Know thyself: Executive functioning and sex predict self-appraisal of functional abilities in community-dwelling older adults

Abstract

Objective: The capacity for accurate self-appraisals of age-related changes in cognitive and functional abilities is integral to the maintenance of independence in later life, yet there is little understanding of the factors that place nondemented older adults at risk for poor self-awareness. This study examined the potential contributions of executive functioning (EF), crystallized intelligence (IQ-Cr), and sex in predicting congruence between performance and self-appraisals of instrumental activities of daily living (IADL) in a group of community-dwelling older adults. Method: A group of 150 nondemented, community-dwelling older adults (White and majority highly educated) completed measures of EF and IQ-Cr. Participants also completed five timed IADL tasks and self-appraised their performance relative to others of similar age. Results: Sex [F(1,148)  =  7.75, p = .006, η_p² = .05] and EF [(F(1,147) = 5.30, p = .02, η_p² = .04)], but not IQ-Cr, predicted the relationship between performance and self-appraisals, such that those with lower EF and those of male sex overestimated their performance more than those with higher EF and females. Conclusions: Findings indicate that having average to below average EF abilities and being of male sex are risk factors for less accurate self-report of IADL abilities and as such might represent important considerations when assessing IADL abilities via self-report among largely independent, community-dwelling older adults.

Keywords:

• Instrumental activities of daily living
• insight
• self-awareness
• executive functioning
• aging

Disclosure statement

This article was co-authored by Yana Suchy, who is the Editor-in-Chief of The Clinical Neuropsychologist. As a Taylor & Francis policy, and in compliance with publishing ethics, no TCN editors (EIC or Associate Editors) have access to any aspects of the review process pertaining to articles on which they are an author or a co-author. For the purpose of this submission, Dr. Steven Woods, a TCN Associate Editor, assumed 100% responsibility for the processing and editorial decisions regarding this manuscript.

Notes

1 Self-appraisal refers to the metacognitive ability to accurately evaluate one’s own capacities and/or performances (Rothlind et al., 2019; Scherling et al., 2016).

2 Cited research has not reported gender separately from sex and has thus only assessed binary sex as a predictor of self-appraisal accuracy.

3 Some motor and EF abilities have been shown to vary as a function of handedness (Beratis et al., 2013; Gunstad et al., 2007).

4 Matching procedures included depressive symptoms because men and women differ in depression base rates (Kuehner, 2017) including in older age (Byers et al., 2010; Luppa et al., 2012); and depression can be negatively correlated with EF performance (Manning et al., 2014; Snyder, 2013) and self-appraisals (Spitznagel et al., 2006).

5 Cronbach’s α was adjusted using Spearman-Brown formula (15 items).

6 Because the study sample included participants from three studies, some participants were administered the WAIS-III and others the WAIS-IV Information subtest. Conversion of raw scores to age-appropriate scaled scores allows for common interpretation across both versions, which are highly correlated (r =  .90) (Wechsler & Psychological Corporation, 2008).

7 Given controversies surrounding the use of post-hoc power analyses (see Dziak, Dierker, & Abar, 2020), power should be interpreted with caution.

8 Recent research on the validity of effect size interpretation indicates that r greater than .20 can be considered meaningful with reasonable certainty in the psychological sciences (For a review, see Funder & Ozer, 2019).

9 Although cognitive status was correlated with EF, the DRS-2 was not included as a covariate given that performance on this measure is highly dependent on executive processes (i.e., the DRS-2 score reflects in large part performance on tasks of verbal fluency, inhibition, working memory, and reasoning, all of which overlap with capacities captured by the EF score).

10 Component process composite was also entered in the model, to isolate the EF construct (see the Measures section).

11 Component process composite was again included to help isolate the EF construct (see the Measures section).

Additional information

Funding

This work was supported by the second author’s professional development fund from the University of Utah.