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An algorithm for defining somatization in children.

Inna Postilnik1, Howard D Eisman, Rebecca Price

  • 1New York Institute for Cognitive and Behavioral Therapies, New York, NY, USA.

Journal of the Canadian Academy of Child and Adolescent Psychiatry = Journal De L'Academie Canadienne De Psychiatrie De L'Enfant Et De L'Adolescent
|April 9, 2008
PubMed
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This study proposes a new algorithm to classify children with somatic symptoms into three groups: sick, somatizers, and well. This approach aids in differentiating pediatric patients in primary care settings.

Area of Science:

  • Pediatric Psychology
  • Child Psychiatry
  • Medical Diagnosis

Background:

  • Pediatric somatization diagnosis is challenging, as existing criteria may be insufficient.
  • Current approaches include questionnaire models and medical diagnosis models.
  • Existing models have limitations in accurately identifying somatization in children.

Purpose of the Study:

  • To review and synthesize existing literature on child somatization classification.
  • To develop an improved method for understanding and classifying pediatric somatization.
  • To propose a novel algorithm for classifying children with somatic symptoms.

Main Methods:

  • Literature review of PubMed, PsycINFO, and CINAHL (1994-2005).
  • Focus on children aged 6-12 years.
Keywords:
algorithmschild psychiatrychild psychologyclassificationdiagnostic techniques and procedurespediatricssomatoform disorders

Related Experiment Videos

  • Incorporation of an integrative approach using multiple data sources.

    • Main Results:

    • An integrative approach to defining child somatization was developed.
    • A step-by-step algorithm was proposed to classify children into three groups: sick, somatizers, and well.
    • The algorithm integrates data from self-report questionnaires, physician questionnaires, and medical charts.

    Conclusions:

    • The proposed algorithm offers a method for differentiating pediatric patients in primary care.
    • This approach categorizes children with somatic symptoms into distinct groups.
    • Further empirical validation is required to confirm the algorithm's clinical utility.