Literature DB >> 32771860

Network structures and temporal stability of self- and informant-rated affective symptoms in Alzheimer's disease.

T T Saari1, I Hallikainen2, T Hintsa3, A M Koivisto4.   

Abstract

BACKGROUND: Affective symptoms in Alzheimer's disease (AD) can be rated with both informant- and self-ratings. Information from these two modalities may not converge. We estimated network structures of affective symptoms in AD with both rating modalities and assessed the longitudinal stability of the networks.
METHODS: Network analyses combining self-rated and informant-rated affective symptoms were conducted in 3198 individuals with AD at two time points (mean follow-up 387 days), drawn from the NACC database. Self-rated symptoms were assessed by Geriatric Depression Scale, and informant-rated symptoms included depression, apathy and anxiety questions from Neuropsychiatric Inventory Questionnaire.
RESULTS: Informant-rated symptoms were mainly connected to symptoms expressing lack of positive affect, but not to the more central symptoms of self-rated worthlessness and helplessness. Networks did not differ in structure (p = .71), or connectivity (p = .92) between visits. Symptoms formed four clinically meaningful clusters of depressive symptoms and decline, lack of positive affect, informant-rated apathy and anxiety and informant-rated depression. LIMITATIONS: The symptom dynamics in our study could have been present before AD diagnosis. The lack of positive affect cluster may represent a methodological artefact rather than a theoretically meaningful subgroup. Requiring follow-up lead to a selection of patients with less cognitive decline.
CONCLUSIONS: Informant rating may only capture the more visible affective symptoms, such as not being in good spirits, instead of more central and severe symptoms, such as hopelessness and worthlessness. Future research should continue to be mindful of differences between self- and informant-rated symptoms even in earlier stages of AD.
Copyright © 2020. Published by Elsevier B.V.

Entities:  

Keywords:  Alzheimer's disease; Anxiety; Apathy; Depression; Network analysis; Neuropsychiatric symptoms

Mesh:

Year:  2020        PMID: 32771860      PMCID: PMC7484410          DOI: 10.1016/j.jad.2020.07.100

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  52 in total

1.  The theoretical status of latent variables.

Authors:  Denny Borsboom; Gideon J Mellenbergh; Jaap van Heerden
Journal:  Psychol Rev       Date:  2003-04       Impact factor: 8.934

2.  Confirmatory factor analysis of the geriatric depression scale.

Authors:  Kathryn Betts Adams; Holly C Matto; Sara Sanders
Journal:  Gerontologist       Date:  2004-12

3.  Don't blame the model: Reconsidering the network approach to psychopathology.

Authors:  Laura F Bringmann; Markus I Eronen
Journal:  Psychol Rev       Date:  2018-07       Impact factor: 8.934

Review 4.  Network analysis: an integrative approach to the structure of psychopathology.

Authors:  Denny Borsboom; Angélique O J Cramer
Journal:  Annu Rev Clin Psychol       Date:  2013       Impact factor: 18.561

5.  A new method for constructing networks from binary data.

Authors:  Claudia D van Borkulo; Denny Borsboom; Sacha Epskamp; Tessa F Blanken; Lynn Boschloo; Robert A Schoevers; Lourens J Waldorp
Journal:  Sci Rep       Date:  2014-08-01       Impact factor: 4.379

6.  "Noncognitive" symptoms of early Alzheimer disease: a longitudinal analysis.

Authors:  Mary Clare Masters; John C Morris; Catherine M Roe
Journal:  Neurology       Date:  2015-02-10       Impact factor: 9.910

7.  Predicting disease progression in Alzheimer's disease: the role of neuropsychiatric syndromes on functional and cognitive decline.

Authors:  Katie Palmer; Federica Lupo; Roberta Perri; Giovanna Salamone; Lucia Fadda; Carlo Caltagirone; Massimo Musicco; Luca Cravello
Journal:  J Alzheimers Dis       Date:  2011       Impact factor: 4.472

8.  Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease.

Authors:  G McKhann; D Drachman; M Folstein; R Katzman; D Price; E M Stadlan
Journal:  Neurology       Date:  1984-07       Impact factor: 9.910

9.  Estimating psychological networks and their accuracy: A tutorial paper.

Authors:  Sacha Epskamp; Denny Borsboom; Eiko I Fried
Journal:  Behav Res Methods       Date:  2018-02

Review 10.  Version 3 of the National Alzheimer's Coordinating Center's Uniform Data Set.

Authors:  Lilah Besser; Walter Kukull; David S Knopman; Helena Chui; Douglas Galasko; Sandra Weintraub; Gregory Jicha; Cynthia Carlsson; Jeffrey Burns; Joseph Quinn; Robert A Sweet; Katya Rascovsky; Merilee Teylan; Duane Beekly; George Thomas; Mark Bollenbeck; Sarah Monsell; Charles Mock; Xiao Hua Zhou; Nicole Thomas; Elizabeth Robichaud; Margaret Dean; Janene Hubbard; Mary Jacka; Kristen Schwabe-Fry; Joylee Wu; Creighton Phelps; John C Morris
Journal:  Alzheimer Dis Assoc Disord       Date:  2018 Oct-Dec       Impact factor: 2.703

View more
  2 in total

1.  Concordance of self- and informant-rated depressive symptoms in nursing home residents with Dementia: cross-sectional findings.

Authors:  Julie L O'Sullivan; Roxana Schweighart; Sonia Lech; Eva-Marie Kessler; Christina Tegeler; Andrea Teti; Johanna Nordheim; Paul Gellert
Journal:  BMC Psychiatry       Date:  2022-04-05       Impact factor: 3.630

Review 2.  Psychometric Properties of the Neuropsychiatric Inventory: A Review.

Authors:  Toni Saari; Anne Koivisto; Taina Hintsa; Tuomo Hänninen; Ilona Hallikainen
Journal:  J Alzheimers Dis       Date:  2022       Impact factor: 4.160

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.