The assessment of MBI involves two important issues: 1) to know the underlying structure of the Mild Behavioral Impairment Checklist (MBI-C) a questionnaire designed to evaluates Neuropsychiatric Symptoms (NPS) in pre-dementia states; and 2) to consider self and proxy (i.e., study partner) symptom ratings that may not capture comparable samples. Our objective is to give some answer to these questions: first, to analyze the underlying structure of the MBI-C at baseline and follow-up using Multidimensional Scaling (MDS) and two, to determine how self and proxy ratings and the choice of rating type impact in the results of the MBI-C.

To analyze MBI-C structure, 200 Subjective Cognitive Decline and Mild Cognitive Impairment patients from the CompAS longitudinal study completed baseline and follow-up assessments. Two-step bidimensional weighted dichotomous MDS were performed. All items were included in the first step. Items closely associated with each dimension (1 SD above or below the mean) were selected in a second step to obtain the final models solution.

We will also present a review of the literature on the importance of self and proxy MBI-C ratings. We will also present new empirical evidence based on data from over 10,000 cognitively normal.

Results from baseline and follow-up showed two dimensions: Dimension I (right-left) differentiate high and low emotional activation and Dimension II (top-down) high and low behavioral activation. The combination of both generates 4 quadrants: resistance, restlessness, flattening and desolation. The final models were built considering the most relevant items, with little differences between baseline and follow-up. The good fit of the models, type of two-dimensional solution and group weights were similar in baseline and follow-up.

Regarding our second objective, the results suggest that self and proxy ratings may not capture comparable samples and that the choice of rating type can indeed impact the conclusions drawn from analysis.

The 4 quadrants identified could be the most useful NPS to determine risk factors for predementia patients. Also, the findings suggest that the way of applying the MBI-C has relevant implications.

Mood disorders are characterised by pronounced symptom heterogeneity, which presents a substantial challenge both to clinical practice and research. Identification of subgroups of individuals with homogeneous symptom profiles that cut across current diagnostic categories could provide insights in to the transdiagnostic relevance of individual symptoms, which current categorical diagnostic systems cannot impart.

To identify groups of people with homogeneous clinical characteristics, using symptoms of manic and/or irritable mood, and explore differences between groups in diagnoses, functional outcomes and genetic liability.

We used latent class analysis on eight binary self-reported symptoms of manic and irritable mood in the UK Biobank and PROTECT studies, to investigate how individuals formed latent subgroups. We tested associations between the latent classes and diagnoses of psychiatric disorders, sociodemographic characteristics and polygenic risk scores.

Five latent classes were derived in UK Biobank (N = 42 183) and were replicated in the independent PROTECT cohort (N = 4445), including ‘minimally affected’, ‘inactive restless’, active restless’, ‘focused creative’ and ‘extensively affected’ individuals. These classes differed in disorder risk, polygenic risk score and functional outcomes. One class that experienced disruptive episodes of mostly irritable mood largely comprised cases of depression/anxiety, and a class of individuals with increased confidence/creativity reported comparatively lower disruptiveness and functional impairment.

Findings suggest that data-driven investigations of psychopathological symptoms that include sub-diagnostic threshold conditions can complement research of clinical diagnoses. Improved classification systems of psychopathology could investigate a weighted approach to symptoms, toward a more dimensional classification of mood disorders.

Loneliness and physical activity are important targets for research into the impact of COVID-19 because they have established links with mental health, could be exacerbated by social distancing policies, and are potentially modifiable. In this study, we aimed to identify whether loneliness and physical activity were associated with worse mental health during a period of mandatory social distancing in the UK.

Population-based observational cohort study.

Mental health data collected online during COVID-19 from an existing sample of adults aged 50 and over taking part in a longitudinal study of aging. All had comparable annual data collected between 2015 and 2019.

Three-thousand two-hundred and eighty-one participants aged 50 and over.

Trajectories of depression (measured by PHQ-9) and anxiety (measured by GAD-7) between 2015 and 2020 were analyzed with respect to loneliness, physical activity levels, and a number of socioeconomic and demographic characteristics using zero-inflated negative binomial regression.

In 2020, PHQ-9 score for loneliness, adjusted for covariates, was 3.23 (95% CI: 3.01–3.44), an increase of around 1 point on all previous years in this group and 2 points higher than people not rated lonely, whose score did not change in 2020 (1.22, 95% CI: 1.12–1.32). PHQ-9 was 2.60 (95% CI: 2.43–2.78) in people with decreased physical activity, an increase of .5 on previous years. In contrast, PHQ-9 in 2020 for people whose physical activity had not decreased was 1.66, 95% CI: 1.56−1.75, similar to previous years. A similar relationship was observed for GAD-7 though the absolute burden of symptoms lower.

After accounting for pre-COVID-19 trends, we show that experiencing loneliness and decreased physical activity are risk factors for worsening mental health during the pandemic. Our findings highlight the need to examine policies which target these potentially modifiable risk factors.

The Neuropsychiatric Inventory (NPI) is predicated on the assumption that psychiatric symptoms are manifestations of disease. Biopsychosocial theories suggest behavioural changes viewed as psychiatric may also arise as a result of external behavioural triggers. Knowing the causes of psychiatric symptoms is important since the treatment and management of symptoms relies on this understanding.

This study sought to understand the causes of psychiatric symptoms recorded in care home settings by investigating qualitatively described symptoms in Neuropsychiatric Inventory-Nursing Home (NPI-NH) interviews.

The current study examined the NPI-NH interviews of 725 participants across 50 care homes. The qualitatively described symptoms from each of the 12 subscales of the NPI were extracted: 347 interviews included at least one qualitatively described symptom (n = 651 descriptions). A biopsychosocial algorithm developed following a process of independent researcher coding (n = 3) was applied to the symptom descriptions. This determined whether the description had predominantly psychiatric features, or features that were cognitive or attributable to other causes (i.e. issues with orientation and memory; expressions of need; poor care and communication; or understandable reactions)

Our findings suggest that the majority (over 80%) of descriptions described symptoms with features that could be attributable to cognitive changes and external triggers (such as poor care and communication).

The finding suggest that in its current form the NPI-NH may over attribute the incidence of psychiatric symptoms in care homes by overlooking triggers for behavioural changes. Measures of psychiatric symptoms should determine the causes of behavioural changes in order to guide treatments more effectively.

In this large population study, we set out to examine the profile of mild behavioral impairment (MBI) by using the Mild Behavioral Impairment Checklist (MBI-C) and to explore its factor structure when employed as a self-reported and informant-rated tool.

This was a population-based cohort study.

Participants were recruited from the Platform for Research Online to Investigate Genetics and Cognition in Aging study (https://www.protect-exeter.org.uk).

A total of 5,742 participant-informant dyads participated in the study.

Both participants and informants completed the MBI-C. The factor structure of the MBI-C was evaluated by exploratory factor analysis.

The most common MBI-C items, as rated by self-reported and informants, related to affective dysregulation (mood/anxiety symptoms), being present in 34% and 38% of the sample, respectively. The least common items were those relating to abnormal thoughts and perception (psychotic symptoms) (present in 3% and 6% of the sample, respectively). Only weak correlations were observed between self-reported and informant-reported MBI-C responses. Exploratory factor analysis for both sets of respondent answers indicated that a five-factor solution for the MBI-C was appropriate, reflecting the hypothesized structure of the MBI-C.

This is the largest and most detailed report on the frequency of MBI symptoms in a nondementia sample. The full spectrum of MBI symptoms was present in our sample, whether rated by self-reported or informant report. However, we show that the MBI-C performs differently in self-reported versus informant-reported situations, which may have important implications for the use of the questionnaire in clinic and research.

Behaviours associated with agitation are common in people living with dementia. The Cohen-Mansfield Agitation Inventory (CMAI) is a 29-item scale widely used to assess agitation completed by a proxy (family carer or staff member). However, proxy informants introduce possible reporting bias when blinding to the treatment arm is not possible, and potential accuracy issues due to irregular contact between the proxy and the person with dementia over the reporting period. An observational measure completed by a blinded researcher may address these issues, but no agitation measures with comparable items exist.

Development and validation of an observational version of the CMAI (CMAI-O), to assess its validity as an alternative or complementary measure of agitation.

Fifty care homes in England.

Residents (N = 726) with dementia.

Two observational measures (CMAI-O and PAS) were completed by an independent researcher. Measures of agitation, functional status, and neuropsychiatric symptoms were completed with staff proxies.

The CMAI-O showed adequate internal consistency (α = .61), criterion validity with the PAS (r = .79, p = < .001), incremental validity in predicting quality of life beyond the Functional Assessment Staging of Alzheimer’s disease (β = 1.83, p < .001 at baseline) and discriminant validity from the Neuropsychiatric Inventory Apathy subscale (r = .004, p = .902).

The CMAI-O is a promising research tool for independently measuring agitation in people with dementia in care homes. Its use alongside the CMAI could provide a more robust understanding of agitation amongst residents with dementia.

Behaviours associated with agitation are common in people living with dementia. The Cohen-Mansfield Agitation Inventory (CMAI) is a 29-item scale widely used to assess agitation completed by a proxy (family carer or staff member). However, proxy informants introduce possible reporting bias when blinding to the treatment arm is not possible, and potential accuracy issues due to irregular contact between the proxy and the person with dementia over the reporting period. An observational measure completed by a blinded researcher may address these issues, but no agitation measures with comparable items exist.

Development and validation of an observational version of the CMAI (CMAI-O), to assess its validity as an alternative or complementary measure of agitation.

Fifty care homes in England.

Residents (N = 726) with dementia.

Two observational measures (CMAI-O and PAS) were completed by an independent researcher. Measures of agitation, functional status, and neuropsychiatric symptoms were completed with staff proxies.

The CMAI-O showed adequate internal consistency (α = .61), criterion validity with the PAS (r = .79, p = < .001), incremental validity in predicting quality of life beyond the Functional Assessment Staging of Alzheimer's disease (β = 1.83, p < .001 at baseline) and discriminant validity from the Neuropsychiatric Inventory Apathy subscale (r = .004, p = .902).

The CMAI-O is a promising research tool for independently measuring agitation in people with dementia in care homes. Its use alongside the CMAI could provide a more robust understanding of agitation amongst residents with dementia.