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Study evaluates personality predictors of dementia diagnosis and neuropathology

Study evaluates personality predictors of dementia diagnosis and neuropathology


In a recent study published in Alzheimer’s & Dementia, researchers analyzed individual-level data from multiple studies to develop Bayesian models to test whether the Big Five personality traits and subjective well-being (SWB) differentially predict dementia diagnoses and neuropathology at autopsy.

Additionally, they investigated whether certain sociodemographic and baseline cognitive health factors moderate these associations.

Study: Personality predictors of dementia diagnosis and neuropathological burden: An individual participant data meta-analysis. Image Credit: Robert Kneschke/Shutterstock.comStudy: Personality predictors of dementia diagnosis and neuropathological burden: An individual participant data meta-analysis. Image Credit: Robert Kneschke/


The Big Five and SWB are widely accepted psychological constructs of personality. The former has five dimensions: extraversion, agreeableness, conscientiousness, neuroticism, and openness, while the latter evaluates an individual’s overall life satisfaction and happiness, encompassing positive and negative effects.

Alzheimer’s disease (AD) is the leading cause of dementia; however, the majority of dementia cases are due to mixed pathologies, which might manifest as vascular, frontotemporal, and Lewy body.

After an extensive review of the literature within Web of Science, PubMed, and EBSCOhost databases, researchers observed that several researchers had examined the associations between well-being and dementia. 

However, there is a lack of systematic investigation of the links between well-being and personality traits with neuropathology and dementia using a meta-analytic approach. 

About the study

Researchers first examined the foundational associations between Big Five personality traits and SWB and the development of neuropathology and its clinical manifestation, i.e., dementia. 

Next, they integrated data from eight longitudinal samples (44,531 participants) simultaneously using a one-stage individual participant data meta-analysis (IPD-MA).

This helped calculate the estimation of the overall robustness of personality and well-being predictors of dementia and pathology while preserving heterogeneity in predictions across studies, such as differences in sociodemographic and design characteristics (e.g., age of participants at baseline and years of follow-up). 

They used individual participant data, including participants in all models for which they had requisite data. Because measures were not identical across samples, they used conceptual harmonization.

Examining these relationships in multiple studies helped researchers understand how these factors were interrelated across different groups of people, different measurement methods, and periods.

Further, it can help gain valuable insights into the mechanisms that elucidate these associations and develop interventions and screening assessments for dementia.

As Big Five and SWB measures were on different scales, they transformed all psychosocial indicators to Percentages Of the Maximum Possible score (POMP), which allowed for interpretation in relative percentiles. 


Results suggested robust prospective associations between some Big Five and SWB psychological factors and dementia diagnosis but not neuropathology. 

Neuroticism and negative affect were risk factors, while extraversion, conscientiousness, and positive affect were protective against incident dementia diagnosis.

Specifically, neuroticism was not directly correlated to neuropathology biomarkers, as shown in prior research.

Average negative affect, one of the Big Five traits dimension, characterized by aversive mood states, anxiety, anger, disgust, guilt, and fear, when assessed on several occasions, is highly related to neuroticism.

Thus, expectedly, negative affect and neuroticism were positively associated with dementia diagnosis. 

Research also suggests that negative affect is associated with neuroinflammation, particularly in individuals with AD who have a high amyloid beta (Aβ) load. 

Moderation analyses suggested that cognitive function at baseline did not moderate associations between Big Five personality traits and neuropathology. Some evidence from these studies favored the cognitive resilience model, where older individuals tended to have higher Braak stages. 

Nonetheless, they emphasize the need for more research on traits, dementia diagnosis, and the Braak stage. Importantly, older individuals with higher conscientiousness were less likely to be diagnosed with dementia. 

Finally, findings evidenced that positive affect, openness to experience, and satisfaction with life might be protective against dementia diagnosis, even though the effects were only significant in some studies. 


Overall, the current IPD-MA extended prior work, providing robust evidence that neuroticism, conscientiousness, and negative affect are associated with incident dementia diagnoses across samples, measures, and time. 

Across all analyses, the directional consistency in estimates despite interstudy differences in operational definitions of dementia diagnosis emphasizes the practicality of using either self-reported or clinical diagnoses of dementia, contributing to conceptual replication efforts and this study’s harmonization approach.

This study also highlighted that assessing personality traits and well-being can be quick and low-cost. Conversely, conducting neuropsychological assessments and collecting neuro biomarkers can be time-consuming, costly, and stressful for patients.

Thus, incorporating psychological trait measures into clinical screening or diagnosis criteria for dementia could be beneficial.

It also facilitates the identification of individuals at a higher risk for developing chronic illnesses in the future. Thus, there will be adequate time to implement interventions, i.e., before the onset of dementia symptoms, potentially leading to better outcomes for patients.

Future work should build upon these findings, focusing on more nuanced questions to determine temporal trends in these associations and their underlying mechanisms.




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