The Harmonized Cognitive Assessment Protocol (HCAP) describes an assessment battery and a family of population-representative studies measuring neuropsychological performance. We describe the factorial structure of the HCAP battery in the US Health and Retirement Study (HRS).

The HCAP battery was compiled from existing measures by a cross-disciplinary and international panel of researchers. The HCAP battery was used in the 2016 wave of the HRS. We used factor analysis methods to assess and refine a theoretically driven single and multiple domain factor structure for tests included in the HCAP battery among 3,347 participants with evaluable performance data.

For the eight domains of cognitive functioning identified (orientation, memory [immediate, delayed, and recognition], set shifting, attention/speed, language/fluency, and visuospatial), all single factor models fit reasonably well, although four of these domains had either 2 or 3 indicators where fit must be perfect and is not informative. Multidimensional models suggested the eight-domain model was overly complex. A five-domain model (orientation, memory delayed and recognition, executive functioning, language/fluency, visuospatial) was identified as a reasonable model for summarizing performance in this sample (standardized root mean square residual = 0.05, root mean square error of approximation = 0.05, confirmatory fit index = 0.94).

The HCAP battery conforms adequately to a multidimensional structure of neuropsychological performance. The derived measurement models can be used to operationalize notions of neurocognitive impairment, and as a starting point for prioritizing pre-statistical harmonization and evaluating configural invariance in cross-national research.

Vascular cognitive impairment (VCI) post-stroke is frequent but may go undetected, which highlights the need to better screen cognitive functioning following a stroke.

We examined the clinical utility of the Montreal Cognitive Assessment (MoCA) in detecting cognitive impairment against a gold-standard neuropsychological battery.

We assessed cognitive status with a comprehensive battery of neuropsychological tests in 161 individuals who were at least 3-months post-stroke. We used receiver operating characteristic (ROC) curves to identify two cut points for the MoCA to maximize sensitivity and specificity at a minimum 90% threshold. We examined the utility of the Symbol Digit Modalities Test, a processing speed measure, to determine whether this additional metric would improve classification relative to the MoCA total score alone.

Using two cut points, 27% of participants scored ≤ 23 and were classified as high probability of cognitive impairment (sensitivity 92%), and 24% of participants scored ≥ 28 and were classified as low probability of cognitive impairment (specificity 91%). The remaining 48% of participants scored from 24 to 27 and were classified as indeterminate probability of cognitive impairment. The addition of a processing speed measure improved classification for the indeterminate group by correctly identifying 65% of these individuals, for an overall classification accuracy of 79%.

The utility of the MoCA in detecting cognitive impairment post-stroke is improved when using a three-category approach. The addition of a processing speed measure provides a practical and efficient method to increase confidence in the determined outcome while minimally extending the screening routine for VCI.