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Spatial autoregressive models in psychology studies require impact decomposition. Ignoring spatial spillovers can alter or reverse findings on narcissism and health behaviors, cautioning against direct effect interpretations.

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Area of Science:

  • Psychology
  • Spatial Econometrics
  • Public Health

Background:

  • Spatial autoregressive (SAR) models are common in psychological research.
  • Researchers often fail to decompose effects into direct, indirect, and total impacts.
  • This omission is a standard practice in spatial econometrics.

Purpose of the Study:

  • To demonstrate the necessity of impact decomposition in SAR models for psychological studies.
  • To re-analyze the U.S. Dark-Triad and health dataset using robust methods.
  • To reveal how spatial spillovers influence psychological and health-related findings.

Main Methods:

  • Applied heteroskedasticity-robust spatial autoregressive (SAR) models.
  • Conducted full impact decomposition analysis.
  • Re-analyzed the U.S. Dark-Triad and health dataset (Gruda et al., 2024).

Main Results:

  • The direct protective effect of narcissism on hypertension mortality vanished after accounting for spatial spillovers.
  • Associations between narcissism and lower cancer prevalence/depression strengthened.
  • Several health behavior findings reversed direction, indicating conflated within- and between-state effects.
  • Machiavellianism and psychopathy associations also shifted significantly.

Conclusions:

  • Spatial spillovers can substantially alter, dilute, or reverse local effect estimates in psychological studies.
  • Naïve regression analyses may confound within- and between-state effects.
  • Policy implications derived solely from direct effect estimates in spatial models can be misleading.