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43 Comparison of Latent Structures for the Neuropsychiatric Inventory Questionnaire (NPI-Q)
- Nicholas R Amitrano, Maximillian A Obolsky, Zachary J Resch, Jason R Soble, David A Gonzälez
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 723-724
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Objective:
Existing research has demonstrated that neuropsychiatric/behavioral-psychological symptoms of dementia (BPSD) frequently contribute to worse prognosis in patients with neurodegenerative conditions (e.g., increased functional dependence, worse quality of life, greater caregiver burden, faster disease progression). BPSD are most commonly measured via the Neuropsychiatric Inventory (NPI), or its briefer, informant-rated questionnaire (NPI-Q). Despite the NPI-Q’s common use in research and practice, there is disarray in the literature concerning the NPI-Q’s latent structure and reliability, possibly related to differences in methods between studies. Also, hierarchical factor models have not been considered, even though such models are gaining favor in the psychopathology literature. Therefore, we aimed to compare different factor structures from the current literature using confirmatory factor analyses (CFAs) to help determine the best latent model of the NPI-Q.
Participants and Methods:This sample included 20,500 individuals (57% female; 80% White, 12% Black, 8% Hispanic), with a mean age of 71 (SD = 10.41) and 15 average years of education (SD = 3.43). Individuals were included if they had completed an NPI-Q during their first visit at one of 33 Alzheimer Disease Research Centers reporting to the National Alzheimer Coordinating Center (NACC). All CFA and reliability analyses were performed with lavaan and semTools R packages, using a diagonally weighted least squares (DWLS) estimator. Eight single-level models using full or modified versions of the NPI-Q were compared, and the top three were later tested in bifactor form.
Results:CFAs revealed all factor models of the full NPI-Q demonstrated goodness of fit across multiple indices (SRMR = 0.039-0.052, RMSEA = 0.025-0.029, CFI = 0.973-0.983, TLI = 0.9670.977). Modified forms of the NPI-Q also demonstrated goodness of fit across multiple indices (SRMR = 0.025-0.052, RMSEA = 0.0180.031, CFI = 0.976-0.993, TLI = 0.968-0.989). Top factor models later tested in bifactor form all demonstrated consistently stronger goodness of fit regardless of whether they were a full form (SRMR = 0.023-0.035, RMSEA = 0.015-0.02, CFI = 0.992-0.995, TLI = 0.985-0.991) or a modified form (SRMR = 0.023-0.042, RMSEA = 0.015-0.024, CFI = 0.985-0.995, TLI = 0.9770.992). Siafarikas and colleagues’ (2018) 3-factor model demonstrated the best fit among the full-form models, whereas Sayegh and Knight’s (2014) 4-factor model had the best fit among all single-level models, as well as among the bifactor models.
Conclusions:Although all factor models had adequate goodness of fit, the Sayegh & Knight 4-factor model had the strongest fit among both single-level and bifactor models. Furthermore, all bifactor models had consistently stronger fit than single-level models, suggesting that BPSD are best theoretically explained by a hierarchical, non-nested framework of general and specific contributors to symptoms. These findings also inform consistent use of NPI-Q subscales.
42 Cognitive Impairment Stage and Dementia Syndromes Explain Latent Structure Variability on the Neuropsychiatric Inventory Questionnaire (NPI-Q)
- Nicholas R Amitrano, Maximillian A Obolsky, Zachary J Resch, Jason R Soble, David A Gonzälez
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 722-723
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Objective:
Neuropsychiatric/behavioral-psychological symptoms of dementia (BPSD) frequently contribute to worse prognosis of patients with neurodegenerative conditions. BPSD are commonly measured via a brief, informant-rated version of the Neuropsychiatric Inventory (NPI), the NPI-Q. Previously (see our other submission to this conference), we established optimal latent structures by comparing different factor models in the literature using confirmatory factor analyses (CFAs). However, questions remain as to why so many different models were found in the literature. One possibility is sampling differences, including different proportions of individuals across cognitive stages (e.g., mild cognitive impairment, moderate dementia) or syndromes (e.g., Alzheimer’s amnestic syndrome, Dementia with Lewy Bodies). We tested this hypothesis by subjecting candidate models to measurement invariance (MI) analyses stratified by cognitive stage and syndrome.
Participants and Methods:Individuals were included if they had completed an NPI-Q during their first visit at an Alzheimer Disease Research Center reporting to the National Alzheimer Coordinating Center (NACC). This resulted in 20,500 individuals (57% female; 80% White, 13% Black, 8% Hispanic), with a mean age of 71 (SD = 10.41) and 15 average years of education (SD = 3.43). Regarding staging, 75.9% of individuals did not meet criteria for all-cause dementia, whereas 24.1% individuals had all-cause dementia. Regarding syndromes, 35.6% had an Alzheimer’s presentation (“AD-type”) and 5.6% had either a behavioral variant frontotemporal dementia or Lewy-Body dementia presentation (“behavioral-type”). A 3-factor and 4-factor model were subject to MI across these groupings. We conducted MI analyses for equal forms, equal loadings, and equal intercepts using the lavaan R package with a diagonally weighted least squares (DWLS) estimator.
Results:The 3-factor model demonstrated good fit among individuals experiencing (CFI = 0.965, TLI = 0.955) and not experiencing (CFI = 0.984, TLI = 0.979) dementia, as well as among AD-type (CFI = 0.983, TLI = 0.978) presentations, but had borderline poor fit for behavioral-type (CFI = 0.932, TLI = 0.912) presentations. The 4-factor model had better fit among those experiencing (CFI = 0.985, TLI = 0.977) and not experiencing (CFI = 0.995, TLI = 0.992) dementia. Additionally, the 4-factor model demonstrated good of fit for AD-type (CFI = 0.993, TLI = 0.989) and poorer fit for behavioral-type (CFI = 0.949, TLI = 0.922) syndromes. Chi-square differences suggested that equal loading and equal intercept hypotheses should be rejected for both 3- and 4-factor models, for both staging and syndromal groupings. However, relative fit indices suggested that the equal form, equal loading, and equal intercept hypotheses could be adequate for only the 4-factor model.
Conclusions:The variability of factor structures in the BPSD literature appears, at least partially, explained by sampling variability among cognitive stages and dementia syndromes. The best models in the literature appear to have good fit in non-demented individuals and, among those who have dementia, in those with an AD syndrome. Only Sayegh & Knight’s 4-factor model had adequate (albeit, not optimal) fit among those with all-cause dementia and, more specifically, among those with a behavioral-type dementia syndrome. These findings inform BPSD theory and practical implementation of NPI-Q subscales.
74 The Impact of Motoric Dysfunction on Neuropsychological Test Performance Within an Electrical Injury Sample
- Maximillian A Obolsky, Humza Khan, Zachary J Resch, Jessica L Paxton, Jason R Soble, Joseph W Fink, Neil H Pliskin
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 67-68
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Objective:
Victims of electrical injury (EI) often experience injuries to the peripheral nervous system and neuromuscular damage that may diminish motor function, such as flexibility/dexterity. These difficulties may continue after rehabilitation due to the reorganization of muscle afferent projections during peripheral nerve regeneration. Therefore, understanding how patients with a history of thermal burn injuries perform on motoric measures is necessary to explain the impact neuromuscular damage has on both motor and non-motor tests of cognition. However, no studies have examined the impact of motor functioning on cognition in patients who experienced thermal and electrical injuries compared to an electrical shock injury. This study explored the impact of motor dysfunction and psychiatric distress measured by depression severity on psychomotor speed and executive test performances among EI patients with and without thermal burn injuries.
Participants and Methods:This cross-sectional study consisted of EI patients undergoing an outpatient neuropsychological evaluation, including tests of motor dexterity (Grooved Pegboard [GP]), psychomotor speed (Wechsler Adult Intelligence Scale-IV Coding, Trail Making Test [TMT] Part A), and executive functioning (Stroop Color and Word Test [SCWT] Color-Word trial, TMT Part B). The sample was 83% male and 17% female, 88% White, 3% Black, 5% Hispanic, and 2% other race/ethnicity, with a mean age of 43.9 years (SD=11.36), mean education of 12.9 years (SD=2.05), and mean depression severity of 20.05 (SD=12.59) on the Beck Depression Inventory-II (BDI-II). Exclusion criteria were: 1) injury history of moderate-to-severe head trauma, 2) >2 performance validity test failures, and 3) any amputation of the upper extremity. Regression analyses included GP T-Scores for dominant hand and BDI-II total score as independent variables and neuropsychological normative test data as dependent variables.
Results:Among validly performing patients with EI (n=86), regression analyses revealed GP performance accounted for significant variance (R2 =.153-.169) on all neuropsychological measures. Among EI patients with burn injuries (n=50), regression analyses revealed GP performance accounted for significant variance (R2 =.197-.266) on all neuropsychological measures. Among EI patients without burn injuries (n=36), analyses revealed that neither GP performance nor BDI-II severity accounted for significant variance across the neurocognitive tests (R2=.056-.142). Furthermore, among EI patients with burn injuries and the total sample, regression analyses revealed depression severity negatively predicted GP performance (R2 =.099-.13), however, in patients without burn injuries, depression did not predict GP performance (R2 =.052).
Conclusions:Overall, results showed that GP performance is a significant predictor of neurocognitive performance on both motor and non-motor measures in EI patients with burn injuries. Therefore, among EI patients with burn injuries, GP performance may have potential utility as an early indicator of injury severity, considering that it predicts neuropsychological test performance on measures of psychomotor speed and executive functioning. Lastly, depression predicted GP performance within the burn injury sample illustrating that psychological distress may negatively impact motor functionality.
21 A Comparison of the Memory and Non-Memory Based Performance Validity Measures for Detecting Invalid Neuropsychological Test Performance among Individuals with and without Memory Impairment
- Humza M Khan, Maximillian A Obolsky, Gabriel P Ovsiew, Jason R Soble, Zachary J Resch
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 703-704
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Objective:
Few to no studies have directly compared the relative classification accuracies of the memory-based (Brief Visuospatial Memory Test-Revised Recognition Discrimination [BVMT-R RD] and Rey Auditory Verbal Learning Test Forced Choice [RAVLT FC]) and non-memory based (Reliable Digit Span [RDS] and Stroop Color and Word Test Word Reading trial [SCWT WR]) embedded performance validity tests (PVTs). This study’s main objective was to evaluate their relative classification accuracies head-to-head, as well as examine how their psychometric properties may vary among subgroups with and without genuine memory impairment.
Participants and Methods:This cross-sectional study included 293 adult patients who were administered the BVMT-R, WAIS-IV Digit Span, RAVLT and SCWT during outpatient neuropsychological evaluation at a Midwestern academic medical center. The overall sample was 58.0% female, 36.2% non-Hispanic White, 41.3% non-Hispanic Black, 15.7% Hispanic, 4.8% Asian/Pacific Islander, and 2.0% other, with a mean age of 45.7 (SD=15.8) and a mean education of 13.9 years (SD=2.8). Three patients had missing data, resulting in a final sample size of 290. Two hundred thirty-three patients (80%) were classified as having valid neurocognitive performance and 57 (20%) as having invalid neurocognitive performance based on performance across four independent, criterion PVTs (i.e., Test of Malingering Memory Trial 1, Word Choice Test, Dot Counting Test, Medical Symptom Validity Test). Of those with valid neurocognitive performance, 76 (48%) patients were considered as having genuine memory impairment through a memory composite band score (T<37 for (RAVLT Delayed Recall T-score + BVMT-R Delay Recall T-score/2).
Results:The average memory composite band score for valid neurocognitive scores was T = 49.63 as compared to T = 27.57 for genuine memory impairment individuals. Receiver operating characteristic [ROC] curve analyses yielded significant areas under the curve (AUCs=.79-.87) for all four validity indices (p’s < .001). When maintaining acceptable specificity (91%-95%), all validity indices demonstrated acceptable yet varied sensitivities (35%-65%). Among the subgroup with genuine memory impairment, ROC curve analyses yielded significantly lower AUCs (.64-.69) for three validity indices (p’s < .001), except RDS (AUC=.644). At acceptable specificity (88%-93%), they yielded significantly lower sensitivities across indices (19%-39%). In the current sample, RAVLT FC and BVMT-R RD had the largest changes in sensitivities, with 19% and 26% sensitivity/90%-92% specificity at optimal cut-scores of <10 and <2, respectively, for individuals with memory impairment, compared to 65% and 61% sensitivity/94% specificity at optimal cut-scores of <13 and <4, respectively, for those without memory impairment.
Conclusions:Of the four validity scales, memory-based embedded PVTs yielded higher sensitivities while maintaining acceptable specificity compared to non-memory based embedded PVTs. However, they were also susceptible to the greatest declines in sensitivity among the subgroup with genuine memory impairment. As a result, careful consideration should be given to using memory-based embedded PVTs among individuals with clinically significant memory impairment based on other sources of information (e.g., clinical history, behavioral observation).