R.-Y. Chao1, T.-F. Chen2, Y.-L. Chang1,2,3,4
1. Department of Psychology, College of Science, National Taiwan University, Taipei, Taiwan (R.O.C.); 2. Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan; 3. Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan; 4. Center for Artificial Intelligence and Advanced Robotics, National Taiwan University, Taipei, Taiwan
Corresponding Author: Yu-Ling Chang, PhD (ORCID: 0000-0003-2851-3652), Department of Psychology, College of Science, National Taiwan University, No. 1, Section 4, Roosevelt Rd, Taipei 10617, Taiwan. Tel/Fax: +886-2-33663105/ +886-2-23629909; E-mail address: firstname.lastname@example.org
J Prev Alz Dis 2020;
Published online October 28, 2020, http://dx.doi.org/10.14283/jpad.2020.61
Background: Although evidence suggests that subjective memory complaints (SMCs) could be a risk factor for dementia, the relationship between SMCs and objective memory performance remains controversial. Old adults with or without mild cognitive impairment (MCI) may represent a highly heterogeneous group, based partly on the demonstrated variability in the level of executive function among those individuals. It is reasonable to speculate that the accuracy of the memory-monitoring ability could be affected by the level of executive function in old adults.
Objective: This study investigated the effects of executive function level on the consistency between SMCs and objective memory performance while simultaneously considering demographic and clinical variables in nondemented older adults.
Setting: Participants were recruited from both the memory clinics and local communities.
Participants: Participants comprised 65 cognitively normal (CN) older adults and 54 patients with MCI.
Measurements: Discrepancy scores between subjective memory evaluation and objective memory performance were calculated to determine the degree and directionality of the concordance between subjective and objective measures. Demographic, emotional, genetic, and clinical information as well as several executive function measurements were collected.
Results: The CN and MCI groups exhibited similar degrees of SMC; however, the patients with MCI were more likely to overestimate their objective memory ability, whereas the CN adults were more likely to underestimate their objective memory ability. The results also revealed that symptoms of depression, group membership, and the executive function level together predicted the discrepancy between the subjective and objective measures of memory function; however, the executive function level retained its unique predictive ability even after the symptoms of depression, group membership, and other factors were controlled for.
Conclusion: Although both noncognitive and cognitive factors were necessary for consideration, the level of executive function may play a unique role in understanding the equivocal relationship of the concurrence between subjective complaints and objective function measures. Through a comprehensive evaluation, high-risk individuals (i.e., CN individuals heightened self-awareness of memory changes) may possibly be identified or provided with the necessary intervention during stages at which objective cognitive impairment remains clinically unapparent.
Key words: Aging, awareness, mild cognitive impairment, memory complaints.
Subjective memory complaints (SMCs), commonly observed in older adults, refer to the self-perception of memory decline that does not require confirmation by cognitive tests. Recent studies on SMCs have revealed that they are associated with underlying brain morphometric changes (1) or increased β-amyloid deposition (2), which is consonant with dementia pathology (3).
Although evidence suggests that SMCs could be a risk factor for dementia (4, 5), the relationship between SMCs and objective memory performance remains controversial. Some studies have reported SMCs to be associated with a decline in objective memory performance (6), whereas other studies have not reported such an association (7, 8). Noncognitive factors, such as old age (9, 10), female gender (11), appearance of health conditions (e.g., hypertension and diabetes mellitus) (9, 12), low education level (9), apolipoprotein E ε4 (ApoE ε4) allele (10, 13), and depression (8-10), could also contribute to the appearance of SMCs and confound the association between SMCs and objective memory performance.
In addition to the noncognitive factors, one aspect that is crucial but has often been overlooked in studies examining the concurrence between subjective and objective memory changes is individual differences in metamemory ability. Metamemory, an aspect of high executive function level (14), is an individual’s self-awareness of his or her own memory contents and capacities. Furthermore, it is the ability of an individual to monitor or judge his or her own learning and memory efficiency. Although an age-related decline in metamemory function has been observed (15, 16), evidence suggests that aging populations, including cognitively normal (CN) older adults and individuals with mild cognitive impairment (MCI), may represent a highly heterogeneous group, based partly on the demonstrated variability in the level of executive function among those individuals (17). Accordingly, it is reasonable to speculate that the accuracy of the memory-monitoring ability could be affected by the level of executive function in both CN older adults and patients with MCI.
Thus, the aim of the present study was to examine the relationship between the level of executive function and the accuracy of SMCs while simultaneously considering noncognitive factors (including demographic variables, mood, ApoE ε4 status, and health conditions) in CN older adults and patients with MCI. To evaluate the accuracy of SMCs, we calculated the discrepancy scores between the self-reported memory concerns using a memory questionnaire and objective memory performance based on standardized neuropsychological tests, which enabled us to evaluate the accuracy of SMCs in two directions (i.e., overestimation or underestimation of objective memory performance). A lower level of executive function was hypothesized to be associated with a higher discrepancy between the subjective report of memory function and objective measurement using standardized memory tests in both CN older adults and patients with MCI, even after controlling for noncognitive (e.g., demographic variables) or clinical (e.g., health conditions and ApoE ε4 status) factors.
Materials and methods
The present study included 119 older adults, of whom 65 and 54 were classified as CN older adults and patients with MCI, respectively. Among the participants, 89 participants (48 CN and 41 MCI) were recruited from memory clinics, and 30 (17 CN and 13 MCI) were through community advertising. Individuals with any current evidence of major neurological diseases that may affect central nervous system function, psychiatric disorders, or a history of substance abuse were excluded.
Participants received a diagnosis of MCI according to the criteria recommended by the International Working Group (18). Specifically, the criteria for MCI were as follows: (1) absence of dementia, (2) defective performance on objective neuropsychological tests, and (3) generally preserved basic daily activities or the slightest impairment in instrumental activities. The objective cognitive decline was determined using the directive suggested by Jak et al. (19): the presence of at least two test scores within a cognitive domain (i.e., memory or executive function) on available neuropsychological tests (Table 1) that were one or more standard deviations less than the age-appropriate norms. Different MCI subtypes could be classified according to the aforementioned guideline. The present sample consisted of 23 patients with amnestic MCI single domain, 29 with amnestic MCI multiple domains, and 2 with nonamnestic MCI single domain. The present study was approved by the Ethics Committee and Institutional Review Board at the National Taiwan University Hospital according to the Declaration of Helsinki. Written informed consent was obtained from all participants.
Neuropsychological and Clinical Measures
A neuropsychological battery was administered to all participants. The measures included five executive function tests, namely the Matrix Reasoning and Similarities subtests of the Wechsler Adult Intelligence Scale-III (WAIS-III), category fluency test (animal and fruit), Modified Card Sorting Test (MCST), and Color Trails Test (CTT-1 and -2). A composite z-score was computed to represent each participant’s relative executive function level; the greater the positive number, the better performance it represented. Specifically, the raw score of participants’ performance on each executive function measure was first transformed into a z-score based on the norms obtained from the entire participant pool in the present study. Because lower scores (indicating that less time was required to complete the task) on the CTT reflect higher performance, the z-score of the CTT was inverted to ensure unidirectionality prior to averaging the z-scores of the five tests.
Four episodic memory tests were administered in the present study, namely the logical memory (LM) test, the visual reproduction (VR) test, the visual paired associates (VP) subtests of the Wechsler Memory Scale-III (WMS-III) (20), and the California Verbal Learning Test-II (CVLT-II) (21). A z-transforming memory composite score representing the relative performance on the episodic memory test was computed for each participant by using the method previously described; thus, a positive number represented higher memory performance. Notably, although all the four memory tests were used to classify participants’ group membership (i.e., CN versus MCI), to match the SMC subscales selected in the present study, only the two verbal episodic memory tests, namely the LM and CVLT-II, were used to compute episodic memory composite scores and for following analyses, which included both immediate (LM I, and CVLT-II List A 1-5 total recall) and delayed (LM II, and CVLT-II long-delayed free recall) recall scores.
SMCs were assessed using the Memory Complaints Inventory (22), which consisted of nine subscales designed to tap different types of reported memory problems: General Memory Problems, Verbal Memory Problems, Numeric Information Problems, Visuospatial Memory Problems, Pain Interferes with Memory, Memory Interferes with Work, Impairment of Remote Memory, Amnesia for Complex Behavior, and Amnesia for Antisocial Behavior. The first six subscales of the inventory included plausible memory complaints, and the last three subscales were intentionally designed to detect individuals with a tendency to exaggerated or feigned memory complaints. In the present study, we included scores from two subscales, namely the General Memory Problems and Verbal Memory Problems, for further analysis to sufficiently match the nature of the objective memory tests used in the present study. Lower scores on the self-evaluated questionnaire reflect a lower endorsement of memory problems by an individual. A z-transforming SMC composite score was calculated to indicate the level of endorsement of memory problems for each individual; to maintain consistency with the direction of objective memory test results, the z-scores of the SMC scores based on the questionnaire were inverted before calculating discrepancy scores. Additionally, the Framingham Stroke Risk Profile (FSRP) (23) and the Geriatric Depression Scale-Short Form (GDS-S) (24) were included to survey the participants’ cerebrovascular burden and depression status, respectively. The ApoE genotyping was conducted based on the method previously published (25), and participants were classified as ApoE ε4 carriers or non-carriers based on the appearance of at least on ε4 allele or not.
Discrepancy between Subjective and Objective Memory Evaluation
We used a modified discrepancy measure based on Miskowiak et al. (26) Specificially, the discrepancy between SMCs and objective memory performance was calculated for each participant by subtracting the standardized objective memory composite z-scores from the inversed z-transforming SMC scores. A positive value of the discrepancy score was considered to indicate that the participants’ rank ordering for their subjective evaluation was higher than their objective performance; that is, they overestimated their objective memory functioning. By contrast, a negative value of the discrepancy score was considered to indicate an underestimation of their objective memory function. Scores near zero were considered to indicate relatively high concordance between self-evaluated memory function and objective memory performance.
Group differences were compared using analysis of variance, t-test, analysis of covariance, or chi-square tests. Statistical significance for demographic and clinical variables were set at an alpha level of 0.05, whereas the significance level for neuropsychological measures was set at p < 0.003 based on Bonferroni correction to avoid inflated type I errors. The discrepancy scores were checked for normal distribution using the Kolmogorov–Smirnov test, and the result indicated that it did not violate the null hypothesis (p > 0.20, with a mean score of 0.01, standard deviation [SD] = 1.53).
Hierarchical regression analyses were conducted to examine the predictive ability of the level of executive function for determining the discrepancy between subjective and objective memory evaluations; the corresponding alpha level was set at 0.05. Specifically, demographic variables including age, sex, and education were considered simultaneously in the first step. Subsequently, clinical variables, including FSRP, depressive state, ApoE ε4 status, and group membership (i.e., CN versus MCI), were considered in the second step. Finally, the composite z-score of executive function level was considered in the third step. All statistical analyses were conducted using SPSS (version 22.0. IBM Corp, Armonk, NY, USA).
Demographics, Clinical Data, and Neuropsychological Performance
The two groups differed in age (F(1, 117) = 10.49, p = 0.002), education (F(1, 117) = 9,32, p = 0.003), and FSRP (F(1, 117) = 6.02, p = 0.016,Table 1), but they did not differ in the distribution of sex (χ2(2, N = 119) = 0.44, p > 0.05), frequency of ApoE ε4 carriers (χ2(2, N = 119) = 0.20, p > 0.05), scores on the depression measures (F(1, 117) = 1.39, p > 0.05), or distribution of recruitment source by the diagnostic group (χ2(2, N = 119) = 0.07, p > 0.05).
Abbreviations: CN, cognitively normal; CVLT-II, California Verbal Learning Test; FSRP, the Framingham Stroke Risk Profile; GDS-S, Geriatric Depression Scale-Short Form; GMCI, Green’s Memory Complaints Inventory; LM, Logical Memory; MCI, mild cognitive impairment; MCST, Modified Card Sorting Test; EF z-score, executive function composite z-score; VP, Visual Paired Associate; VR, Visual Reproduction Associate; η2, effect size of analysis of variance or analysis of covariance; SD, standard deviation; * p < 0.05. ** p < 0.003 (Bonferroni correction); †Group difference controlling for age, education, and FSRP. ‡ Time difference was calculated by subtracting CTT-1 from CTT-2.
After the effects of age, education, and FSRP were controlled for, the performance of the CN group was higher than that of the MCI group on all executive function measures (see Table 1), including the WAIS-III Matrix Reasoning subtest (F(1, 113) = 18.19, p < 0.001), VF (F(1, 113) = 14.08, p < 0.001), MCST (F(1, 114) = 26.40, p < 0.001), and executive function composite z-score (F(1, 114) = 30.68, p < 0.001), except for the WAIS-III Similarities subtest (F(1, 113) = 6.60, p > 0.003) and CTT measure (i.e., CTT-2 − CTT-1; F(1, 114) = 6.08, p > 0.003). Furthermore, the performance of the CN group was higher than that of the MCI group on all episodic memory measures, including the immediate recall (F(1, 114) = 33.31, p < 0.001), delayed recall (F(1, 114) = 55.19, p < 0.001), and delayed recognition (F(1, 114) = 43.51, p < 0.001) of the WMS-III VR subtests; immediate (F(1, 114) = 39.61, p < 0.001) and delayed recall (F(1, 114) = 26.01, p < 0.001) of the VP subtests; immediate (F(1, 114) = 44.21, p < 0.001) and delayed recall (F(1, 114) = 57.90, p < 0.001) of the LM subtest; immediate List A 1-5 total recall (F(1, 112) = 99.68, p < 0.001) and long-delayed free recall (F(1, 112) = 106.55, p < 0.001) of the CVLT-II; and episodic memory composite z-score (F(1, 114) = 105.36, p < 0.001).
Subjective and Objective Memory Discrepancy Measures
No differences in the SMC scores were observed between the groups (F(1, 114) = 1.12, p > 0.05) after age, education, and FSRP were controlled for. In addition, no differences in the SMC scores were observed by recruitment source of participants in the CN group (T(63) = -1.03, p > 0.05) or in the MCI group (T(52) = -1.38, p > 0.05). However, the absolute discrepancy score values differed between the two groups (F(1,114) = 14.60, p < 0.001, eta square = 0.11) after the effects of age, education, and FHS-stroke risk were controlled for; in which the CN group exhibited a relatively higher accuracy (i.e., values trended toward zero regardless of the directionality) than the MCI group in estimating objective memory. Furthermore, the two groups demonstrated significant differences in discrepancy scores (F(1, 114) = 16.71, p < 0.001) when directionality (i.e., overestimation versus underestimation) was considered and age, education, and FSRP were controlled for. We observed that this differential pattern of discrepancy scores remained significant even after further controlling for the level of executive function (F(1, 113) = 7.50, p = 0.007, η2 = 0.06); this finding suggests that the CN group, despite its relatively high objective memory performance, tended to endorse more memory complaints than the MCI group did, but the MCI group exhibited an opposite pattern.
We also compared the frequencies of overestimation and underestimation of memory function between the two groups by dichotomizing the discrepancy scores (i.e., ≥0 and <0). The results showed that the two groups exhibited significant differences in the frequency distribution of the two discrepancy categories (χ2(2, N = 119) = 19.13, p < 0.001). The number of participants underestimating their objective memory ability was higher in the CN group than in the MCI group, whereas that of participants overestimating their objective memory ability was higher in the MCI group than in the CN group (Figure 1). We further analyzed the demographic and clinical characteristics of the two subgroups (i.e., underestimation versus overestimation of objective memory ability) in each of the CN and MCI groups. Within the CN group, the underestimation and the overestimation subgroups did not differ in age (T(63) = -1.16, p = > 0.05), education(T(63) = 0.43, p = > 0.05), distribution of sex (χ2(1, N = 65) = 1.87, p > 0.05), FSRP (T(63) = -1.03, p = > 0.05), frequency of ApoE ε4 carriers (χ2(1, N = 65) = 3.11, p > 0.05), depression status(T(63) = 0.83, p > 0.05), or executive function (T(63) = 1.61, p > 0.05). Notably, a trend of higher executive function was observed among CN participants who underestimated their memory ability (executive function z-score = 0.44 ± 0.53) compared with those who overestimated their memory ability (executive function z-score = 0.22 ± 0.54). Similarly, within the MCI group, the underestimation and the overestimation subgroups did not differ in age (T(52) = -1.90, p = > 0.05), education (T(52) = 0.58, p = > 0.05), distribution of sex (χ2(1, N =54) = 0.02, p > 0.05), frequency of ApoE ε4 carriers (χ2(1, N =54) = 0.89, p > 0.05), or depression status(T(52) = 0.19, p = > 0.05), but the subgroup with overestimation of objective memory ability demonstrated a higher FSRP score(T(52) = -2.43, p = 0.001, FSRP score = 16.6% ±12.15) and marginally lower executive function (T(52) = 1.87, p = 0.06, executive function z-score = -0.54 ± 0.70) compared to the underestimation subgroup (FSRP score = 8.5% ± 4.38; executive function z-score = -0.16 ± 0.57).
Notably, when participants were classified into small (i.e., z-scores within the range between +1 to −1) versus large discrepancy scores (z-scores > + 1 or < −1) without considering the directionality of the scores, significantly more MCI patients (55.6%) obtained large discrepancy scores, indicating a larger misjudgment for their memory ability compared than for the CN group (26.2%) (χ2(1, N = 119) = 10.67, p = 0.001). We further analyzed the demographic and clinical characteristics of the two subgroups (i.e., small versus large discrepancy) in each of the CN and MCI groups. Within the CN group, the two subgroups did not differ in age (T(63) = 0.24, p = > 0.05), education(T(63) = -0.99, p = > 0.05), distribution of sex (χ2(1, N = 65) = 0.80, p > 0.05), FSRP (T(63) = -0.68, p = > 0.05), frequency of ApoE ε4 carriers (χ2(1, N = 65) = 1.42, p > 0.05), or depression score (T(63) = -0.97, p > 0.05). The two subgroups did not differ in executive function (T(63) = −0.96, p > 0.05). However, a trend toward higher executive function was observed among those with a greater degree of misjudgment (executive function z-score = 0.48 ± 0.51) compared with patients with mild misjudgment (executive function z-score = 0.33 ± 0.55). Within the MCI group, the two subgroups did not differ in age (T(52) = -1.22, p = > 0.05), education (T(52) = -0.72, p = > 0.05), distribution of sex (χ2(1, N =54) = 0.84, p > 0.05), FSRP score (T(52) = -0.31, p > 0.05), frequency of ApoE ε4 carriers (χ2(1, N =54) = 0.73, p > 0.05), depression score (T(52) = 1.37, p = > 0.05), or executive function (T(52) = 0.17, p > 0.05).
Relationships between Executive Function Level and Discrepancy Score
Hierarchical multiple regression analysis (Table 2) demonstrated that increased endorsement of depressive symptoms predicted negative discrepancy scores (i.e., increase in self-reporting of memory concerns and an underestimation of objective memory ability) (β = −0.17, p = 0.046), and diagnosis of MCI predicted positive discrepancy scores (i.e., overestimation of objective memory ability) (β = 0.26, p = 0.008). Moreover, the level of executive function (β = −0.24, ΔR2 = 0.03, p = 0.027) explained the unique variances in the discrepancy scores in addition to the demographic and clinical variables; a higher level of executive function was associated with underestimation of objective memory ability (Figure 2).
Abbreviations: FSRP, the Framingham Stroke Risk Profile; GDS-S, Geriatric Depression Scale-Short Form; Group, participants were classified as cognitively normal older adults or patients with mild cognitive impairment; ApoE ε4: participants were classified as ApoEε4 carriers or noncarriers; EF z-score, executive function composite z-score. * p < 0.05; ** p < 0.01.
The primary objective of this study was to investigate the effect of the level of executive function on the consistency between SMCs and performance on objective memory function measures while considering demographic (e.g., age, education, and sex), emotional (i.e., symptoms of depression), and clinical (e.g., ApoEε4 status, and health conditions related to cardiovascular risk factors) variables in a sample comprising CN older adults and patients with MCI. An analysis of the discrepancy scores between the subjective and objective measures revealed that although the symptoms of depression, group membership, and level of executive function together predicted the discrepancy between the subjective and objective measures of memory performance, the level of executive function retained its predictive ability even after the symptoms of depression, group membership, or other factors were controlled for.
In this study, we used five executive function measures to assess the relationships between the level of executive function and the consistency between the subjective and objective measures of memory functioning; these five measures were thought to involve prefrontal function (27) and were essential for successful self-monitoring (28), such as reasoning, ability to use external feedback to modify thinking or behavior, and shifting and updating information. As predicted, we found that a lower level of executive function was associated with a greater degree of discrepancy between subjective and objective measures of memory function in our sample of elderly participants. This result is consistent with the emerging literature that has demonstrated a relationship between reduced awareness of memory loss and frontal lobe dysfunction in patients with Alzheimer disease (29) and MCI (30).
Another critical finding in this study was that the CN group generally had higher accuracy in estimating their memory ability compared with the MCI group, despite the CN and MCI groups exhibiting similar degrees of memory complaints. Furthermore, group membership predicted the discrepancy scores. Notably, the two groups exhibited different patterns of discrepancy scores: The participants in the CN group were more likely to underestimate their objective memory ability. However, 63% (27 out of 43) of participants in the underestimation subgroup underestimated their memory ability within a relatively mild range (i.e., discrepancy z-scores > −1). By contrast, the participants in the MCI group were more likely to overestimate their objective memory ability. Such findings appear to be consistent with those of a recent study by Fragkiadaki et al. (31), who used an “in-session” cognitive efficiency measure and found that CN older adults underestimated their performance, whereas patients with MCI overestimated their performance on a task. This inclination to underestimate actual performance was also reported by Vannini et al. (30) in CN older people with β-amyloid deposition; the authors introduced the term “hypernosognosia” to indicate that heightened memory self-awareness may be the first stage of progression toward Alzheimer disease in a hypothetical memory awareness model. Notably, the subset of CN participants in the present study with a larger degree of underestimation (i.e., discrepancy z-scores < −1) of their objective memory ability exhibited a trend of higher executive function compared with participants with mild underestimation of their memory ability. Despite its counterintuitive nature, our findings may suggest that individuals with hypernosognosia may have relatively high self-monitoring ability and may have experienced some memory loss relative to a previously higher baseline memory function, which could not be captured by the neuropsychological tests employed here. Although we attempted to include multiple measures of memory in the present study to ensure the reliability and sensitivity of the measurements, these measures might still not be sufficiently sensitive to detect subtle within-person memory declines, because the calculations of the objective memory index are completely based on comparisons with group norms. Consequently, the CN older adults with hypernosognosia may represent a group of people who are at risk of dementia in the future, particularly when factors such as symptoms of depression or healthy conditions, which could potentially confound the interpretations of their “worries,” were considered. Following up CN older adults with hypernosognosia longitudinally to further examine such a hypothesis is crucial.
Consistent with accumulating studies that have regarded depression as a crucial factor accounting for SMCs (32), in the present study, we also observed that an increase in the symptoms of depression was predictive of an increase in self-reporting of memory concerns and an underestimation of memory ability. Previous studies have indicated that a higher frequency of SMCs were strongly associated with a higher number of depressive symptoms, regardless of the objective cognitive performance (8). By contrast, other evidence indicates late-life depression to be a risk factor for progression to dementia (32). Although the exact relationships among depressive symptoms, SMC, and objective cognitive function warrant further investigation, the present study extends previous findings by demonstrating that the contribution of the level of executive function is crucial because its contribution to the concurrence between subjective and objective measures is unique and is separate from that of the symptoms of depression per se.
Despite the potential clinical value of our findings, our study has limitations. First, we included only depressive symptoms in the analyses, and we did not consider other affective (e.g., anxiety) or personality factors, which might also affect the concurrence between the objective and subjective memory measures as reported by previous studies (32, 33). Second, the cross-sectional design of the present study precluded us from investigating the relationship among the level of executive function, discrepancy scores, and subsequent function declines. This design also limited our ability to examine the linear continuum versus nonlinear evolution from SCD to MCI. In addition, the sample size of the current study was relatively small, particularly when considering the number of predictive variables used for the regression model. The small sample size also prevented us from clarifying the heterogeneity among the older adults, particularly among the patients with MCI. Despite the aforementioned limitations, the present study is the first to consider various factors in investigating the directionality of the concurrence between subjective and objective memory function. We also extend previous studies by using a more ecologically relevant self-report measure to survey the individuals’ subjective memory concerns and objectively measure memory function through standardized cognitive tests.
In conclusion, the present study reveals the complexity involved in understanding the meaning of SMCs. Although both noncognitive and cognitive factors were necessary for consideration, the level of executive function may play a unique role in understanding the equivocal relationship of the concurrence between subjective complaints and objective function measures in the literature. Through a comprehensive evaluation, high-risk individuals (i.e., CN individuals with hypernosognosia) may possibly be identified or provided with the necessary intervention during stages at which objective cognitive impairment remains clinically unapparent. Inclusion of biomarkers and longitudinal follow-up data can provide additional information on the neural mechanism underlying the discordance.
Funding: This work was supported by the Taiwan Ministry of Science and Technology (grant numbers 107-2314-B-182A-065 and108-2410-H-002-106-MY2 to Y.L.C.). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.
Acknowledgements: The authors thank Yen-Shiang Chiu, Chia-Hua Lin, and Yi-Yuan Zhuo for assistance in data collection, and Dr. Jung-Lung Hsu for constructive feedbacks.
Conflict of interest: The authors have no conflict of interest to report.
Ethical Standards: The institutional Review Board(IRB) approved this study, and all participants gave informed consent before participating.
1. Peters F, Villeneuve S, Belleville S. Predicting progression to dementia in elderly subjects with mild cognitive impairment using both cognitive and neuroimaging predictors. J Alzheimers Dis 2014;38(2): 307-18..
2. Wolfsgruber S, Polcher A, Koppara A, Kleineidam L, Frolich L, Peters O, et al. Cerebrospinal Fluid Biomarkers and Clinical Progression in Patients with Subjective Cognitive Decline and Mild Cognitive Impairment. J Alzheimers Dis, 2017.
3. Jessen F, Wolfsgruber S, Wiese B, Bickel H, Mosch E, Kaduszkiewicz H, et al. AD dementia risk in late MCI, in early MCI, and in subjective memory impairment. Alzheimers Dement 2014;10(1): 76-83.
4. Buckley RF, Maruff P, Ames D, Bourgeat P, Martins RN, Masters CL, et al. Subjective memory decline predicts greater rates of clinical progression in preclinical Alzheimer’s disease. Alzheimers Dement 2016;12(7): 796-804.
5. Abner EL, Kryscio RJ, Caban-Holt AM, Schmitt FA. Baseline subjective memory complaints associate with increased risk of incident dementia: the PREADVISE trial. J Prev Alzheimers Dis 2015;2(1): 11-16.
6. Seo EH, Kim H, Lee KH, Choo IH. Altered Executive Function in Pre-Mild Cognitive Impairment. J Alzheimers Dis 2016;54(3): 933-40.
7. Edmonds EC, Delano-Wood L, Galasko DR, Salmon DP, Bondi MW, Alzheimer’s Disease Neuroimaging I. Subjective cognitive complaints contribute to misdiagnosis of mild cognitive impairment. Journal of the International Neuropsychological Society : JINS 2014;20(8): 836-47.
8. Zlatar ZZ, Muniz M, Galasko D, Salmon DP. Subjective Cognitive Decline Correlates With Depression Symptoms and Not With Concurrent Objective Cognition in a Clinic-Based Sample of Older Adults. The journals of gerontology Series B, Psychological sciences and social sciences, 2017.
9. Chen ST, Siddarth P, Ercoli LM, Merrill DA, Torres-Gil F, Small GW. Modifiable risk factors for Alzheimer disease and subjective memory impairment across age groups. PloS one 2014;9(6): e98630.
10. Chhetri JK, de Souto Barreto P, Cantet C, Cesari M, Coley N, Andrieu S, et al. Trajectory of the MAPT-PACC-Preclinical Alzheimer Cognitive Composite in the Placebo Group of a Randomized Control Trial: Results from the MAPT Study: Lessons for Further Trials. J Prev Alzheimers Dis 2018;5(1): 31-35.
11. Jonker C, Geerlings M, Schmand B. Are Memory Complaints Predictive for Dementia? A Review of Clinical and Population-based Studies. Int J Geriatr Psychiatry 2000;15: 983-91.
12. Zhang X, Schmitt FA, Caban-Holt AM, Ding X, Kryscio RJ, Abner E. Diabetes mitigates the role of memory complaint in predicting dementia risk: Results from the Prevention of Alzheimer’s Disease with Vitamin E and Selenium Study. J Prev Alzheimers Dis 2017;4(3): 143-48.
13. Krell-Roesch J, Woodruff BK, Acosta JI, Locke DE, Hentz JG, Stonnington CM, et al. APOE epsilon4 Genotype and the Risk for Subjective Cognitive Impairment in Elderly Persons. J Neuropsychiatry Clin Neurosci 2015;27(4): 322-5.
14. Royall DR, Lauterbach EC, Cummings JL, Reeve A, Rummans TA, Kaufer DI, et al. Executive Control Function: A Review of Its Promise and Challenges for Clinical Research. A report from the Committee on Research of the American Neuropsychiatric Association. The Journal of neuropsychiatry and clinical neurosciences 2002;14(4): 377-405.
15. Morson SM, Moulin CJ, Souchay C. Selective deficits in episodic feeling of knowing in ageing: a novel use of the general knowledge task. Acta Psychol (Amst) 2015;157: 85-92
16. Sacher M, Isingrini M, Taconnat L. Effects of aging and divided attention on episodic feeling-of-knowing accuracy. Acta Psychol (Amst) 2013;144(2): 258-63.
17. Chang YL, Jacobson MW, Fennema-Notestine C, Hagler DJ, Jr., Jennings RG, Dale AM, et al. Level of executive function influences verbal memory in amnestic mild cognitive impairment and predicts prefrontal and posterior cingulate thickness. Cereb Cortex 2010;20(6): 1305-13.
18. Winblad B, Palmer K, Kivipelto M, Jelic V, Fratiglioni L, Wahlund LO, et al. Mild cognitive impairment–beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine 2004;256(3): 240-46.
19. Jak AJ, Bondi MW, Delano-Wood L, Wierenga C, Corey-Bloom J, Salmon DP, et al. Quantification of five neuropsychological approaches to defining mild cognitive impairment. Am J Geriatr Psychiatry 2009;17(5): 368-75.
20. Hua MSC, B.S.; Lin, K.N.; Yang, J.M.; Lu, S.R.; Chen, H.Y. Wechsler Memory Scale (WMS), Third Edition. Taipei, Taiwan: The Chinese Behavioral Science Corporation.
21. Delis DCK, J. H.; Kaplan, E.; Ober, B. A. Manual for the California Verbal Learning Test, (CVLT-II). San Antonio, TX: The Psychological Corporation, 2000.
22. Green P, Gervais R, Merten T. Das Memory Complaints Inventory (MCI): Gedächtnisstörungen, Beschwerdenschilderung und Leistungsmotivation. Neurologie & Rehabilitation 2005;11(3).
23. D’Agostino RB, Wolf PA, Belanger AJ, Kannel WB. Stroke risk profile: adjustment for antihypertensive medication. The Framingham Study. Stroke 1994;25(1): 40-3.
24. Liu CY, Wang SJ, Teng EL, Fuh JL, Lin CC, Lin KN, et al. Depressive disorders among older residents in a Chinese rural community. Psychological Medicine 1997;27: 943-49.
25. Chang YL, Yen YS, Chen TF, Yan SH, Tseng WY. Clinical Dementia Rating Scale Detects White Matter Changes in Older Adults at Risk for Alzheimer’s Disease. Journal of Alzheimer’s disease : JAD 2016;50(2): 411-23.
26. Miskowiak KW, Petersen JZ, Ott CV, Knorr U, Kessing LV, Gallagher P, et al. Predictors of the discrepancy between objective and subjective cognition in bipolar disorder: a novel methodology. Acta Psychiatr Scand 2016;134(6): 511-21.
27. Stuss DT, Levine B. Adult clinical neuropsychology: lessons from studies of the frontal lobes. Annual review of psychology 2002;53(1): 401-33.
28. Galeone F, Pappalardo S, Chieffi S, Iavarone A, Carlomagno S. Anosognosia for memory deficit in amnestic mild cognitive impairment and Alzheimer’s disease. Int J Geriatr Psychiatry 2011;26(7): 695-701.
29. Zamboni G, Drazich E, McCulloch E, Filippini N, Mackay CE, Jenkinson M, et al. Neuroanatomy of impaired self-awareness in Alzheimer’s disease and mild cognitive impairment. Cortex 2013;49(3): 668-78.
30. Vannini P, Amariglio R, Hanseeuw B, Johnson KA, McLaren DG, Chhatwal J, et al. Memory self-awareness in the preclinical and prodromal stages of Alzheimer’s disease. Neuropsychologia 2017;99: 343-49.
31. Fragkiadaki S, Kontaxopoulou D, Beratis IN, Andronas N, Economou A, Yannis G, et al. Self-awareness of cognitive efficiency: Differences between healthy elderly and patients with mild cognitive impairment (MCI). J Clin Exp Neuropsychol 2016;38(10): 1144-57.
32. Rabin LA, Smart CM, Amariglio RE. Subjective Cognitive Decline in Preclinical Alzheimer’s Disease. Annu Rev Clin Psychol 2017;13: 369-96.
33. Balash Y, Mordechovich M, Shabtai H, Giladi N, Gurevich T, Korczyn AD. Subjective memory complaints in elders: depression, anxiety, or cognitive decline? Acta Neurol Scand 2013;127(5): 344-50.