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Arch Dermatol Res ; 313(4): 235-243, 2021 May.
Article in English | MEDLINE | ID: mdl-32596742

ABSTRACT

Differentiating between benign and malignant skin lesions can be very difficult and should only be done by sufficiently trained and skilled clinicians. To our knowledge there are no validated tests for reliable assessments of clinicians' ability to perform skin cancer diagnostics. To develop and gather validity evidence for a test in skin cancer diagnostics, a multiple-choice questionnaire (MCQ) was developed based on informal interviews with seven content experts from five skin cancer centers in Denmark. Validity evidence for the test was gathered from May until July 2019 using Messick's validity framework (content, response process, internal structure, relationship to other variables and consequences). Item content was revised through a Delphi-like review process and then piloted on 36 medical students and 136 doctors using a standardized response process. Results enabled an analysis of the internal structure and relationship to other variables of the test. Finally, the contrasting groups method was used to investigate the test's consequences (pass-fail standard). The initial 90-item MCQ was reduced to 40 items during the Delphi-like review process. Item analysis revealed that 25 of the 40 selected items were level I-III quality items with a high internal consistency (Cronbach's α = 0.83) and highly significant (P ≤ 0.0001) differences in test scores between participants with different occupations or levels of experience. A pass-fail standard of 12 (48%) correct answers was established using the contrasting groups' method. The skin cancer diagnostics MCQ developed in this study can be used for reliable assessments of clinicians' competencies.


Subject(s)
Clinical Competence/statistics & numerical data , Skin Neoplasms/diagnosis , Surveys and Questionnaires , Dermatologists/statistics & numerical data , Diagnosis, Differential , General Practitioners/statistics & numerical data , Humans , Reproducibility of Results , Skin/diagnostic imaging , Students, Medical/statistics & numerical data , Surgeons/statistics & numerical data
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