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Resignation Syndrome: Catatonia? Culture-Bound?

Karl Sallin1, Hugo Lagercrantz2, Kathinka Evers3

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Resignation syndrome (RS) is a disorder in traumatized, migrating youth, characterized by severe withdrawal and unresponsiveness. A new neurobiological model suggests negative expectations may cause this condition, requiring diagnostic re-evaluation.

Keywords:
apathycatatoniaculture-bound syndromhopelessnessmigrationpervasive refusalpredictive codingpsychogenic

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Area of Science:

  • Psychiatry
  • Neuroscience
  • Global Health

Background:

  • Resignation syndrome (RS) affects traumatized children during migration, presenting as severe withdrawal and unresponsiveness.
  • Hundreds of cases in Sweden led to its recognition as a distinct diagnosis, yet the prevailing stress hypothesis is insufficient.
  • Existing literature suggests similar conditions, indicating RS is not novel but its scale and distribution are notable.

Purpose of the Study:

  • To re-evaluate the diagnostics and treatment of resignation syndrome.
  • To propose an alternative hypothesis for the etiology and endemic distribution of RS.
  • To develop a neurobiological model for RS based on predictive coding principles.

Main Methods:

  • Literature review of RS and related disorders.
  • Analysis of epidemiological data regarding RS distribution.
  • Application of predictive coding models to understand RS psychogenesis.

Main Results:

  • Psychogenic catatonia is proposed as a better fit for RS clinical presentation.
  • Culture-bound factors and expectations are suggested to influence symptom expression and endemic distribution.
  • A neurobiological model posits that overwhelming negative expectations down-regulate behavioral systems in vulnerable individuals.

Conclusions:

  • RS diagnosis and treatment require re-evaluation beyond the current stress hypothesis.
  • Psychogenic catatonia and culture-bound psychogenesis offer plausible explanations for RS.
  • A neurobiological model integrating predictive coding and negative expectations provides a novel framework for understanding RS.