Neuropsychological contributions to the early identification of Alzheimer's disease

The ambivalence toward neuropsychology in dementia research, diagnosis, and drug development: Myths and misconceptions

Clinical assessment remains the gold standard for diagnosing dementia, monitoring progression, and conducting clinical research. Biomarkers hold promise for targeted therapeutic approaches, selection of participants in clinical trials, and direct physiological efficacy readouts. However, the anchoring of biomarker research to clinical symptomatology is often based on short and insensitive cognitive screening. This gives the impression that cognitive symptoms occur relatively late and that their progression in the early stages of the disease is slow. A thorough cognitive assessment is a powerful tool and has a key role in the accurate and early diagnosis of dementia. It is very different from the cognitive testing usually seen in biomarker research and drug development. Yet the distinction between these approaches is unclear to many. This paper highlights the misconceptions around cognitive research in dementia and suggests a way forward to facilitate biomarker and drug development through the improved utility of cognitive assessment tools.

Expecting the best or fearing the worst: Discrepancies between self-rated health and frailty in an ageing Irish population

OBJECTIVES

Ageing populations have the propensity to rate their health status more inaccurately than their younger counterparts. As a result, we (1) devised a metric which categorized older adults into groups based on the discrepancy between their self-rated health (SRH) and Frailty Index (FI) scores, and (2) investigated which factors predict group membership.

DESIGN

A cross-sectional design was employed using data from The Irish Longitudinal Study of Ageing (TILDA).

METHODS

A health asymmetry metric was derived: this categorized 6907 participants (aged 50+ years) into three groups: 'health pessimistic' where participants underestimated their healthiness, 'health realistic' where participants accurately assessed their health, and 'health optimistic' where participants overestimated their healthiness. A multinomial logistic regression modelled the ability of a set of sociodemographic, psychosocial, and health behaviour variables in predicting membership of these categories.

RESULTS

A significant proportion of the study population were categorized as 'health realistic' (~69%). The prevalence rates of health optimistic individuals increased in older age groups, and conversely, health pessimistic rates decreased in older age groups. Most notably, psychosocial factors significantly predicted being health pessimistic: such as anxiety (OR = 1.03), loneliness (OR = 1.04), and decreased social connectedness (OR = 0.87). However, less clear sociodemographic, psychosocial, and health behaviour associations were found for being health optimistic.

CONCLUSION

Health asymmetry is a useful method of identifying at-risk individuals for inaccurate SRH. The ability of this metric to predict clinical mental health outcomes should be investigated.