Related Experiment Video
Updated: Aug 30, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Clinimetric Properties of the Integrated Self-Screening Instrument for Geriatric Health Testing (INSIGHT) to Identify
Chia-Ming Chang1,2,3,4, Ya-Li Wang3,4, Ching-Ju Chiu3,4
1Department of Geriatrics and Gerontology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Abstract:
Administration of comprehensive geriatric assessment is time-consuming and labor intensive. A new instrument, the Integrated Self-Screening Instrument for Geriatric Health Testing (INSIGHT), was developed to quickly identify common geriatric problems. The present study evaluated the clinimetric properties of the INSIGHT. Content Validity Index (CVI) was measured via expert review. Older adults (≥65 years) attending geriatric outpatient visits for the first time (N=224) completed the INSIGHT. Internal consistency was calculated using McDonald's ω, greatest lower bound, and Cronbach's α. Factor structure was evaluated using parallel analysis and exploratory factor analysis (EFA) based on domain scores. After two rounds of expert review, scale-level CVI/universal agreement was 0.95, and all scale-level CVIs/average were 1.00. Using the INSIGHT, 15.2% of the 224 participants had no potential health problems identified, while 14.3% had one, and over 70% had ≥ two. Internal consistency was good (> 0.8), and EFA confirmed unidimensionality with all domain factor loadings >0.3. The INSIGHT demonstrates good content validity, internal consistency, and unidimensional structure, supporting its reliability for rapid geriatric health screening.
