The Frontal Behavioral Battery: A Measure of Frontal Lobe Symptoms in Brain Aging and Neurodegenerative Disease

Abstract

Background:

Approximately 90% of persons living with dementia experience behavioral symptoms, including frontal lobe features involving motivation, planning, social behavior, language, personality, mood, swallowing, and gait.

Objective:

We conducted a two-stage study with a development sample (n = 586) and validation sample (n = 274) to evaluate a brief informant-rated measure of non-cognitive features of frontal lobe dysfunction: the Frontal Behavioral Battery (FBB).

Methods:

In the development sample, internal consistency, principal factor analysis, and correlations between the FBB and outcomes were evaluated. In the validation sample, we examined (a) FBB scores by diagnosis, (b) known-group validity by demographics, subjective complaints, and dementia staging, and (c) correlation between FBB and MRI volumes. Receiver operator characteristic curves assessed the ability of the FBB to discriminate individuals with frontal lobe features due to a neurodegenerative disease.

Results:

The FBB characterized 11 distinct frontal lobe features. Individuals with dementia with Lewy bodies and frontotemporal degeneration had the greatest number of frontal lobe features. Premorbid personality traits of extroversion, agreeableness, and openness were associated with fewer frontal lobe behavioral symptoms, while subjective cognitive complaints were associated with greater symptoms. The FBB provided very good discrimination between individuals with and without cognitive impairment (diagnostic odds ratio: 13.1) and between individuals with and without prominent frontal lobe symptoms (diagnostic odds ratio: 84.8).

Conclusion:

The FBB may serve as an effective and efficient method to assess the presence of non-cognitive symptoms associated with frontal lobe dysfunction, but in a brief fashion that could facilitate its use in clinical care and research.

INTRODUCTION

Alzheimer’s disease and related dementias (AD RD) are significant public health challenges, affecting more than 6 million people in the US [1] and more than 50 million worldwide [2]. ADRD not only result in progressive cognitive impairment but changes in activities of daily living and behavior. Approximately 90% of persons living with dementia will experience behavioral and psychological symptoms of dementia including aggression, agitation, irritability, mood disturbances, psychosis, resistance to care, sleep disturbances, and changes in appetite [3, 4]. A large proportion of persons living with dementia may develop other changes including unusual movements, difficulties with speech and swallowing, and changes in gait with increased risk of falling. These changes may contribute significantly to negative health outcomes [5, 6], declines in physical functionality [7], increasing caregiver burden [8], and the potential for inappropriate medication use [9].

Common to many neurodegenerative disorders are non-cognitive symptoms attributed to frontal lobe dysfunction including higher functioning processes such as motivation, planning and decision making, social behavior, and language [10–12]. However, other frontal lobe functions include personality, mood, cortical control of swallowing, gait, and eye movements. Specific patterns of non-cognitive symptoms can be mapped to injury or neurodegeneration in different frontal anatomical and functional regions: the primary motor cortex, the supplementary and premotor cortex, and the prefrontal cortex. In addition to direct cortical damage, injury to frontal-subcortical white matter tracts can result in similar symptom manifestations [12–14]. Many studies have examined the cognitive features of frontal lobe dysfunction including impairments in executive function [10, 15, 16], and a number of instruments have been developed and validated to characterize these features [17–19]. There are fewer instruments to characterize the non-cognitive signs and symptoms associated with frontal lobe dysfunction with most focusing on prefrontal lobe symptoms [15, 20, 21]. The Frontal Systems Behavior Scale (FrSBe) [20] can be used to quantify behaviors associated with frontal lobe damage across three subscales to assess apathy, disinhibition, and executive dysfunction [15]. The FrSBe can discriminate cortical dementias such as Alzheimer’s disease (AD) from subcortical dementias and frontal lobe injury from trauma [20]. The Frontal Behavioral Inventory (FBI) is a 24-item caregiver questionnaire validated in frontotemporal degeneration (FTD) across two domains: negative behaviors and disinhibition [21]. A commonly used measure of behavioral and psychological features in neurodegenerative disease is the Neuropsychiatric Inventory (NPI) [22, 23], which includes 12 constructs including mood states (depression, anxiety, apathy, euphoria), psychosis (hallucinations, delusions), behaviors (agitation, irritability, disinhibition), and vegetative features (appetite, sleep, repetitive movement). However, these constructs are not specifically targeting frontal lobe function and do not include other features common to frontal lobe disorders such as swallowing, speech, social interactions, falling, and movement disorders.

We conducted a two-stage cross-sectional study to develop and validate a new brief measure of behaviors and non-cognitive symptoms associated with frontal lobe dysfunction called the Frontal Behavioral Battery (FBB). We compared the FBB to patient and caregiver rating scales, neuropsychological test performance, the NPI, and MRI. The goal was to create an instrument that could 1) characterize non-cognitive symptoms associated with frontal dysfunction in individuals diagnosed with FTD, and 2) provide further characterization in other neurodegenerative disease based on behavioral profiles while maintaining brevity and ease of scoring to facilitate use in clinical practice and research.

METHODS

Participants

This retrospective cross-sectional study was conducted using two independent samples. The development sample consisted of 586 caregiver respondents responding to a survey request from the Association for Frontotemporal Degeneration (AFTD). Caregivers reported on the medical, psychosocial, and economic impact of FTD and reported on the clinical characteristics and diagnostic experiences from individuals with different FTD phenotypes [24] including the behavioral variant of FTD (bvFTD), primary progressive aphasia (PPA), FTD with motor neuron disease (FTD-MND), progressive supranuclear palsy/corticobasal syndrome (PSP/CBS), or unspecified forms of FTD. Details of the survey have been previous reported [25–27]. In addition to the previously reported survey questions, respondents completed the FBB.

The validation sample consisted of 274 participant-study partner dyads that either attended our center for clinical care or participated in cognitive aging research. During the 3-hour visit, patients and caregivers underwent a comprehensive clinical, cognitive, functional, and behavioral evaluation modeled after the Uniform Data Set (UDS) from the National Institute of Aging Alzheimer Disease Research Center Program [28, 29] with additional components including FBB. Study partners completed a psychosocial assessment while the participant underwent neuropsychological testing, physical and neurologic examinations [30] and protocols in the clinic and research projects are identical. The study included older adults ranging from no dementia to individuals with moderate-to-severe dementia of any etiology. Individuals living in skilled nursing facilities were excluded. A waiver of consent was obtained for clinic patients, while prospective research participants provided written informed consent. This study was approved by the University of Miami Institutional Review Board.

Frontal behavioral battery

The FBB items were derived from a review of the literature, the clinical and research experience of the investigators, interviews with patients and family caregivers, and input from the staff at AFTD reflecting the experiences reported by their constituents to cover functional and behavioral symptoms attributed to frontal lobe function or frontal-subcortical connections in the development sample. Final item selections for the FBB included 11 features (Fig. 1): difficulty speaking, difficulty swallowing, speaking in an aggressive manner, physical aggression, inappropriate sexual behavior, inappropriate shopping/spending, inappropriate clothing choices, change in communication and interaction with family, falling, unusual movements, and refusal to bath or groom. The wording of the questions was deliberate to avoid medical jargon (i.e., aphasia) and permit the respondent to answer the questions in an on-line survey. For example, the “Difficulty Speaking” question was designed to capture aphasia (fluent and non-fluent) in a single question, thus we wished to capture all aspects of language (speaking, reading, writing, comprehension) in a manner that the lay public could complete without assistance. Similarly, the “Talked in an Aggressive Manner, Shouted or Yelled at People” was designed to capture changes in the manner in which the participant speaks to other people, distinct from aphasic issues. Inappropriate or unwanted touching was captured with two questions: sexual and physical. A two-stage scoring paradigm was used with the respondent first rating whether the symptom was absent (score = 0) or present (score = 1) in the past month. If present, the respondent was asked to rate the severity of the symptom as mild (score = 1), moderate (score = 2), or severe (score = 3). The product of presence and severity were calculated and totaled to derive the FBB score. The possible range of scores was 0–33, with higher scores representing more severe frontal lobe symptoms. The FBB took 2–3 minutes to complete. The FBB was administered along with NPI for an assessment of non-cognitive symptoms.

Fig. 1. FRONTAL BEHAVIORAL BATTERY.

Have any of following symptoms been present in the past month? Please select “Yes” or “No”. If symptom has been present, please rate the severity using the following guide: Mild: Noticeable, but not a significant change; minimal distress. Moderate: Significant but not a dramatic change; mild-to-moderate distress. Severe: Very marked or dramatic change; moderate-to-severe distress.

Development sample evaluation

Demographic information was collected from the caregiver respondents on themselves, and the persons with FTD they are caring for (e.g., age, sex, education level, race, and ethnicity). The survey also collected information on the caregiver’s relationship to the persons with FTD (spouse, child, other), duration of disease, and specific FTD diagnosis (bvFTD, PPA, FTD-MND, PSP/CBS, non-specified) [25–27]. Caregiver respondents completed a global rating of the persons with FTD using the informant version of the Quick Dementia Rating System (QDRS) [31]. The QDRS is a 10-item multiple choice questionnaire with scores ranging from 0–30, with higher scores representing greater impairment. A Clinical Dementia Rating (CDR) and its sum of boxes (CDR-SB) [32] can be derived from the QDRS with excellent accuracy [31]. Health-related quality of life was captured with the 8-item Health Utilities Index-Mark 3 (HUI-3) [33], (range: −0.0371 to 1.371; lower scores = worse quality of life). The 10-item Functional Activities Questionnaire (FAQ) assessed instrumental activities of daily living (range: 0–30; higher score = greater impairment) [34]. Neuropsychiatric symptoms such as delusions, hallucinations, aggression, and depression were measured using the 12-question Neuropsychiatric Inventory (NPI) [23] with scores ranging from 0–36, with higher scores representing more behavioral symptoms. Perceived caregiver burden was captured with the Zarit Burden Inventory (ZBI) [35]. The ZBI assesses perceived emotional, physical, and social strain associated with caregiving. Each of the 12 items received one of five responses (never [0 points], rarely, sometimes, quite frequently, nearly always [4 points]), and the item scores are summed for the total ZBI score (range: 0–48, higher scores = greater burden). Lastly, the respondents completed the FBB.

Validation sample evaluation

Demographic information including age, sex, education, race, ethnicity, past medical history, medications, alcohol, tobacco, and substance use history, co-morbidities, and family history were collected. The Charlson Comorbidity Index [36] was used to measure overall health and medical comorbidities with scores ranging from 0–33, with higher scores signifying more comorbidities. Global physical performance was captured with the mini-Physical Performance Test (mPPT) [37] with scores ranging from 0–16, with scores less than 12 supporting impaired physical functionality. Frailty was assessed with the Fried Frailty Scale [38] with scores ranging from 0–5, with scores 1–2 representing pre-frailty and scores 3–5 representing frailty. Vascular contributions to dementia were assessed with the modified Hachinski scale [39] with scores ranging from 0–12, with higher scores representing greater vascular risk factors.

1). Clinical staging

Standardized scales from the UDS were administered to the informants to provide ratings of cognition, function, and behavior [28, 29]. The CDR [32] was used to determine the presence or absence of dementia and to stage its severity; a global CDR 0 indicates no dementia; CDR 0.5 represents MCI or very mild dementia; CDR 1, 2, or 3 correspond to mild, moderate, or severe dementia. The CDR-SB was calculated by adding up the individual CDR categories (range: 0–18; higher scores supporting more severe impairment). Because CDR 0 includes individuals with and without subjective cognitive complaints, and CDR 0.5 includes individuals with MCI and very mild dementia, each individual was also staged using the Global Deterioration Scale (GDS) [40]. A GDS 1 indicates no cognitive impairment; GDS 2 indicates subjective cognitive impairment; GDS 3 corresponds to mild cognitive impairment (MCI); GDS 4–7 corresponds to mild, moderate, moderate-severe, or severe dementia. In this study, GDS 5–7 were grouped together as a single variable representing moderate-to-severe dementia.

2). Caregiver ratings of health-related quality of life, function, and behavior

The following scales were completed by the study partner to rate the participant. Activities of daily living were captured with the FAQ [34]. Dementia-related behaviors and psychological features were measured with the NPI [23]. The participant’s health-related quality of life was measured with the Health Utilities Index-Mark 3 (HUI-3) [33]. Participant personality traits were captured with the Ten-Item Personality Inventory (TIPI) [41] that characterizes five constructs of personality: extraversion, agreeableness, conscientiousness, emotional stability, and openness. Reverse scoring of emotional stability allowed the capture of neuroticism that is commonly reported in other personality inventories [42]. Informants were asked to rate the participant’s premorbid personality traits prior to the onset of cognitive and behavioral changes.

3). Cognitive evaluation

The participant and study partner independently completed the QDRS [31, 43] for a global dementia rating. Cognitive testing included the Montreal Cognitive Assessment [44] for a global screen, and the UDS psychometric battery supplemented with additional measures: 15-item Multilingual Naming Test (naming) [29]; Animal naming fluency (verbal fluency) [29]; Hopkins Verbal Learning Task (HVLT, episodic memory for word lists – immediate and delayed recall) [43]; Number forward/backward tests (working memory) [29]; Trailmaking A (processing and visuospatial abilities) and Trailmaking B (executive function) [46]; and the Number-Symbol Coding Test (executive function) [47]. The cognitive test battery was combined to create a composite sum of z-scores. The Hospital Anxiety and Depression Scale (HADS) [48] was performed for distinct ratings (range 0–21) of depression and anxiety.

4). Consensus diagnoses

Global rating scales (CDR, GDS) were combined with cognitive performance, the neurologic examination, and laboratory tests to assign individuals to the following diagnostic categories after a consensus conference: Cognitively normal controls, MCI[49] or Dementia. Cognitively normal controls were individuals without dementia(CDR0) who had no functional decline and scored within the normal range on cognitive tests. MCI individuals were those with cognitive impairment (CDR 0.5) who had no functional decline but scored more than 1.5 standard deviations in at least one cognitive domain [49]. Dementia diagnoses were determined using standard criteria for AD [50], dementia with Lewy bodies (DLB) [51], vascular contributions to cognitive impairment and dementia (VCID) [52], and FTD [24].

5). Ratings of caregiver characteristics

Caregiver burden was captured with the 12-item ZBI [35]. Caregiver mood was assessed using the Personal Health Questionnaire-4 (PHQ4) [53] with scores ranging from 0–12, with higher scores representing greater mood disturbance. An assessment of the overall caregiver experience was captured with the Positive and Negative Appraisals of Caregiving (PANAC) scale [54], providing separate scores for positive and negative appraisals ranging from 0–32, with higher scores representing more positive or negative feelings about caregiving.

Apolipoprotein E genotyping

Apolipoprotein E (APOE) genotyping was performed by True Health Diagnostics LLC (Richmond, VA) in the validation sample. Six possible allelic combinations were obtained with individuals dichotomized as being APOE 4 carriers or noncarriers.

Volumetric MRI

A subset of CDR 0, 0.5, and 1 participants in the validation sample (n = 49) underwent volumetric MRI with NeuroQuant software (CorTechs Labs, San Diego, CA), an FDA-approved automated quantitative analysis of brain MRI images with normative reference data adjusted for age, sex, and intracranial volume with high correlation to FreeSurfer [55] and visual assessment [56]. Two measures of hippocampal structure used: hippocampal volume and hippocampal occupancy [57]. While hippocampal volume is often used as a predictor of conversion of MCI to AD, hippocampal occupancy measures the degree of hippocampal atrophy accounting for volume loss and compensatory inferior lateral ventricle expansion. It is calculated as a ratio of hippocampal volume to the sum of the hippocampal and inferior lateral ventricle volumes in each hemisphere separately, which are then averaged and normalized for age and sex. This measure may aid in differentiation of individuals with congenitally small hippocampi from those with small hippocampi due to a degenerative disorder [57]. Two additional measures associated with frontal lobe structure are available from NeuroQuant: frontal parenchymal volume and superior lateral ventricle volume.

Statistical analysis

Analyses were conducted using SPSS v26 (IBM, Armonk, NY). Descriptive statistics were used to examine demographic characteristics of participants and caregivers, informant and patient rating scales, dementia staging paradigms, and neuropsychological testing. Demographic characteristics were compared using one-ANOVA for continuous variables and Chi-square for categorical variables. Tests of normality for FBB and NPI showed a skewed distribution with a right-sided tail so non-parametric statistics were used to compare groups. Mann-Whitney U(two groups) or Kruskal-Wallis with Bonferroni correction for multiple tests (for more than two groups) were used for continuous data and Chi-square analyses were used for categorical data. In cells with less than 5 samples, Fisher’s exact tests were used.

In the development sample, internal consistency was examined as the proportion of the variability in the responses that is the result of differences in respondents, reported as the Cronbach alpha reliability coefficient. Coefficients greater than 0.7 are good measures of internal consistency [31, 43]. To assess item variability in the developmental sample, the item frequency distributions, mean, standard deviations, inter-item and item-total correlations were calculated. Principal factor analysis with a Varimax rotation was performed to examine data structure of the FBB. Total FBB scores and individual items were compared across different FTD etiologies using Mann-Whitney U tests (two group comparisons) or Kruskal-Wallis with Bonferroni correction for multiple tests (more than two group comparisons). Strength of association between the FBB and outcomes were compared using Spearman correlation coefficients with Bonferroni correction for multiple comparisons.

In the validation sample, the presence of each FBB feature across different consensus diagnoses was compared using Chi-square analyses. Severity scores for each FBB variable across different consensus diagnoses was compared using Kruskal-Wallis with Bonferroni correction for multiple tests. Known-group validity was assessed by examining the FBB and NPI scores by participant age and sex, APOE status, subjective complaints based on patient-reported QDRS, informant type (spouse versus non-spouse), CDR and GDS staging, and dementia etiology [31, 43, 47]. Sex imbalances in the validation sample (i.e., more women in the healthy control group) were controlled for by covarying CDR stage. Strength of association was assessed comparing FBB and NPI scores with participant characteristics (e.g., age, duration of disease), performance on each measures of health (e.g., Charlson, Fried Frailty), cognition (i.e., neuropsychological testing), function (i.e., FAQ), behavior (e.g., HADS anxiety and depression), and caregiver ratings (e.g., ZBI, PHQ-4) factors using Spearman correlation coefficients with Bonferroni correction for multiple comparisons following the unified framework of construct validity [58]. Strength of association between MRI volumes were compared for two behavioral scales (FBB, NPI) and three cognitive scales (MoCA, NSCT, z-score).

Receiver operator characteristic (ROC) curves were used to assess the ability of the FBB and NPI to discriminate between (a) individuals with and without cognitive impairment, and (b) individuals with and without frontal lobe features. Results are reported as area under the curve (AUC) with standard errorsand 95% confidence intervals (CIs). AUCs between 0.70–0.79 are good, between 0.80–0.89 are very good, and 0.9 and greater are excellent. Positive and negative likelihood ratios, and diagnostic odds ratio for the FBB and NPI were calculated. The likelihood ratio of any screening test (which is independent of disease prevalence) is the probability that a positive test is found in persons with disease divided by the probability of the same finding in persons without disease [59, 60]. Likelihood ratios range from 0 to infinity, with larger numbers providing more convincing evidence of disease; smaller numbers argue that disease is less likely. Ratios close to 1 lack diagnostic value. The diagnostic odds ratio is a measure of the effectiveness of a diagnostic test [61, 62]. It is defined as the ratio of the odds of the test being positive if the subject has the condition of interest relative to the odds of the test being positive if the subject does not have the condition of interest. The diagnostic odds ratio is a single indicator of test performance but is independent of prevalence and presented as an odds ratio, which is familiar to medical practitioners and clinical researchers.

RESULTS

Development sample characteristics

The development sample (n = 586) had a mean age of 64.5±8.4 years, 96.8% had at least a high school education, 68.4% were female, 95.9% were White, and 2.4% reported Hispanic ethnicity. The mean duration of disease was 4.6±3.4 years and caregiver respondents rated 87% of the persons with FTD being in the moderate-to-severe stage. The mean caregiver version of the QDRS score was 18.3±7.4 and the mean CDR-SB score was 11.4±5.0, also supporting participants with FTD were in the moderate-to-severe stages. Caregiver respondents rated the persons with FTD with significant functional (mean FAQ: 22.8±7.8), behavioral (mean NPI: 12.7±6.9) and health-related quality of life (mean HUI-3:0.108±0.316) deficits. Moderate-to-severe caregiver burden was reported (mean ZBI: 27.9±8.0). The mean FBB score was 9.9±5.5 (range 0–33). FTD subtypes included 318 bvFTD, 124 PPA, 43 FTD-MND, 26 PSP/CBS, and 75 unspecified FTD. Characteristics by FTD subtypes are shown in Table 1.

Table 1.

Development Sample Characteristics (n = 586)

	bvFTD (n = 318)	PPA (n = 124)	FTD-MND (n = 43)	PSP/CBS (n = 26)	Non-specified (n = 75)	p
Age	64.7 (8.0)	66.5 (7.6)	63.8 (8.9)	68.8 (10.4)	66.0 (9.7)	0.032
Education, % 6th grade or less	0.0	0.0	2.3	0.0	1.4	0.759
% 7–9th grade	0.3	0.0	0.0	0.0	1.4
% 10–11th grade	2.8	1.6	2.3	3.8	2.7
% 12th grade	14.8	11.3	14.0	15.4	12.3
% partial college	22.0	26.6	23.3	34.6	19.2
% college graduate	28.0	27.4	34.9	23.1	30.1
% post-graduate	32.1	33.1	23.3	23.1	32.9
Sex, % female	70.8	70.2	74.4	38.5	63.0	0.009
Duration of disease, y	4.4 (3.6)	4.8 (2.7)	3.8 (2.7)	4.5 (2.9)	5.5 (3.6)	0.102
Severity of disease, % mild	7.9	5.6	4.7	7.7	5.5	0.466
% moderate	51.4	42.7	51.2	38.5	41.1
% severe	34.4	46.0	37.2	53.8	45.2
% recently died	6.3	5.6	7.0	0.0	8.2
QDRS	5.3 (1.8)	5.4 (2.5)	5.1 (2.4)	4.5 (1.7)	5.8 (2.8)	0.270
CDR-SB1	3.1 (1.1)	3.3 (1.9)	3.2 (1.7)	2.9 (1.5)	3.5 (1.9)	0.429
NPI	13.9 (6.9)	10.9 (6.7)	11.6 (7.6)	9.1 (5.8)	12.3 (6.1)	< 0.001
FAQ	22.4 (7.8)	23.8 (7.6)	23.9 (7.6)	21.6 (7.3)	22.9 (8.4)	0.428
ZBI	28.8 (7.6)	26.4 (8.4)	27.3 (8.1)	26.5 (8.8)	27.6 (8.3)	0.053
HUI-3	0.13 (0.3)	0.09 (0.3)	0.12 (0.3)	0.09 (0.3)	0.01 (0.26)	0.079
FBB	10.4 (5.7)	9.2 (5.1)	10.3 (5.5)	7.9 (3.5)	9.9 (5.4)	0.077
FBB Range of scores (Min-Max)	0–33	0–23	1–21	0–13	0–25

One-Way ANOVA with Mean (SD) or Chi square (%). QDRS, Quick Dementia Rating System; CDR-SB, Clinical Dementia Rating Sum of Boxes; NPI, Neuropsychiatric Inventory; FAQ, Functional Activities Questionnaire; ZBI, Zarit Burden Inventory; HUI-3, Health Utilities Index-Mark 3; FBB, Frontal Behavioral Battery.

¹CDR-SB derived from first 6 QDRS domain scores.

FBB data quality and psychometric properties

The mean, standard deviation, and inter-item correlations for each of the 11 FBB items is shown in Table 2. The individual FBB items were weakly-to-moderately correlated with each other suggesting that each question covered a different behavioral manifestation, however each item was moderately-to-strongly correlated with the total FBB. The internal consistency of the FBB as measured with Cronbach’s alpha was 0.699 (95%CI:0.64–0.75) suggesting acceptable reliability. Principal factor analysis (Table 3) of FBB revealed a three-factor solution: Disinhibition (24.2% variance explained), Functional (15.9% variance explained), and Social Interaction (10.7% variance explained).

Table 2.

Frontal Behavioral Battery item distributions, inter-item, and item-total correlations

FBB Item	Mean (SD)	Inter-Item Correlations											Item-Total R
		Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9	Q10	Q11
Difficulty with Speaking (Q1)	1.96 (1.1)	1											0.411
Difficulty with Swallowing (Q2)	0.81 (1.0)	0.304	1										0.427
Verbal Aggression (Q3)	0.68 (1.0)	−0.022	−0.030	1									0.498
Physical Aggression (Q4)	0.38 (0.8)	0.066	0.089	0.417	1								0.509
Inappropriate Sexual Behavior (Q5)	0.31 (0.7)	−0.031	0.045	0.158	0.225	1							0.383
Inappropriate Shopping (Q6)	0.65 (1.0)	−0.099	−0.044	0.339	0.177	0.206	1						0.453
Inappropriate Clothing Choices (Q7)	0.62 (0.9)	0.100	−0.033	0.253	0.219	0.253	0.315	1					0.506
Change in Communication (Q8)	1.69 (1.2)	0.241	0.103	0.194	0.214	0.171	0.152	0.286	1				0.573
Falling (Q9)	0.86 (1.1)	0.106	0.349	0.143	0.147	0.053	0.100	−0.022	0.078	1			0.472
Unusual Movements (Q10)	0.093 (1.1)	0.195	0.270	0.050	0.081	0.070	0.104	0.075	0.197	0.377	1		0.504
Refusal to Bathe/Hygiene (Q11)	1.12 (1.2)	0.165	0.119	0.219	0.247	0.181	0.200	0.345	0.301	0.135	0.173	1	0.597

FBB, Frontal Behavioral Battery. Bold signifies R-value significance after correction for multiple comparisons (corrected p-value < 0.0045).

Table 3.

Factor Analyses for Frontal Behavioral Battery

FBB Item	Factor 1 Disinhibition	Factor 2 Functional	Factor 3 Social Interaction
Verbal Aggression	0.666	0.067	−0.060
Inappropriate Clothing Choices	0.519	−0.103	0.301
Inappropriate Spending/Shopping	0.516	0.019	−0.059
Physical Aggression	0.503	0.137	0.106
Inappropriate Sexual Behavior	0.353	0.010	0.084
Falling	0.119	0.751	−0.072
Difficulty Swallowing	−0.073	0.507	0.229
Unusual Movements	0.113	0.489	0.179
Change in Speaking/Language	−0.119	0.242	0.552
Change in Communicating with Family/Friends	0.353	0.096	0.458
Refusal to Bath/Hygiene	0.394	0.087	0.402
Eigenvalue	2.66	1.75	1.18

Principal Factor Analysis with Varimax Rotation. FBB, Frontal Behavioral Battery. Bold signifies factor that item best loads.

Relationship of FBB to diagnoses and caregiver-reported outcomes

Mean scores for individual FBB items and total FBB scores by FTD subtype diagnoses are shown in Table 4. With post-hoc testing correcting for multiple comparisons, significant differences in responses to change in speaking and language, inappropriate sexual behavior, inappropriate shopping/spending, inappropriate clothing choices, change in communicating with family, and falling were found between FTD subtypes. However, there were no differences in total FBB scores between FTD subtypes (H = 6.8, p = 0.147). There was no relationship between FBB and patient age or duration of disease. Significant correlation was found between FBB scores and caregiver-reported QDRS (ρ = 0.426, p < 0.001), FAQ (ρ = 0.332, p < 0.001), NPI (ρ = 0.688, p < 0.001), HUI-3 (ρ = −0.441, p < 0.001), and ZBI scores (ρ = 0.387, p < 0.001).

Table 4.

Frontal Behavioral Battery Severity Score by FTD Subtypes

	bvFTD (n = 318)	PPA (n = 124)	FTD-MND (n = 43)	PSP/CBS (n = 26)	Non-specified (n = 75)	p
Change in Speaking/Language	1.7 (1.2)	2.5 (0.9)	1.9 (1.2)	1.8 (1.2)	2.1 (1.1)	< 0.001a
Difficulty Swallowing	0.7 (0.9)	0.8 (1.0)	1.1 (1.1)	1.1 (1.2)	0.9 (1.1)	0.028
Verbal Aggression	0.8 (1.1)	0.5 (0.8)	0.5 (0.9)	0.4 (0.7)	0.6 (0.9)	0.030b
Physical Aggression	0.4 (0.9)	0.3 (0.8)	0.2 (0.6)	0.2 (0.5)	0.4 (0.8)	0.574
Inappropriate Sexual Behavior	0.4 (0.8)	0.3 (0.8)	0.2 (0.7)	0.0 (0.0)	0.2 (0.6)	< 0.001c
Inappropriate Spending/Shopping	0.8 (1.1)	0.4 (0.8)	0.7 (1.1)	0.0 (0.0)	0.5 (0.9)	< 0.001d
Inappropriate Clothing Choices	0.7 (1.0)	0.6 (0.9)	0.2 (0.7)	0.1 (0.3)	0.7 (1.1)	0.001e
Change in Communicating with Family/Friends	1.8 (1.2)	1.6 (1.3)	1.3 (1.3)	0.7 (0.9)	1.3 (1.3)	< 0.001f
Falling	0.7 (1.0)	0.6 (0.9)	1.4 (1.2)	1.6 (1.1)	0.8 (1.1)	< 0.001g
Unusual Movements	0.9 (1.1)	0.7 (0.9)	1.2 (1.1)	1.0 (1.1)	0.7 (1.1)	0.015h
Refusal to Bath/Hygiene	1.2 (1.2)	0.9 (1.1)	0.9 (1.2)	0.5 (0.9)	1.0 (1.2)	0.014i
Total FBB Score	10.4 (5.7)	9.2 (5.1)	10.3 (5.5)	7.9 (3.5)	9.9 (5.4)	0.147
FBB Range of scores (Min-Max)	0–33	0–23	1–21	0–13	0–25

Kruskal-Wallis with Mean (SD) shown. bvFTD, Behavioral Variant of Frontotemporal Degeneration; PPA, Primary Progressive Aphasia; FTD-MND, Frontotemporal Degeneration with Motor Neuron Disease; PSP, Progressive Supranuclear Palsy; CBS, Corticobasal Syndrome; FBB, Frontal Behavioral Battery. Post-hoc comparisons adjusted for multiple tests.

^aPPA different from bvFTD, FTD-MND, PSP/CBS; bvFTD different from non-specified.

^bPPA different from bvFTD.

^cbvFTD different from PSP/CBS, non-specified.

^dbvFTD different from PPA, PSP/CBS; PSP/CBS different from FTD-MND.

^ebvFTD different from FTD-MND, PSP/CBS.

^fbvFTD different from non-specified; PSP/CBS different from bvFTD, PPA.

^gFTD-MND different from bvFTD, PPA, non-specified; PSP/CBS different from bvFTD, PPA, non-specified.

^hPPA different from FTD-MND.

ⁱbvFTD different from PSP/CBS.

Validation sample characteristics

The validation sample (n = 274) had a mean age of 74.5±9.8 years (range 38–98), 15.4±2.6 years of education (range 8–20) and a duration of disease of 3.3±2.9 years (range 0–16). The participants were 51.1% female, 96.7% White, with 5.5% of the sample reporting Hispanic ethnicity. The study partners had a mean age 56.3±15.3 years (range 20–76), 16.0±2.6 years of education (range 4–20), 62.5% were women and 68.8% were spouses. The sample consisted of 46 cognitively normal controls, 87 MCI, 44 AD, 71 DLB, 18 VCID, and 8 FTD. APOE ε4 alleles were present in 38% of the sample. The sample mean MoCA score was 19.1±6.9 (range 1–30) with a mean CDR-SB of 4.4±4.7 (range 0–18). The mean informant-reported QDRS was 5.8±5.8 (range 0–28) and the mean patient-reported QDRS was 4.5±4.9 (range 0–24). The mean FAQ score was 8.4±9.5 (range 0–30), the mean NPI score was 5.5±5.2 (range 0–27) and the mean HUI-3 score was 0.55±0.34 (range −0.23–1.40). The characteristics of the validation sample by consensus diagnosis is shown in Table 5.

Table 5.

Characteristics for Validation Sample (n = 274)

Variable	Control (N = 46)	MCI (N = 87)	AD (N = 44)	DLB (N = 71)	VCID (N = 18)	FTD (N = 8)	F-value or χ2	p
Age, y	66.3 (9.6)	72.5 (9.5)	80.7 (8.7)	77.2 (7.8)	79.9 (5.2)	73.4 (4.4)	16.5	< 0.001
Education, y	16.0 (2.2)	15.9 (2.5)	14.9 (2.5)	14.9 (2.8)	14.9 (2.5)	15.4 (3.2)	2.22	0.052
Sex, %F	76.1	48.3	56.8	31.0	66.7	50.0	25.6	< 0.001
Duration of disease, y	n/a	2.5 (2.6)	3.6 (2.6)	4.3 (3.2)	3.6 (2.4)	4.9 (3.6)	6.0	< 0.001
QDRS-Informant	0.7 (1.1)	2.8 (3.1)	7.1 (3.8)	10.7 (6.5)	9.2 (6.8)	7.6 (5.9)	37.7	< 0.001
QDRS-Patient	0.5 (1.1)	2.6 (2.9)	4.8 (3.8)	8.1 (5.4)	7.7 (6.4)	8.6 (9.2)	26.2	< 0.001
FAQ	0.1 (0.5)	2.8 (4.4)	12.2 (7.9)	16.2 (9.1)	15.2 (11.0)	9.9 (11.1)	46.6	< 0.001
NPI	1.4 (1.9)	4.4 (4.5)	5.6 (3.5)	9.2 (6.1)	6.6 (4.9)	6.2 (3.3)	18.3	< 0.001
HUI-3	0.87 (0.2)	0.67 (0.2)	0.45 (0.3)	0.32 (0.3)	0.36 (0.4)	0.56 (0.4)	25.9	< 0.001
mPPT	13.1 (1.6)	10.9 (2.8)	8.4 (3.6)	7.8 (3.4)	6.9 (2.9)	10.1 (2.6)	25.5	< 0.001
MoCA	26.5 (2.4)	23.0 (3.1)	13.7 (6.0)	14.2 (5.7)	14.2 (6.6)	14.3 (3.7)	68.9	< 0.001
Z-Score	1.16 (0.3)	0.35 (0.6)	−1.03 (0.8)	−0.91 (0.6)	−0.91 (0.7)	−1.15 (0.9)	74.7	< 0.001
Hachinski	0.4 (0.5)	0.8 (1.2)	0.8 (0.90	0.9 (1.2)	4.0 (1.5)	0.4 (0.7)	30.1	< 0.001
Fried Frailty	0.9 (0.9)	2.0 (1.4)	2.8 (1.3)	3.4 (1.1)	3.3 (0.7)	2.0 (0.6)	26.5	< 0.001
Charlson	0.9 (1.4)	2.4 (1.6)	2.8 (1.40	2.7 (1.6)	3.8 (2.0)	1.5 (0.7)	11.9	< 0.001
CDR-SB	0.1 (0.2)	1.5 (1.1)	6.2 (3.7)	8.6 (4.6)	7.2 (5.2)	6.2 (5.1)	59.3	< 0.001

One-way ANOVA with Mean (SD) or Chi square with %. MCI, mild cognitive impairment; AD, Alzheimer’s disease; DLB, dementia with Lewy bodies; VCID, vascular contributions to cognitive impairment and dementia; FTD, frontotemporal degeneration; QDRS, Quick Dementia Rating System; FAQ, Functional Activities Questionnaire; NPI, Neuropsychiatric Inventory; HUI-3, Health Utilities Index-Mark 3; mPPT, mini-Physical Performance Test; MoCA, Montreal Cognitive Assessment; CDR-SB, Clinical Dementia Rating Sum of Boxes; ZBI, Zarit Caregiver Burden Inventory.

Properties of FBB in the validation sample

The mean FBB score was 2.9±3.4 (range 0–17). The presence (%) and severity (mean) of the 11 individual FBB items are shown in Table 6. The validation sample had lower total FBB scores than the development sample due to (a) the inclusion of cognitively normal controls and MCI individuals, and (b) the overall lower global severity in individuals with AD, DLB, VCID, and FTD as measured by the CDR-SB and QDRSscores. Despite differences in the samples, there was a range of presence and severity scores for each FBB item that aligns well with known behavioral and functional features for each diagnosis.

Table 6.

Presence and Severity of Frontal Behavioral Battery by Diagnosis

Presence of Symptom, %	Control (N = 46)	MCI (N = 87)	AD (N = 44)	DLB (N = 71)	VCID (N = 18)	FTD (N = 8)	χ2	p a
Change in Speaking/Language	4.5	31.0	61.4	81.7	33.3	100.0	89.0	< 0.001
Difficulty Swallowing	2.3	9.2	9.1	25.7	5.6	42.9	22.6	< 0.001
Verbal Aggression	6.8	18.4	9.1	22.5	27.8	50.0	14.0	0.016
Physical Aggression	2.3	2.3	0.0	5.6	0.0	37.5	29.7	< 0.001
Inappropriate Sexual Behavior	0.0	3.4	2.3	5.6	0.0	12.5	5.5	0.354
Inappropriate Spending/Shopping	6.8	8.1	11.4	12.7	16.7	12.5	2.3	0.803
Inappropriate Clothing Choices	2.3	2.3	9.1	19.7	16.7	0.0	19.6	0.001
Change in Communicating with Family/Friends	6.8	12.6	18.2	35.2	22.2	50.0	22.4	< 0.001
Falling	4.7	19.5	18.2	40.8	22.2	37.5	22.9	< 0.001
Unusual Movements	4.5	20.7	20.5	50.0	11.1	12.5	37.3	< 0.001
Refusal to Bath/Hygiene	0.0	5.7	15.9	29.6	5.6	12.5	29.3	< 0.001
Severity Scores, Mean (SD)	Control (N = 46)	MCI (N = 87)	AD (N = 44)	DLB LB (N = 71)	VCID (N = 18)	FTD (N = 8)	H	p
Change in Speaking/Language	0.04 (0.21)	0.49 (0.80)	1.05 (1.01)	1.35 (0.94)	0.56 (0.86)	2.00 (0.93)	20.4	< 0.001b
Difficulty Swallowing	0.02 (0.15)	0.13 (0.45)	0.11 (0.39)	0.34 (0.68)	0.17 (0.71)	0.86 (1.21)	4.7	< 0.001c
Verbal Aggression	0.09 (0.36)	0.28 (0.62)	0.14 (0.46)	0.42 (0.89)	0.44 (0.86)	0.63 (0.74)	2.4	0.016
Physical Aggression	0.04 (0.29)	0.02 (0.15)	0.00 (0.00)	0.10 (0.45)	0.00 (0.00)	0.50 (0.76)	4.4	0.001d
Inappropriate Sexual Behavior	0.00 (0.00)	0.03 (0.18)	0.05 (0.30)	0.08 (0.37)	0.00 (0.00)	0.25 (0.71)	1.5	0.334
Inappropriate Spending/Shopping	0.07 (0.25)	0.10 (0.38)	0.14 (0.41)	0.20 (0.58)	0.44 (1.04)	0.13 (0.35)	1.8	0.708
Inappropriate Clothing Choices	0.02 (0.15)	0.05 (0.34)	0.09 (0.29)	0.34 (0.77)	0.28 (0.75)	0.00 (0.00)	3.8	0.001e
Change in Communicating with Family/Friends	0.09 (0.36)	0.24 (0.69)	0.20 (0.46)	0.61 (0.96)	0.33 (0.84)	0.88 (1.13)	4.3	< 0.001f
Falling	0.04 (0.21)	0.31 (0.70)	0.30 (0.67)	0.62 (0.88)	0.39 (0.85)	0.50 (0.76)	3.8	< 0.001g
Unusual Movements	0.04 (0.21)	0.31 (0.70)	0.34 (0.78)	0.80 (0.97)	0.17 (0.51)	0.13 (0.35)	7.2	< 0.001h
Refusal to Bath/Hygiene	0.00 (0.00)	0.09 (0.39)	0.32 (0.77)	0.46 (0.81)	0.06 (0.24)	0.13 (0.35)	5.4	< 0.001i

Chi-square analyses/Fisher exact tests with% or Kruskal-Wallis with Mean (SD) shown.

^aBold signifies significance in Chi-square tests after correction for multiple comparisons (corrected p-value < 0.0045). MCI, mild cognitive impairment; AD, Alzheimer’s disease; DLB, dementia with Lewy bodies; VCID, vascular contributions to cognitive impairment and dementia; FTD, frontotemporal degeneration. Kruskal-Wallis Post-hoc comparisons adjusted for multiple tests.

^bControls different from AD, DLB, FTD; MCI different from AD, DLB, FTD; VCID different from DLB and FTD.

^cControls different from DLB and FTD; MCI different from DLB.

^dFTD different from all other groups.

^eControls different from DLB, MCI different from DLB.

^fControls different from DLB; MCI different from DLB; FTD different from Controls, MCI, AD and VCID.

^gMCI different from DLB.

^hDLB different from Controls, MCI, AD, and VCID.

ⁱDLB different from Controls and MCI.

Known group validity of the FBB

The performance of the FBB was compared between participant age, sex, GDS stage, patient-reported QDRS scores, CDR stages, informant type, and consensus diagnosis in Table 7. For comparison, NPI score as also presented. Post-hoc analyses adjusting for multiple comparisons demonstrated differences by age with younger individuals having less FBB symptoms than older individuals (H = 18.9, p < 0.001). There was no difference in age between male (75.1±9.2 years) and female (73.9±10.3, p = 0.302) participants; however, after adjusting for dementia severity with the CDR-SB, male participants experienced more symptoms than females (p < 0.001). There was no difference in FBB scores by informant type (spouse versus non-spouse). There was no difference in FBB scores by APOE carrier status (data not shown). Using a cut-off of 2 on the patient-reported QDRS as a measure of subjective complaints, individuals with subjective complaints had significantly higher FBB scores than individuals without subjective complaints (p < 0.001). Using the GDS as a global rating further supported this finding, with GDS 2 individuals having numerically higher FBB scores than GDS 1 individuals (0.8±1.5 versus 0.1±0.5, p = 0.08). This finding of subjective complaints resulting in higher FBB scores was similarly true in both MCI (2.9±3.5 versus 1.2±1.5, p = 0.003) and dementia (4.5±3.7 versus 1.9±1.7, p = 0.005) participants who had subjective cognitive complaints compared with those that did not. This was not the case with the NPI, which did not distinguish between those with and without subjective complaints. As measured by both the GDS and CDR, post-hoc analyses adjusted for multiple comparisons demonstrated that FBB scores increased with severity (H_GDS = 84.1, p < 0.001; H_CDR = 88.9, p < 0.001). When examined by consensus diagnoses, post-hoc analyses adjusting for multiple comparisons revealed that DLB and FTD individuals had the highest FBB scores, followed by AD and VCID. Cognitively normal controls were different from MCI and dementia groups, while MCI was different from dementia groups (H = 90.6, p < 0.001).

Table 7.

Known Group Validity for FBB

	Age, y					Sex
	< 60 (n = 21)	60–69 (n = 57)	70–79 (n =105)	80+ (n = 91)	p	Male (n = 134)	Female (n = 140)	p
FBB	1.3 (2.5)	2.2 (3.2)	3.2 (3.8)	3.3 (3.2)	< 0.001a	3.9 (4.0)	1.9 (2.4)	< 0.001b
NPI	3.8 (4.1)	4.7 (5.2)	6.1 (5.7)	5.9 (4.8)	0.055	6.9 (5.8)	4.2 (4.1)	< 0.001
	Global Deterioration Scale (GDS) Stages						Patient QDRS
	1 (n = 26)	2 (n = 20)	3 (n = 86	4 (n = 72)	5+ (n = 70)	p	< 2 (n = 102)	≥2 (n = 161)	p
FBB	0.1 (0.5)	0.8 (1.4)	2.2 (3.0)	3.1 (3.1)	5.2 (3.9)	< 0.001c	0.9 (1.5)	3.9 (3.7)	< 0.001
NPI	0.9 (1.4)	2.3 (2.4)	4.4 (4.6)	6.4 (4.9)	8.7 (5.5)	< 0.001	2.9 (3.6)	6.9 (5.3)	< 0.001
	Clinical Dementia Rating (CDR) Stages						Informant Type
	0 (n = 46)	0.5 (n = 117)	1 (n = 59)	2 (n = 35)	3 (n = 17)	p	Spouse (n = 179)	Non-Spouse (n = 81)	p
FBB	0.5 (1.0)	2.1 (2.8)	4.1 (3.4)	5.1 (3.9)	6.3 (3.9)	< 0.001d	3.2 (3.6)	2.6 (3.1)	0.193
NPI	1.4 (1.9)	4.7 (4.4)	7.3 (5.2)	9.3 (5.8)	8.5 (6.1)	< 0.001	5.9 (5.2)	5.1 (5.3)	0.102
	Consensus Diagnosis
	Control (n = 46)	MCI (n = 87)	AD (n = 44)	DLB (n = 71)	VCID (n = 18)	FTD (n = 8)	p
FBB	0.5 (1.0)	2.1 (2.8)	2.7 (2.4)	5.3 (3.9)	2.8 (3.8)	5.9 (3.1)	< 0.001e
NPI	1.4 (1.9)	4.5 (4.5)	5.6 (3.5)	9.2 (6.1)	6.6 (4.9)	6.2 (3.3)	< 0.001

Mann-Whitney U (two groups) or Kruskal-Wallis (more than two groups), with Mean (SD) shown. FBB, Frontal Behavioral Battery; NPI, Neuropsychiatric Inventory; GDS, Global Deterioration Scale; QDRS, Quick Dementia Rating System; CDR, Clinical Dementia Rating; MCI, mild cognitive impairment; AD, Alzheimer’s disease; DLB, dementia with Lewy bodies; VCID, vascular contributions to cognitive impairment and dementia; FTD, frontotemporal degeneration. FBB Post-hoc analyses with adjusted p-values for multiple tests:

^a< 60 different from 70–79 and 80+; 60–69 different from 80+ .

^bMales different from females after controlling for dementia severity (CDR).

^cGD1 different from GDS 3–5+; GDS 2 different from GDS 4–5+; GDS 3 different from GDS 5+; GDS 4 different from GDS 5 + .

^dCDR 0 different from other groups; CDR 0.5 different from other groups; CDR 1–3 not different from each other.

^eControls different from other groups; MCI different from controls, DLB and FTD; DLB different from controls, MCI, AD and VCID; FTD different from controls and MCI.

Relationship between FBB and participant personality

Five different personality traits collected as part of the TIPI [41] were examined for their relationship to the study partner’s endorsement of frontal lobe symptoms (Table 8). We first examined the strength of association between each personality trait and total FBB scores with Spearman correlation coefficients. After correcting for multiple comparisons, we found negative correlation between FBB scores and the traits of extroversion, agreeableness, and openness. We then compared mean FBB scores for each trait considering individuals whose caregivers reported high premorbid scores vs individuals who had low premorbid scores for that trait. After correction for multiple comparisons, individuals with high pre-morbid extroversion (p < 0.001), agreeableness (p = 0.005), and openness (p < 0.001) were associated with lower FBB scores.

Table 8.

Relationship Between FBB and Personality

Personality Trait	ρ (p)	Personality Trait (% individuals)	Mean (SD)	p
Extroversion	−0.345 (< 0.001)	Low (41.2%)	3.7 (3.6)	0.001
		High (58.8%)	2.2 (3.6)
Agreeableness	−0.245 (0.005)	Low (40.5%)	3.9 (3.9)	0.007
		High (59.5%)	2.2 (3.3)
Conscientiousness	−0.151 (0.084)	Low (25.2%)	4.1 (4.9)	0.102
		High (74.8%)	2.4 (3.1)
Neuroticism	0.226 (0.009)	Low (67.9%)	2.5 (3.6)	0.054
		High (32.1%)	3.5 (3.6)
Openness	−0.304 (<0.001)	Low (45.8%)	3.4 (3.7)	0.009
		High (54.2%)	2.4 (3.5)

Spearman coefficient and Mann-Whitney U Test. Bold signifies significance after correction for multiple comparisons (corrected p < 0.01). FBB, Frontal Behavioral Battery.

Strength of association between FBB scores and outcome measures

Table 9 demonstrates the construct (concurrent) validity of the FBB by the strength of association between the FBB and participant characteristics, caregiver ratings, and measures of cognition, function, behavior, and physical functionality. For comparison, strength of association with NPI is provided for each outcome measure. Moderate-to-strong correlations are demonstrated between the FBB and informant ratings of global cognition (QDRS, CDR-SB), function (FAQ), health-related quality of life (HUI-3), and caregiver distress (PANAC-negative, ZBI, PHQ-4). There were weak-to-moderate correlations between the FBB and patient characteristics and cognitive performance. This pattern was similar to strengths of association seen with the NPI. These data suggest that the FBB captures non-cognitive frontal lobe features that are disturbing to caregivers as opposed to cognitive performance.

Table 9.

Strength of Association Between Study Variables, FBB and NPI

Variable	FBB	NPI
Participant Characteristics
Age	0.244	0.171
Education	−0.078	−0.004
Disease Duration	0.342	0.307
QDRS-patient	0.580	0.519
Hachinski	0.061	0.087
Mini Physical Performance Test	−0.356	−0.309
Charlson	0.233	0.229
Fried Frailty	0.379	0.369
HADS-Anxiety	0.173	0.243
HADS-Depression	0.282	0.385
Participant Performance
MoCA	−0.452	−0.446
Numbers Forward	−0.157	−0.176
Numbers Backward	−0.262	−0.197
HVLT-Immediate	−0.412	−0.424
HVLT-Delay	−0.339	−0.363
Trailmaking A	0.422	0.379
Trailmaking B	0.345	0.316
Number Symbol Coding Task	−0.431	−0.420
Animal Naming	−0.436	−0.379
Multilingual Naming Test	−0.220	−0.219
Composite z-Score	−0.361	−0.416
Informant Ratings
QDRS-Informant	0.658	0.669
Functional Activities Questionnaire	0.604	0.561
NPI	0.716	—
Health Utilities Index Mark-3	−0.599	−0.587
CDR-SB	0.613	0.555
PANAC-Negative	0.437	0.536
PANAC-Positive	−0.043	0.032
Zarit Burden Inventory	0.624	0.663
Personal Health Questionnaire-4	0.445	0.512

Spearman ρ-coefficient (p-value); Bold signifies significance after correction for multiple comparisons (p < 0.0017). FBB, Frontal Behavioral Battery; NPI, Neuropsychiatric Inventory; QDRS, Quick Dementia Rating System; HADS, Hospital Anxiety and Depression Scale; MoCA, Montreal Cognitive Assessment; HVLT, Hopkins Verbal Learning Task; PANAC, Positive and Negative Appraisals of Caregiving; ZBI, Zarit Caregiver Burden Inventory; CDR-SB, Clinical Dementia Rating Sum of Boxes.

Convergent validity between FBB scores and individual domains for patient and informant QDRS and CDR are shown in Table 10. There is moderate-to-strong correlation between FBB scores for all QDRS and CDR domains. The patient QDRS attention domain (ρ = 0.518) shows the strongest association with FBB, while the language domain (ρ = 0.318) shows the weakest. The informant QDRS attention domain (ρ = 0.612) shows the strongest association, while the personal hygiene and toileting domain shows the weakest association (ρ = 0.449). The CDR domain home and hobbies shows the strongest association (ρ = 0.508), while the supplemental CDR domain language shows the weakest association (ρ = 0.389).

Table 10.

Convergent Validity Between FBB, Patient and Informant Version of QDRS, and CDR Domains

QDRS/CDR Domain	FBB Correlation with:
	Patient QDRS	Informant QDRS	CDR
Memory	0.342	0.496	0.414
Orientation	0.346	0.473	0.409
Judgment	0.332	0.526	0.493
Community Activities	0.394	0.502	0.468
Home and Hobbies	0.324	0.551	0.508
Personal Hygiene	0.333	0.449	0.456
Behavior	0.444	0.561	0.436 *
Language	0.318	0.489	0.389 *
Mood	0.382	0.537	n/a
Attention	0.518	0.612	n/a

Spearman ρ-coefficient (p-value). Bold signifies significance after correction for multiple comparisons (p < .005). FBB, Frontal Behavioral Battery; QDRS, Quick Dementia Rating System; CDR, Clinical Dementia Rating System; n/a, not applicable.

^*Behavior and Language domains are supplemental CDR domains not included in global rating.

Relationship between FBB and MRI volumes

We explored potential neuroanatomical substrates for FBB in a subset of individuals rated CDR 0, 0.5, or 1 (n = 49) who underwent volumetric MRI using NeuroQuant. Strength of association between 2 hippocampal measures (hippocampal volume, hippocampal occupancy) and 2 putative frontal measures (frontal parenchymal volume, superior lateral ventricle volume) and FBB are shown in Table 11. For comparison, strength of association with another behavioral measure (NPI) and three cognitive measures, MoCA (global), NSCT (executive function), and z-scores were provided for each MRI measure. Neither FBB or NPI were associated with any MRI measures while cognitive measures were associated with hippocampal volume, hippocampal occupancy, and superior lateral ventricle volume. Frontal parenchymal volumes were only associated with cognitive z-scores.

Table 11.

Relationship Between FBB, NPI and Cognitive Tests with MRI Volumes and EPR Measures

MRI Measure	FBB	NPI	MoCA	NSCT	Composite z-Score
Hippocampal Volume (cm3)	−0.106 (0.478)	−0.230 (0.121)	0.509 (0.001)	0.585 (< 0.001)	0.598 (< 0.001)
Hippocampal Occupancy Score	−0.177 (0.225)	−0.306 (0.032)	0.618 (< 0.001)	0.656 (< 0.001)	0.661 (< 0.001)
Superior Lateral Ventricle (cm3)	0.133 (0.368)	0.177 (0.230)	−0.432 (0.002)	−0.468 (0.001)	−0.471 (0.001)
Frontal Parenchyma Volume (cm3)	0.051 (0.731)	0.025 (0.866)	0.352 (0.014)	0.332 (0.021)	0.398 (0.007)

Spearman ρ-coefficient (p-value). Bold signifies significance after correction for multiple comparisons (p < 0.0125). FBB, Frontal Behavioral Battery; NPI, Neuropsychiatric Inventory; MoCA, Montreal Cognitive Assessment; NSCT, Number Symbol Coding Task; MRI, magnetic resonance imaging.

Discriminability of the FBB

We tested the ability of the FBB to discriminate between individuals with and without cognitive impairment using ROC analyses. For comparison, we repeated the ROC analyses with the NPI. The FBB provided very good discrimination (AUC: 0.812; 95% CI: 0.755–0.869, p < 0.001) between cognitive normal controls and those with any form of cognitive impairment. The NPI also provided very good discrimination (AUC: 0.836; 95% CI: 0.781–0.892, p < 0.001). For the FBB, a cut-off of 2 or greater provided the best combination of sensitivity (0.739) and specificity (0.774). The positive likelihood ratio was 5.65 while the negative likelihood ratio was 0.43 with a diagnostic odds ratio of 13.1.

Based on our analyses, DLB and FTD had higher FBB scores and more frontal lobe features than cognitively normal controls, MCI, AD, and VCID cases. We therefore repeated the ROC analyses for the FBB and NPI to discriminate cases with prominent frontal lobe features (DLB and FTD) versus other diagnoses. The FBB provide very good discrimination (AUC: 0.800; 95% CI: 0.745–0.856, p < 0.001) while the NPI provided good discrimination (AUC: 0.759; 95% CI: 0.697–0.820, p < 0.001). A cut-off score of 2 on the FBB again provided the best combination of sensitivity (0.848) and specificity (0.738) with a positive likelihood ratio of 2.12, a negative likelihood ratio of 0.25, and a diagnostic odds ratio of 84.8.

DISCUSSION

We found that the measurement and quantification of frontal lobe symptoms was feasible using the FBB, permitting the characterization of 11 distinct features. In both the development and validation samples, the FBB detected frontal lobe features associated with neurodegenerative disease. These results suggest that the FBB captured a different set of behavioral symptoms compared with the NPI, although the two were highly correlated. The FBB was more strongly correlated with global rating scales (e.g., QDRS, CDR, FAQ) than with neuropsychological tests, suggesting that the FBB captures and characterizes non-cognitive features of neurologic disease.

The FBB scores increase with age and dementia severity but were not specifically linked to disease duration, supporting that the FBB could be used to characterize frontal lobe symptoms throughout the continuum of neurodegenerative disease. Individuals with DLB and FTD had the highest FBB scores compared with other causes of cognitive impairment. Although there were fewer cases of FTD in the validation sample, the large number of FTD cases in the development sample supports the ability of the FBB to capture a wide array of frontal lobe symptoms across distinct syndromes (bvFTD, PPA, FTD-MND, PSP, CBS) associated with frontal lobe degeneration. We found that men experienced more frontal lobe symptoms than women. The reasons for this need further exploration but could be due to the higher prevalence of men in the groups that experienced the highest frontal lobe symptoms (69% of DLB, 50% of FTD), or that women may experience other symptoms not captured in the FBB.

We also found that individuals who had premorbid personality traits of extroversion, agreeableness, and openness had significantly fewer FBB symptoms reported by caregivers compared with other personality traits. Agreeableness is associated with pro-social traits and behaviors including sympathy, altruism, cooperation, and consideration [41, 42]. Individuals who score high in agreeableness tend to be more people-oriented and trustful with good social skills and avoid conflict, whereas people who score low in agreeableness tend to be selfish, competitive, aggressive, and uncooperative [41, 42]. Interestingly, of the 5 personality traits, agreeableness is least affected by age [63], so that changes in an individual’s level of agreeableness may be symptomatic of neurodegenerative disease. These findings may provide new areas of research as personality traits that have been associated with cognitive decline and dementia include low conscientiousness and openness and high neuroticism [64]. The extant literature is unclear of the potential role of extraversion and agreeableness in the risk of dementia, and associations tend to vary by dementia-type, country, and personality measurement instruments [64]. Here, we describe the potential protective relationship between premorbid traits of extroversion, agreeableness, and openness from development of frontal lobe behavioral symptoms.

We also found that individuals with subjective cognitive complaints (as captured by the patient-reported QDRS or in the GDS staging) had higher FBB scores that those individuals without subjective complaints, regardless of their cognitive status. This was not the case with the NPI, suggesting that the FBB symptoms are more recognizable to informants in individuals with preserved insight since they may alter or impair the person living with dementia’s daily functioning and typically social interactions. The NPI captures more psychotic (e.g., hallucinations, delusions) or mood (e.g., apathy, euphoria) features, and the informants may not recognize or endorse these symptoms early in the course of disease.

The anatomic substrate of the behavioral symptoms captured by the FBB was explored in a subset of individuals with structural MRI. While cognitive scores were associated with hippocampal and lateral ventricle volumes, neither behavioral measure was correlated with available volumes. Although NeuroQuant and more commonly used research programs for volumetric analyses (i.e., Freesurfer) are similar [55, 56], the number of regions available from NeuroQuant are limited and only a subset of individuals from the sample had volumetric imaging. Future studies could explore more detailed structural analyses [65] and diffusion imaging to examine white matter tract integrity [14, 66].

The FBB provided very good discrimination between individuals with and without cognitive impairment with a 13-fold increase in the odds of a neurodegenerative disease with scores 2 or greater. The FBB also provided very good discrimination between individuals with and without frontal lobe features with an 84-fold odds ratio. While the NPI performed equally well discriminating between those with and without cognitive impairment, the FBB appeared to perform better discriminating those with non-cognitive frontal lobe symptoms. This suggests that the FBB could potentially be used in screening paradigms to detect and describe frontal behavioral phenomena in conjunction with other measures used to discriminate healthy controls from those with cognitive impairment. It also suggests that the FBB could be applied to other neurologic (e.g., traumatic brain injury, multiple sclerosis) and psychiatric (i.e., schizophrenia) conditions that affect frontal lobe functioning.

The measure of behavioral symptoms is generally done by caregiver input or direct observation of the person living with dementia. As direct observation is rarely practical, informant-based assessments have become the norm in clinical research. There are several scales available, including the Behavioral Pathology in Alzheimer Disease Rating Scale [67], the Cornell Scale for Depression in Dementia [68], the Behavioral and Emotional Activities Manifested in Dementia [69], and the NPI [22, 23]. The NPI is a comprehensive and commonly used measure with established reliability and validity. The NPI captures 12 dementia-associated behaviors, although some behaviors such as elation/euphoria are infrequently endorsed. In community-based samples, the prevalence of neuropsychiatric symptoms varied based on the type of disease (e.g., AD, FTD, VCID), who completed the assessment (formal or informal caregivers or other health care providers), severity of disease (mild versus moderate or severe impairment) and sex [70–73]. These studies noted that the majority of symptoms seem to be more common in individuals with VCID compared to those with AD. Specifically, there was more euphoria, apathy, irritability and sleep disturbance in individuals with VCID than those with AD, and females with AD tended to have more delusions and disinhibition. The NPI does not capture functional deficits associated with frontal lobe such as swallowing, language, falls, or social interaction [74, 75]. The FBB offers the opportunity to capture features not included in the NPI in a brief fashion that can be used in parallel with the NPI to capture psychotic and mood disturbances not captured by the FBB.

There are several published instruments to examine frontal lobe cognitive function. The Executive Interview-25 (EXIT 25) [17], Frontal Assessment Battery (FAB) [18], and FRONTIER executive screen [19] are examples of neuropsychological screening tools that can provide brief measures of executive function and have been used in studies of AD and FTD [76]. There are fewer instruments designed to specifically look at non-cognitive frontal lobe features. The Frontal Systems Behavior Scale (FrSBe) [20] can be used to quantify behaviors associated with frontal lobe damage. The FrSBe has three subscales to assess apathy, disinhibition, and executive dysfunction [15] and can discriminate cortical dementias such as AD from subcortical dementias such as Huntington’s disease [77] and frontal lobe injury from trauma [20]. The FBI is a 24-item caregiver questionnaire validated in bvFTD and takes 20 minutes to complete [21]. Questions cover two domains: negative behaviors and disinhibition. Negative behavior questions include apathy, aspontaneity, emotional flatness, inattention, personal neglect, loss of insight, logopenia, and several questions regarding language and comprehension. Disinhibition questions include inappropriate behaviors, hyperorality, poor judgment, irritability, incontinence and hypersexuality. The FBI scores were previously reported to be highest in bvFTD than other dementias with scores higher in VCID than PPA and AD [24, 78]. In another study, the FBI was able to discriminate FTD from non-FTD, while the NPI was not [79]. Neither the FBI nor FrSBe have been evaluated in DLB. In our study, the FBB worked well across all causes of dementia detecting a differential expression of symptoms in impaired individuals while few symptoms were endorsed by study partners of cognitively normal controls. We also found that FTD and DLB had higher symptoms reported than AD and VCID. Individuals with MCI had higher scores than healthy controls, but lower scores than all causes of dementia.

A potential advantage the FBB provides in comparison to these other instruments is consideration of frontal lobe functioning associated not just with prefrontal cortex but also with motor, premotor, and supplementary motor cortex, Broca’s area, and frontal-subcortical projections across different neurodegenerative disorders. These features include aphasia [10], dysphagia [80–82], falls [13, 83], abnormalities in movement [12, 14], social conduct [11], and interaction with family and friends [10, 11]. A second advantage is that the FBB was developed in a sample of FTD that included diverse presentations including bvFTD, PPA, FTD-MND, PSP, and CBS and a validation sample that included healthy controls, MCI and various dementia etiologies demonstrating a differential distribution of the 11 constructs across the different disorders.

There are several limitations in this study. As this is a cross-sectional study, the longitudinal properties of the FBB, and response to potential interventions cannot be established. The FBB was tested as a caregiver reported outcome, thus is dependent on an observant informant for completion. Future testing of the FBB could include testing as a patient-reported outcome. Caregiver respondents in the development sample reported their best knowledge of the person living with dementia’s diagnosis and symptoms but in-person evaluations were not conducted. Other features associated with frontal lobe dysfunction described in the literature, such as hyperorality, were not included in the FBB as these features were not regularly endorsed by caregivers or suggested by AFTD advisors during development stage. Features that were already captured as part of standard clinical research measures (e.g., apathy, depression) such as the NPI were also not included in the FBB. Participants and their caregivers for the validation study were seen in the context of an academic memory disorders clinic and research program, where the prevalence of MCI and dementia are high and both patients and caregivers tend to be better educated and predominantly White. Validation of the FBB in other clinical and research settings, other countries, and in individuals from diverse racial, ethnic, and cultural backgrounds is needed. Our research projects and clinic focus on healthy aging, MCI, and early stage ADRD so fewer moderate to severe patients are seen by us. The majority of cases consisted of MCI, AD, and DLB with fewer VCID and FTD cases, and biomarker examination was limited to ApoE genotypes. Analyses with more advanced MRI imaging and specific fluid or imaging biomarkers measuring amyloid-β protein and tau (AD), α-synuclein (DLB and PD), TDP-43 (FTD), NFL (neurodegeneration), and vascular pathology are needed.

Strengths of this study include a two-stage validation process with a large development sample of FTD cases with known frontal lobe dysfunction and an independent well-characterized validation cohort that underwent a comprehensive evaluation with extensive characterization of cognitive, functional, and behavioral constructs using Gold Standard instruments in older adults with and without various forms of cognitive impairment. The diagnostic odds ratio of 13.1 supports the detection of healthy brain aging and a lower risk of ADRD in individuals with an FBB < 2. Similarly, the diagnostic odds ratio of 84.1 supports that FBB scores greater than 2 are likely to have non-cognitive frontal lobe features and are more likely to have DLB or FTD. Another advantage of the FBB is its brevity being completed in 3 minutes and can be done prior to the research evaluation or clinical office visit without the need for clinician or staff time. The FBB could be used as a screening instrument for patients or research participants to be referred for a more extensive evaluation for behavioral symptoms and frontal lobe dysfunction. The FBB would not replace other Gold Standard assessments (e.g., NPI), but rather could be used as a complementary measure capturing non-cognitive frontal lobe signs and symptoms not covered by these other instruments in a standardized fashion.

As a measure of frontal lobe dysfunction, the FBB had good strength of association with global rating scales of cognition, function, and behavior, thus could provide an estimate of clinical and behavioral status prior to the formal assessment—it can be filled out at home or in the waiting room. In clinical practice, this could be helpful as the busy clinician might not have the time or capacity to perform a comprehensive behavioral evaluation on everyone but just those individuals whose caregivers report symptoms. Because of the wide range of distinct signs and symptoms and possible scores, the FBB could help facilitate referrals to behavioral health specialists, guide therapeutic options, or serve as an outcome measure. Similarly, the FBB could provide researchers with a baseline assessment of frontal lobe function and assist in inclusion/exclusion criteria. The FBB performed well in comparison to Gold Standard clinical and research measures, but in a brief fashion that could facilitate its use for detection of frontal lobe dysfunction in clinical care and research.