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Related Experiment Videos

Interventions for treating disruptive behavior in demented elderly people

C K Beck1, V M Shue

  • 1College of Medicine, University of Arkansas for Medical Sciences, Little Rock.

The Nursing Clinics of North America
|March 1, 1994
PubMed
Summary

Understanding disruptive behaviors requires conceptual frameworks. Research is exploring psychological theories and biological factors to develop a unified understanding and effective interventions for these behaviors.

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Area of Science:

  • Behavioral Science
  • Psychology
  • Gerontology

Background:

  • Disruptive behaviors require explanation and reduction strategies.
  • Current research lacks consistent conceptual frameworks for understanding disruptive behaviors.
  • Interventions often lack clear theoretical underpinnings.

Purpose of the Study:

  • To highlight the need for conceptual frameworks in studying disruptive behaviors.
  • To emphasize the necessity of a multicausal approach, integrating psychosocial and biological factors.
  • To advocate for the evaluation of interventions for cost-effectiveness and quality of life impact.

Main Methods:

  • Review of existing research and theoretical frameworks (e.g., reactance theory, Piagetian concepts, resistance).
  • Identification of ongoing studies examining biological factors (e.g., artificial lighting, exercise).

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  • Discussion of the need for evaluating intervention systems.
  • Main Results:

    • Existing research utilizes diverse conceptual frameworks, leading to inconsistency.
    • Emerging research incorporates biological and psychosocial factors into explanations.
    • The need for cost-effectiveness and quality of life evaluations for interventions is recognized.

    Conclusions:

    • Conceptual frameworks are essential for advancing the study of disruptive behaviors.
    • A comprehensive understanding requires integrating biological and psychosocial perspectives.
    • Future research should focus on developing and evaluating evidence-based interventions within robust conceptual models.