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Record W7116881831 · doi:10.1002/alz70860_098151

Investigating the Mediating Role of Paranoid Delusions in Depression and Cognitive Decline

2025· article· en· W7116881831 on OpenAlexaboutno aff
S.P. Kalra, Deepak Kalra, Hannah Gardener, Carolina M Gutierrez, Mohammad Nafeli Shahrestani, Debina Laishram, Karlon Howard Johnson, Nandakumar Nagaraja, WayWay M. Hlaing, T. Rundek

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)Cognitive declineObservational studyCognitionAffect (linguistics)

Abstract

fetched live from OpenAlex

BACKGROUND: Psychotic symptoms, including delusions, are prevalent in Alzheimer's disease and depression, where they are associated with poorer outcomes. Cognitive Load Theory posits that depression impairs cognitive function by increasing rumination and negative thought patterns, depleting cognitive resources. The role of delusions as a mediator between depression and cognitive outcomes remains unexplored. METHODS: Using data from the National Alzheimer's Coordinating Center (NACC), we examined the mediating role of paranoid delusions in the relationship between depression severity and cognitive outcomes. Data were collected from 14,588 participants during their first visit to an Alzheimer's Disease Center (March 2015-Dec 2024, NACC Version 3). Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA). Depression severity was proxy-reported by caregivers using the Neuropsychiatric Inventory Questionnaire (NPI-Q), while paranoid delusion severity was self-reported based on beliefs about others stealing or planning harm. Structural equation modeling (SEM) was employed to estimate direct, indirect, and total effects while adjusting for covariates informed by a theoretical framework. These covariates included sex, age, race, education, body mass index, living arrangement, independence, residence type, alcohol and tobacco use, diabetes, heart failure, hypertension, and stroke. Model fit was assessed using root mean square error, comparative fit index, and standardized residuals. RESULTS: Participants had a mean age of 69.3 years, with 57.4% female, 78.5% White, 17.5% Black or African American, and 4.0% from other racial groups. The average MoCA score was 23 (median = 24, SD=5.8). Overall, 26% had mild or greater depressive symptoms, and 4.6% exhibited mild or greater delusions. Delusion prevalence increased with depression severity: 1.3% in those without depressive symptoms, 7.7% in mild, 14.5% in moderate, and 28% in severe depression. Depression severity was significantly associated with delusions (β=0.092, p <0.001), poor cognitive outcomes (β=-0.79, p <0.001), and indirectly via delusional severity (β_indirect=-0.188, p <0.001). Delusions mediated 19.3% of the total effect of depression severity on cognitive outcomes. The SEM model demonstrated an excellent fit. CONCLUSIONS: The poorer cognitive outcomes in patients with depression are partially mediated through delusions. Given the observational design, this needs to be confirmed through prospective studies and may provide an avenue to improve cognitive outcomes in patients with depression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.319
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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