Comparative analysis of five diagnostic tools in detecting mild cognitive impairment in older adults

Abstract

Background: Mild Cognitive Impairment is a critical condition in older adults requiring accurate diagnostic tools for early detection. This study evaluates diagnostic accuracy of five cognitive assessment tools for detecting MCI among older women. Methods: A cross-sectional psychometric study was conducted with 293 women aged ≥ 60 from Women Day Care Centers in Iran. Participants were assessed using the Montreal Cognitive Assessment at two time points, the London Tower Test, the Wisconsin Card Sorting Test, and the Wechsler Memory Scale-Third Edition. Statistical analyses included binomial proportion tests, Bayesian analysis, chi-square tests, and Bland–Altman analysis to assess diagnostic performance, agreement, and reliability. Sensitivity, specificity, and accuracy were calculated using R and JAMOVI softwares. Results: The WCST demonstrated the highest specificity (0.850) and strong evidence for detecting cognitive impairments (BF₁₀ = 5.24E + 13, p < 0.001). The WMS-III showed the highest sensitivity (0.700) and accuracy (0.625). MoCA scores improved slightly from T1 (mean = 23.03) to T2 (mean = 24.56), but its reliability varied. The LTT provided moderate evidence for detecting impairments (p = 0.026, BF₁₀ = 0.9778). Socioeconomic status and education significantly influenced cognitive performance, with 46.8% diagnosed with MCI. Agreement between human diagnosis and tool-based assessments was significant (p < 0.001), particularly for WCST and WMS-III. Conclusion: The WCST and WMS-III are the most reliable tools for detecting MCI, excelling in specificity and sensitivity, respectively. Combining multiple tests enhances diagnostic accuracy. Future research should explore larger populations and integrate advanced methods like neuroimaging.