Development of a subjective cognitive decline questionnaire using item response theory: A pilot study. Issue 4 (5th October 2015)

• Record Type: Journal Article
• Authors: Gifford, Katherine A.; Liu, Dandan; Romano, Raymond R.; Jones, Richard N.; Jefferson, Angela L.
• Is Part Of: Alzheimer's & dementia. Volume 1:Issue 4(2015)
• Page Start: 429
• Page End: 439
• Publication Date: 2015-10-05
• Subjects: Subjective cognitive decline -- Item response theory -- Factor analysis -- Computerized adaptive testing -- Psychometrics -- Mild cognitive impairment; Alzheimer's disease -- Periodicals; Alzheimer's disease -- Diagnosis -- Periodicals; Dementia -- Periodicals; Dementia -- Diagnosis -- Periodicals; 616.831
• DOI: 10.1016/j.dadm.2015.09.004
• Languages: English
• ISSNs: 2352-8729

Abstract

Abstract: Introduction: Subjective cognitive decline (SCD) may indicate unhealthy cognitive changes, but no standardized SCD measurement exists. This pilot study aimed to identify reliable SCD questions. Methods: A total of 112 cognitively normal (NC; 76 ± 8 years; 63% female), 43 mild cognitive impairment (MCI; 77 ± 7 years; 51% female), and 33 diagnostically ambiguous participants (79 ± 9 years; 58% female) were recruited from a research registry and completed 57 self‐report SCD questions. Psychometric methods were used for item reduction. Results: Factor analytic models assessed unidimensionality of the latent trait (SCD); 19 items were removed with extreme response distribution or trait‐fit. Item response theory (IRT) provided information about question utility; 17 items with low information were dropped. Post hoc simulation using computerized adaptive test (CAT) modeling selected the most commonly used items (n = 9 of 21 items) that represented the latent trait well ( r = 0.94) and differentiated NC from MCI participants ( F [1, 146] = 8.9, P = .003). Discussion: IRT and CAT modeling identified nine reliable SCD items. This pilot study is a first step toward refining SCD assessment in older adults. Replication of these findings and validation with Alzheimer's disease biomarkers will be an important next step for the creation of a SCD screener.