Reliability and Validity of the Chinese Version of Mild Behavioral Impairment Checklist in Mild Cognitive Impairment and Mild Alzheimer's Disease

Validity and Reliability of the Turkish Version of Mild Behavioral Impairment Checklist in Patients With Cognitive Impairment

BACKGROUND AND OBJECTIVE

The Mild Behavioral Impairment-Checklist (MBI-C) was developed to detect and standardize neuropsychiatric symptoms. The objective of this study was to evaluate the Turkish adaptation, validity, and reliability of the MBI-C.

METHODS

The sample of our study consisted of 80 patients with cognitive impairment and a control group with 113 participants whose cognitive impairment was not detected in standard tests. Participants were evaluated with the Standardized Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale-15 (GDS-15), MBI-C and Neuropsychiatric Inventory (NPI).

RESULTS AND CONCLUSION

In the reliability analysis, the Cronbach-alpha value for MBI-C was found to be .810. In the ROC analysis performed with the total MBI-C score, the area under the curve (AUC) was calculated as .821 and the cut-off score was determined as 8.5; sensitivity was calculated as .77 and specificity as .83. A strong positive correlation was found between test-retest MBI-C scores (r = .886, P < .0019). A strong positive correlation was found between MBI-C and NPI scores (r = .964, P < .001). MBI-C scores were significantly negatively correlated with MMSE and MoCA scores and positively correlated with GDS-15 scores. The results of our study showed that the Turkish version of the MBI-C is a valid and reliable measurement.

[Mild behavioral impairment checklist : English-German translation and feasibility study assessing its use in clinical practice]

BACKGROUND

The mild behavioral impairment (MBI) syndrome is defined by the emergence in later life of persistent neuropsychiatric symptoms. The MBI checklist (MBI-C) can be used for systematic detection and documentation of such symptoms.

OBJECTIVE

Development of a German version of the MBI‑C and assessment of its application in a clinical setting.

MATERIAL AND METHODS

The MBI‑C was translated from English into German in collaboration with the main author of the original version, and its practical application was then tested on a study population (n = 21) in a gerontopsychiatric inpatient clinic. Patient compliance, understanding of questions, time effort, evaluation procedure and possible discrepancy between patient and family member evaluations were assessed.

RESULTS

The German translation of the original MBI‑C obtained certification as an official version and can be downloaded at https://mbitest.org . All 34 questions were fully completed by the study population, the level of understanding of questions was good, with the mean time effort being 16 min. In some cases, significant differences between patients' and family members' responses were found.

DISCUSSION

The presence of MBI may indicate the development of an otherwise presymptomatic neurodegenerative dementia syndrome. Hence, the MBI‑C could aid in the early detection of neurodegenerative dementia. By means of the translated version of the MBI‑C presented in this study, this hypothesis can now be tested in German-speaking countries.

Prevalence of mild behavioural impairment and its association with cognitive and functional impairment in normal cognition, mild cognitive impairment, and mild Alzheimer's dementia

BACKGROUND

Mild behavioural impairment (MBI) is an emergent and persistent neuropsychiatric symptom (NPS) in subjects aged 50 and older who are at risk for cognitive decline. We examined the prevalence of MBI across the spectrum from cognitively normal (CN), mild cognitive impairment (MCI), to dementia, and further investigated the association between the MBI domain and cognitive and functional impairment.

METHOD

MBI was assessed in 2337 elderly patients in the Alzheimer's Disease Neuroimaging Initiative database (mean age, 73.04 years; 52.8% male). Among the subjects, 868 (37.1%) had normal cognition, 1066 (45.6%) had MCI, and 403 (17.2%) had mild Alzheimer's dementia (AD). MBI was evaluated in accordance with the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment diagnostic criteria for MBI, utilising the Neuropsychiatric Inventory. We compared the prevalence of the MBI domain with CN using multinominal logistic regression analysis and further quantified the magnitude of the association between MCI/AD and the MBI domains by calculating the population attributable risk (PAR). We assessed the association between the MBI domains and cognitive and functional impairment using simultaneous linear regression analysis.

RESULTS

The most common MBI domains in each diagnostic group were affective dysregulation followed by impulse dyscontrol, decreased motivation, social inappropriateness, and abnormal perception or thought content. The PARs for MBI domains in subjects with MCI or AD were respectively: 16.60% and 24.34% for affective dysregulation; 3.72% and 18.06% for impulse dyscontrol; 4.78% and 14.13% for decreased motivation, 1.91% and 2.29% for social inappropriateness; and 0.68% and 3.85% for abnormal perception or thought content. All MBI domains except for social inappropriateness were significantly associated with a higher 11-item Alzheimer's Disease Assessment Scale-Cognitive Subscale total score. All MBI domains were significantly associated with a higher Functional Activities Questionnaire total score.

CONCLUSION

Our findings show that MBI is highly prevalent across subjects with CN, MCI, and AD and is associated with cognitive and functional decline. MBI could be a crucial clinical phenotype relevant to the risk of cognitive and functional impairment, and provides a useful dimension pertinent to diagnostic approaches.

Mild Behavioral Impairment in Parkinson's Disease: An Updated Review on the Clinical, Genetic, Neuroanatomical, and Pathophysiological Aspects

Neuropsychiatric symptoms (NPS), including depression, anxiety, apathy, visual hallucinations, and impulse control disorders, are very common during the course of Parkinson's disease (PD), occurring even at the prodromal and premotor stages. Mild behavioral impairment (MBI) represents a recently described neurobehavioral syndrome, characterized by the emergence of persistent and impactful NPS in later life, reflecting arisk of dementia. Accumulating evidence suggests that MBI is highly prevalent in non-demented patients with PD, also being associated with an advanced disease stage, more severe motor deficits, as well as global and multiple-domain cognitive impairment. Neuroimaging studies have revealed that MBI in patients with PD may be related todistinct patterns of brain atrophy, altered neuronal connectivity, and distribution of dopamine transporter (DAT) depletion, shedding more light on its pathophysiological background. Genetic studies in PD patients have also shown that specific single-nucleotide polymorphisms (SNPs) may be associated with MBI, paving the way for future research in this field. In this review, we summarize and critically discuss the emerging evidence on the frequency, associated clinical and genetic factors, as well as neuroanatomical and neurophysiological correlates of MBI in PD, aiming to elucidate the underlying pathophysiology and its potential role as an early "marker" of cognitive decline, particularly in this population. In addition, we aim to identify research gaps, and propose novel relative areas of interest that could aid in our better understanding of the relationship of this newly defined diagnostic entity with PD.

Relationship between Loneliness and Mild Behavioral Impairment: Validation of the Japanese Version of the MBI Checklist and a Cross-Sectional Study

Background

Mild behavioral impairment (MBI) and loneliness are associated with cognitive decline and an increased risk of dementia.

Objective

Our aim was to examine the validity of the Japanese version of the MBI checklist (MBI-C) and investigate the relationship between loneliness and MBI.

Methods

The participants in this cross-sectional study included 5 cognitively normal persons and 75 persons with mild cognitive impairment. MBI-C and the revised University of California at Los Angeles loneliness scale (LS) were used to assess MBI and loneliness, respectively. Diagnostic performance of MBI-C was examined using receiver operating characteristic analysis. The relationship between MBI-C and LS was examined using multiple linear regression in 67 subjects who were assessed with both scales, with MBI-C total or domain score as the dependent variable and LS as the independent variable, adjusted for age, gender, living situation, presence of visual and hearing impairment, and Mini-Mental State Examination score.

Results

Per the Youden index, in this mostly MCI sample, the optimal MBI-C cut-off score was 5.5 with sensitivity 0.917 and specificity 0.949. In multiple linear regression analysis, LS score was detected as a significant predictor of MBI-C total scores, and MBI-C decreased motivation, affective dysregulation, and abnormal thought and perception scores.

Conclusions

The caregiver-rated Japanese MBI-C has excellent diagnostic performance. Loneliness is associated with a greater MBI burden, especially in the decreased motivation, affective dysregulation, and abnormal thought and perception domains. Interventions for loneliness in older people may have the potential to improve MBI.

Optimizing detection of Alzheimer's disease in mild cognitive impairment: a 4-year biomarker study of mild behavioral impairment in ADNI and MEMENTO

BACKGROUND

Disease-modifying drug use necessitates better Alzheimer disease (AD) detection. Mild cognitive impairment (MCI) leverages cognitive decline to identify the risk group; similarly, mild behavioral impairment (MBI) leverages behavioral change. Adding MBI to MCI improves dementia prognostication over conventional approaches of incorporating neuropsychiatric symptoms (NPS). Here, to determine if adding MBI would better identify AD, we interrogated associations between MBI in MCI, and cerebrospinal fluid biomarkers [β-amyloid (Aβ), phosphorylated-tau (p-tau), and total-tau (tau)-ATN], cross-sectionally and longitudinally.

METHODS

Data were from two independent referral-based cohorts, ADNI (mean[SD] follow-up 3.14[1.07] years) and MEMENTO (4.25[1.40] years), collected 2003-2021. Exposure was based on three-group stratification: 1) NPS meeting MBI criteria; 2) conventionally measured NPS (NPSnotMBI); and 3) noNPS. Cohorts were analyzed separately for: 1) cross-sectional associations between NPS status and ATN biomarkers (linear regressions); 2) 4-year longitudinal repeated-measures associations of MBI and NPSnotMBI with ATN biomarkers (hierarchical linear mixed-effects models-LMEs); and 3) rates of incident dementia (Cox proportional hazards regressions).

RESULTS

Of 510 MCI participants, 352 were from ADNI (43.5% females; mean [SD] age, 71.68 [7.40] years), and 158 from MEMENTO (46.2% females; 68.98 [8.18] years). In ADNI, MBI was associated with lower Aβ42 (standardized β [95%CI], -5.52% [-10.48-(-0.29)%]; p = 0.039), and Aβ42/40 (p = 0.01); higher p-tau (9.67% [3.96-15.70%]; p = 0.001), t-tau (7.71% [2.70-12.97%]; p = 0.002), p-tau/Aβ42 (p < 0.001), and t-tau/Aβ42 (p = 0.001). NPSnotMBI was associated only with lower Aβ42/40 (p = 0.045). LMEs revealed a similar 4-year AD-specific biomarker profile for MBI, with NPSnotMBI associated only with higher t-tau. MBI had a greater rate of incident dementia (HR [95%CI], 3.50 [1.99-6.17; p < 0.001). NPSnotMBI did not differ from noNPS (HR 0.96 [0.49-1.89]; p = 0.916). In MEMENTO, MBI demonstrated a similar magnitude and direction of effect for all biomarkers, but with a greater reduction in Aβ40. HR for incident dementia was 3.93 (p = 0.004) in MBI, and 1.83 (p = 0.266) in NPSnotMBI. Of MBI progressors to dementia, 81% developed AD dementia.

CONCLUSIONS

These findings support a biological basis for NPS that meet MBI criteria, the continued inclusion of MBI in NIA-AA ATN clinical staging, and the utility of MBI criteria to improve identification of patients for enrollment in disease-modifying drug trials or for clinical care.

Clinical observation and mechanism of acupuncture on amnestic mild cognitive impairment based on the gut-brain axis: study protocol for a randomized controlled trial

Background

Amnestic mild cognitive impairment (aMCI) is a pre-dementia condition associated with declined cognitive function dominated by memory impairment. The occurrence of aMCI is associated with the gut-brain axis. Previous studies have shown cognitive improvements in MCI after acupuncture treatment. This study evaluates whether acupuncture can produce a therapeutic effect in patients with aMCI by modulating the gut-brain axis.

Methods and design

This is a prospective, parallel, multicenter randomized controlled trial. A total of 40 patients with aMCI will be randomly assigned to an acupuncture group (AG) or a waiting-list group (WG), participants in both groups will receive health education on improving cognitive function at each visit, and acupuncture will be conducted twice a week for 12 weeks in the AG. Another 20 matched healthy volunteers will be enrolled as normal control. The primary outcome will be the change in Alzheimer's Disease Assessment Scale-cognitive scale score before and after treatment. Additionally, functional magnetic resonance imaging data, faeces, and blood will be collected from each participant to characterize the brain function, gut microbiota, and inflammatory cytokines, respectively. The differences between patients with aMCI and healthy participants, and the changes in the AG and WG groups before and after treatment will be observed. Ultimately, the correlation among brain function, gut microbiota, inflammatory cytokines, and clinical efficacy evaluation in patients with aMCI will be analyzed.

Discussion

This study will identify the efficacy and provide preliminary data on the possible mechanism of acupuncture in treating aMCI. Furthermore, it will also identify biomarkers of the gut microbiota, inflammatory cytokines, and brain function correlated with therapeutic effects. The results of this study will be published in peer-reviewed journals.

Clinical trial registration

http://www.chictr.org.cn, identifier ChiCTR2200062084.

A review of current evidence for mild behavioral impairment as an early potential novel marker of Alzheimer's disease

Mild behavioral impairment (MBI) is a neurobehavioral syndrome that occurs in the absence of cognitive impairment later in life (≥50 years of age). MBI is widespread in the pre-dementia stage and is closely associated with the progression of cognitive impairment, reflecting the neurobehavioral axis of pre-dementia risk states and complementing the traditional neurocognitive axis. Despite being the most common type of dementia, Alzheimer's disease (AD) does not yet have an effective treatment; therefore, early recognition and intervention are crucial. The Mild Behavioral Impairment Checklist is an effective tool for identifying MBI cases and helps identify people at risk of developing dementia. However, because the concept of MBI is still quite new, the overall understanding of it is relatively insufficient, especially in AD. Therefore, this review examines the current evidence from cognitive function, neuroimaging, and neuropathology that suggests the potential use of MBI as a risk indicator in preclinical AD.

Validating the Mild Behavioral Impairment Checklist in a Cognitive Clinic: Comparisons With the Neuropsychiatric Inventory Questionnaire

OBJECTIVE

To compare the utility of the Mild Behavioral Impairment-Checklist (MBI-C) and Neuropsychiatric Inventory Questionnaire (NPI-Q) to capture NPS in subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia.

METHODS

In this cross-sectional memory clinic study, linear regression models compared MBI-C (n = 474) and NPI-Q (n = 1040) scores in relation to Montreal Cognitive Assessment (MoCA) score.

RESULTS

MBI prevalence was 37% in subjective cognitive decline, 54% in mild cognitive impairment, and 62% in dementia. Worse diagnostic status was associated with higher MBI-C and NPI-Q score (P < .001), lower MoCA (P < .001), and greater age (P < .001). Higher MBI-C (β -.09; 95% CI -.13, -.05) and NPI-Q (β -.17; 95% CI -.23, -.10) scores were associated with lower MoCA scores, with psychosis most strongly associated (β -1.11; 95% CI -1.56, -.65 vs β -1.14; 95% CI -1.55, -.73).

CONCLUSIONS

The MBI-C captures global and domain-specific NPS across cognitive stages. Both the MBI-C and NPI-Q have utility in characterizing NPS.

Preliminary Validation Study of the French-Quebec Version of the Mild Behavioral Impairment Checklist

BACKGROUND

Alzheimer disease dementia may be preceded by cognitive stages during which behavioral and psychological changes can occur. More precisely, behavioral symptoms may be observed during the subjective cognitive decline (SCD) or the mild cognitive impairment (MCI) stages; these symptoms can be measured using the Mild Behavioral Impairment Checklist (MBI-C).

OBJECTIVE

To validate the French-Quebec version of the MBI-C in individuals ages 60-85 years.

METHOD

The sample included 60 participants (20 MCI, 20 SCD, 20 cognitively healthy) and their informants. To assess the discriminant validity of the MBI-C, a Kruskal-Wallis analysis with a multiple comparisons test was performed on the MBI-C Total score. To determine convergent validity, Spearman correlations were calculated between the MBI-C subscales and a set of validation tools. Finally, test-retest reliability was assessed with Spearman correlations of MBI-C scores between two test sessions.

RESULTS

All of the analyses indicated satisfactory psychometric properties for the French-Quebec version of the MBI-C.

CONCLUSION

This validation study reveals that the MBI-C can be used successfully in dementia risk assessments. From now on, the use of a validated MBI-C will be possible in the French-Quebec population.

Validation and Comparison of the Informant-Rated and Self-Rated Versions of the Mild Behavioral Impairment Checklist

Background: The Mild Behavioral Impairment Checklist (MBI-C) has been developed to assess mild behavioral impairment (MBI). However, no study has validated the use of MBI-C using a promising translation method in Taiwan. Thus, consistency and discrepancy between informant-rated and self-rated scores have not been extensively researched. Objective: This study validated and compared the informant- and self-rated versions of the MBI-C among community-dwelling people in Taiwan. Method: We recruited 202 pairs of individuals without dementia aged ≥50 years and their cohabitating informants. The participants completed the MBI-C (MBI-C-self), and the informants completed the MBI-C (MBI-C-informant) and the Neuropsychiatric Inventory Questionnaire (NPI-Q) independently. Internal consistency, inter-rater reliability, and convergent validity were examined. Results: Both MBI-C-self and MBI-C-informant exhibited satisfactory Cronbach’s α values (0.92 and 0.88, respectively). The MBI-C-informant total scorewas correlated with the NPI-Q total score (r = 0.83, p < 0.001). Inter-rater reliability between the two versions, as represented by the inter-rater correlation coefficient, was 0.57 (p < 0.001). The prevalence of MBI based on the MBI-C-informant scores was 1.5% higher than that based on the MBI-C-self scores according to the suggested cut-off score of 8.5. The affective dysregulation domain score of MBI-C-informant was significantly lower than that of MBI-C-self. Conclusion: MBI-C-informant exhibited both high reliability and validity. Discrepancies between MBI-C-informant and MBI-C-self related to the detection rates and affective dysregulation domain scores were noted. The level of consistency and discrepancy between these two versions provide implications for the use of MBI-C in clinical practice and future research.

Psychosis as a Treatment Target in Dementia: A Roadmap for Designing Interventions

Psychotic phenomena are among the most severe and disruptive symptoms of dementias and appear in 30% to 50% of patients. They are associated with a worse evolution and great suffering to patients and caregivers. Their current treatments obtain limited results and are not free of adverse effects, which are sometimes serious. It is therefore crucial to develop new treatments that can improve this situation. We review available data that could enlighten the future design of clinical trials with psychosis in dementia as main target. Along with an explanation of its prevalence in the common diseases that cause dementia, we present proposals aimed at improving the definition of symptoms and what should be included and excluded in clinical trials. A review of the available information regarding the neurobiological basis of symptoms, in terms of pathology, neuroimaging, and genomics, is provided as a guide towards new therapeutic targets. The correct evaluation of symptoms is transcendental in any therapeutic trial and these aspects are extensively addressed. Finally, a critical overview of existing pharmacological and non-pharmacological treatments is made, revealing the unmet needs, in terms of efficacy and safety. Our work emphasizes the need for better definition and measurement of psychotic symptoms in dementias in order to highlight their differences with symptoms that appear in non-dementing diseases such as schizophrenia. Advances in neurobiology should illuminate the development of new, more effective and safer molecules for which this review can serve as a roadmap in the design of future clinical trials.

Risk Management of Island Petrochemical Park: Accident Early Warning Model Based on Artificial Neural Network

Island-type petrochemical parks have gradually become the ‘trend’ in establishing new parks because of the security advantages brought by their unique geographical locations. However, due to the frequent occurrence of natural disasters and difficulties in rescue in island-type parks, an early warning model is urgently needed to provide a basis for risk management. Previous research on early warning models of island-type parks seldom considered the particularity. In this study, the early warning indicator system is used as the input parameter to construct the early warning model of an island-type petrochemical park based on the back propagation (BP) neural network, and an actual island-type petrochemical park was used as a case to illustrate the model. Firstly, the safety influencing factors were screened by designing questionnaires and then an early warning indicator system was established. Secondly, particle swarm optimization (PSO) was introduced into the improved BP neural network to optimize the initial weights and thresholds of the neural network. A total of 30 groups of petrochemical park data were taken as samples—26 groups as training samples and 4 groups as test samples. Moreover, the safety status of the petrochemical park was set as the output parameter of the neural network. The comparative analysis shows that the optimized neural network is far superior to the unoptimized neural network in evaluation indicators. Finally, the Zhejiang Petrochemical Co., Ltd., park was used as a case to verify the accuracy of the proposed early warning model. Ultimately, the final output result was 0.8324, which indicates that the safety status of the case park was “safer”. The results show that the BP neural network introduced with PSO can effectively realize early warning, which is an effective model to realize the safety early warning of island-type petrochemical parks.