Psychometric properties of the Neuropsychiatric Inventory for adults with intellectual disability

Revisiting delusion subtypes in schizophrenia based on their underlying structures

A clear understanding of the pathophysiology of schizophrenia and related spectrum disorders has been limited by clinical heterogeneity. We investigated whether relative severity and predominance of one or more delusion subtypes might yield clinically differentiable patient profiles. Patients (N = 286) with schizophrenia spectrum disorders (SSD) completed the 21-item Peters et al. Delusions Inventory (PDI-21). We performed factor analysis followed by k-means clustering to identify delusion factors and patient subtypes. Patients were further assessed via the Brief Psychiatric Rating Scale, Brief Negative Symptom Scale, Digit Symbol and Digit Substitution tasks, use of cannabis and tobacco, and stressful life events. The overall patient sample clustered into subtypes corresponding to Low-Delusion, Grandiose-Predominant, Paranoid-Predominant, and Pan-Delusion patients. Paranoid-Predominant and Pan-Delusion patients showed significantly higher burden of positive symptoms, while Low-Delusion patients showed the highest burden of negative symptoms. The Paranoia delusion factor score showed a positive association with Digit Symbol and Digit Substitution tasks in the overall sample, and the Paranoid-Predominant subtype exhibited the best performance on both tasks. Grandiose-Predominant patients showed significantly higher tobacco smoking severity than other subtypes, while Paranoid-Predominant patients were significantly more likely to have a lifetime diagnosis of Cannabis Use Disorder. We suggest that delusion self-report inventories such as the PDI-21 may be of utility in identifying sub-syndromes in SSD. From the current study, a Paranoid-Predominant form may be most distinctive, with features including less cognitive impairment and a stronger association with cannabis use.

Neuropsychiatric Disorders: Bridging the Gap Between Neurology and Psychiatry

Given the ongoing difficulties faced by clinicians and researchers in dealing with neuropsychiatric illnesses, it is becoming more and more evident that there is a need to go beyond traditional disciplinary boundaries. This research consolidates existing material, examining changes in history, the fundamental neurobiological aspects, and the shared clinical manifestations between neurology and psychiatry. This inquiry examines the historical development of neuropsychiatry, focusing on the relationship between early understandings of mental illness and the later division of neurology and psychiatry. The focus is on recent advancements in comprehending the common neurobiological pathways and genetic factors that highlight the merging of these fields. The research highlights the complexities of clinical presentations in neuropsychiatric illnesses by analyzing the overlapping cognitive, affective, and behavioral symptoms. The text critiques the diagnostic issues in traditional frameworks, emphasizing the limitations in differentiating between neurological and psychiatric origins. This has ramifications for achieving correct diagnosis and arranging appropriate treatment. The paper explores developing multidisciplinary care approaches, highlighting successful collaborations between neurologists and psychiatrists. This study examines the difficulties in carrying out a plan and the process of identifying obstacles to combining different elements. It also highlights the urgent need for improved instruction and learning for smooth cooperation. The paper examines the therapeutic implications by investigating pharmacological therapies focusing on shared pathways. It also discusses the difficulties involved in managing neurological and psychiatric diseases that occur together. The study also explores non-pharmacological therapies, such as psychotherapy and rehabilitation methods, as part of a comprehensive treatment approach. Anticipating the future, the report identifies areas where the study could be improved and forecasts the influence of technological improvements on the subject. Suggestions are put out to encourage additional exploration, cooperation, and originality to narrow the divide between neurology and psychiatry, ultimately augmenting our comprehension and treatment of neuropsychiatric illnesses. This real-time synthesis adds to the ongoing discussion, providing valuable insights that align with the ever-changing field of contemporary neuropsychiatric research and therapy.

Clusterization of Behavioral and Psychological Symptoms of Dementia as Assessed by Neuropsychiatric Inventory: A Case Against the Use of Principal Component Analysis

Background

The term Behavioral and Psychological Symptoms of Dementia (BPSD) covers a group of phenomenologically and medically distinct symptoms that rarely occur in isolation. Their therapy represents a major unmet medical need across dementias of different types, including Alzheimer's disease. Understanding of the symptom occurrence and their clusterization can inform clinical drug development and use of existing and future BPSD treatments.

Objective

The primary aim of the present study was to investigate the ability of a commonly used principal component analysis to identify BPSD patterns as assessed by Neuropsychiatric Inventory (NPI).

Methods

NPI scores from the Aging, Demographics, and Memory Study (ADAMS) were used to characterize reported occurrence of individual symptoms and their combinations. Based on this information, we have designed and conducted a simulation experiment to compare Principal Component analysis (PCA) and zero-inflated PCA (ZI PCA) by their ability to reveal true symptom associations.

Results

Exploratory analysis of the ADAMS database revealed overlapping multivariate distributions of NPI symptom scores. Simulation experiments have indicated that PCA and ZI PCA cannot handle data with multiple overlapping patterns. Although the principal component analysis approach is commonly applied to NPI scores, it is at risk to reveal BPSD clusters that are a statistical phenomenon rather than symptom associations occurring in clinical practice.

Conclusions

We recommend the thorough characterization of multivariate distributions before subjecting any dataset to Principal Component Analysis.

Cardiometabolic Effects of Antipsychotics in Challenging Behavior and Neuropsychiatric Symptoms in Patients With Intellectual Disability

Introduction Despite the well-established association between antipsychotics and metabolic adverse effects in psychiatric disorders, the variable influence of long-term and off-label antipsychotic medication on behavioral disorders has not been investigated in detail. Objective To clarify the impact of antipsychotic use on challenging behavior (CB) and neuropsychiatric symptoms (NPS), we evaluated the clinical findings and cardiometabolic effects in individuals with intellectual disability (ID) hospitalized in our residential facility for profoundly disabled patients. Patients and methods A total of 130 individuals hospitalized in our residential facility were retrospectively investigated and divided into two groups - individuals with and without CB and NPS. Antipsychotics (first- and second-generation antipsychotics) are prescribed to all individuals in the CB and NPS-positive ID group. Conversely, antipsychotics were not prescribed to any individuals in the CB- and NPS-negative ID groups. To investigate the cardiometabolic effects of antipsychotics, the following metabolic parameters were measured: body weight (BW), total calorie intake per day, body mass index (BMI), blood pressure, serum lipid levels (total cholesterol, high-density lipoprotein cholesterol, and triglyceride), and corrected QT interval (QTc) of electrocardiogram (ECG). The etiology of disabilities, level of ID, severity of motor disability, and presence or absence of epilepsy were also examined. Results Two main results were derived: (1) Autism spectrum disorder was the most predominant etiology in individuals with CB and NPS who were prescribed antipsychotics, and (2) the mean values of metabolic parameters were all normal in both medicated and nonmedicated individuals, but the total calorie intake was significantly higher in individuals who were prescribed antipsychotics. Conclusions Our investigation demonstrated that in individuals with an adequate energy intake, most metabolic parameters can be maintained within normal limits. We suggest that body weight control is the primary step in avoiding the cardiometabolic adverse effects of antipsychotics in intellectually disabled individuals with CB and NPS.