Training competencies in dysmorphology: learning needs for professionals involved in clinical genetics

Introduction: Recent advances in molecular genetics and the use of artificial intelligence require professionals whose work is related to clinical genetics to have a basic knowledge of dysmorphology. It is therefore necessary to design a teaching strategy to improve their professional performance. Objective: To identify learning needs in dysmorphology for professions related to clinical genetics.Methods: A descriptive cross-sectional observational study was conducted on a non-probabilistic accidental sample of 80 professionals who attended the face-to-face conference “Dysmorphology: current challenges” and who were willing to respond to an anonymous printed questionnaire. Descriptive statistical methods were used to process the data. Results: The average age of those who responded to the questionnaire was 46.83, the majority were female (92.5%), predominantly doctors (48.75%), with an average of 23 years of professional experience. Fifty-one point twenty-five percent were in teaching positions and fifty-two point five percent were scientists. Most attendees were satisfied with the conference, and the majority of proposals for postgraduate activities to be carried out during the course (sixty-three point three percent) included the use of technology for diagnosis (one hundred percent) and the use of nomenclature in dysmorphology (ninety-five point five percent). Conclusion: The handling of nomenclature in semiology and the application of technology for diagnosis were identified as learning needs.

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Journal
South Health and Policy
Published
2025-06-20
DOI
https://doi.org/10.56294/shp2025166
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
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article

Training competencies in dysmorphology: learning needs for professionals involved in clinical genetics

Roberto Lardoeyt Ferrer, Rosaralis Arrieta García, Miladys Orraca Castillo, Damarys García Gómez et al.
South Health and Policy
Genomics and Rare Diseases
article

Training competencies in dysmorphology: learning needs for professionals involved in clinical genetics

Roberto Lardoeyt Ferrer, Rosaralis Arrieta García, Miladys Orraca Castillo, Damarys García Gómez, Estela Morales Peralta, Daniel Quintana Hernández
article en

Abstract

Introduction: Recent advances in molecular genetics and the use of artificial intelligence require professionals whose work is related to clinical genetics to have a basic knowledge of dysmorphology. It is therefore necessary to design a teaching strategy to improve their professional performance. Objective: To identify learning needs in dysmorphology for professions related to clinical genetics.Methods: A descriptive cross-sectional observational study was conducted on a non-probabilistic accidental sample of 80 professionals who attended the face-to-face conference “Dysmorphology: current challenges” and who were willing to respond to an anonymous printed questionnaire. Descriptive statistical methods were used to process the data. Results: The average age of those who responded to the questionnaire was 46.83, the majority were female (92.5%), predominantly doctors (48.75%), with an average of 23 years of professional experience. Fifty-one point twenty-five percent were in teaching positions and fifty-two point five percent were scientists. Most attendees were satisfied with the conference, and the majority of proposals for postgraduate activities to be carried out during the course (sixty-three point three percent) included the use of technology for diagnosis (one hundred percent) and the use of nomenclature in dysmorphology (ninety-five point five percent). Conclusion: The handling of nomenclature in semiology and the application of technology for diagnosis were identified as learning needs.

South Health and PolicyVol. 4
Centro de Genética Clínica (PT), Centro de Ingeniería Genética y Biotecnología (CU), Escola Superior de Ciências da Saúde (BR), Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CU), University of Camagüey (CU)
Openalex Percentile: Top 82%
Genomics and Rare Diseases
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