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Updated: Feb 26, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Adaptation and validation into Portuguese language of the six-item cognitive impairment test (6CIT)
João Luís Alves Apóstolo1, Diana Dos Santos Paiva2, Rosa Carla Gomes da Silva3
1a Health Sciences Research Unit: Nursing (UICISA: E) , Nursing School of Coimbra , Coimbra , Portugal.
Background:
The six-item cognitive impairment test (6CIT) is a brief cognitive screening tool that can be administered to older people in 2-3 min.
Objective:
To adapt the 6CIT for the European Portuguese and determine its psychometric properties based on a sample recruited from several contexts (nursing homes; universities for older people; day centres; primary health care units).
Method:
The original 6CIT was translated into Portuguese and the draft Portuguese version (6CIT-P) was back-translated and piloted. The accuracy of the 6CIT-P was assessed by comparison with the Portuguese Mini-Mental State Examination (MMSE). A convenience sample of 550 older people from various geographical locations in the north and centre of the country was used.
Results:
The test-retest reliability coefficient was high (r = 0.95). The 6CIT-P also showed good internal consistency (α = 0.88) and corrected item-total correlations ranged between 0.32 and 0.90. Total 6CIT-P and MMSE scores were strongly correlated. The proposed 6CIT-P threshold for cognitive impairment is ≥10 in the Portuguese population, which gives sensitivity of 82.78% and specificity of 84.84%. The accuracy of 6CIT-P, as measured by area under the ROC curve, was 0.91.
Conclusion:
The 6CIT-P has high reliability and validity and is accurate when used to screen for cognitive impairment.
