Elena Sophia Doll, Seraina Petra Lerch, Katja Maria Schmalenberger, Karla Alex, Stefan Kölker, Heiko Brennenstuhl, Stacey Pereira, Hadley Smith, Eva C Winkler, Julia Mahal, Beate Ditzen
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引用次数: 0
Abstract
Purpose: This systematic review aims to identify factors that influence parents' decisions regarding pediatric diagnostic and predictive genetic testing (DT/PT). Factors are integrated into a conceptual model of decision-making. Implications for genetic counseling, research, and ethics are derived.
Methods: PubMed, PsychInfo, WebofScience and references of related reviews were searched for original publications between 2000 and 2023. Extracted factors were categorized into an existing model.
Results: Of 5843 publications, 56 met inclusion criteria. The included studies differentiate between DT, traditional, and expanded PT and describe factors impacting parental decisions on both to have the child genetically tested and to be informed about additional findings. Factors included: 1. benefits/hopes, 2. worries/concerns, 3. values and beliefs, 4. individual circumstances, and 5. emotional states.
Conclusion: Our work extends an existing empirical decision model of family decisions about genome sequencing to genetic testing in pediatrics in general, adding the categories "individual circumstances" and "emotional states". The factors can be further integrated into the Health Belief Model; the importance of emotional states is reflected in dual-process theories, such as Fuzzy Trace Theory. Research is required on emotional states, differences between DT and PT, parents' decisions about result disclosure, and dyadic variables as decision-making predictors.
期刊介绍:
Genetics in Medicine (GIM) is the official journal of the American College of Medical Genetics and Genomics. The journal''s mission is to enhance the knowledge, understanding, and practice of medical genetics and genomics through publications in clinical and laboratory genetics and genomics, including ethical, legal, and social issues as well as public health.
GIM encourages research that combats racism, includes diverse populations and is written by authors from diverse and underrepresented backgrounds.