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. 2019 Dec 24;35(4):365–376. doi: 10.1093/arclin/acz065

Neuropsychological Correlates of Anosognosia for Objective Functional Difficulties in Older Adults on the Mild Cognitive Impairment Spectrum

Kayla A Steward 1,✉, Tyler P Bull 1, Richard Kennedy 2, Michael Crowe 1, Virginia G Wadley 2
PMCID: PMC7244883  PMID: 31875876

Abstract

Objective

To examine the neuropsychological correlates of anosognosia for instrumental activities of daily living (IADLs) in older adults with mild cognitive impairment (MCI) and mild dementia.

Method

Participants (n = 103; age range = 54–88, 52% female) with MCI and mild dementia were recruited from neurology and geriatrics clinics for cross-sectional analysis. They completed neuropsychological tests along with subjective and performance-based assessments of six IADLs: financial management, driving, grocery shopping, nutrition evaluation, telephone use, and medication management. For each IADL, participants were classified as having anosognosia when there was objective difficulty but no subjective complaints.

Results

Depending on functional domain, 13–39% of the sample had objective IADL difficulty, and of those, 65–93% lacked insight into these deficits. Binomial logistic regression models controlling for demographic variables revealed that measures of global cognition, executive function, visual attention, and verbal memory predicted classification of anosognosia, and these relationships varied across IADLs. In contrast, basic auditory attention, working memory, depressive symptoms, nor cognitive reserve were significantly related to anosognosia for any IADL.

Conclusion

Results support the Conscious Awareness Model, which theorizes that accurate metacognitive output is reliant on attentional, memory, and executive functioning systems. Findings from this study suggest that anosognosia for different IADLs may arise from breakdowns at varying points in this model, explaining both inter- and intra-patient variability in self-awareness of functional deficits.

Keywords: Mild cognitive impairment, dementia, instrumental activities of daily living, anosognosia, neuropsychology

Introduction

Older adults with both mild and severe dementia consistently underreport current cognitive, behavioral, physical, emotional, and functional problems (Agnew & Morris, 1998; Starkstein, Jorge, Mizrahi, & Robinson, 2006; Wilson, Sytsma, Barnes, & Boyle, 2016)—a well-documented phenomenon known as anosognosia or impaired awareness. Less is known about the degree of self-awareness in individuals with mild cognitive impairment (MCI) despite evidence that this population begins to exhibit both cognitive deficits along with reduced efficiency and accuracy in performing instrumental activities of daily living (IADLs) such as financial management, grocery shopping, using technology, and driving (Jekel et al., 2015; Lassen-Greene et al., 2017).

Within the MCI population, most prior studies have focused on self-awareness of cognitive deficits, particularly memory performance. Some have found that these individuals generally retain good insight into their memory decline (Reisberg & Gauthier, 2008) while others noted that those with MCI often overestimate their current cognitive abilities (Fragkiadaki et al., 2016; Vogel et al., 2004). Interestingly, others have found that a proportion of older adults are prone to underestimating their cognitive abilities, reporting more cognitive complaints than objectively exist (Bassett & Folstein, 1993). The discrepancy in these findings is likely due to methodological differences in the calculation of anosognosia (Piras, Piras, Orfei, Caltagirone, & Spalletta, 2016), with many of these studies relying on the discrepancy between self- and informant reports of memory functioning (with informant reports serving as the indicators of “true” abilities). However, there is substantial evidence now to suggest that informant-reports are often biased by a variety of personal and interpersonal factors and thus prone to inaccuracy (Ready, Ott, & Grace, 2004; Zanetti, Geroldi, Frisoni, Bianchetti, & Trabucchi, 1999). In addition, this heterogeneity in findings suggests that there may be domain-specificity in self-awareness (i.e., patients retain insight into some of their abilities but not others).

Few studies have specifically examined self-awareness of the mild functional deficits often seen MCI, and fewer yet have used objective functional testing as their estimate of performance. These studies found that approximately 25–50% of those with amnestic MCI and very mild Alzheimer’s disease (AD) overestimate their ability to perform IADLs, especially in financial management, driving, and cooking-related domains (Okonkwo et al., 2009; Okonkwo et al., 2008; Steward, Bull, & Wadley, 2019a). Importantly, these individuals are at higher risk for converting to dementia (Tabert et al., 2002) as well as continuing to engage in daily activities that may now be dangerous for them due to their cognitive-functional impairments (e.g., choosing to continue driving because they lack awareness of the on-road difficulties they have) (Lin et al., 2010; Starkstein, Jorge, Mizrahi, Adrian, & Robinson, 2007).

Several theories have been proposed to help explain the individual differences in both breadth and extent of anosognosia within neurodegenerative populations. One of the most prominent is the Conscious Awareness Model (CAM), which was originally proposed by Agnew and Morris (1998) and recently revised (Morris & Mograbi, 2012; Piras et al., 2016). This model incorporates aspects of previously proposed models (Hannesdottir & Morris, 2007; Mograbi, Brown, & Morris, 2009; Morris & Hannesdottir, 2004) and theorizes that accurate metacognitive output is reliant on attentional, memory, and executive functioning systems. In summary, individuals first attend to and process basic sensory input in domain specific modules (e.g., language, motor, visual). This input needs to be able to pass to working memory so that it can be evaluated by the ‘comparator mechanism’ within the executive system to assess for problems and errors and determine if current performance is consistent with past abilities. Individuals with a malfunctioning ‘comparator mechanism’ are no longer able to evaluate their task performance and therefore they no longer experience the concept of failure. Finally, information about task success or failure needs to pass from short-term to long-term memory through consolidation processes so that it can update the individual’s ‘personal database,’ which is essentially a repository of information about oneself containing semantic representations such as ‘I am a good driver.’ If an individual’s memory is affected, they can no longer recalibrate their personal database, leading to what is known as a ‘petrified self,’ where current sense of self is stable but outdated. According to this model, a failure in one or more of these steps could lead to reduced awareness of current abilities.

The CAM is supported by studies that have found a relationship between impaired self-awareness and executive dysfunction (Amanzio et al., 2013; Kashiwa et al., 2005; Michon, Deweer, Pillon, Agid, & Dubois, 1994) and evidence that verbal and visual learning and memory is positively correlated with insight into deficits (Bruce et al., 2008; Farias, Mungas, & Jagust, 2005; Hannesdottir & Morris, 2007; Orfei et al., 2010; Salmon et al., 2006; Tremont & Alosco, 2011). Given that this model hypothesizes the involvement of numerous cognitive systems in maintaining accurate self-appraisal, CAM is also supported by studies which have found that anosognosia is linked more broadly to reduced global cognition and dementia severity (Kalbe et al., 2005; Karlawish, Casarett, Bioethics, Xie, & Kim, 2005; Kashiwa et al., 2005; Okonkwo et al., 2008; Tremont & Alosco, 2011; Vogel, Hasselbalch, Gade, Ziebell, & Waldemar, 2005; Vogel et al., 2004) and to premorbid factors such as cognitive reserve (as measured by years of education)(Salmon et al., 2006; Spitznagel, Tremont, Brown, & Gunstad, 2006). In contrast, other studies have found no relationship between neuropsychological measures and degree of insight into cognitive performance (Derouesne et al., 1999; Guerrier et al., 2018; Seltzer, Vasterling, Mathias, & Brennan, 2001).

Finally, poor awareness into deficits is associated with lower levels of depression and anxiety and higher levels of apathy, although the causal direction of these relationships is unclear (Derouesne et al., 1999; Kashiwa et al., 2005; Okonkwo et al., 2008; Salmon et al., 2006; Smith, Henderson, McCleary, Murdock, & Buckwalter, 2000).

Identification of the neuropsychological correlates of impaired awareness may help to pinpoint the mechanisms involved in this phenomenon and help explain why individuals at a similar stage of disease process express different levels of insight into their deficits. To our knowledge, no studies have examined whether the CAM remains valid when the ‘object’ of awareness is concrete everyday functional abilities rather than a more abstract construct such as general memory abilities. The current study is the first to examine neuropsychological correlates of impaired self-awareness across a broad spectrum of IADLs (financial management, driving, grocery shopping, nutrition evaluation, telephone use, and medication management) in older adults on the continuum of MCI and mild dementia. Moreover, this study responds to past methodological limitations by using a self-report versus objective measurement methodology to calculate anosognosia. We hypothesize that poor self-awareness will be associated with worse global cognition, verbal memory, attention, and executive function. In addition, we hypothesize that poor self-awareness will be associated with lower cognitive reserve and lower level of depressive symptoms.

Methods

Participants

Older adults were recruited from outpatient neurology and geriatrics clinics if they were given a working-diagnosis of MCI within the last year. Individuals with history of moderate/severe traumatic brain injury, brain tumor, clinical stroke within last 2 years, or psychiatric conditions other than depression were excluded from participation. Participants were recruited as part of a longitudinal clinical trial investigating the efficacy of a technology-based cognitive intervention; however, only pre-intervention data from this ongoing trial were used for the current analyses.

During their initial visit, trained psychometrists administered a full neuropsychological testing battery and collected behavioral observations on each participant. Additionally, participants completed questionnaires about their sociodemographics, medical history, and emotional status and an informant was interviewed separately about the participant’s functional status. Current medications were obtained primarily via medical records and self-report.

These data were reviewed by a multidisciplinary team of study investigators (including neuropsychology, geropsychology, and behavioral neurology) who followed current diagnostic guidelines for MCI and dementia (Winblad et al., 2004). Each case was randomly assigned to two panel members; the entire panel adjudicated cases of diagnosis disagreement until a majority opinion was reached. Generally, if two or more tests within a specific cognitive domain fell 1.5 standard deviations or more below expected performance based on demographically adjusted normative data, the individual was considered impaired in that cognitive domain. Diagnostic classifications for the participants (n = 103) in this study included: subjective cognitive complaint (SCC; subjective cognitive complaints from individual or informant but limited evidence of objective cognitive impairment; n = 9), amnestic MCI (n = 75), non-amnestic MCI (n = 4), and mild dementia (cognitive and functional complaints with mild to moderate objective cognitive impairment; n = 13). Participants with objective cognitive impairment but unclear diagnostic classification [e.g., the participant may have had moderate-to-severe objective impairment but only on one test within a cognitive domain(s)] were categorized as cognitive impairment-cannot classify (n = 2).

During their second visit, which occurred within 2 months from the first, participants completed a self-evaluation of their current functional abilities across six skills areas followed by an objective measurement in each of the respective areas, including laboratory-based assessment with a trained psychometrist and an on-road driving evaluation with a licensed occupational therapist. Subjective functional measures were administered prior to objective measures to reduce the effect of performance bias on self-ratings.

This study used both verbal and written consent for undergoing all study procedures. All participants completed a consent interview at their first visit using the Competency Assessment Checklist for Research Informed Consent (Daniel Marson, J.D., Ph.D, V.2 October 2002; MCI Study version 1 July 2004). All procedures were approved by the Institutional Review Board.

Measures

IADL assessment

Brief descriptions of the objective and subjective instruments used to measure each of the six IADLs are listed in Table 1. Of note, all subjective measures used were designed to parallel the domains and items assessed in the respective objective measure. Briefly, to evaluate financial management skills, participants were objectively assessed using the Financial Capacity Instrument-Short Form (FCI-SF) (Gerstenecker et al., 2016) and subjectively assessed with the Past and Present Financial Capacity Form (PPFCF) (Wadley, Harrell, & Marson, 2003). For the driving domain, participants who identified as current drivers and possessed a valid driver’s license were given a 45–60 min. on-road driving evaluation (non-highway, fair-weather only) with a Certified Driving Rehabilitation Specialist (CDRS)/licensed occupational therapist (OTR/L) and a back seat rater, who rated the participants’ overall driving performance (Wadley et al., 2009). Subjective driving ability was assessed with the Mobility/Driving Habits for Current Drivers Questionnaire (Owsley, Stalvey, Wells, & Sloane, 1999). Telephone use, grocery shopping, nutrition evaluation, and medication management skills were objectively assessed using the Timed Instrumental Activities of Daily Living (TIADL) (Owsley, McGwin, Sloane, Stalvey, & Wells, 2001; Owsley, Sloane, McGwin, & Ball, 2002) and subjectively assessed with the MILES Self-Report Questionnaire (Okonkwo et al., 2009). More detailed descriptions of measures have been previously published (Steward et al., 2019a; Steward, Kennedy, Erus, Nasrallah, & Wadley, 2019b).

Table 1.

Objective and subjective measures used to assess performance across six instrumental activities of daily living

IADLs and associated measures Type of measure Brief description Test range Difficulty classification
Financial management
 Financial Capacity Instrument—Short Forma Objective Lab-based instrument with 37 items evaluating aspects of financial management (e.g., writing a check, using a bank statement) that produces a total score 0–74 Total raw scores transformed to age- and education-adjusted standardized scores; if score 1 SD or more below normative mean, classified as having difficulty
 Past and Present Financial Capacity Formb Subjective Questionnaire that includes an item (4-point scale) asking participants whether they are able to independently manage all of their money and financial affairs at the present time 1–4 If participants did not respond ‘Yes, without help’ (the highest rating), classified as having difficulty
Driving
 On-road driving evaluationc Objective 45–60 min. on-road driving evaluation (non-highway, fair-weather only) on a standard route using an instrumented vehicle under supervision of a CDRS/OTR-L and a backseat rater (doctoral-level psychologist) who both rated overall driving performance using 5-point scale; scores were averaged due to strong inter-rater reliability (κ = .858, p < .001) 1–5 If averaged rating was 3 or less, classified as having difficulty
 Mobility/Driving Habits for Current Drivers Questionnaired Subjective Questionnaire that includes an item (5-point scale) asking participants to rate the overall quality of their driving performance 1–5 Scores reversed to match on-road driving eval. Scale; If rating was 3 or less, classified as having difficulty
Nutrition evaluation
 Timed Instrumental Activities of Daily Livinge Objective Lab-based instrument evaluating accuracy and speed of performance on several functional domains (3 items assess Nutrition Eval.—each on 4-point scale) 3–12 If participants did not compete all items within allotted time limit and without error (i.e., score > 3), classified as having difficulty
 MILES Self-Report Questionnairef Subjective Questionnaire asking participants to rate the difficulty of performing various tasks necessary for independent living using 4-point scale (1 item assesses each IADL) 1–4 If participants did not respond that the task is ‘Not difficult’ (the highest rating), classified as having difficulty
Grocery shopping
 Timed Instrumental Activities of Daily Livinge Objective Lab-based instrument evaluating accuracy and speed of performance on several functional domains (1 item assesses Grocery Shopping—on 3-point scale) 1–3 If participants did not compete item within allotted time limit and without error (i.e., score > 1), classified as having difficulty
 MILES Self-Report Questionnairef Subjective See previous description of measure 1–4 See previous description of measure
Telephone use
 Timed Instrumental Activities of Daily Livinge Objective Lab-based instrument evaluating accuracy and speed of performance on several functional domains (1 item assesses Telephone Use—on 3-point scale) 1–3 If participants did not compete item within allotted time limit and without error (i.e., score > 1), classified as having difficulty
 MILES Self-Report Questionnairef Subjective See previous description of measure 1–4 See previous description of measure
Medication management
 Timed Instrumental Activities of Daily Livinge Objective Lab-based instrument evaluating accuracy and speed of performance on several functional domains (2 items assess Medication Mgmt.—each on 4-point scale) 2–8 If participants did not compete all items within allotted time limit and without error (i.e., score > 2), classified as having difficulty
 MILES Self-Report Questionnairef Subjective See previous description of measure 1–4 See previous description of measure
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Abbreviations: CDRS/OTR-L, Certified Driving Rehabilitation Specialist/Licensed Occupational Therapist; IADLs, Instrumental Activities of Daily Living.

Note. Items in self-report questionnaires were originally designed to parallel their objective measurement counterparts. For the Financial Capacity Instrument-Short Form and on-road driving evaluation, higher raw score is better. For TIADL items, lower raw score is better.

For each objective and subjective measure, performance was classified as either “1 = has difficulty” or “0 = no difficulty” for data reduction purposes and also to aid in comparison between objective and subjective performance. Table 1 provides information on criteria used to determine whether participants demonstrated or reported difficulty for each measure/task. Similar methods and cut-off criteria have been previously published (Okonkwo et al., 2009; Okonkwo et al., 2008; Steward et al., 2019a; Steward et al., 2019b).

Anosognosia classification

Self-awareness was assessed for each of the six IADLs by calculating a discrepancy score between the dichotomized objective and subjective difficulty ratings for each IADL. The dichotomized subjective difficulty rating was subtracted from the dichotomized objective difficulty rating. Individuals were classified as having anosognosia if they had a discrepancy score of +1, indicating that there was objective difficulty but not subjective complaints.

Neuropsychological assessment

Participants were administered a neuropsychological battery consisting of several clinically relevant neurocognitive domains. These measures have appropriate reliability and validity across the age range, educational level, and racial/ethnic makeup of the study sample. The following domains (and selected measures of each) were used to predict poor self-awareness of difficulties for each of the six IADLs:

Global cognition was assessed using the Dementia Rating Scale-2 (DRS-2) (Jurica, Leitten, & Mattis, 2001) (total raw score). Basic visual and auditory attention were assessed using the Trail Making Test (TMT) (Reitan & Wolfson, 1985) Part A (seconds to complete) and the Wechsler Adult Intelligence Scale, fourth edition (WAIS-IV) (Wechsler, 2008) Digits Forward subtest (number of correct trials), respectively. Working memory was measured using the WAIS-IV Digits Backward subtest (number of correct trials). To assess executive functioning, TMT Part B (seconds to complete) was given. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) (Morris et al., 1989) Word List Memory Task (delay recall) was used to assess verbal memory. The Center for Epidemiologic Studies Depression Scale (CES-D) (Radloff, 1977) (total score) was used to measure depressive symptoms. Years of education served as the proxy for cognitive reserve.

Statistical Analyses

All statistical analyses were performed using IBM SPSS Statistics v25. Binomial logistic regression models were used to examine neuropsychological predictors of impaired self-awareness of deficits (1 = anosognosia; 0 = no anosognosia) for each of the six functional domains. Predictors included demographic variables (age, gender [male = 0; female = 1], education) along with neuropsychological test variables (DRS-2, TMT-A, TMT-B, Digits Forward, Digits Backward, CERAD Word List Memory Task, and CES-D). Statistical significance was set at p < .05.

Results

Table 2 displays the demographic characteristics of study participants. Table 3 presents neuropsychological test results for the study sample. With regard to objective tests of functional performance, two participants did not complete the TIADL Medication Management items and four participants were not current drivers and thus did not have an on-road driving evaluation. Additionally, on the MILES Self-Report Questionnaire, one participant did not complete the Grocery Shopping item and four did not complete the Nutrition Evaluation item. Due to this missing data, an anosognosia rating could not be calculated for these individuals on those particular IADLs and they were excluded from the respective analyses. Results of the primary analyses are reported in Table 4 and summarized by IADL in the following sections. Note that for variables with a significant odds ratio of less than 1 (indicating a negative relationship with anosognosia; e.g., DRS-2, CERAD Word List, gender), the percentages corresponding to the inverse odds are reported below.

Table 2.

Demographic characteristics of study participants (n = 103)

Variable N %
Age (years)
 54–64 13 13
 65–74 43 41
 75–88 47 46
Gender
 Male 49 48
 Female 54 52
Race
 Caucasian 92 89
 African-American 9 9
 Asian 2 2
Education
 Some high school 5 5
 High school diploma or GED 12 12
 Some college/associate’s degree 22 21
 Bachelor’s degree 29 28
 Additional college/graduate degree 35 34
Working at least part-time
 Yes 16 16
 No 87 84
Living arrangement
 Lives alone 19 18
 Lives with other(s) 84 82
Takes medication for memory loss
 Yes 57 55
 No 39 38
 Unknown 7 7
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Table 3.

Performance on neuropsychological testing

Raw score Z-scorea % Classified as impairedb
Instrument Min. Max. M SD M SD
Dementia Rating Scale, 2nd Edition (DRS-2) Total Score 108 144 130.2 8.0 −0.70 1.0 36
Center for Epidemiological Studies Depression Scale (CES-D) 0 35 9.5 7.6 — — 17c
Digits Forward (trials correct) 5 16 9.2 2.2 0.4d 0.9 0
Digits Backward (trials correct) 2 16 7.6 2.3
Trail Making Test, Part A (seconds) 20 169 51.6 23.0 −0.8 2.1 20
Trail Making Test, Part B (seconds) 40 300e 163.4 81.7 −2.8 4.7 43
CERAD Word List Memory Task (delay recall) 0 10 2.6 2.6 −2.6 1.5 76
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Abbreviations: CERAD, Consortium to Establish a Registry for Alzheimer’s Disease.

Note. For Trail Making Test and CES-D, higher raw score indicates worse performance and more depressive symptoms, respectively.

a

Z-scores (M = 0, SD = 1) calculated from test administration and scoring manuals and published normative data for the DRS-2 (Jurica, Leitten, & Mattis, 2001), Digits Forward and Backwards (Wechsler, 1997), Trail Making Test (Tombaugh, 2004), and CERAD Word List (Andel et al., 2003).

b

Calculated as the number of people whose performance fell 1.5 SD or more below the population mean on the test divided by the total number of people who took the test.

c

Eighteen participants (17%) had a score above the recommended clinical cut-off of 16 (Radloff, 1977).

d

Standardized score and % classified as impaired are provided for the sum of Digits Forward and Backwards as individual subtest z-scores were not available for analysis.

e

Test was discontinued after 5 min if participants were not finished and they were given a score of 300 seconds (n = 15).

Table 4.

Binomial logistic regression models predicting anosognosia on each instrumental activity of daily living based on demographic and neuropsychological variables

Financial management Driving Nutrition evaluation Grocery shopping Medication Management
OR 95% CI p OR 95% CI p OR 95% CI p OR 95% CI p OR 95% CI p
Age .98 .90–1.06 .605 1.07 .96–1.19 .222 1.20 1.06–1.35 .003 .99 .89–1.11 .889 .93 .84–1.03 .156
Gender 1.78 .53–5.94 .348 3.75 .84–16.68 .083 .22 .06–.82 .024 3.17 .58–17.41 .184 .79 .18–3.40 .746
Education 1.18 .94–1.49 .160 .92 .72–1.17 .484 .93 .72–1.18 .535 1.15 .86–1.54 .354 .89 .70–1.13 .330
CES-D .96 .90–1.03 .304 .93 .84–1.03 .160 1.05 .96–1.15 .261 .95 .86–1.05 .295 .95 .85–1.05 .314
DRS-2 Total Score .90 .82–.99 .023 .85 .75–.96 .009 .89 .80–.98 .024 .98 .87–1.10 .701 .87 .77–.98 .019
Digits Forward .96 .70–1.32 .795 1.10 .77–1.57 .612 .82 .58–1.17 .278 1.10 .72–1.68 .659 1.15 .78–1.70 .493
Digits Backward .84 .60–1.16 .291 1.15 .76–1.72 .514 .70 .47–1.03 .066 .78 .51–1.19 .254 .90 .61–1.32 .582
TMT-A .99 .96–1.02 .348 1.05 1.02–1.09 .005 .97 .93–1.01 .195 .98 .94–1.01 .318 .99 .95–1.02 .390
TMT-B 1.01 1.00–1.02 .007 1.00 .99–1.01 .446 1.00 .99–1.01 .522 1.01 1.00–1.03 .035 1.01 1.00–1.02 .111
CERAD Word List Delayed Recall .71 .53–.93 .015 .93 .65–1.33 .926 .96 .70–1.33 .822 1.21 .84–1.74 .303 1.23 .86–1.75 .265
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Abbreviations: CERAD, Consortium to Establish a Registry for Alzheimer’s Disease; CES-D, Center for Epidemiological Studies Depression Scale; CI, Confidence Interval; DRS-2, Dementia Rating Scale 2nd Edition; OR, Odds Ratio; TMT, Trail Making Test.

Note. Gender is for females compared to males. Results for Telephone Use domain not presented as none of the variables in the model significantly predicted anosognosia.

Bold indicates significance at p < .05.

Financial Management

Forty participants (39%) were classified as having objective difficulty on the FCI-SF, and of these individuals, 26 participants (65%) displayed poor insight into these deficits. The overall logistic regression model was statistically significant, χ2 (10) = 26.656, p < .01, and the model explained 34% (Nagelkerke R2) (Nagelkerke, 1991) of the variance in anosognosia and correctly classified 79% of cases. The odds of having anosognosia for financial management skills is: (a) 12% higher for every one-point decrease in DRS-2 total score (p < .05), (b) 41% higher for every one-point decrease in CERAD Word List delayed recall scores (p < .05), and (c) 1% higher for every one-second increase in time to complete TMT-B (p < .01). For comparison, these percentages change to 187% for the DRS-2 and to 10% for TMT-B when there is a 10-unit change in each variable (Note: Not calculated for CERAD Word List as 1-unit is a clinically significant interval for a test with a range of 0–10).

Driving

Twenty-eight participants (27%) were classified as having difficulty on the on-road driving evaluation and 23 of these individuals (82%) denied having any problems with driving. The overall logistic regression model was statistically significant, χ2 (10) = 39.689, p < .001, and the model explained 51% (Nagelkerke R2) of the variance in anosognosia and correctly classified 85% of cases. The odds of having anosognosia for driving difficulty is (a) 18% higher for every one-point decrease in DRS-2 total score (p < .01), and (b) 5% higher for every one-second increase in time to complete TMT-A (p < .01). For comparison, these percentages change to 407 and 62%, respectively, when there is a 10-unit change in each variable.

Nutrition Evaluation

Thirty-five individuals (34%) displayed difficulty on the TIADL Nutrition Evaluation domain. Moreover, 30 of those participants (86%) demonstrated poor awareness of their abilities in this area. The overall logistic regression model was statistically significant, χ2 (10) = 47.159, p < .001. The model explained 54% (Nagelkerke R2) of the variance in self-awareness and correctly classified 82% of cases. Several predictors in this model were statistically significant. The odds of having anosognosia for nutrition evaluation skills is (a) 20% higher for each additional year of age (p < .01), (b) 354% higher for men compared to the odds of having anosognosia in women (p < .05), and (c) 13% higher for every one-point decrease in DRS-2 total score (p < .05), or 220% higher for every 10-point decrease in DRS-2 total score.

Grocery Shopping

Thirteen participants (13%) had difficulty on the TIADL Grocery Shopping domain, and 11 of these participants (85%) had poor self-awareness into their problems with this task. The overall logistic regression model was not statistically significant, χ2 (10) = 12.037, p = .283. The model explained 23% (Nagelkerke R2) of the variance in anosognosia and correctly classified 87% of cases. The odds of having anosognosia for grocery shopping skills is 1% higher for every one-second increase in time to complete TMT-B (p < .05), or 10% higher for every 10-second increase in time to complete TMT-B.

Medication Management

Fifteen individuals (15%) were classified as having difficulty on the TIADL Medication Management domain. All but one of these participants (93%) had poor insight into this deficit. The overall logistic regression model was statistically significant, χ2 (10) = 18.812, p < .05, and the model explained 31% (Nagelkerke R2) of the variance in anosognosia and correctly classified 87% of cases. The odds of having anosognosia for medication management abilities is 15% higher for every one-point decrease in DRS-2 total score (p < .05), or 303% higher for every 10-point decrease in DRS-2 total score.

Telephone Use

Twenty-two (21%) participants demonstrated difficulty on the TIADL Telephone Use domain, and 16 of those participants (73%) denied problems with this IADL. The overall logistic regression model was statistically significant, χ2 (10) = 19.295, p < .05, and the model explained 31% (Nagelkerke R2) of the variance in anosognosia and correctly classified 85% of cases. However, impaired self-awareness was not significantly related to any demographic or neuropsychological variables.

Supplementary Analyses

Analyses assessing the relationship amongst predictors revealed that performance on the DRS-2 was correlated with TMT-A (r = −.235, p < .05), TMT-B (r = −.520, p < .01), and the CERAD Word List Memory Task (r = .534, p < .01); however, it is important to note that all variance inflation factors (VIFs) were well below the cutoff suggesting multicollinearity (Hair, Black, Babin, Anderson, & Tatham, 2006). Regardless, to bolster validity of findings, post hoc analyses were conducted in which the DRS-2 was removed from the models. Results for financial management, nutrition evaluation, and grocery shopping domains remained unchanged. However, with the DRS-2 excluded from models, the CERAD Word List Memory Task became a significant predictor of anosognosia for driving skills (OR = .71, 95% CI = .51–.98, p < .05), and TMT-B became a significant predictor of anosognosia for telephone use (OR = 1.01, 95% CI = 1.00–1.02, p < .05) and medication management ability (OR = 1.01, 95% CI = 1.00–1.02, p < .05).

Additional supplementary analyses were conducted in order to ensure that original results were not driven entirely by the minority of participants classified as having mild dementia (n = 13). First, a diagnostic breakdown of individuals classified as having anosognosia was conducted for each functional domain. Out of those with anosognosia, the following number were classified as having mild dementia: Financial Management (3 out of 26), Driving (5 out of 23), Telephone Use (4 out of 16), Nutrition Evaluation (5 out of 30), Grocery Shopping (2 out of 11), and Medication Management (5 out of 14). In addition, original models (with all demographic and cognitive predictors) were re-analyzed excluding those 13 individuals with mild dementia. With these individuals excluded, results remained relatively unchanged with the exception of one notable difference: TMT-B was no longer a predictor of anosognosia for grocery shopping deficits but became a significant predictor of anosognosia for telephone use difficulties (OR = 1.02, 95% CI = 1.00–1.03, p < .05).

Discussion

The current study examined the relationship between neuropsychological functioning and self-awareness of functional deficits in older adults with MCI and mild dementia. Importantly, self-awareness was assessed across six separate IADLs (financial management, driving, nutrition evaluation, grocery shopping, telephone use, and medication management) by examining the discrepancy between self-reported functioning and objective measures of each IADL. We hypothesized that anosognosia would be associated with worse global cognition, verbal memory, attention, executive function, and cognitive reserve, and would be associated with fewer symptoms of depression.

We found that 13% (grocery shopping) to 39% (financial management) of our sample had objective difficulty on IADL performance depending on the specific domain. Moreover, of those with difficulty, 65% (financial management) to 93% (medication management) displayed impaired insight into their deficits. These results are consistent with literature that suggests that individuals with MCI begin to display decrements in speed and accuracy of their everyday functional abilities (Lassen-Greene et al., 2017) and that anosognosia of these abilities is a clinically significant phenomenon in persons with neurodegenerative disease (Amanzio et al., 2016; Okonkwo et al., 2009; Okonkwo et al., 2008).

Additionally, our findings confirmed a relationship between cognition and self-awareness of functional deficits in older adults with MCI and mild dementia, and this relationship varied somewhat based on the specific IADL. In summary, global cognition was the most consistent predictor of self-awareness across functional domains. Lower global cognition was associated with anosognosia for financial management, driving, nutrition evaluation, and medication management skills. Those with more impaired verbal memory were more likely to lack awareness into their problems with financial management (and when the effect of global cognition was removed, also driving). Similarly, those who performed more poorly on a measure of basic visual attention were more likely to have anosognosia for driving deficits. Worse executive function performance was associated with anosognosia for financial management and grocery shopping skills (and when the effect of global cognition was removed, also telephone use and medication management domains). One caveat to these findings is that approximately 15% of our participants displayed a floor effect on our measure of executive functioning (TMT-B), which may have negatively impacted our ability to detect predictor effects. Finally, older age and male gender were associated with anosognosia for nutrition evaluation deficits. In contrast, basic auditory attention, working memory, depressive symptoms, nor cognitive reserve (i.e., years of education) were significantly related to self-awareness for any functional domain in our overall models.

Our results support the CAM (Agnew & Morris, 1998; Morris & Mograbi, 2012), which theorizes that accurate awareness of current abilities is reliant on attentional, memory, and executive functioning systems, and a breakdown in one or more of these cognitive systems could lead to impaired metacognition. Findings from the current study suggest that anosognosia for different functional domains may arise from failures at different step(s) in this model. This might explain why some patients lack insight into their performance in one area but retain good awareness for another domain. This model could also explain how patients at a similar stage of disease process evidence different levels of insight into their current abilities.

Given that self-awareness is reliant on several higher-order cognitive functions, it follows that we would find that a measure of dementia severity and global cognition would generally be the most predictive of anosognosia, consistent with findings in the literature (Kalbe et al., 2005; Karlawish et al., 2005; Kashiwa et al., 2005; Okonkwo et al., 2008; Tremont & Alosco, 2011; Vogel et al., 2005; Vogel et al., 2004). An important caveat of our findings is that our measure of global cognition, the DRS-2, encompasses aspects of a variety of cognitive domains and may have diminished the relationship between anosognosia and other cognitive domains assessed in the study, in particular verbal memory (driving domain) and executive functioning (telephone use and medication management domains). It is also potentially true that anosognosia may be predicted by specific cognitive domains assessed by the DRS-2 that were not otherwise assessed in the current study, such as conceptualization, initiation/perseveration, visuo-construction, and visual memory.

Of note, we did not find a relationship between cognitive reserve and self-awareness. It is possible that our proxy for cognitive reserve, years of education, was not an accurate measure of this concept and another measure of reserve, such as IQ or estimates of educational quality (e.g., word reading tests) may be better estimates (Stern, 2002). Another likelihood is that we did not have sufficient variability in our sample since 62% of our sample had at least 16 years of education. We also did not find a relationship between depressive symptoms and self-awareness of deficits. Prior literature found that depression is often related to an over-reporting of symptoms (i.e., more subjective complaints than objectively exist) (Kashiwa et al., 2005; Okonkwo et al., 2008; Smith et al., 2000). Since our primary interest was in examining predictors of anosognosia, we collapsed our accurate- and over-estimators into one group, which likely affected the ability to detect a relationship between depression and insight.

There are a few important limitations to the current study that necessitate discussion. First, the cross-sectional design of this study limits the ability to distinguish between causal and correlational relationships between cognition and anosognosia. Moreover, we are unable to evaluate how these relationships may change over time or whether they can predict rate of conversion to dementia. Secondly, our sample size required relatively parsimonious statistical models, and therefore we did not include other important cognitive domains that may contribute to self-awareness, such as visual memory, language, visuospatial skills, and additional aspects of executive functioning. Third, we chose to evaluate the concept of anosognosia using a categorical rather than continuous variable. This method was in part selected to aid in maintaining consistency in making anosognosia classifications across IADLs that used different psychometric instruments to evaluate objective and subjective performance. Although this method is consistent with the literature (Ford et al., 2014; Marshall et al., 2004; Nobili et al., 2010; Okonkwo et al., 2009) and also eases clinical interpretability of findings, we acknowledge that a dichotomous classification of anosognosia vs. no anosognosia eliminates much of the individual variability in insight and becomes more subject to confounding by the underlying level of impairment. Finally, future studies should include participants with increased diversity with regards to race and ethnicity, educational background, socioeconomic status, and referral source/diagnostic classification. Our participants were clinic-referred individuals predominantly diagnosed with amnestic MCI and primarily white, well-educated, and affluent, which likely limits the generalizability to other populations that may have a wider range of cognitive reserve, neuropsychological test performance, and experience with the IADLs assessed in this study (e.g., owning and regularly driving a car or managing finances and investments).

Notwithstanding these limitations, there are a number of methodological strengths to the current study. To our knowledge, this is the first study to examine the neuropsychological correlates of anosognosia for functional abilities: (a) across a variety of IADLs important for everyday functioning, (b) by evaluating self-awareness using a subjective vs. objective performance approach, (c) by recruiting a relatively large sample size including older adults with well-characterized diagnoses ranging from SCC to mild dementia, and (d) by including a number of cognitive and psychological predictors using well-established neuropsychological instruments.

Individuals with anosognosia underreport IADL difficulties to their family members and medical providers, which could delay diagnosis and treatment. This issue is critical given that these same individuals are at higher risk for converting to dementia (Tabert et al., 2002). Medical providers should be cautioned against reliance on self-reported symptoms in this population and collect informant reports and objective ratings when possible. Moreover, patients who lack insight and fail to report their functional difficulties may delay the implementation of behavioral interventions such as home modifications or increased supervision and aid from caregivers. This poses both an individual and public safety risk given that they are likely to continue engaging in IADLs that they are no longer cognitively capable of performing independently, such as driving, managing their medications, cooking, and handling finances. We hope that the results of this study will aid in understanding the underlying cognitive mechanisms of anosognosia and improve identification of individuals with impaired self-awareness of their functional deficits.

Funding

This work was supported by the National Institute on Aging (R01 AG045154, Virginia Wadley Bradley, PI); facilities and resources were also provided by the Edward R. Roybal Center at the University of Alabama at Birmingham (P30 AG022838).

Conflict of Interest

None declared.

Acknowledgements

The authors would like to thank Jesse Passler, Cheyenne Barba, and Caroline Lassen-Greene for their assistance in participant assessment. We would also like to acknowledge Marianne McLaughlin for her administrative assistance and role in study coordination and Drs David Geldmacher and Daniel Marson for referral of study participants. Finally, the authors thank the participants and their families for taking part in this study.

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