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Classification issues and challenges in child and adolescent psychopathology
1Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK. camilla.azis@kcl.ac.uk
This review examines advances in child and adolescent psychopathology classification over 50 years, focusing on Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD) differences. Recommendations for ICD-11 are provided.
Area of Science:
- Child and adolescent psychology
- Psychopathology
- Medical classification systems
Background:
- Over the last 50 years, significant advancements have occurred in understanding child and adolescent psychopathology.
- Classification systems are crucial for diagnosis, treatment, and research in this field.
Purpose of the Study:
- To review major advances in child and adolescent psychopathology classification.
- To analyze conceptual issues and differences between the Diagnostic and Statistical Manual of Mental Disorders (DSM) and the International Classification of Diseases (ICD).
- To propose specific recommendations for changes in the International Classification of Diseases, 11th Revision (ICD-11).
Main Methods:
- Literature review of major advances in psychopathology classification over the past half-century.
- Comparative analysis of conceptual issues and differences in the DSM and ICD classification systems.
- Development of specific recommendations for ICD-11 based on the review and analysis.
Main Results:
- Key advances impacting classification in child and adolescent psychopathology were identified.
- Significant conceptual differences and issues between DSM and ICD were highlighted.
- Specific, evidence-based recommendations for ICD-11 revisions were formulated.
Conclusions:
- The evolution of classification systems is critical for advancing the field of child and adolescent psychopathology.
- Addressing conceptual differences between DSM and ICD is essential for global consistency.
- The proposed ICD-11 recommendations aim to improve diagnostic accuracy and clinical utility.
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