Emerging evidence suggests a potential association between “leaky gut syndrome” and low-grade systemic inflammation in individuals with psychiatric disorders, such as schizophrenia. Gut dysbiosis could increase intestinal permeability, allowing the passage of toxins and bacteria into the systemic circulation, subsequently triggering immune-reactive responses. This study delves into understanding the relationship between plasma markers of intestinal permeability and symptom severity in schizophrenia. Furthermore, the influence of lifestyle habits on these intestinal permeability markers was determined.

Biomarkers of intestinal permeability, namely lipopolysaccharide-binding protein (LBP), lipopolysaccharides (LPS), and intestinal fatty acid binding protein (I-FABP), were analyzed in 242 adult schizophrenia patients enrolled in an observational, cross-sectional, multicenter study from four centers in Spain (PI17/00246). Sociodemographic and clinical data were collected, including psychoactive drug use, lifestyle habits, the Positive and Negative Syndrome Scale to evaluate schizophrenia symptom severity, and the Screen for Cognitive Impairment in Psychiatry to assess cognitive performance.

Results revealed elevated levels of LBP and LPS in a significant proportion of patients with schizophrenia (62% and 25.6%, respectively). However, no statistically significant correlation was observed between these biomarkers and the overall clinical severity of psychotic symptoms or cognitive performance, once confounding variables were controlled for. Interestingly, adherence to a Mediterranean diet was negatively correlated with I-FABP levels (beta = −0.186, t = −2.325, p = 0.021), suggesting a potential positive influence on intestinal barrier function.

These findings underscore the importance of addressing dietary habits and promoting a healthy lifestyle in individuals with schizophrenia, with potential implications for both physical and psychopathological aspects of the disorder.

This article examines the challenges and opportunities to integrate diverse sources of evidence in assessments produced by international platforms working at the science–policy interface. Diversity (or pluralism) of sources of literature, both in terms of their geographic origin and disciplinary focus, is essential for assessments to inform decision-making across social–ecological contexts. Using the recently completed ‘Methodological Assessment of the Diverse Values and Valuation of Nature’ of the Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services as a case, we find that significant effort has been dedicated to reviewing diverse literature. We discuss three strategies to expand pluralism in future assessments.

Representing plural views in science–policy platforms is essential to avoid reproducing geographic and epistemic biases that permeate contemporary scientific knowledge production and synthesis. The Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services (IPBES) has strived to produce assessments that incorporate information from diverse regions and knowledge systems. We explore the geographic and epistemic pluralism of the literature included in the ‘Methodological Assessment of the Diverse Values and Valuation of Nature’ (VA), and the challenges and opportunities to achieve such knowledge pluralism. We applied a bibliometric analysis to the sources of evidence cited in the VA, and reflected on the assessment development process, in which we were directly involved. Our results highlight the success of different strategies developed by VA experts to engage with diverse sources of literature. Still, most evidence was English-language academic literature produced in Western Europe, Canada, and the United States, echoing the prominence of this literature in scientific publication in environmental disciplines. Reflecting on our experiences, we discuss strategies that could further enhance the geographic and epistemic pluralism in the information reviewed for future environmental assessments produced by IPBES and other international science–policy platforms.

Epistemic and geographic pluralism was partially achieved in IPBES Values Assessment, and can be further enhanced in future assessments.

Delirium is an acute and fluctuating disorder characterized by a disturbance in attention and cognition that is commonly observed in hospitalized older adults; being present in up to 23% of patients admitted to a general medical service and as many as 85% of patients in the intensive care unit. Delirium causes complications such as increased morbidity, persistent functional decline, mortality, increased frailty and increased length of hospital stay. Nonetheless, it is often underdiagnosed, especially when it occurs in its hypoactive form. The objective of this study is to describe characteristics and factors associated with the presence of delirium in patients ≥65 years treated by the liaison psychiatric units in seven general hospitals.

This is an observational, cross-sectional, multicentre study. We obtained data from a sample of 165 patients (≥65 years) admitted to seven general hospitals in Spain referred from different departments to each liaison psychiatry unit. Data was collected for a month and a half period. Psychiatric evaluations were performed while the patients were on wards.

We obtained a sample of 165 patients (78 women, 88 men) with a mean age of 76,03 years old (42.10% <75 years, 57,83% ≥ 75 years). Most of them were married and they lived accompanied (67,27%). Delirium was diagnosed in 20% of the consultations. A multivariate analysis was developed with the presence of delirium as the independent variable. The nature of the underlying pathology, the presence of a previous mental disorder, functionality using the Barthel and Lawton Brody Indexes and the prescribed pharmacological treatments were used as dependent variables. Cohen’s kappa statistics were used to estimate the agreement between delirium diagnose made by psychiatrists and the diagnoses considered by the referring doctors. Low agreement was found for the presence of delirium (Kappa= 0,2341). We also explored the relationship between the presence of delirium and the mean length of stay, as well as the discharge destination of these patients.

There are still many difficulties in the diagnosis and treatment of patients with delirium. Better knowledge of the factors associated with its appearance would improve the management of these patients.

The prevalence of medical illnesses is high among patients with psychiatric disorders. The current study aimed to investigate multi-comorbidity in patients with psychiatric disorders in comparison to the general population. Secondary aims were to investigate factors associated with metabolic syndrome and treatment appropriateness of mental disorders.

The sample included 54,826 subjects (64.73% females; 34.15% males; 1.11% nonbinary gender) from 40 countries (COMET-G study). The analysis was based on the registration of previous history that could serve as a fair approximation for the lifetime prevalence of various medical conditions.

About 24.5% reported a history of somatic and 26.14% of mental disorders. Mental disorders were by far the most prevalent group of medical conditions. Comorbidity of any somatic with any mental disorder was reported by 8.21%. One-third to almost two-thirds of somatic patients were also suffering from a mental disorder depending on the severity and multicomorbidity. Bipolar and psychotic patients and to a lesser extent depressives, manifested an earlier (15–20 years) manifestation of somatic multicomorbidity, severe disability, and probably earlier death. The overwhelming majority of patients with mental disorders were not receiving treatment or were being treated in a way that was not recommended. Antipsychotics and antidepressants were not related to the development of metabolic syndrome.

The finding that one-third to almost two-thirds of somatic patients also suffered from a mental disorder strongly suggests that psychiatry is the field with the most trans-specialty and interdisciplinary value and application points to the importance of teaching psychiatry and mental health in medical schools and also to the need for more technocratically oriented training of psychiatric residents.

Existing research has demonstrated that neuropsychiatric/behavioral-psychological symptoms of dementia (BPSD) frequently contribute to worse prognosis in patients with neurodegenerative conditions (e.g., increased functional dependence, worse quality of life, greater caregiver burden, faster disease progression). BPSD are most commonly measured via the Neuropsychiatric Inventory (NPI), or its briefer, informant-rated questionnaire (NPI-Q). Despite the NPI-Q’s common use in research and practice, there is disarray in the literature concerning the NPI-Q’s latent structure and reliability, possibly related to differences in methods between studies. Also, hierarchical factor models have not been considered, even though such models are gaining favor in the psychopathology literature. Therefore, we aimed to compare different factor structures from the current literature using confirmatory factor analyses (CFAs) to help determine the best latent model of the NPI-Q.

This sample included 20,500 individuals (57% female; 80% White, 12% Black, 8% Hispanic), with a mean age of 71 (SD = 10.41) and 15 average years of education (SD = 3.43). Individuals were included if they had completed an NPI-Q during their first visit at one of 33 Alzheimer Disease Research Centers reporting to the National Alzheimer Coordinating Center (NACC). All CFA and reliability analyses were performed with lavaan and semTools R packages, using a diagonally weighted least squares (DWLS) estimator. Eight single-level models using full or modified versions of the NPI-Q were compared, and the top three were later tested in bifactor form.

CFAs revealed all factor models of the full NPI-Q demonstrated goodness of fit across multiple indices (SRMR = 0.039-0.052, RMSEA = 0.025-0.029, CFI = 0.973-0.983, TLI = 0.9670.977). Modified forms of the NPI-Q also demonstrated goodness of fit across multiple indices (SRMR = 0.025-0.052, RMSEA = 0.0180.031, CFI = 0.976-0.993, TLI = 0.968-0.989). Top factor models later tested in bifactor form all demonstrated consistently stronger goodness of fit regardless of whether they were a full form (SRMR = 0.023-0.035, RMSEA = 0.015-0.02, CFI = 0.992-0.995, TLI = 0.985-0.991) or a modified form (SRMR = 0.023-0.042, RMSEA = 0.015-0.024, CFI = 0.985-0.995, TLI = 0.9770.992). Siafarikas and colleagues’ (2018) 3-factor model demonstrated the best fit among the full-form models, whereas Sayegh and Knight’s (2014) 4-factor model had the best fit among all single-level models, as well as among the bifactor models.

Although all factor models had adequate goodness of fit, the Sayegh & Knight 4-factor model had the strongest fit among both single-level and bifactor models. Furthermore, all bifactor models had consistently stronger fit than single-level models, suggesting that BPSD are best theoretically explained by a hierarchical, non-nested framework of general and specific contributors to symptoms. These findings also inform consistent use of NPI-Q subscales.

The accurate assessment of instrumental activities of daily living (iADL) is essential for those with known or suspected Alzheimer's disease or related disorders (ADRD). This information guides diagnosis, staging, and treatment planning, and serves as a critical patient-centered outcome. Despite its importance, many iADL measures used in ADRD research and practice have not been sufficiently updated in the last 40-50 years to reflect how technology has changed daily life. For example, digital technologies are routinely used by many older adults and those with ADRD to perform iADLs (e.g., online financial management, using smartphone reminders for medications.) The purpose of the current study was to a) asses the applicability of technology-related iADL items in a clinical sample; b) evaluate whether technology-based iADLs are more difficult for those living with ADRD than their traditional counterparts; and c) test if adding technology-based iADL items changes the sensitivity and specificity of iADL measures to ADRD.

135 clinically referred older adults (mean age 75.5 years) undergoing neuropsychological evaluation at a comprehensive multidisciplinary memory clinic were included in this study [37% with mild cognitive impairment (MCI) and 51.5% with dementia]. Collateral informants completed the Functional Activities Questionnaire (FAQ; Pfeffer, 1982) as well as 11 items created to parallel the FAQ wording that assessed technology-related iADLs such as digital financial management (i.e. online bill pay), everyday technology skills (i.e. using a smartphone; remembering a password), and other technology mediated activities (i.e. visiting internet sites; online shopping).

Care partners rated tech iADLs items as applicable for the majority of items. For example, technology skill items were applicable to 90.4% of the sample and online financial management questions were applicable for 76.4% of participants. Applicability ratings were similar across patients in their 60's and 70's, and lower in those over age 80. Care partners indicated less overall impairment on technology-related iADLs (M =1.22, SD =.88) than traditional FAQ iADLs (M =1.36, SD = .86), t(129) = 3.529, p =.001). A composite of original FAQ paperwork and bill pay items (M = 1.62, SD = 1.1) was rated as more impaired than digital financial management tasks (M = 1.30, SD = 1.09), t(122) = 4.77, p <.001). In terms of diagnostic accuracy, tech iADL items (AUC= .815, 95% CI [.731, -.890]) appeared to perform comparably to slightly better than the traditional FAQ (AUC =.788, 95% CI [.705, .874]) at separating MCI and dementia, though the difference between the two was not statistically significant in this small pilot sample.

Technology is rapidly changing how older adults and those with ADRD perform a host of iADLs. This pilot study suggests broad applicability of tech iADL to the lives of those with ADRD and highlights how measurement of these skills may help identify trends in iADL habits that may help to mitigate the impact of ADRD on daily functions. Further, this data suggests the need to refine and improve upon existing iADL measures to validly capture the evolving technological landscape of those living with ADRD.

Neuropsychiatric/behavioral-psychological symptoms of dementia (BPSD) frequently contribute to worse prognosis of patients with neurodegenerative conditions. BPSD are commonly measured via a brief, informant-rated version of the Neuropsychiatric Inventory (NPI), the NPI-Q. Previously (see our other submission to this conference), we established optimal latent structures by comparing different factor models in the literature using confirmatory factor analyses (CFAs). However, questions remain as to why so many different models were found in the literature. One possibility is sampling differences, including different proportions of individuals across cognitive stages (e.g., mild cognitive impairment, moderate dementia) or syndromes (e.g., Alzheimer’s amnestic syndrome, Dementia with Lewy Bodies). We tested this hypothesis by subjecting candidate models to measurement invariance (MI) analyses stratified by cognitive stage and syndrome.

Individuals were included if they had completed an NPI-Q during their first visit at an Alzheimer Disease Research Center reporting to the National Alzheimer Coordinating Center (NACC). This resulted in 20,500 individuals (57% female; 80% White, 13% Black, 8% Hispanic), with a mean age of 71 (SD = 10.41) and 15 average years of education (SD = 3.43). Regarding staging, 75.9% of individuals did not meet criteria for all-cause dementia, whereas 24.1% individuals had all-cause dementia. Regarding syndromes, 35.6% had an Alzheimer’s presentation (“AD-type”) and 5.6% had either a behavioral variant frontotemporal dementia or Lewy-Body dementia presentation (“behavioral-type”). A 3-factor and 4-factor model were subject to MI across these groupings. We conducted MI analyses for equal forms, equal loadings, and equal intercepts using the lavaan R package with a diagonally weighted least squares (DWLS) estimator.

The 3-factor model demonstrated good fit among individuals experiencing (CFI = 0.965, TLI = 0.955) and not experiencing (CFI = 0.984, TLI = 0.979) dementia, as well as among AD-type (CFI = 0.983, TLI = 0.978) presentations, but had borderline poor fit for behavioral-type (CFI = 0.932, TLI = 0.912) presentations. The 4-factor model had better fit among those experiencing (CFI = 0.985, TLI = 0.977) and not experiencing (CFI = 0.995, TLI = 0.992) dementia. Additionally, the 4-factor model demonstrated good of fit for AD-type (CFI = 0.993, TLI = 0.989) and poorer fit for behavioral-type (CFI = 0.949, TLI = 0.922) syndromes. Chi-square differences suggested that equal loading and equal intercept hypotheses should be rejected for both 3- and 4-factor models, for both staging and syndromal groupings. However, relative fit indices suggested that the equal form, equal loading, and equal intercept hypotheses could be adequate for only the 4-factor model.

The variability of factor structures in the BPSD literature appears, at least partially, explained by sampling variability among cognitive stages and dementia syndromes. The best models in the literature appear to have good fit in non-demented individuals and, among those who have dementia, in those with an AD syndrome. Only Sayegh & Knight’s 4-factor model had adequate (albeit, not optimal) fit among those with all-cause dementia and, more specifically, among those with a behavioral-type dementia syndrome. These findings inform BPSD theory and practical implementation of NPI-Q subscales.

Cross-national neuropsychological research is needed to understand the social, economic, and cultural factors associated with cognitive risk and resilience across global aging populations. Memory and language have been shown to be sensitive to age-related cognitive decline and pathological cognitive aging processes and may be more sensitive to subtle cognitive decline than measures of global cognitive function. Thus, we aimed to derive and validate harmonized cognitive domain scores for memory and language across population-based studies in the US and Mexico.

Data came from the Health and Retirement Study (HRS) Harmonized Cognitive Assessment Protocol (HCAP) and the Mexican Health and Aging Study (MHAS) Ancillary Study on Cognitive Aging (Mex-Cog). We used confirmatory factor analysis methodology to create statistically co-calibrated cognitive domains of memory and language. We performed differential item functioning (DIF) analysis to evaluate measurement differences across studies, using a cultural neuropsychological approach to identify comparable items across studies (i.e., cross-study anchors). We evaluated harmonized scores by examining their relationship to age and education in each study.

We included 3347 participants from the HRS-HCAP study [Mage=76.6(7.5), 60% female] and 2042 participants from the Mex-Cog study [Mage=68.1(9.0), 59% female]. Education was classified according to the International Standard Classification of Education in the following categories (HRS-HCAP and Mex-Cog, respectively): none or early childhood education: (0.7%; 50.5%), primary education (4.1%; 22.3%), lower secondary education (7.1%; 15.7%), upper secondary education (41.1%; 3.0%), and any college (47.1%; 8.5%). DIF analyses revealed that 5 out of the 7 memory items and 1 out of the 12 language items demonstrated statistical evidence of measurement differences across studies, meaning that these items measured each underlying cognitive construct differently across studies. After adjusting for DIF by not allowing the items with DIF to be cross-study anchors, harmonized memory and language scores showed generally the expected associations with age and education in each study. Increasing age was associated with lower memory (r=-0.40 in HRS-HCAP; r=-0.44 in Mex-Cog) and language (r=-0.31 in HRS-HCAP and r=-0.67 in Mex-Cog) scores. Increasing years of education was associated with better memory and language scores, with mean scores ranging from z=-0.86 and z=-0.29 among those with a primary education or lower to z=0.33 and z=0.90 among those with any college, for HRS-HCAP and Mex-Cog, respectively.

A cultural neuropsychology approach to statistical harmonization facilitates the generation of harmonized measures of cognitive functioning in cross-national studies. Future work can utilize these harmonized cognitive scores to investigate determinants of late-life cognitive decline and dementia in the US and Mexico.