Single Latent Trait Research Articles

A Note on the Asymptotic Posterior Normality of Multivariate Latent Traits in an IRT Model for Polytomous Items of Mixed Format

The asymptotic posterior normality (APN) of the latent vector in an item response theory model is an important argument in modeling and inference. For a single latent trait, Chang and Stout proved its APN for binary items under general conditions, which generalized Chang for polytomous data and Kornely and Kateri for multivariate latent traits (MLT) and binary items. As MLT and polytomous items are nowadays common in psychometry, an APN-theory covering both simultaneously remains an open and ongoing problem. We generalize the APN-theory accordingly, providing thus a broader foundation for developments relying on APN. We also prove consistency of common estimators for the MLT, extending the according results of Chang and Kornely and Kateri.

Item Response Theory Validation of the Forgotten Joint Score for Persons Undergoing Total Knee Replacement.

The Forgotten Joint Score (FJS), a commonly used patient-reported outcome measure, was developed without fully confirming assumptions such as unidimensionality (all items reflect 1 underlying factor), appropriate weighting of each item in scoring, absence of differential item functioning (in which different groups, e.g., men and women, respond differently), local dependence (pairs of items are measuring only 1 underlying factor), and monotonicity (persons with higher function have a higher score). We applied item response theory (IRT) to perform validation of the FJS according to contemporary standards, and thus support its ongoing use. We aimed to confirm that the FJS reflects a single latent trait. In addition, we aimed to determine whether an IRT model could be fitted to the FJS. Participants undergoing primary total knee replacement provided responses to the FJS items preoperatively and at 6 and 12 months postoperatively. An exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and Mokken analysis were conducted. A graded response model (GRM) was fitted to the data. A total of 1,774 patient responses were analyzed. EFA indicated a 1-factor model (all 12 items reflecting 1 underlying trait). CFA demonstrated an excellent model fit. Items did not have equal weighting. The FJS demonstrated good monotonicity and no differential item functioning by sex, age, or body mass index. GRM parameters are reported in this paper. The FJS meets key validity assumptions, supporting its use in clinical practice and research. The IRT-adapted FJS has potential advantages over the traditional FJS: it provides continuous measurements with finer granularity between health states, includes individual measurement error, and can compute scores despite more missing data (with only 1 response required to estimate a score). It can be applied retrospectively to existing data sets or used to deliver individualized computerized adaptive tests. Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.

Estimation of a Simple Structure in a Multidimensional IRT Model Using Structure Regularization.

We develop a method for estimating a simple matrix for a multidimensional item response theory model. Our proposed method allows each test item to correspond to a single latent trait, making the results easier to interpret. It also enables clustering of test items based on their corresponding latent traits. The basic idea of our approach is to use the prenet (product-based elastic net) penalty, as proposed in factor analysis. For optimization, we show that combining stochastic EM algorithms, proximal gradient methods, and coordinate descent methods efficiently yields solutions. Furthermore, our numerical experiments demonstrate its effectiveness, especially in cases where the number of test subjects is small, compared to methods using the existing L1 penalty.

Positive Mental Health Scale (PMHS) in Parents of Children with Cancer: A Psychometric Evaluation Using Item Response Theory.

Mental health is currently a public health issue worldwide. However, evidence is lacking regarding the validity of the instruments used to measure and assess positive mental health in specific populations. The objective of this study was to evaluate the psychometric properties of the PMHS using IRT. A cross-sectional retrospective study with non-probabilistic convenience sampling was conducted with 623 parents of children undergoing cancer treatment at the National Institute of Health in Mexico City. The participants responded to a battery of tests, including a sociodemographic questionnaire, the PMHS, Measurement Scale of Resilience, Beck Depression Inventory, Inventory of Quality of Life, Beck Anxiety Inventory, an interview regarding caregiver burden, and the World Health Organization Well-Being Index. PMHS responses were analyzed using Samejima's graded response model. The PMHS findings indicated that the IRT-based graded response model validated the single latent trait model. The scale scores were independent of depression, anxiety, well-being, caregiver burden, quality of life, and resilience. The PMHS scores were associated with low subjective well-being. The PMHS findings reveal that from an IRT-based perspective, this scale is unidimensional and is a valid, reliable, and culturally relevant instrument for assessing positive mental health in parents of children with chronic diseases.

In Schizophrenia, the Effects of the IL-6/IL-23/Th17 Axis on Health-Related Quality of Life and Disabilities Are Partly Mediated by Generalized Cognitive Decline and the Symptomatome.

Schizophrenia patients show increased disabilities and lower quality of life (DisQoL). Nevertheless, there are no data on whether the activation of the interleukin (IL)-6, IL-23, T helper (Th)-17 axis, and lower magnesium and calcium levels impact DisQoL scores. This study recruited 90 patients with schizophrenia (including 40 with deficit schizophrenia) and 40 healthy controls and assessed the World Health Association QoL instrument-Abbreviated version and Sheehan Disability scale, Brief Assessment of Cognition in Schizophrenia (BACS), IL-6, IL-23, IL-17, IL-21, IL-22, tumor necrosis factor (TNF)-α, magnesium and calcium. Regression analyses showed that a large part of the first factor extracted from the physical, psychological, social and environmental HR-QoL and interference with school/work, social life, and home responsibilities was predicted by a generalized cognitive deterioration (G-CoDe) index (a latent vector extracted from BACs scores), and the first vector extracted from various symptom domains ("symptomatome"), whereas the biomarkers had no effects. Partial Least Squares analysis showed that the IL6IL23Th17 axis and magnesium/calcium had highly significant total (indirect + direct) effects on HR-QoL/disabilities, which were mediated by G-CoDe and the symptomatome (a first factor extracted from negative and positive symptoms). The IL6IL23Th17 axis explained 63.1% of the variance in the behavioral-cognitive-psycho-social (BCPS) worsening index a single latent trait extracted from G-CoDe, symptomatome, HR-QoL and disability data. In summary, the BCPS worsening index is partly caused by the neuroimmunotoxic effects of the IL6IL23Th17 axis in subjects with lowered antioxidant defenses (magnesium and calcium), thereby probably damaging the neuronal circuits that may underpin deficit schizophrenia.

Major neurocognitive psychosis: a novel schizophrenia endophenotype class that is based on machine learning and resembles Kraepelin's and Bleuler's conceptions.

The purpose of this study is to describe how to use the precision nomothetic psychiatry approach to (a) delineate the associations between schizophrenia symptom domains, including negative symptoms, psychosis, hostility, excitation, mannerism, formal thought disorders, psychomotor retardation (PHEMFP), and cognitive dysfunctions and neuroimmunotoxic and neuro-oxidative pathways and (b) create a new endophenotype class based on these features. We show that all symptom domains (negative and PHEMFP) may be used to derive a single latent trait called overall severity of schizophrenia (OSOS). In addition, neurocognitive test results may be used to extract a general cognitive decline (G-CoDe) index, based on executive function, attention, semantic and episodic memory, and delayed recall scores. According to partial least squares analysis, the impacts of adverse outcome pathways (AOPs) on OSOS are partially mediated by increasing G-CoDe severity. The AOPs include neurotoxic cytokines and chemokines, oxidative damage to proteins and lipids, IgA responses to neurotoxic tryptophan catabolites, breakdown of the vascular and paracellular pathways with translocation of Gram-negative bacteria, and insufficient protection through lowered antioxidant levels and impairments in the innate immune system. Unsupervised machine learning identified a new schizophrenia endophenotype class, named major neurocognitive psychosis (MNP), which is characterised by increased negative symptoms and PHEMFP, G-CoDe and the above-mentioned AOPs. Based on these pathways and phenome features, MNP is a distinct endophenotype class which is qualitatively different from simple psychosis (SP). It is impossible to draw any valid conclusions from research on schizophrenia that ignores the MNP and SP distinctions.

Psychometric Assessment of Pilot Language and Communication Items on the 2018 and 2019 National Survey of Children's Health.

Until recently, normative data on language and communication development among children in the United States have not been available to inform critical efforts to promote language development and prevent impairments. This study represents the first psychometric assessment of nationally representative data derived from a National Survey of Children's Health (NSCH) pilot measure of language and communication development among children ages 1 to 5 years. We analyzed 14,573 parent responses to language and communication items on the 2018 and 2019 NSCH to evaluate whether the newly added 11 items represent a single latent trait for language and communication development and to determine normative age of success on each item. We applied weighted, one-parameter Item Response Theory to rate and cluster items by difficulty relative to developmental language ability. We examined differential item functioning (DIF) using weighted logistic regression by demographic factors. Together, exploratory factor analysis resulting in a single factor > 1 and explaining 93% of the variance and positive correlations indicated unidimensionality of the measure. Item characteristic curves indicated groupings were overall concordant with proposed milestone ages and representative of an approximate 90% success cut-point by child age. Indicated normative age cut-points for 3 of the items differed slightly from proposed milestone ages. Uniform DIF was not observed and potential nonuniform DIF was observed across 5 items. Results have the potential to enhance understanding of risk and protective factors, inform efforts to promote language and communication development, and guide programmatic efforts on early detection of language delays.

Asymptotic Posterior Normality of Multivariate Latent Traits in an IRT Model

The asymptotic posterior normality (APN) of the latent variable vector in an item response theory (IRT) model is a crucial argument in IRT modeling approaches. In case of a single latent trait and under general assumptions, Chang and Stout (Psychometrika, 58(1):37–52, 1993) proved the APN for a broad class of latent trait models for binary items. Under the same setup, they also showed the consistency of the latent trait’s maximum likelihood estimator (MLE). Since then, several modeling approaches have been developed that consider multivariate latent traits and assume their APN, a conjecture which has not been proved so far. We fill this theoretical gap by extending the results of Chang and Stout for multivariate latent traits. Further, we discuss the existence and consistency of MLEs, maximum a-posteriori and expected a-posteriori estimators for the latent traits under the same broad class of latent trait models.

The psychometric properties of PSYCHLOPS, an individualized patient-reported outcome measure of personal distress.

Few studies report the psychometric properties of individualized patient-reported outcome measures (I-PROMs) combining traditional analysis and Item Response Theory (IRT). Pre- and posttreatment PSYCHLOPS data derived from six clinical samples (n = 939) were analyzed for validity, reliability, and responsiveness; caseness cutoffs and reliable change index were calculated. Exploratory and confirmatory factor analyses were used to determine whether items represented a unidimensional construct; IRT examined item properties of this construct. Values for internal consistency, construct validity, convergent and discriminant validity, and structural validity were satisfactory. Responsiveness was high: Cohen's d, 1.48. Caseness cutoff and reliable clinical change scores were 6.41 and 4.63, respectively. IRT analysis confirmed that item scores possess strong properties in assessing the underlying trait measured by PSYCHLOPS. PSYCHLOPS met the criteria for norm-referenced measurement of patient psychological distress. PSYCHLOPS functioned as a measure of a single latent trait, which we describe as "personal distress."

Supporting digitally enhanced learning through measurement in higher education: Development and validation of a university students' digital competence scale

AbstractDigital competence is critical for university students to adapt to and benefit from digitally enhanced learning. Prior studies on its measurement mostly focus on educators and relied on factor analyses. However, there is a lack of valid and convenient tools to measure university students' digital competence. This study aimed to develop a digital competence scale for university students (DC‐US) in digitally enhanced learning with robust psychometric properties. An initial DC‐US with 23 items was proposed to measure the single latent trait of digital competence. It was validated and refined continuously through a pilot study, a main study and a predictive validity study in three datasets involving 825 participants altogether, using factor analyses, Rasch analyses and the partial least squares modelling. The final DC‐US turned out to comprise two subscales: technical literacy and digital skills, with 10 items retained, and manifested high internal consistency, unidimensionality and measurement invariance. The scale also demonstrated strong predictive validity, with technical literacy greatly predicting digital skills, which negatively predicted technostress. The DC‐US enables instructors and school administrators to conveniently obtain preliminary information of university students' digital competence, informing their digital class preparation and development of timely interventions for addressing digital deficiencies.

In schizophrenia, immune-inflammatory pathways are strongly associated with depressive and anxiety symptoms, which are part of a latent trait which comprises neurocognitive impairments and schizophrenia symptoms.

Background. The aim is to examine whether biomarkers of the immune-inflammatory response (IRS) and endogenous opioid (EOS) systems are associated with affective symptoms in schizophrenia.Methods. We recruited 115 schizophrenia patients and 43 healthy controls and assessed the Hamilton Depression (HDRS) and Anxiety (HAM-A) rating Scale scores as well as serum levels of interleukin (IL)-6, IL-10, eotaxin (CCL11), high mobility group box 1 (HMGB1), Dickkopf-related protein 1 (DKK1), and mu (MOR) and kappa (KOR) opioid receptors.Results. The HDRS and HAM-A scores are significantly and positively correlated with a) psychosis, hostility, excitation, mannerism, negative symptoms, psychomotor retardation, and formal thought disorders; and b) lowered scores on semantic and episodic memory, executive functions, and attention tests as measured with the Brief Assessment of Cognition in Psychiatry. Both HDRS and HAM-A are significantly increased in non-responders to treatment as compared with partial responders. Both affective scores are strongly associated with a latent vector extracted from all symptoms, reflecting overall severity of schizophrenia symptoms (OSOS), and neurocognitive test scores, reflecting a generalized cognitive decline (G-CoDe). The HDRS score was strongly and positively associated with IL-6, HMGB1, KOR, and MOR levels, and the HAM-A score with IL-6, IL-10, CCL11, HMGB1, KOR, and MOR levels. A single latent trait may be extracted from OSOS, G-CoDe, and the HDRS and HAMA scores, and this latent vector score is strongly predicted by HMGB1, MOR, and DKK1.Conclusion. Immune-inflammatory and EOS pathways contribute to the phenome of schizophrenia, which comprises OSOS, affective, and physiosomatic symptoms, and G-CoDe.

Construction of an exposure-pathway-phenotype in children with depression due to transfusion-dependent thalassemia: Results of (un)supervised machine learning.

Background: Transfusion dependent thalassemia (TDT) patients are treated with continued blood transfusions and show a higher prevalence of depression. TDT with consequent iron overload and inflammation is associated with increased severity of depressive symptoms in TDT children. Aim of the study: To construct a pathway-phenotype which combines iron overload and neuro-immune biomarkers with depressive symptom subdomains in TDT children. Methods: We measured iron status parameters (iron, ferritin, transferrin saturation percentage) and inflammatory (interleukin-1β and tumour necrosis factor-α) biomarkers in TDT (n=111) and healthy (n=53) children and analyzed the results using machine learning. Results: Cluster analysis separated TDT children with depression from those without depression and revealed two depressive subgroups one with low self-esteem and another with increased social-irritability scores. Exploratory factor analysis validated four depressive symptom dimensions as reliable constructs, namely key depressive, physiosomatic, lowered self-esteem and social-irritability dimensions. Partial Least Squares showed that 73.0% of the variance in a latent vector extracted from those four clinical subdomains, immune-inflammatory and iron overload biomarkers was explained by exposure variables including the number of blood transfusions and hospitalizations and use of deferoxamine. The exposure data, iron and immune biomarkers, and symptom subdomains are reflective manifestations of a single latent trait, which shows internal consistency reliability and predictive relevance. Conclusions: The nomological network combining exposure, pathways and behavioral phenome manifestations provides an index of overall severity and disease risk and, therefore, constitutes a new drug target, indicating that iron overload and immune activation should be targeted to treat depression due to TDT.

Headache complexity (number of symptom features) differentiates post-traumatic from non-traumatic headaches.

Post-traumatic headaches are a common sequela of mild traumatic brain injury (concussion). It is unclear whether or how these headaches differ phenotypically from primary headaches. Determine whether there is an overarching unobserved latent trait that drives the expression of observed features of post-traumatic headache and other headaches. Data from this post-hoc analysis come from the Warrior Strong Cohort Study conducted from 2010 through 2015. Approximately 25,000 soldiers were screened for concussion history at routine post-deployment health assessments. A random sample was invited to participate, enrolling 1567. Twelve observed headache phenotypic features were used to measure "headache complexity", the latent trait of clinical interest, using single factor confirmatory factor analysis. We compared headache complexity between groups and determined whether headache complexity predicted accessing medical care for headache. Of 1094 soldiers with headaches, 198 were classified as having post-traumatic headache. These headaches were compared to those in the other soldiers (647 without concussion history and 249 with concussion history). Soldiers with post-traumatic headache had greater endorsement of all 12 headache features compared to the soldiers with non-concussive headaches. The confirmatory factor analysis showed good model fit (χ2 (51) = 95.59, p = 0.0002, RMSEA = 0.03, comparative fit index = 0.99, and Tucker-Lewis index = 0.99), providing empirical support for the headache complexity construct. Soldier groups differed in their mean headache complexity level (p < 0.001) such that post-traumatic headache soldiers had greater headache complexity compared to non-concussed soldiers (standardized mean difference = 0.91, 95% confidence interval: 0.72-1.09, p < 0.001 and to concussed soldiers with coincidental headaches standardized mean difference = 0.75, 95% confidence interval: 0.53-0.96, p < 0.001). Increasing headache complexity predicted medical encounters for headache (odds ratio = 1.87, 95% confidence interval: 1.49-2.35, p < 0.001) and migraine (odds ratio = 3.74, 95% confidence interval: 2.33-5.98, p < 0.001) during the year following deployment.Conclusions and relevance: The current study provided support for a single latent trait, characterized by observed headache symptoms, that differentiates between concussive and non-concussive headaches and predicts use of medical care for headache. The single trait confirmatory factor analysis suggests that post-traumatic headaches differ from non-concussive headaches by severity more than kind, based on the symptoms assessed.ClinicalTrials.gov identifier NCT01847040.

Defending as a unit: sex- and context-specific territorial defence in a duetting bird

Behaviours such as territorial defence represent functionally integrated traits that underlie multiple behavioural variables such as physical and acoustic responses. Characterizing the multivariate structure of such traits is fundamental to understand their evolution. In bird species that form stable pair bonds and are territorial year-round, both sexes are expected to defend their territory; however, the role that each sex plays in defending their shared territory remains largely unknown. Evidence for the sex-roles during territorial defence is mixed and sex- and context-specific characterizations of territorial defence embracing the multivariate nature of the trait are currently lacking. Here, we investigated sex- and context-specific variation in a hypothesised latent variable called ‘territorial defence’ and tested whether duets were part of territorial defence in a wild population of rufous hornero (Furnarius rufus). To do so, we combined a simulated territorial intrusion approach during nest building and provisioning contexts with a structural equation modelling approach. Our results showed that, in males and females, the six measured behavioural variables were linked by a single latent trait, territorial defence, in both contexts. Flights over the decoy and duet songs were equally good proxies of territorial defence. Although males were defending more the territory than females, pair members showed a positive correlation in their behaviour. The structural equation modelling framework enabled us to capture a complex correlation pattern among behavioural variables, expanding upon a classic body of research on territorial defence. Thus, the combination of classical behavioural approaches with sophisticated statistical analyses brings new exciting possibilities to the field of behavioural ecology. Territorial defence is a key behaviour in territorial species as it plays a major role in an individual’s reproductive success and survival. Additionally, territorial defence has been proposed as one possible evolutionary driver of duetting behaviour, one of the most fascinating vocal behaviours in birds. As behaviours are evolutionary characters, they must be studied in a multivariate framework. In this study, we focused on characterizing territorial defence during a simulated territorial intrusion in an integrative manner using a structural equation modelling framework. We did so in male and female rufous horneros (Aves: Furnaridae) across two breeding contexts, while simultaneously testing theoretical predictions about the role of duetting behaviour as key part of territorial defence. Overall, our study provides for the first time a sex- and context-comparison of the multivariate, latent variable ‘territorial defence’ in duetting birds, while highlighting the potential of combining field behavioural approaches with structural equation modelling.

Psychometric Evaluation of the Big Five Questionnaire for Children (BFQ-C): A Rasch Model Approach

The Big Five Questionnaire for Children, (BFQ-C) is an instrument for personality assessment in children and adolescents widely used worldwide. The aim of this work was to study the psychometric properties of the instrument scores from the item response theory (IRT) perspective. We worked with a Partial Credit Rasch Model to analyze an Argentinean sample to validate the scale for its use in this population. We opted for an instrumental design, and for each factor we applied an item calibration plan consisting of different analysis: unidimensionality, classification of response categories, fit levels of items and persons, specific objectivity, and differential item functioning as regards sex. We worked with a sample of 1162 high school students aged 12–17 years. The five original subscales did not show satisfactory fit, so modifications were made to improve their properties. As a result, we could demonstrate that each subscale measures a single latent trait, meets the invariance assumption regarding the sample and the assumption of local independence, showing no sex differential item functioning (DIF). Finally, the ordinal scores were converted to an interval scale, which allows more accurate analysis and better confidence in outcomes. Our results showed that the five subscales corresponding to each factor were in line with the IRT key parameters, although we suggest further studies on both the test capacity to assess extreme scores and the relevance of using a five-response category scoring.

Schizophrenia phenomenology revisited: positive and negative symptoms are strongly related reflective manifestations of an underlying single trait indicating overall severity of schizophrenia.

To examine whether negative symptoms, psychosis, hostility, excitation, and mannerism (PHEM symptoms), formal thought disorders (FTD) and psychomotor retardation (PMR) are interrelated phenomena in major neurocognitive psychosis (MNP) or deficit schizophrenia and whether those domains belong to an underlying latent vector reflecting general psychopathology. In this study, we recruited 120 patients with MNP or deficit schizophrenia and 54 healthy subjects and measured the above-mentioned symptom domains. In MNP, there were significant associations between negative and PHEM symptoms, FTD and PMR. A single latent trait, which is essentially unidimensional, underlies these key domains of schizophrenia and MNP and additionally shows excellent internal consistency reliability, convergent validity, and predictive relevance. Confirmatory Tedrad Analysis indicates that this latent vector fits a reflective model. The lack of discriminant validity shows that positive (and PHEM or psychotic) and negative symptoms greatly overlap and probably measure the same latent construct. Soft independent modeling of class analogy (SIMCA) shows that MNP (diagnosis based on negative symptoms) is better modeled using PHEM symptoms, FTD, and PMR than negative symptoms. In stable phase MNP, which is a restricted sample of the schizophrenia population, negative and PHEM symptoms, FTD and PMR belong to one underlying latent vector reflecting overall severity of schizophrenia (OSOS). The bi-dimensional concept of "positive" and "negative" symptoms cannot be validated and, therefore, future research in stable phase schizophrenia should consider that the latent phenomenon OSOS as well as its reflective manifestations are the key factors of schizophrenia phenomenology.

Schizophrenia phenomenology comprises a bifactorial general severity and a single-group factor, which are differently associated with neurotoxic immune and immune-regulatory pathways

In schizophrenia, a single latent trait underlies psychosis, hostility, excitation, mannerism, negative (PHEMN) symptoms, formal thought disorders (FTD) and psychomotor retardation (PMR). Schizophrenia is accompanied by a breakdown of gut and blood-brain-barrier (BBB) pathways, increased tryptophan catabolite (TRYCAT) levels, bacterial translocation, and lowered natural IgM and paraoxonase (PON)1 activity. The aim of this study was to examine the factor structure of schizophrenia symptom domains and the biomarker correlates of these factors. We recruited 80 patients with schizophrenia and 40 healthy subjects and assessed the IgA/IgM responses to paracellular/transcellular (PARA/TRANS) ratios, IgA responses to TRYCATs, natural IgM to malondialdehyde and Gram-negative bacteria, and PON1 enzymatic activity. Direct Hierarchical Exploratory Factor Analysis showed a bifactorial oblique model with a) a general factor which loaded highly on all symptom domains, named overall severity of schizophrenia ("OSOS"); and b) a single-group factor (SGF) loading on negative symptoms and PMR. We found that 40% of the variance in OSOS score was explained by IgA/IgM to PARA/TRANS ratio, male sex and education while 36.9% of the variance in SGF score was explained by IgA to PARA/TRANS, IgM to Gram-negative bacteria, female sex (positively associated) and IgM to MDA, and PON1 activity (negatively associated). Schizophrenia phenomenology comprises two biologically-validated dimensions, namely a general OSOS dimension and a single-group negative symptom dimension, which are associated with a breakdown of gut/BBB barriers, increased bacterial translocation and lowered protection against oxidation, inflammation and bacterial infections through lowered PON1 and natural IgM.

Schizophrenia Phenomenology Revisited: Positive and Negative Symptoms Are Strongly Related Reflective Manifestations of an Underlying Single Trait Indicating Overall Severity of Schizophrenia.

Schizophrenia comprises various symptom domains the two most important being positive and negative symptoms. Nevertheless, using (un)supervised machine learning techniques it was shown that a) negative symptoms are significantly interrelated with PHEM (psychosis, hostility, excitation, and mannerism) symptoms, formal thought disorders (FTD) and psychomotor retardation (PMR); and b) stable phase schizophrenia comprises two distinct classes, namely Major Neuro-Cognitive Psychosis (MNP, largely overlapping with deficit schizophrenia) and Simple NP (SNP). In this study, we recruited 120 MNP patients and 54 healthy subjects and measured the above-mentioned symptom domains. In MNP, there were significant associations between negative and PHEM symptoms, FTD and PMR. A single latent trait, which is essentially unidimensional, underlies these key domains of schizophrenia and additionally shows excellent internal consistency reliability, convergent validity, and predictive relevance. Confirmatory Tedrad Analysis indicates that this latent vector fits a reflective model. Soft Independent Modeling of Class Analogy (SIMCA) shows that MNP (diagnosis based on negative symptoms) is better modeled with PHEM symptoms, FTD and PMR than with negative symptoms. In conclusion, in MNP, a restricted sample of the schizophrenia population, negative and PHEM symptoms, FTD and PMR belong to one underlying latent vector reflecting general psychopathology and, therefore, may be used as an overall severity of schizophrenia (OSOS) index. The bi-dimensional concept of positive and negative symptoms and type I and II schizophrenia is revised.

A clinical assessment tool to improve the use of pain relieving treatments in knee osteoarthritis

A clinical assessment tool to improve the use of pain relieving treatments in knee osteoarthritis

Personality dimensions emerging during adolescence and young adulthood are underpinned by a single latent trait indexing impairment in social functioning

BackgroundPersonality with stable behavioural traits emerges in the adolescent and young adult years. Models of putatively distinct, but correlated, personality traits have been developed to describe behavioural styles including schizotypal, narcissistic, callous-unemotional, negative emotionality, antisocial and impulsivity traits. These traits have influenced the classification of their related personality disorders. We tested if a bifactor model fits the data better than correlated-factor and orthogonal-factor models and subsequently validated the obtained factors with mental health measures and treatment history.MethodA set of self-report questionnaires measuring the above traits together with measures of mental health and service use were collected from a volunteer community sample of adolescents and young adults aged 14 to 25 years (N = 2443). Results: The bifactor model with one general and four specific factors emerged in exploratory analysis, which fit data better than models with correlated or orthogonal factors. The general factor showed high reliability and validity.ConclusionsThe findings suggest that a selected range of putatively distinct personality traits is underpinned by a general latent personality trait that may be interpreted as a severity factor, with higher scores indexing more impairment in social functioning. The results are in line with ICD-11, which suggest an explicit link between personality disorders and compromised interpersonal or social function. The obtained general factor was akin to the overarching dimension of personality functioning (describing one’s relation to the self and others) proposed by DSM-5 Section III.