Comparing self and informant perspectives on neuropsychiatric symptoms in older adults in a memory clinic

Abstract

Background

In individuals with cognitive deficit, neuropsychiatric symptoms (NPS) are typically assessed through informant-based reports. In contrast, affective symptoms in cognitively normal individuals are typically evaluated using self-report measures, leveraging their sufficient insight. Comparison of these assessments in previous studies indicated differences in their perspectives.

Objective

We aimed to analyze differences between self- and informant-reported NPS using the Mild Behavioral Impairment-Checklist (MBI-C) and their relationship with cognitive deficit.

Methods

The study included 127 participant-informant dyads from a memory clinic cohort, classified as subjective cognitive decline (SCD; N = 38) or mild cognitive impairment (MCI; N = 89) based on comprehensive neuropsychological assessment; MCI group was diagnosed according to core clinical criteria for MCI due to Alzheimer's disease. A control group consisted of 26 cognitively healthy individuals. Participants and their informants completed the MBI-C, evaluating five symptom domains.

Results

Both self- and informant-rated MBI-C scores were higher in the SCD and MCI groups compared to controls. Informant ratings correlated more strongly with objective cognitive deficit, particularly in memory and executive function domains, whereas self-ratings showed only one association (higher apathy with worse attention). In MCI, informants reported more severe impulse dyscontrol symptoms. Correlations between self and informant ratings were weak to moderate.

Conclusions

This study highlights discrepancies between self- and informant-rated NPS assessments, with informant ratings more strongly linked to cognitive deficits in older adults without dementia. Therefore, we suggest using both assessments to capture informants’ and patients’ subjective experiences and facilitate early identification of neurodegenerative diseases.

Keywords

Alzheimer's disease mild behavioral impairment-checklist mild cognitive impairment neuropsychiatric symptoms self-informant comparison subjective cognitive decline

Introduction

Neuropsychiatric symptoms (NPS), changes in mood, behavior, or personality in older individuals, can be part of normal aging but may also indicate early neurodegeneration including Alzheimer's disease (AD).¹ These symptoms often emerge before dementia, i.e., in mild cognitive impairment (MCI) and subjective cognitive decline (SCD).² New-onset NPS in these populations are associated with a higher risk of developing dementia in AD.³ Informant reports further suggest that NPS severity increases with advancing cognitive impairment.⁴

To raise awareness about NPS as early symptoms of pathological aging, a syndrome termed mild behavioral impairment (MBI) was introduced. MBI refers to persistent new-onset NPS in adults aged 50 + without dementia. These symptoms cannot be attributable to another current psychiatric disorder (e.g., major depression) and should cause at least mild functional impairment.⁵ MBI can be diagnosed concurrently with MCI but can also precede any objective cognitive deficit.⁶ Studies have indicated that MBI reflects neurodegenerative changes in the brain and that it can be present in any neurodegeneration including AD.^7–9 To assess MBI, the Mild Behavioral Impairment Checklist (MBI-C) was developed.¹⁰

In dementia, NPS are typically evaluated by informants (a relative or other close person) due to patients’ reduced insight.¹¹ In cognitively normal or mildly impaired individuals, NPS are often assessed via self–rated questionnaires.^12,13 Given the subjective nature of symptom reporting through questionnaires, informants may differ from patients, potentially having significant implications. Self-informant rating discrepancies in cognitive complaints showed potential to predict incident cognitive decline in participants at risk of AD, which led to the formation of a specialized working group.¹⁴ Similar discrepancies appear in affective symptoms, with greater differences observed in more pronounced cognitive deficit.^15–17 Such differences may stem from both patient- and informant-related factors: reduced patient insight due to memory or executive deficits and caregiver burden leading to overestimation of symptoms.^18–20 However, most previous studies used different instruments for patients and informants, limiting the direct comparability of their ratings. One exception is a study using the Apathy Evaluation Scale, showing higher self-rated apathy in cognitively normal individuals, but lower in MCI patients at risk of AD, compared to external assessments.¹⁶

The MBI-C, suitable for both self and informant rating, enables direct comparison. Recently, patient administration has begun to be used more often.^21–23 However, only a few studies have directly compared both perspectives.^24,25 They concluded that both informants and participants with SCD and MCI most frequently reported affective dysregulation, impulse dyscontrol and decreased motivation. It is important to note that their ratings differed in severity and correlated only weakly.^24,25 Notably, these studies involved community-dwelling older adults without comprehensive neuropsychological assessment. No study to date has examined MBI-C self-informant discrepancies in a clinical population.

Our study addresses this gap by examining self-informant differences in the MBI-C in a memory clinic sample of older adults without dementia. Across the cognitive continuum, we aim to describe and compare the severity of NPS reported by participants and informants and to investigate the self-informant agreement in NPS ratings and its relation to cognitive impairment. We hypothesize an increase in NPS severity across the cognitive continuum (lowest in controls, higher in SCD, highest in MCI, for both self and informant ratings). Furthermore, we expect only modest self-informant associations in NPS ratings, resulting in a discrepancy in their MBI-C scores. These self-informant differences will increase with cognitive impairment, particularly in memory and executive function.

Methods

Participants

The study included 127 participant-informant dyads referred to a memory clinic for cognitive complaints and subsequently enrolled in the Czech Brain Aging Study.²⁶ Based on comprehensive neurological and neuropsychological examination, participants were classified as SCD or MCI. SCD (n = 38) was diagnosed using the SCD-Initiative Workgroup criteria and required subjective cognitive decline without objective impairment in the neuropsychological assessment based on age-, sex- and education-adjusted norms.²⁷ MCI (n = 89) was diagnosed according to core clinical criteria for MCI due to AD, and included persons with subjective cognitive complaints, neuropsychologically confirmed objective impairment (>1.5 SD below norms on ≥2 tests within a domain) and preservation of functional independence.²⁸ Both amnestic (n = 79) and non-amnestic (n = 10) MCI were included. All diagnoses were made by consensus involving cognitive neurologists and neuropsychologists.

Additionally, a control group of participant-informant dyads was included (n = 26). Controls were cognitively healthy volunteers (from the University of the Third Age or patient's close relatives) with no significant subjective cognitive complaints and normal performance on neuropsychological testing.

Exclusion criteria included a diagnosis of dementia and other neurological or psychiatric condition significantly affecting cognition or NPS (e.g., Parkinson's disease, frontotemporal lobar degeneration, traumatic brain injury, stroke, alcohol or substance abuse, or current/past major psychiatric disorder). Demographic characteristics of the participants are presented in Table 1.

Table 1.

Demographic and neuropsychological characteristics of the participants.

Characteristics	CN (n = 26; M ± SD)	SCD (n = 38; M ± SD)	MCI (n = 89; M ± SD)	Group differences
Age^a	70.5 ± 5.07	67.1 ± 8.30	73.8 ± 7.28	CN < MCI; SCD < MCI**
Female, n (%)^b	24 (92.31)	31 (81.58)	44 (49.44)	CN > MCI*; SCD > MCI*
Education^a	16.5 ± 1.90	15.9 ± 2.81	15.7 ± 3.16	–
MMSE, score^a	29.62 ± 0.64	29.21 ± 1.14	27.01 ± 2.08	CN > MCI*; SCD > MCI*
WAIS-III Digit Span, score^a	16.85 ± 4.35	16.13 ± 2.78	14.04 ± 3.06	CN > MCI; SCD > MCI**
Digit Symbol, score^a	43.96 ± 11.39	42.87 ± 7.74	31.15 ± 10.72	CN > MCI*; SCD > MCI*
TMT A, time to completion (s) ^a	40.52 ± 11.22	41.00 ± 12.38	59.72 ± 28.52	CN < MCI*; SCD < MCI*
TMT B, time to completion (s) ^a	82.13 ± 22.46	83.03 ± 16.46	176.21 ± 82.65	CN < MCI*; SCD < MCI*
P-VF, score^a	49.65 ± 10.24	54.97 ± 11.76	38.89 ± 11.32	CN > MCI*; SCD > MCI*
C-VF animals, score^a	26.96 ± 5.88	27.03 ± 5.43	18.49 ± 5.63	CN > MCI*; SCD > MCI*
BNT-30, mistakes after a semantic cue^a	2.42 ± 2.00	1.45 ± 1.37	4.61 ± 3.80	CN < MCI*; SCD < MCI*
LM delayed recall, score^a	17.96 ± 3.68	17.03 ± 3.28	8.22 ± 5.62	CN > MCI*; SCD > MCI*
RAVLT 1–5, score^a	56.23 ± 7.86	56.58 ± 8.10	37.72 ± 8.95	CN > MCI*; SCD > MCI*
RAVLT delayed recall, score^a	11.77 ± 2.36	11.71 ± 2.19	4.65 ± 3.23	CN > MCI*; SCD > MCI*
ROCF copy, score^a	30.96 ± 3.09	31.00 ± 2.60	26.56 ± 6.16	CN > MCI*; SCD > MCI*
ROCF recall, score^a	19.58 ± 6.53	18.83 ± 4.26	9.92 ± 6.12	CN > MCI*; SCD > MCI*

CN: cognitively normal; MCI: mild cognitive impairment; SCD: subjective cognitive decline; MMSE: Mini-Mental State Examination; TMT: Trial Making Test; P-VF: phonemic verbal fluency – letters N, K, and P; C-VF: category verbal fluency; BNT-30: Boston Naming Test – 30-item version; LM: logical memory; RAVLT: Rey Auditory Verbal Learning Test; ROCF: Rey–Osterrieth complex figure.

ANOVA with Games-Howell post hoc test, ^bchi-square.

*p < 0.05; **p < 0.01; ***p < 0.001.

All participants provided written informed consent according to the Declaration of Helsinki and the study was approved by the Ethics Committee of Motol University Hospital.

Neuropsychological assessment

The neuropsychological battery included the Mini-Mental State Examination (MMSE) as a screening of global cognition and the following tests covering five cognitive domains^28,29: (1) memory: Rey Auditory Verbal Learning Test (RAVLT),³⁰ Logical Memory from the Wechsler Memory Scale-III (LM),²⁹ and 3-min recall of the Rey-Osterrieth Complex Figure Test (ROCFT recall)³¹; (2) executive function: Trail Making Test B (TMT B)²⁹ and phonemic verbal fluency – letters N, K, P (P-VF)³²; (3) language: 30-item Boston Naming Test (BNT) and category verbal fluency-animals (C-VF)²⁹; (4) attention and working memory: Trail Making Test A (TMT A) and Digit Span Forward and Backward (DS) from the Wechsler Adult Intelligence Scale-III²⁹; and (5) visuospatial function: Rey-Osterrieth Complex Figure Test (ROCFT copy).³¹

Neuropsychiatric assessment

The Czech version of the MBI-C was completed by both participants and their informants (partner, descendant, or another relative).³³ The MBI-C is a 34-item questionnaire designed to assess NPS before the onset of dementia.¹⁰ It covers five domains aligned with MBI diagnostic criteria: decreased motivation (6 items), affective dysregulation (6), impulse dyscontrol (12), social inappropriateness (5), and abnormal perception and thought content (5).⁵ Each item is rated for presence (yes/no) and severity (1-mild, 2-moderate, 3-severe). The symptoms should represent a change from the person's usual behavior and persist over the last 6 months. Total and domain scores are calculated by summing severity ratings (e.g., total score is 0–102). Participants with ≥4 missing MBI-C items were excluded; if ≤3 items were missing, both total and domain scores were calculated without these items. In total, 41 items (0.4%) of the 10 404 patient and informant items were omitted. No single MBI-C item was commonly omitted; missing responses were distributed across items.

Statistical analyses

Group differences in demographic and neuropsychological variables were assessed using ANOVA with Games–Howell post hoc tests, or chi-square tests for categorical data. Because MBI-C data distribution was skewed, nonparametric tests were used: Kruskal–Wallis tests (with Dwass-Steel-Critchlow-Fligner post hoc comparisons) to compare MBI-C scores among diagnostic groups, and Wilcoxon signed-rank test for paired data to compare informant- and self-ratings within each diagnostic group, visualized with ggplot2.³⁴ Associations between informant- and self-rated MBI-C scores were analyzed using Spearman correlations and these correlations were compared between diagnostic groups using bootstrapping.

Associations between MBI-C scores and cognitive domains (memory, attention and working memory, executive functions, language, visuospatial functioning and global cognition) were examined using linear regression analysis. Cognitive domains were composite z-scores calculated as the averages of z-scores of administrated neuropsychological tests for each cognitive domain. Scores for TMT A, TMT B and BNT were reversed before being transformed into z-scores. Since it is plausible that informant and self-rated NPS could have both separate and combined associations with cognition and that these could differ by cognitive domain, multiple sets of analyses were conducted. To examine the effect of larger variance explained in cognition by using MBI-C informant and patient scores separately rather than informant-minus-patient difference scores, two competing regression analyses were run for each MBI domain predicting each cognitive domain. In the first, informant-minus-patient difference score was used, and in the second, the informant and patient scores were entered separately.

Only SCD and MCI participants data were included in the regression analyses, because most MBI-C scores in CN were zero. Data from SCD and MCI participants were combined to increase statistical power. MBI-C variables were log-transformed after adding 1 to MBI-C scores (see Supplemental Figures 1 and 2 for distributions before and after transformation). p-values were adjusted following Holm, considering a set of cognitive domains predicted by a single MBI domain as a family.³⁵ In analyses with age, sex and education as covariates, only the p-values of MBI-C variables were adjusted since our primary focus was on MBI-C, not on the well-established associations of demographic factors with cognitive performance.

The assumptions of linear regression were checked with residual plots, Q-Q plots and checking the variance inflation factors. Most models met the assumptions of linear regression, but some models, particularly those with social inappropriateness or abnormal thought and perception content as predictors had deviations from these assumptions. On the whole, these deviations were not considered sufficient to alter the analytic strategy that aimed to examine associations of all MBI domains with multiple cognitive domains.

Analyses were run in and R 4.3.2, with p < 0.05 considered significant.³⁶ According to a priori determined sample size using G*power 3.1.9.7, 27 dyads per diagnostic group was required to detect medium-sized effect in MBI-C differences between diagnostic groups and self-informant correlations and differences within diagnostic groups (alpha = 0.05, power = 0.80).³⁷

Results

Clinical and demographic characteristics of the study sample

The clinical and demographic characteristics of the study sample are shown in Table 1. MCI participants were older than CN (p = 0.028) or SCD (p < 0.001), but there were no statistically significant differences between diagnostic groups in education or sex distribution. As expected, the MCI group performed worse than CN or SCD in all neuropsychological tests and there was no significant difference between SCD and CN. Table 2 shows the informant and self-rated MBI-C scores. Of note, both abnormal thought and perception and social inappropriateness were rarely endorsed, with 84% and 88% of patients, respectively, scoring zero in these domains, and 86% of informants reporting zero scores in both of these domains (Supplemental Table 3).

Table 2.

Neuropsychiatric characteristics of the participants – MBI-C informant and self-rating.

MBI-C domain	Informant				Self-rating
MBI-C domain	CN (M ± SD)	SCD (M ± SD)	MCI (M ± SD)	Group differences	CN (M ± SD)	SCD (M ± SD)	MCI (M ± SD)	Group differences
Total score (0−102)	0.73 ± 1.61	3.95 ± 5.62	7.35 ± 9.53	CN < SCD** < MCI; CN < MCI**	1.00 ± 1.74	4.79 ± 5.72	5.94 ± 6.63	CN < SCD; CN < MCI*
Decreased motivation (0−18)	0.04 ± 0.20	0.55 ± 1.22	1.57 ± 1.22	CN < SCD* < MCI; CN < MCI**	0.12 ± 0.43	1.00 ± 1.85	1.65 ± 2.60	CN < SCD; CN < MCI**
Affective dysregulation (0−18)	0.12 ± 0.33	1.58 ± 2.99	2.55 ± 3.42	CN < SCD; CN < MCI*	0.58 ± 1.17	2.13 ± 2.79	2.24 ± 2.68	CN < SCD; CN < MCI*
Impulse dyscontrol (0−36)	0.58 ± 1.33	1.45 ± 2.10	2.52 ± 3.70	CN < MCI***	0.27 ± 0.60	1.24 ± 1.65	1.63 ± 2.25	CN < SCD; CN < MCI**
Social inappropriateness (0−15)	0.00 ± 0.00	0.21 ± 0.53	0.35 ± 0.97	–	0.04 ± 0.20	0.26 ± 0.72	0.20 ± 0.61	–
Abnormal perception and thought content (0−15)	0.00 ± 0.00	0.16 ± 0.44	0.36 ± 1.05	CN < MCI*	0.00 ± 0.00	0.16 ± 0.37	0.23 ± 0.47	CN < MCI*

Difference between groups: Kruskal-Wallis with Dwass-Steel-Critchlow-Fligner post hoc test. MBI-C: Mild Behavioral Impairment–Checklist; CN: cognitively normal; SCD: subjective cognitive decline; MCI: mild cognitive impairment.

*p < 0.05; **p < 0.01; ***p < 0.001.

The MCI group scored higher than the CN group on the MBI-C total and domain scores in both informant and self-ratings, except for social inappropriateness (abnormal perception and thought content domain according to informant p = 0.049, according to patient p = 0.031, the rest was p < 0.001). SCD participants had higher MBI-C scores than CN in informant- and self-rated total scores (p = 0.006 and p = 0.002, respectively), decreased motivation (informant p = 0.041, patient p = 0.016) and affective dysregulation (informant p = 0.009, patient p = 0.006) and self-rated impulse dyscontrol (p = 0.010). The MCI group had higher MBI-C scores than SCD group in informant-rated total score (p = 0.038) and decreased motivation (p = 0.047), but there were no differences between these groups when rated by participants.

As for the informants, most of them were spouses (94 informants; 61.4%), fewer were descendants (50 informants, 32.7%) and the remainder (6 informants; 3.9%) were others (e.g., siblings, grandchildren).

Self-informant rating discrepancies

Overall, self- and informant-rated MBI-C scores correlated weakly to moderately (r_s = 0.23–0.55, ps < 0.005; Table 3). No statistically significant differences between the self-informant correlations were observed when comparing the diagnostic groups (Supplemental Table 1). When comparing informant and self-rated scores of the same domain within diagnostic groups (Figure 1), self-rated scores were higher than informant-rated scores for affective dysregulation (p = 0.049) for the CN group and informant-rated scores were higher than self-rated scores in impulse dyscontrol for MCI group (p = 0.013).

Figure 1.

Comparison of MBI-C informant and participant scores within diagnostic groups.

Table 3.

Correlations between informant- and self-rated MBI-C scores.

	r_s (95% CI)	p
Total score	0.55 (0.41–0.68)	<0.001
Decreased motivation	0.52 (0.37–0.64)	<0.001
Affective dysregulation	0.49 (0.35–0.63)	<0.001
Impulse dyscontrol	0.53 (0.39–0.65)	<0.001
Social inappropriateness	0.23 (0.01–0.46)	0.004
Abnormal perception and thought content	0.41 (0.19–0.61)	<0.001

MBI-C: Mild Behavioral Impairment–Checklist; rs: Spearman correlation.

Associations with cognitive domains

The results comparing linear regression analyses with informant- and self-rated scores as separate terms versus informant-self difference scores are presented in Supplemental Table 2. In summary, the models with separate scores (mean R² = 0.06) had on average 0.04 higher R² than difference scores (mean R² = 0.02). In separate term models, informant scores were statistically significant in 10 (27.8%) models whereas participant scores were statistically significant in only 1 (2.8%) model after adjusting for multiple comparisons. Of all 36 difference score models, only impulse dyscontrol predicting language functions was significant after adjusting for multiple comparisons. Across all models, whenever the difference score was significantly related to cognition before p-value adjustment, significance was observed solely for the informant score (and not for the self-rated score) in the separate term model. No model showed both informant- and self-rated scores to be statistically significantly associated with cognition after adjusting for multiple comparisons; therefore, higher-order models were not pursued in this study.

Having shown that using separate MBI-C informant and participant scores increase R² compared to difference scores, we finally analyzed the associations of MBI-C participant and informant scores and cognitive domains after adjusting for age, sex and education (Table 4). For informant-rated MBI-C measures, statistically significant associations that survived adjustment for multiple comparison were found between MBI-C total score and memory performance (β = −0.28, SE = 0.07, p = 0.002), decreased motivation and memory (β = −0.25, SE = 0.11, p = 0.003), affective dysregulation and global cognition (β = −0.29, SE = 0.07, p = 0.001), affective dysregulation and executive functions (β = −0.27, SE = 0.10, p = 0.004), affective dysregulation and memory (β = −0.31, SE = 0.10, p = 0.001). For self-rated MBI-C scores, an association was found only between decreased motivation and attention (β = −0.29, SE = 0.09, p = 0.001).

Table 4.

Associations between MBI-C informant and patient scores after adjusting for covariates.

	Memory		Attention		EF		Language		Visuospat		Global
	β	SE	β	SE	β	SE	β	SE	β	SE	β	SE
	MBI-C total
MBI-C Informant	−0 . 28*	−0.07	−0.12	0.06	−0.26	0.07	−0.24	0.07	−0.03	0.09	−0.24	0.05
MBI-C Patient	0.00	0.08	−0.14	0.07	0.00	0.08	0.01	0.08	0.07	0.10	−0.00	0.06
R²	0.28		0.23		0.26		0.31		0.07		0.33
AIC	305.00		274.10		300.19		287.17		364.77		220.03
	Decreased Motivation
MBI-C Informant	−0.25*	0.11	−0.04	0.09	−0.21	0.10	−0.17	0.10	−0.01	0.14	−0.18	0.07
MBI-C Patient	−0.12	0.11	−0.29*	0.09	−0.17	0.10	−0.16	0.10	−0.13	0.14	−0.22	0.07
R²	0.31		0.27		0.30		0.33		0.08		0.38
AIC	300.07		266.31		294.47		283.51		363.17		209.65
	Affective Dysregulation
MBI-C Informant	−0.31**	0.10	−0.13	0.09	−0.27*	0.10	−0.25	0.09	−0.16	0.12	−0.29**	0.07
MBI-C Patient	0.04	0.10	−0.12	0.09	0.00	0.10	−0.02	0.09	0.13	0.13	0.02	0.07
R²	0.29		0.23		0.27		0.32		0.08		0.35
AIC	303.65		274.09		299.44		285.52		362.49		216.00
	Impulse Dyscontrol
MBI-C Informant	−0.21	0.10	−0.09	0.09	−0.24	0.10	−0.25	0.09	0.03	0.13	−0.19	0.07
MBI-C Patient	0.05	0.12	−0.10	0.11	0.14	0.12	0.17	0.11	0.10	0.15	0.10	0.09
R²	0.24		0.20		0.24		0.30		0.08		0.30
AIC	311.92		277.79		303.63		288.38		363.45		225.62
	Social Inappropriateness
MBI-C Informant	−0.01	0.20	−0.06	0.18	−0.04	0.20	−0.10	0.19	−0.01	0.24	−0.05	0.14
MBI-C Patient	0.07	0.24	−0.04	0.21	0.07	0.24	0.06	0.22	0.11	0.29	0.08	0.17
R²	0.21		0.19		0.20		0.26		0.07		0.28
AIC	316.85		280.37		309.99		295.45		363.81		229.57
	Abnormal Thoughts and Perception
MBI-C Informant	−0.06	0.21	−0.06	0.18	−0.16	0.20	−0.07	0.20	0.07	0.26	−0.07	0.15
MBI-C Patient	−0.10	0.28	−0.14	0.24	−0.03	0.27	−0.03	0.26	−0.04	0.34	−0.08	0.20
R²	0.23		0.21		0.23		0.26		0.07		0.29
AIC	314.64		276.62		305.91		295.57		364.85		227.51

p-values adjusted using Holm correction considering analyses using MBI domains as families. Multiple comparison adjustment did not include the covariates of sex, age and education. MBI-C: Mild Behavioral Impairment–Checklist; EF: Executive functions, Visuospat: Visuospatial functions.

*p < 0.05; **p < 0.01; ***p < 0.001 in multiple-comparison adjusted p-values.

Discussion

This is the first clinical study using both informant- and self-rated versions of the MBI-C in a neuropsychologically characterized memory clinic sample of non-demented older adults. We compared self and informant ratings of 127 individuals across cognitive continuum preceding dementia and examined their associations with the patients’ cognition. Both self and informant ratings were higher in SCD and MCI compared to the control group. Importantly, informant-rated NPS severity in the clinical (SCD + MCI) group was associated with impairment across multiple cognitive domains, contrasting with the lack of substantial correlation with the self-rated NPS. On average, informants reported more severe impulse dyscontrol than participants themselves. Overall, patient-informant agreement on NPS was weak-to-moderate.

NPS across the cognitive continuum

Our study builds upon previous population-based studies by examining NPS across the cognitive continuum preceding dementia.^24,25 Consistent with these studies, we found that both participants and informants most frequently reported decreased motivation, affective dysregulation and impulse dyscontrol, while social inappropriateness and abnormal perception and thought content were rarely reported. As expected, NPS were higher in both clinical groups than in controls.

We observed continuing gradient of worsening informant-rated NPS through the cognitive continuum (CN-SCD-MCI) in the total score and in the decreased motivation domain. Informants also reported higher affective dysregulation in both SCD and MCI compared to CN, with no difference between clinical groups. Our results are consistent with previous clinical studies showing increasing NPS severity across the cognitive continuum as measured by the MBI-C or the NPI-Q.^2,4,38 Higher impulse dyscontrol and abnormal perception and thought content emerged only in MCI compared to CN, in line with studies showing time course of various NPS.^2,39

Although patient administration of the MBI-C has begun to be used more often in studies, our study is the first investigation using MBI-C self-report in clinical population.^21–25 A recent community-based study using the self-rated MBI-C found that the MCI group reported more symptoms than CN in total score, decreased motivation, affective dysregulation and abnormal perception and thought content domains.²³ Our study aligns with these results; in addition, we found higher scores in the impulse dyscontrol domain in MCI group compared to CN. On the other hand, Leow et al. did not find any difference between SCD and CN in any MBI-C domain contrasting with our study, where the SCD group had higher scores in the majority of MBI-C domains.²³ This discrepancy likely reflects sample differences: clinical SCD cohorts generally have a higher prevalence of subjective cognitive complaints, NPS, and amyloid positivity than community samples, increasing the likelihood of detecting NPS differences.¹⁰^40–43 Indeed, other clinical studies using domain-specific self-report questionnaires have also found higher NPS not only in MCI but also in SCD group compared to CN.^44–46 In contrast, we observed no significant differences between SCD and MCI in any self-rated MBI-C domain, which aligns with another clinical study reporting comparable levels of self-rated depressive symptoms in these groups.⁴⁵

Altogether, our results confirm the presence of mild NPS in both clinical groups of nondemented older adults. We observed that CN and SCD groups, although similar in cognitive performance, differed in several NPS as reported by themselves or their informants. Cognition-related anxiety and worry are among the main reasons for which SCD individuals seek medical help and may be overlapping with MBI, but our study shows that there are also other NPS, such as apathy and impulse dyscontrol, that the individuals experience and informants observe in this stage.⁶ Meanwhile, SCD and MCI groups, although cognitively different by definition, only differed in informant-rated total MBI-C and decreased motivation scores, suggesting that increasing cognitive impairment is associated with greater NPS severity only in certain domains. This pattern partially aligns with a finding that Aβ-positive SCD individuals did not differ from Aβ-positive MCI in any NPI-Q score.⁴⁷ The slightly higher NPS levels of apathy observed in our study (compared to studies using NPI-Q) may indicate a higher sensitivity of the MBI-C for capturing these changes in nondemented older adults.

Self-informant rating discrepancies

Analogously to previous studies, informant and self MBI-C ratings showed only weak-to-moderate correlations.^24,25 We also found that informants reported systematically more impulse dyscontrol symptoms than patients with MCI, consistent with previous research highlighting the greatest self-informant discrepancy in this domain.²⁵ Patients may underreport behaviors like irritability, impulsivity, or aggression—either due to lack of insight or an attempt to maintain a positive self-image—whereas informants may overestimate the severity of these symptoms based on their observations, because it occurs often in social situations and is associated with perceived burden.^48–50 In a previous study, items with the greatest self–informant discrepancy were primarily related to negative personality traits, supporting this interpretation.²⁵

We observed no significant self-informant discrepancy in the affective dysregulation domain. Prior studies on depressive and anxiety symptoms have yielded mixed results, with some finding higher self-ratings and others higher informant ratings.^16,24,51,52 Only two population studies examined self-informant differences in NPS with MBI-C: one found no self-informant difference in affective symptoms, whereas the other reported that participants endorsed more affective symptoms than their informants, which we did not confirm in our clinical groups.^24,25 Notably, the raw MBI-C scores (including affective dysregulation) were higher in our clinical groups than in those community samples.²⁴ In a clinical population, affective symptoms are typically more pronounced and thus more apparent to informants, whereas in community samples, the symptoms tend to be milder and more difficult for informants to detect.^10,42 As a result, informants may not observe the milder symptoms that participants still experience. Another explanation of these differences between self- and informant-rated depressive symptoms could be their different nature (externally observable versus internally experienced).⁵³

Associations with cognitive domains

Our findings highlight that informant and patient NPS ratings have distinct relationships with objective cognition. While the overall variance in cognition explained by NPS ratings was modest (maximum 15% of a cognitive domain), informant-rated NPS showed consistently stronger links to cognitive performance than self-rated NPS. We found that higher informant total and domain scores were associated with poorer memory, executive, and global cognitive function, whereas self-ratings showed only one association (higher self-rated apathy with worse attention). This pattern aligns with previous reports: informant-rated MBI-C scores correlate with worse global cognition in clinical sample and with memory and executive deficits in community sample, whereas self-rated MBI-C shows minimal cognitive associations.^4,54,55 However, the association of the self-rating with attention in our study was not found in informant ratings, highlighting a unique contribution of the patient self-reports in this instance. Of note, this association was as strong as those found between informant ratings and other cognitive domains, suggesting that patient self-ratings can still provide valuable insight.

Discrepancies between patient and informant NPS ratings have been observed to widen with more severe impairment in memory and executive function, likely reflecting emerging anosognosia (unawareness of deficits) in the patient.^15,18 Anosognosia is linked to memory impairment and can manifest even in prodromal stages of neurodegenerative diseases.¹⁹^56–58 Notably, in our analyses the informant rating alone was a better predictor of cognitive outcomes than the informant-patient difference score, suggesting that the informant perspective largely drives the association between NPS and cognitive impairment.

These discrepancies between patient and informant reports also raise the question of whether clinician-administered assessments could provide added value. The MBI-C administration instructions also allow for a clinical interview. Although we did not examine this mode of administration, studies with related instruments suggest potential benefits: for instance, the clinician-rated Apathy Evaluation Scale (AES-C) predicted progression from MCI to dementia better than self- or informant-reports.¹⁶ Also, the Neuropsychiatric Inventory clinician version (NPI-C) was developed to enhance objectivity through clinical judgment.⁵⁹ Similar advantages may apply to the MBI-C, but further validation of clinician interview administration is needed.

Limitations

This study has several limitations. First, the sample came from a memory clinic, which limits the generalizability to the general population—clinical populations tend to exhibit a higher prevalence of NPS than community samples.^10,42 Second, we examined an etiologically heterogeneous sample without biomarkers. However, in this way our sample reflects clinical practice where biomarkers are often missing. Third, our informant-based measures did not account for informant characteristics. Recent research indicates informant factors (such as age, gender, or relationship to the patient) can influence reported NPS.⁶⁰ Future studies should consider adjusting for informant characteristics. Fourth, domains of social inappropriateness and abnormal perception and thought content were very infrequent in our sample, as expected in early-stage AD, which may cause small differences and lack of association with cognition in those domains.¹ Analyses using these domains did not unequivocally meet the assumptions of linear regression and might benefit from different statistical approaches than the ones employed here. However, for most models, the assumptions of linear regression were met. Finally, the correlations between self- and informant reports would ideally be interpreted with the reliability of these measures in mind. However, to estimate reliability in cross-sectional data informatively would require establishing the dimensionality of the MBI-C with factor analysis, which our sample size is not equipped to do. Therefore, it is a limitation of our study that we have used the MBI-C scales with the a priori structure rather than testing whether this structure holds in factor analysis and provides reasonable reliability estimates.

Conclusion

This clinical study highlights important self-informant discrepancies in reporting NPS in older adults without dementia. Informant ratings consistently showed stronger associations with cognitive deficits particularly in memory and executive function suggesting they may offer a more accurate reflection of the patient's current cognitive status. Furthermore, impulse dyscontrol was consistently underestimated by patients. Yet, self-ratings provided relevant data, with self-perceived apathy correlating with attention deficit, highlighting a patient perspective that informants may miss. Our findings have important clinical implications supporting the need for complementing self-reports with information from their informants even in early stages of neurodegenerative diseases. Future studies should examine these discrepancies on biomarker-defined cohorts and from longitudinal perspectives.

Supplemental Material

sj-docx-1-alz-10.1177_13872877251401620 - Supplemental material for Comparing self and informant perspectives on neuropsychiatric symptoms in older adults in a memory clinic

Supplemental material, sj-docx-1-alz-10.1177_13872877251401620 for Comparing self and informant perspectives on neuropsychiatric symptoms in older adults in a memory clinic by Monika Krejčí, Veronika Matušková, Toni T Saari, Hana Horáková, Šárka Borovská, Jan Laczó, Jakub Hort and Martin Vyhnálek in Journal of Alzheimer's Disease

Supplemental Material

sj-xlsx-2-alz-10.1177_13872877251401620 - Supplemental material for Comparing self and informant perspectives on neuropsychiatric symptoms in older adults in a memory clinic

Supplemental material, sj-xlsx-2-alz-10.1177_13872877251401620 for Comparing self and informant perspectives on neuropsychiatric symptoms in older adults in a memory clinic by Monika Krejčí, Veronika Matušková, Toni T Saari, Hana Horáková, Šárka Borovská, Jan Laczó, Jakub Hort and Martin Vyhnálek in Journal of Alzheimer's Disease

Supplemental Material

sj-xlsx-3-alz-10.1177_13872877251401620 - Supplemental material for Comparing self and informant perspectives on neuropsychiatric symptoms in older adults in a memory clinic

Supplemental material, sj-xlsx-3-alz-10.1177_13872877251401620 for Comparing self and informant perspectives on neuropsychiatric symptoms in older adults in a memory clinic by Monika Krejčí, Veronika Matušková, Toni T Saari, Hana Horáková, Šárka Borovská, Jan Laczó, Jakub Hort and Martin Vyhnálek in Journal of Alzheimer's Disease

Footnotes

Acknowledgements

We would like to express our thanks to our neuropsychological team: doc. Mgr. et Mgr. Tomáš Nikolai, PhD, Mgr. Adéla Fendrych Mazancová, PhD and Mgr. Terezie Zuntychová, and our neurologists: MUDr. Ondřej Lerch, MUDr. Jiří Cerman, PhD, MUDr. Martina Laczó, PhD and MUDr. Zuzana Nedelská, M.Sc., PhD, who also participated on the data acquisition.

During the preparation of this work the authors used DeepL and ChatGPT to improve the readability and language of the manuscript. After using these tools, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

ORCID iDs

Monika Krejčí

Veronika Matušková

Toni T Saari

Hana Horáková

Šárka Borovská

Jan Laczó

Jakub Hort

Martin Vyhnálek

Ethical considerations

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. The study was reviewed and approved by Ethics Committee of Second Faculty of Medicine, Charles University and Motol University Hospital.

Consent to participate

The participants provided their written informed consent to participate in this study.

Consent for publication

Not applicable

Author contribution(s)

Monika Krejčí: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Visualization; Writing – original draft; Writing – review & editing.

Veronika Matušková: Conceptualization; Investigation; Methodology; Supervision; Writing – original draft; Writing – review & editing.

Toni T Saari: Formal analysis; Visualization; Writing – original draft.

Hana Horáková: Investigation; Resources; Writing – review & editing.

Jan Laczó: Investigation; Writing – review & editing.

Jakub Hort: Funding acquisition; Investigation; Resources; Writing – review & editing.

Martin Vyhnálek: Conceptualization; Funding acquisition; Investigation; Methodology; Supervision; Writing – original draft; Writing – review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Charles University Grant Agency (grant number 62924); the National Institute for Neurological Research (Program EXCELES): Funded by EU – Next Generation EU (grant number LX22NPO5107); and Ministry of Health, Czech Republic – conceptual development of research organization, University Hospital Motol, Prague, Czech Republic (grant number 00064203).

Declaration of conflicting interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Martin Vyhnalek is an Associate Editor of this journal but was not involved in the peer-review process of this article nor had access to any information regarding its peer-review. Other authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The datasets presented in this article are not readily available because of the policy of the Czech Brain Aging Study (CBAS), which allows sharing of the data only after previous approval. Requests to access the datasets should be directed to MV, martin.vyhnalek@fnmotol.cz. The study was not preregistered.

Supplemental material

Supplemental material for this article is available online.

References

Gallagher

Fischer

Iaboni

. Neuropsychiatric symptoms in mild cognitive impairment: an update on prevalence, mechanisms, and clinical significance. Can J Psychiatry 2017; 62: 161–169.

Wise

Rosenberg

Lyketsos

, et al. Time course of neuropsychiatric symptoms and cognitive diagnosis in national Alzheimer’s coordinating centers volunteers. Alzheimers Dement (Amst) 2019; 11: 333–339.

McGirr

Nathan

Ghahremani

, et al. Progression to dementia or reversion to normal cognition in mild cognitive impairment as a function of late-onset neuropsychiatric symptoms. Neurology 2022; 98: e2132–e2139.

Patten

Charlton

, et al. Validating the mild behavioral impairment checklist in a cognitive clinic: comparisons with the neuropsychiatric inventory questionnaire. J Geriatr Psychiatry Neurol 2023; 36: 107–120.

Ismail

Smith

Geda

, et al. Neuropsychiatric symptoms as early manifestations of emergent dementia: provisional diagnostic criteria for mild behavioral impairment. Alzheimers Dement 2016; 12: 195–202.

Ismail

McGirr

Gill

, et al. Mild behavioral impairment and subjective cognitive decline predict cognitive and functional decline. J Alzheimers Dis 2021; 80: 459–469.

Matsuoka

Imai

Narumoto

. Neuroimaging of mild behavioral impairment: a systematic review. Psychiatry Clin Neurosci Rep 2023; 2: e81.

Matuskova

Ismail

Nikolai

, et al. Mild behavioral impairment is associated with atrophy of entorhinal cortex and hippocampus in a memory clinic cohort. Front Aging Neurosci 2021; 13: 643271.

Guan

Rehman

Nathan

, et al. Neuropsychiatric symptoms: risk factor or disease marker? A study of structural imaging biomarkers of Alzheimer’s disease and incident cognitive decline. Hum Brain Mapp 2024; 45: e70016.

10.

Ismail

Agüera-Ortiz

Brodaty

, et al. The mild behavioral impairment checklist (MBI-C): a rating scale for neuropsychiatric symptoms in pre-dementia populations. J Alzheimers Dis 2017; 56: 929–938.

11.

Verhülsdonk

Quack

Höft

, et al. Anosognosia and depression in patients with Alzheimer’s dementia. Arch Gerontol Geriatr 2013; 57: 282–287.

12.

Balsamo

Cataldi

Carlucci

, et al. Assessment of late-life depression via self-report measures: a review. Clin Interv Aging 2018; 13: 2021–2044.

13.

Therrien

Hunsley

. Assessment of anxiety in older adults: a systematic review of commonly used measures. Aging Ment Health 2012; 16: 1–16.

14.

Nosheny

Amariglio

Sikkes

SAM

, et al. The role of dyadic cognitive report and subjective cognitive decline in early ADRD clinical research and trials: current knowledge, gaps, and recommendations. Alzheimers Dement (N Y) 2022; 8: e12357.

15.

Gold

Rosowsky

Piryatinsky

, et al. Comparing patient and informant ratings of depressive symptoms in various stages of Alzheimer’s disease. Neuropsychology 2020; 34: 535–550.

16.

Guercio

Donovan

Munro

, et al. The apathy evaluation scale: a comparison of subject, informant, and clinician report in cognitively normal elderly and mild cognitive impairment. J Alzheimers Dis 2015; 47: 421–432.

17.

Kwak

Kim

, et al. Lower cognitive function attenuates the convergence between self-ratings and observer ratings of depressive symptoms in late-life cognitive impairment. Brain Behav 2023; 13: e2898.

18.

Brunet

Cummings

Banks

, et al. Awareness of psychiatric symptoms in a mixed clinical sample of older adults. J Geriatr Psychiatry Neurol 2020; 33: 124–134.

19.

De Carolis

Cipollini

Corigliano

, et al. Anosognosia in people with cognitive impairment: association with cognitive deficits and behavioral disturbances. Dement Geriatr Cogn Disord Extra 2015; 5: 42–50.

20.

Pfeifer

Drobetz

Fankhauser

, et al. Caregiver rating bias in mild cognitive impairment and mild Alzheimer’s disease: impact of caregiver burden and depression on dyadic rating discrepancy across domains. Int Psychogeriatr 2013; 25: 1345–1355.

21.

Guan

Mortby

Pike

, et al. Linking cognitive and behavioral reserve: evidence from the CAN-PROTECT study. Alzheimers Dement (N Y) 2024; 10: e12497.

22.

Leow

Saffari

Vipin

, et al. Mild behavioral impairment and cortical thinning: biomarkers of early neurodegeneration. Biol Psychiatry Cogn Neurosci Neuroimaging Epub ahead of print 7 July 2025. DOI: 10.1016/j.bpsc.2025.06.010

23.

Leow

Soo

Kumar

, et al. Mild behavioral impairment and cerebrovascular profiles are associated with early cognitive impairment in a community-based southeast Asian cohort. J Alzheimers Dis 2024; 97: 1727–1735.

24.

Chen

T-H

Yeh

Y-C

Huang

M-F

, et al. Validation and comparison of the informant-rated and self-rated versions of the mild behavioral impairment checklist. J Alzheimers Dis 2022; 90: 1203–1213.

25.

Creese

Griffiths

Brooker

, et al. Profile of mild behavioral impairment and factor structure of the mild behavioral impairment checklist in cognitively normal older adults. Int Psychogeriatr 2020; 32: 705–717.

26.

Sheardova

Vyhnalek

Nedelska

, et al. Czech Brain aging study (CBAS): prospective multicentre cohort study on risk and protective factors for dementia in the Czech Republic. BMJ Open 2019; 9: e030379.

27.

Jessen

Amariglio

Boxtel

, et al. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimers Dement 2014; 10: 844–852.

28.

Albert

DeKosky

Dickson

, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the national institute on aging-Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7: 270–279.

29.

Nikolai

Stepankova

Kopecek

, et al. The uniform data set, Czech version: normative data in older adults from an international perspective. J Alzheimers Dis 2018; 61: 1233–1240.

30.

Bezdicek

Stepankova

Moták

, et al. Czech Version of rey auditory verbal learning test: normative data. Aging Neuropsychol Cogn 2014; 21: 693–721.

31.

Drozdová

Štěpánková

Lukavský

, et al. Normative data for the Rey-Osterrieth Complex figure test in older Czech adults. Cesk Slov Neurol N 2015; 78/111: 542–549.

32.

Nikolai

Štěpánková

Michalec

, et al. Tests of verbal fluency, Czech normative study in older patients. Cesk Slov Neurol N 2015; 78/111: 292–299.

33.

Matušková

Nikolai

Marková

, et al. Neuropsychiatric symptoms as early manifestation of Alzheimer’s disease. Cesk Slov Neurol N 2020; 83/116: 64–72.

34.

Wickham

. ggplot2: Elegant graphics for data analysis. [software]. 2016. Available from: https://doi.org/10.1007/978-3-319-24277-4_9.

35.

Holm

. A simple sequentially rejective multiple test procedure. Scand J Statist 1979; 6: 65–70.

36.

R Core Team. _R: A language and environment for statistical computing_. Version 4.3.2 [software]. 2023. Available from: https://www.R-project.org/.

37.

Faul

Erdfelder

Buchner

, et al. Statistical power analyses using G*power 3.1: tests for correlation and regression analyses. Behav Res Methods 2009; 41: 1149–1160.

38.

Park

. Prevalence of mild behavioural impairment and its association with cognitive and functional impairment in normal cognition, mild cognitive impairment, and mild Alzheimer’s dementia. Psychogeriatrics 2024; 24: 555–564.

39.

Masters

Morris

Roe

. “Noncognitive” symptoms of early Alzheimer disease: a longitudinal analysis. Neurology 2015; 84: 617–622.

40.

Janssen

Jansen

Vos

SJB

, et al. Characteristics of subjective cognitive decline associated with amyloid positivity. Alzheimers Dement 2022; 18: 1832–1845.

41.

Markova

Nikolai

Mazancova

, et al. Differences in subjective cognitive complaints between non-demented older adults from a memory clinic and the community. J Alzheimers Dis 2019; 70: 61–73.

42.

Kuhn

Moulinet

Perrotin

, et al. Cross-sectional and longitudinal characterization of SCD patients recruited from the community versus from a memory clinic: subjective cognitive decline, psychoaffective factors, cognitive performances, and atrophy progression over time. Alzheimers Res Ther 2019; 11: 61.

43.

Yabuuchi

Kimura

Masuda

, et al. Comparison of brain amyloid deposition and cortical glucose metabolism between clinic- and community-based cohort. J Alzheimers Dis 2023; 95: 299–306.

44.

Perrotin

La Joie

De La Sayette

, et al. Subjective cognitive decline in cognitively normal elders from the community or from a memory clinic: differential affective and imaging correlates. Alzheimers Dement 2017; 13: 550–560.

45.

Sannemann

Schild

A-K

Altenstein

, et al. Neuropsychiatric symptoms in at-risk groups for AD dementia and their association with worry and AD biomarkers – results from the DELCODE study. Alzheimers Res Ther 2020; 12: 131.

46.

Vloeberghs

Opmeer

De Deyn

, et al. De relatie tussen apathie, depressie en cognitief functioneren bij patiënten met MCI en dementie. Tijdschr Gerontol Geriatr 2018; 49: 95–102.

47.

Eikelboom

Van Den Berg

Singleton

, et al. Neuropsychiatric and cognitive symptoms across the Alzheimer disease clinical spectrum: cross-sectional and longitudinal associations. Neurology 2021; 97: e1276–e1287.

48.

Bozgeyik

Ipekcioglu

Yazar

, et al. Behavioural and psychological symptoms of Alzheimer’s disease associated with caregiver burden and depression. Psychiatry Clin Psychopharmacol 2019; 29: 656–664.

49.

Isaksson

Corker

Cotney

, et al. Coping with stigma and discrimination: evidence from mental health service users in England. Epidemiol Psychiatr Sci 2018; 27: 577–588.

50.

Matsumoto

Ikeda

Fukuhara

, et al. Caregiver burden associated with behavioral and psychological symptoms of dementia in elderly people in the local community. Dement Geriatr Cogn Disord 2007; 23: 219–224.

51.

Calamia

Bernstein

JPK

. Comparison of self-reported and informant-reported depressive symptoms in an outpatient neuropsychology clinic sample. J Clin Exp Neuropsychol 2017; 39: 525–533.

52.

Kashiwa

Kitabayashi

Narumoto

, et al. Anosognosia in Alzheimer’s disease: association with patient characteristics, psychiatric symptoms and cognitive deficits. Psychiatry Clin Neurosci 2005; 59: 697–704.

53.

Saari

Hallikainen

Hintsa

, et al. Network structures and temporal stability of self- and informant-rated affective symptoms in Alzheimer’s disease. J Affect Disord 2020; 276: 1084–1092.

54.

Kassam

Chen

Nosheny

, et al. Cognitive profile of people with mild behavioral impairment in brain health registry participants. Int Psychogeriatr 2023; 35: 643–652.

55.

Creese

Brooker

Ismail

, et al. Mild behavioral impairment as a marker of cognitive decline in cognitively normal older adults. Am J Geriatr Psychiatry 2019; 27: 823–834.

56.

Galioto

Thamilavel

Blum

, et al. Awareness of cognitive deficits in older adults with epilepsy and mild cognitive impairment. J Clin Exp Neuropsychol 2015; 37: 785–793.

57.

Chen

Song

, et al. Hyperconnectivity associated with anosognosia accelerating clinical progression in amnestic mild cognitive impairment. ACS Chem Neurosci 2022; 13: 120–133.

58.

Vannini

Hanseeuw

Gatchel

, et al. Trajectory of unawareness of memory decline in individuals with autosomal dominant Alzheimer disease. JAMA Netw Open 2020; 3: e2027472.

59.

de Medeiros

Robert

Gauthier

, et al. The neuropsychiatric inventory-clinician rating scale (NPI-C): reliability and validity of a revised assessment of neuropsychiatric symptoms in dementia. Int Psychogeriatr 2010; 22: 984–994.

60.

Guan

Mudalige

Munro

, et al. The effect of study partner characteristics on the reporting of neuropsychiatric symptoms across the neurocognitive spectrum. Int Psychogeriatr 2024; 36: 675–688.

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