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Related Concept Videos

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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
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Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
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Motivations to learn genomic information are not exceptional: Lessons from behavioral science.

Jennifer M Taber1, Ellen Peters2, William M P Klein3

  • 1Department of Psychological Sciences, Kent State University, Kent, Ohio, USA.

Clinical Genetics
|July 26, 2023
PubMed
Summary

People often seek genome sequencing for personal reasons beyond medical benefit. Understanding these motivations, like cognitive curiosity or social factors, is key for informed decisions about genetic testing.

Keywords:
behavioral scienceclinical utilitydecision makinggenetic testinggenome sequencingmotivationpersonal utilitysocial psychologyutility theory

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Area of Science:

  • Behavioral Science
  • Genomics
  • Medical Ethics

Background:

  • Genome sequencing decisions are typically voluntary.
  • Individuals pursue genomic information irrespective of its immediate clinical utility.
  • Motivations for seeking genetic information are diverse, encompassing cognitive, affective, and social factors.

Purpose of the Study:

  • To review behavioral science principles influencing genome sequencing engagement.
  • To identify and elucidate motivations for undergoing genome sequencing, particularly when clinical utility is low or absent.
  • To provide a framework for understanding personal and clinical utility in genetic testing decisions.

Main Methods:

  • Literature review of behavioral science research.
  • Analysis of motivations driving engagement with genome sequencing.
  • Categorization of motivations based on perceived information value (clinical and personal utility).

Main Results:

  • Identified 10 distinct motivations underlying decisions for genome sequencing.
  • Highlighted that motivations are comparable to seeking other personal health information.
  • Emphasized the role of perceived clinical and personal utility in driving decisions.

Conclusions:

  • Recognizing diverse motivations is crucial for facilitating informed decision-making in genomics.
  • Understanding non-clinical drivers enhances patient counseling and engagement with genetic testing.
  • Future research should explore these motivations to support the increasing availability of genome sequencing.