
The idea that people fare better when their characteristics match those of their surroundings, such as their region's typical personality.
Geographical psychology
The study of how psychological traits are distributed across places and how that relates to regional outcomes.
Profile shape similarity
The correlation between a person's pattern of traits and a comparison profile, ignoring overall level.
Multilevel modelling
A regression approach for nested data, here yearly observations within people within cantons.
Complementary fit
The idea that differing from one's environment can be beneficial by filling a gap, as opposed to fit through similarity (supplementary fit).

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Quiz yourself

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Which fit index most consistently predicted higher wellbeing?

Common questions

Did every measure of fit predict wellbeing?

No. Only shape similarity predicted wellbeing in the expected direction; elevation was mostly null and scatter went the opposite way.

Why remove neuroticism in one robustness check?

Low neuroticism is both desirable and typical, so fit scores could just reflect being emotionally stable; removing it tests whether fit adds anything beyond that.

How much does the canton itself matter for wellbeing?

Very little directly: at most 1.97% of the variance in any wellbeing outcome lay between cantons; most was between or within individuals.

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