42 Cognitive Impairment Stage and Dementia Syndromes Explain Latent Structure Variability on the Neuropsychiatric Inventory Questionnaire (NPI-Q)
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...
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description | 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 (CF |
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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.</description><identifier>ISSN: 1355-6177</identifier><identifier>EISSN: 1469-7661</identifier><identifier>DOI: 10.1017/S1355617723009001</identifier><language>eng</language><publisher>New York, USA: Cambridge University Press</publisher><subject>Alzheimer's disease ; Assessment/Psychometrics/Methods (Adult) ; Cognitive ability ; Dementia ; Dementia disorders ; Frontotemporal dementia ; Hypotheses ; Lewy bodies ; Neurodegenerative diseases ; Poster Session 08: Assessment | Psychometrics | Noncredible Presentations | Forensic ; Sampling</subject><ispartof>Journal of the International Neuropsychological Society, 2023-11, Vol.29 (s1), p.722-723</ispartof><rights>Copyright © INS. Published by Cambridge University Press, 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S1355617723009001/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,780,784,27924,27925,55628</link.rule.ids></links><search><creatorcontrib>Amitrano, Nicholas R</creatorcontrib><creatorcontrib>Obolsky, Maximillian A</creatorcontrib><creatorcontrib>Resch, Zachary J</creatorcontrib><creatorcontrib>Soble, Jason R</creatorcontrib><creatorcontrib>Gonzälez, David A</creatorcontrib><title>42 Cognitive Impairment Stage and Dementia Syndromes Explain Latent Structure Variability on the Neuropsychiatric Inventory Questionnaire (NPI-Q)</title><title>Journal of the International Neuropsychological Society</title><addtitle>J Int Neuropsychol Soc</addtitle><description>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.</description><subject>Alzheimer's disease</subject><subject>Assessment/Psychometrics/Methods (Adult)</subject><subject>Cognitive ability</subject><subject>Dementia</subject><subject>Dementia disorders</subject><subject>Frontotemporal dementia</subject><subject>Hypotheses</subject><subject>Lewy bodies</subject><subject>Neurodegenerative diseases</subject><subject>Poster Session 08: Assessment | Psychometrics | Noncredible Presentations | Forensic</subject><subject>Sampling</subject><issn>1355-6177</issn><issn>1469-7661</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1UE1LAzEQXURBrf4AbwEveljNJOmGHKVWLRS1VL0u2Wy2TekmazZb3J_hPzalBQ_iaR4z72N4SXIB-AYw8Ns50OEwA84JxVhgDAfJCbBMpDzL4DDieE639-PktG1XkUAB45PkmxE0cgtrgtloNKkbaXytbUDzIBcaSVuie71dGInmvS29q3WLxl_NWhqLpjLsuL5TofMafUhvZGHWJvTIWRSWGj3rzrum7dXSyOCNQhO7iSLnezTrdBuMszaGanT1_DpJZ9dnyVEl160-389B8v4wfhs9pdOXx8nobpoqGHJIBSMVIbggCoSQmSqJJoRoWmlcDQUpKC9lISIELHmJFVdFxihRnAhGFeN0kFzufBvvPreP5CvXeRsjcyIwA2Cc0ciCHUt517ZeV3njTS19nwPOt83nf5qPGrrXyLrwplzoX-v_VT9MeIZj</recordid><startdate>202311</startdate><enddate>202311</enddate><creator>Amitrano, Nicholas R</creator><creator>Obolsky, Maximillian A</creator><creator>Resch, Zachary J</creator><creator>Soble, Jason R</creator><creator>Gonzälez, David A</creator><general>Cambridge University Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope></search><sort><creationdate>202311</creationdate><title>42 Cognitive Impairment Stage and Dementia Syndromes Explain Latent Structure Variability on the Neuropsychiatric Inventory Questionnaire (NPI-Q)</title><author>Amitrano, Nicholas R ; Obolsky, Maximillian A ; Resch, Zachary J ; Soble, Jason R ; Gonzälez, David A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1571-942f220b2c199a6cd2e222e3fe0f592b37dab9f5910a7d0c7cb6432c72943c473</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Alzheimer's disease</topic><topic>Assessment/Psychometrics/Methods (Adult)</topic><topic>Cognitive ability</topic><topic>Dementia</topic><topic>Dementia disorders</topic><topic>Frontotemporal dementia</topic><topic>Hypotheses</topic><topic>Lewy bodies</topic><topic>Neurodegenerative diseases</topic><topic>Poster Session 08: Assessment | Psychometrics | Noncredible Presentations | Forensic</topic><topic>Sampling</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Amitrano, Nicholas R</creatorcontrib><creatorcontrib>Obolsky, Maximillian A</creatorcontrib><creatorcontrib>Resch, Zachary J</creatorcontrib><creatorcontrib>Soble, Jason R</creatorcontrib><creatorcontrib>Gonzälez, David A</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><jtitle>Journal of the International Neuropsychological Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Amitrano, Nicholas R</au><au>Obolsky, Maximillian A</au><au>Resch, Zachary J</au><au>Soble, Jason R</au><au>Gonzälez, David A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>42 Cognitive Impairment Stage and Dementia Syndromes Explain Latent Structure Variability on the Neuropsychiatric Inventory Questionnaire (NPI-Q)</atitle><jtitle>Journal of the International Neuropsychological Society</jtitle><addtitle>J Int Neuropsychol Soc</addtitle><date>2023-11</date><risdate>2023</risdate><volume>29</volume><issue>s1</issue><spage>722</spage><epage>723</epage><pages>722-723</pages><issn>1355-6177</issn><eissn>1469-7661</eissn><abstract>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.</abstract><cop>New York, USA</cop><pub>Cambridge University Press</pub><doi>10.1017/S1355617723009001</doi><tpages>2</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Alzheimer's disease Assessment/Psychometrics/Methods (Adult) Cognitive ability Dementia Dementia disorders Frontotemporal dementia Hypotheses Lewy bodies Neurodegenerative diseases Poster Session 08: Assessment | Psychometrics | Noncredible Presentations | Forensic Sampling |
title | 42 Cognitive Impairment Stage and Dementia Syndromes Explain Latent Structure Variability on the Neuropsychiatric Inventory Questionnaire (NPI-Q) |
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