Investigating the performance of exploratory graph analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial

A behavioural exploration of language aptitude and experience, cognition and more using Graph Analysis

Language aptitude has recently regained interest in cognitive neuroscience. Traditional language aptitude testing included phonemic coding ability, associative memory, grammatical sensitivity and inductive language learning. Moreover, domain-general cognitive abilities are associated with individual differences in language aptitude, together with factors that have yet to be elucidated. Beyond domain-general cognition, it is also likely that aptitude and experience in domain-specific but non-linguistic fields (e.g. music or numerical processing) influence and are influenced by language aptitude. We investigated some of these relationships in a sample of 152 participants, using exploratory graph analysis, across different levels of regularisation, i.e. sensitivity. We carried out a meta cluster analysis in a second step to identify variables that are robustly grouped together. We discuss the data, as well as their meta-network groupings, at a baseline network sensitivity level, and in two analyses, one including and the other excluding dyslexic readers. Our results show a stable association between language and cognition, and the isolation of multilingual language experience, musicality and literacy. We highlight the necessity of a more comprehensive view of language and of cognition as multivariate systems.

Comparing the Clique Percolation algorithm to other overlapping community detection algorithms in psychological networks: A Monte Carlo simulation study

In psychological networks, one limitation of the most used community detection algorithms is that they can only assign each node (symptom) to a unique community, without being able to identify overlapping symptoms. The clique percolation (CP) is an algorithm that identifies overlapping symptoms but its performance has not been evaluated in psychological networks. In this study, we compare the CP with model parameters chosen based on fuzzy modularity (CPMod) with two other alternatives, the ratio of the two largest communities (CPRat), and entropy (CPEnt). We evaluate their performance to: (1) identify the correct number of latent factors (i.e., communities); and (2) identify the observed variables with substantive (and equally sized) cross-loadings (i.e., overlapping symptoms). We carried out simulations under 972 conditions (3x2x2x3x3x3x3): (1) data categories (continuous, polytomous and dichotomous); (2) number of factors (two and four); (3) number of observed variables per factor (four and eight); (4) factor correlations (0.0, 0.5, and 0.7); (5) size of primary factor loadings (0.40, 0.55, and 0.70); (6) proportion of observed variables with substantive cross-loadings (0.0%, 12.5%, and 25.0%); and (7) sample size (300, 500, and 1000). Performance was evaluated through the Omega index, Mean Bias Error (MBE), Mean Absolute Error (MAE), sensitivity, specificity, and mean number of isolated nodes. We also evaluated two other methods, Exploratory Factor Analysis and the Walktrap algorithm modified to consider overlap (EFA-Ov and Walk-Ov, respectively). The Walk-Ov displayed the best performance across most conditions and is the recommended option to identify communities with overlapping symptoms in psychological networks.

Factor retention in ordered categorical variables: Benefits and costs of polychoric correlations in eigenvalue-based testing

An essential step in exploratory factor analysis is to determine the optimal number of factors. The Next Eigenvalue Sufficiency Test (NEST; Achim, 2017) is a recent proposal to determine the number of factors based on significance tests of the statistical contributions of candidate factors indicated by eigenvalues of sample correlation matrices. Previous simulation studies have shown NEST to recover the optimal number of factors in simulated datasets with high accuracy. However, these studies have focused on continuous variables. The present work addresses the performance of NEST for ordinal data. It has been debated whether factor models - and thus also the optimal number of factors - for ordinal variables should be computed for Pearson correlation matrices, which are known to underestimate correlations for ordinal datasets, or for polychoric correlation matrices, which are known to be instable. The central research question is to what extent the problems associated with Pearson correlations and polychoric correlations deteriorate NEST for ordinal datasets. Implementations of NEST tailored to ordinal datasets by utilizing polychoric correlations are proposed. In a simulation, the proposed implementations were compared to the original implementation of NEST which computes Pearson correlations even for ordinal datasets. The simulation shows that substituting polychoric correlations for Pearson correlations improves the accuracy of NEST for binary variables and large sample sizes (N = 500). However, the simulation also shows that the original implementation using Pearson correlations was the most accurate implementation for Likert-type variables with four response categories when item difficulties were homogeneous.

Happy children! A network of psychological and environmental factors associated with the development of positive affect in 9-13 children

To deepen the development of positive affect during early adolescence and shed new light on its predictors, this study adopts an exploratory network approach to first identify the main domains that describe the variability of children's psychological, environmental, and behavioral characteristics, and then use these domains to longitudinally predict positive affect and its development within a latent growth framework. To this aim, we considered 10,904 US participants (9 years old at baseline; 13 years old 42 months later), six measurement occasions of positive affect, and 46 baseline indicators from the ABCD study. Our results not only confirm that positive affect declines between 9 and 13 years old, but also show that among the five domains identified (behavioral dysregulation, cognitive functioning, psychological problems, supportive social environment, and extracurricular activities), only a supportive social environment consistently predicts positive affect. This is crucial for practitioners and policymakers, as it can help them focus on the elements within our complex network of psychological, social, and environmental variability.

Revisiting the Structure of the Chinese Version of the Questionnaire of Cognitive and Affective Empathy and Its Relationships with Schizotypy and Paranoia Using Network Approaches

Empathy is predominantly assessed with self-report questionnaires. However, their structural validities were not well-supported. This study aimed to re-explore and refine the factor structure of the Chinese version of the Questionnaire of Cognitive and Affective Empathy (QCAE) and investigate the pathways linked between dimensions of empathy and schizotypy. Data from a valid sample of 1,360 community-dwelling adults (aged 18-35) were subjected to the exploratory graph analysis (EGA) and bootstrap EGA for factor retention. A goodness-of-fit evaluation was conducted using confirmatory factor analysis (CFA). Lastly, a Gaussian graphical model with sum scores of the resultant empathy dimensions, positive, negative, and disorganized schizotypy, and paranoia as nodes was estimated. Results supported a three-factor structure for the revised 20-item QCAE, demonstrating a good model fit. The new Online simulation subscale was associated with reduced disorganized schizotypy, whereas the new Perspective-taking subscale was associated with decreased disorganized schizotypy and increased positive schizotypy. The composite Affective empathy subscale was associated with decreased negative schizotypy and increased positive and disorganized schizotypy and paranoia. Overall, the revised QCAE demonstrated good structural validity, measuring three separable and internally cohesive factors of empathy. Each factor possessed unique and differential relationships with schizotypy dimensions that merit research and clinical attention.

Dimensionality assessment in the presence of wording effects: A network psychometric and factorial approach

This study proposes a procedure for substantive dimensionality estimation in the presence of wording effects, the inconsistent response to regular and reversed self-report items. The procedure developed consists of subtracting an approximate estimate of the wording effects variance from the sample correlation matrix and then estimating the substantive dimensionality on the residual correlation matrix. This is achieved by estimating a random intercept factor with unit loadings for all the regular and unrecoded reversed items. The accuracy of the procedure was evaluated through an extensive simulation study that manipulated nine relevant variables and employed the exploratory graph analysis (EGA) and parallel analysis (PA) retention methods. The results indicated that combining the proposed procedure with EGA or PA achieved high accuracy in estimating the substantive latent dimensionality, but that EGA was superior. Additionally, the present findings shed light on the complex ways that wording effects impact the dimensionality estimates when the response bias in the data is ignored. A tutorial on substantive dimensionality estimation with the R package EGAnet is offered, as well as practical guidelines for applied researchers.

Assessment of psychometric properties of the union physio-psycho-social assessment questionnaire (UPPSAQ-70) in a large sample of general hospital psychiatric outpatients

OBJECTIVE

To evaluate the psychometric properties of the Union Physio-Psycho-Social Assessment Questionnaire (UPPSAQ-70) among general hospital psychiatric outpatients.

METHODS

A total of 2000 participants responded to the survey. Factor analyses were used to test the construct validity of the scale. Convergent validity was evaluated by the correlation between UPPSAQ-70 and symptoms measured using the Chinese versions of Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), Patient Health Questionnaire-15 (PHQ-15), Somatic Symptom Disorder - B Criteria Scale (SSD-12) and Pittsburgh Sleep Quality Index (PSQI).

RESULTS

The nine-factor model was supported (χ2 = 8816.395, df = 2309, χ2/df = 3.818, RMSEA = 0.053, CFI = 0.929). The UPPSAQ-70 showed significant correlation with the SAS (r = 0.396, P < .001), SDS (r = 0.451, P < .001), PHQ-15 (r = 0.381, P < .001), SSD-12 (r = 0.324, P < .001) and PSQI (r = 0.220, P < .001). UPPSAQ-70 and its subscales showed good internal consistency with Cronbach's alpha coefficients ranging from 0.79 to 0.96.

CONCLUSIONS

The UPPSAQ-70 was a rating scale with good construct validity and reliability, which can measure overall health in the biological, psychological, and social domains for Chinese psychiatric outpatients, but its convergent validity still requires further empirical research.

Assessment of psychometric performance for the Chinese version of the Brief Inventory of Perceived Stress integrating exploratory graph analysis and confirmatory factor analysis

OBJECTIVE

This study was to evaluate measurement properties of the Chinese version of the Brief Inventory of Perceived Stress (BIPS-C) and confirm possible solutions for measuring the constructs underlying perceived stress.

METHODS

A total of 1356 community residents enrolled and were randomly split into two halves. The first half was used to explore the underlying constructs of the BIPS-C by exploratory graph analysis (EGA) and the second half was used to compare and confirm the constructs by confirmatory factor analysis (CFA).

RESULTS

The EGA identified a one-factor model of the BIPS-C with an accuracy of 99.3%. One-factor, three-factor, second-order, and bifactor models were compared by CFAs. The bifactor model with one general and three specific factors was found to be the most adequate [comparative fit index (CFI) = 0.990; Tucker-Lewis index (TLI) = 0.979; root mean square error of approximation (RMSEA) = 0.058] and was superior to the other models. The related bifactor indices showed a stronger existence of the general factor. The bifactor model of the BIPS-C also showed adequate internal consistency with McDonald's omega and omega subscales ranging from moderate to strong (0.677-0.869).

CONCLUSION

The BIPS-C demonstrates sufficient measurement properties for assessing general perceived stress.

Validation and structural exploration of the Chinese version of the Body Talk Scale

The Body Talk Scale (BTS) measures both negative body talk (including fat talk and muscle talk) and positive body talk across genders. In this study, we translated it into Chinese and assessed its structure, reliability and validity among mainland Chinese residents. Item analyses indicated that no item deletion was necessary for this study, and both exploratory factor analysis (n = 1853) and exploratory graph analysis (n = 1583) supported the three-factor structure of the original scale. Confirmatory factor analysis showed that the scale had a good model fit with CFI= 0.95, GFI= 0.93, TLI= 0.94, and RMSEA= 0.079(90 %CI [0.075, 0.084]). The results also showed that the Chinese version of the BTS had adequate criterion-related validity，internal consistency and six-week test-retest reliability. Meanwhile, the scale has good measurement invariance with respect to gender and can be tested for gender differences. In conclusion, the BTS showed sufficient psychometric properties in a Chinese sample, making it a valid instrument for studying body talk and health status in Chinese populations.

Using exploratory graph analysis (EGA) in validating the structure of the Perth alexithymia questionnaire in Iranians with chronic pain

Background

Chronic pain's influence on emotional well-being can be significant. It may evoke feelings of despair, frustration, nervousness, and melancholy in individuals, which often manifest as reactions to enduring pain and disruptions in their daily lives. In this study, we seek to perform Bootstrap Exploratory Graph Analysis (EGA) on the Persian Version of the Perth Alexithymia Questionnaire (PAQ) in a cohort of people with chronic pain.

Methods

The research concentrated on the population of individuals encountering chronic pain within Tehran province from 2022 to 2023. Ultimately, the analysis comprised information from 234 male participants (with a mean age of 30.59, SD = 6.84) and 307 female participants (with a mean age of 30.16, SD = 6.65). After data collection, statistical analysis was conducted using the EGAnet2.0.4 package in R.4.3.2 software.

Results

The outcome of bootstrapped EGA unveiled a two-dimensional configuration of the PAQ comprising Factor 1 denoted as negative difficulty in describing and identifying feelings (N-DDIF) and Factor 2 characterized as general-externally orientated thinking (GEOT), representing robust structural integrity and item consistency (all items have stabilities > 0.70).

Conclusion

These findings endorse the validity of the PAQ, as evidenced by its confirmation in a broader sample using a novel methodology consistent with existing literature on two-factor decentering models.

The Network Structure of Cognitive Impairment: From Subjective Cognitive Decline to Alzheimer's Disease

It was proposed that a reorganization of the relationships between cognitive functions occurs in dementia, a vision that surpasses the idea of a mere decline of specific domains. The complexity of cognitive structure, as assessed by neuropsychological tests, can be captured by exploratory graph analysis (EGA). EGA was applied to the neuropsychological assessment of people (humans) with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD; total N = 638). Both sexes were included. In AD, memory scores detach from the other cognitive functions, and memory subdomains reduce their reciprocal relation. SCD showed a pattern of segregated neuropsychological domains, and MCI showed a noisy and less stable pattern. Results suggest that AD drives a reorganization of cognitive functions toward a less-fractionated architecture compared with preclinical conditions. Cognitive functions show a reorganization that goes beyond the performance decline. Results also have clinical implications in test interpretations and usage.

Psychometric Evaluation of the Affective Reactivity Index Among Children and Adolescents in China: A Multi-Method Assessment Approach

The Affective Reactivity Index (ARI) is one of the most studied scales for assessing youth irritability, but little is known about its measurement performance in community populations. This study applied item response theory (IRT), network analysis, and classical test theory (CTT) to examine the psychometric properties of the ARI in a sample of n = 395 community-based children (Mage = 13.44, SD = 2.51) and n = 403 parents. In this sample, the ARI demonstrated good reliability, as well as convergent and concurrent validity. The one-factor structure was supported by both confirmatory factor analysis (CFA) and network analysis. IRT analysis revealed that the ARI effectively distinguished between various levels of irritability within the community population. Network analysis identified "Loses temper easily,""Gets angry frequently," and "Often loses temper" are central aspects of irritability. The findings support the ARI as a brief, reliable, and valid instrument to assess irritability in community children and adolescents.

Confirmatory validation of the Mesothelioma Psychological Distress Tool-Patients: A brief patient-reported outcome measure assessing psychological distress in malignant mesothelioma patients

OBJECTIVE

Psychological suffering in patients with Malignant Mesothelioma (MM) is different from the one experienced by patients with other cancers due to its occupational or environmental etiology and its peculiar symptomatology and prognosis (i.e., poor prognosis, reduced effectiveness of the therapies, poor quality of residual life, and advanced age at the time of diagnosis). Therefore, the Mesothelioma Psychological Distress Tool-Patients (MPDT-P) has been developed to evaluate the specific profile of psychological suffering in this population. This paper describes the item selection, factor analysis, and psychometric evaluation of the revised MPDT-P.

METHODS

The analyses of the current work aimed to confirm the factorial structure found in the first version of the MPDT-P. In the case of nonfit, it aimed to find an alternative structure and causes of nonfit in the model. The search for the fit of the factorial model was conducted using a Bayesian approach.

RESULTS

The two-factor model reported in the first version of the instrument did not fit the data. Confirmatory Bayesian analyses showed adequate fit for the three-factor solution. Based on the content of the items, we labeled the factors as dysfunctional emotions, claims for justice, and anxieties about the future.

CONCLUSIONS

Integrating the MPDT-P into clinical practice could help clinicians gain insight into the specific suffering related to MM and investigate potential differences related to different occupational and environmental exposure contexts.

Beyond sound irritation: cross-cultural evidence on the robustness of the five aspects of misophonic experience measured by the S-Five in a Polish sample

Misophonia is commonly associated with negative emotional or physiological responses to specific sounds. However, the consensus definition emphasizes that misophonia entails much more than that. Even in cases of subclinical misophonia, where individuals do not meet the disorder criteria, the experience can still be burdensome, despite not currently causing significant distress or impairment. The S-Five is a psychometric tool for comprehensive assessment of five aspects of misophonic experience: internalizing, externalizing, impact, threat, and outburst, and includes S-Five-T section to evaluate feelings evoked by triggering sounds and their intensity. We examined whether the five-factor structure developed in the UK could be replicated in a Polish sample, including individuals with and without self-identified misophonia. The Polish version of the S-Five was translated and tested on 288 Polish-speaking individuals. Comprehensive psychometric evaluation, including factor structure, measurement invariance, test-retest reliability, internal consistency, and concurrent validity evaluations, was conducted on the translated scale. Exploratory factor analysis suggested similar structure to the original English study, while bootstrap exploratory graph analysis showed the factor structure to be reproducible in other samples. The scale was found to be bias free with respect to gender, internally consistent and stable in time, and evidence of validity was provided using MisoQuest and Misophonia Questionnaire. These results offer support for the cross-cultural stability of the five factors and provide preliminary evidence for the suitability of the Polish version for clinical and research purposes. The study also investigated five facets of misophonia, triggering sounds, emotional responses, and their associations with symptoms of psychopathology across various cultures. It underscores the central role of anger, distress, and panic, while also highlighting the mixed role of irritation and disgust in misophonia across different cultural contexts. Mouth sounds evoked the most pronounced reactions compared to other repetitive sounds, although there were discernible cultural differences in the nature and intensity of reactions to various trigger sounds. These findings hold significant implications for future research and underscore the importance of considering cultural nuances in both research and the clinical management of misophonia.

Contemporaneous and temporal network analysis of complex Posttraumatic stress disorder among Chinese college students with Childhood adversity: A longitudinal study

OBJECTIVE

To enhance understanding of the longitudinal progression of complex posttraumatic stress disorder (CPTSD) symptoms, this longitudinal study examined how CPTSD symptoms interact over time in Chinese college students with childhood trauma.

METHODS

From 18,933 college students who took part in two surveys 12 months apart, 4,006 participants who reported adverse childhood experiences were screened. Cross-sectional network comparisons and cross-lagged panel network (CLPN) analysis characterized interactions among CPTSD symptoms.

RESULTS

In the cross-sectional networks, feeling like a failure and avoid activities reminiscent of the trauma were the central symptoms. Takes long time to calm down and exaggerated startle are important bridge symptoms in the two networks respectively. The comparison of cross-sectional networks indicates that the global network strength was stable. The findings of the CLPN model reveal that feel worthless and feel like a failure had the highest "out" expected influence; exaggerated startle and avoid thoughts and feelings about the trauma had the highest "in" expected influence.

CONCLUSIONS

By conducting cross-sectional network analyses, the study illuminated the attributes of CPTSD networks across various time points. Additionally, the CLPN analysis uncovered the longitudinal patterns of CPTSD symptoms.

Identifying symptom clusters and temporal interconnections in patients with lung tumors after CT-guided microwave ablation: A network analysis

PURPOSE

To explore symptom clusters and interrelationships using a network analysis approach among symptoms in patients with lung tumors who underwent computed tomography (CT)-guided microwave ablation (MWA).

METHODS

A longitudinal study was conducted, and 196 lung tumor patients undergoing MWA were recruited and were measured at 24 h, 48 h, and 72 h after MWA. The Chinese version of the MD Anderson Symptom Inventory and the Revised Lung Cancer Module were used to evaluate symptoms. Network analyses were performed to explore the symptom clusters and interrelationships among symptoms.

RESULTS

Four stable symptom communities were identified within the networks. Distress, weight loss, and chest tightness were the central symptoms. Distress, and weight loss were also the most key bridge symptoms, followed by cough. Three symptom networks were temporally stable in terms of symptom centrality, global connectivity, and network structure.

CONCLUSION

Our findings identified the central symptoms, bridge symptoms, and the stability of symptom networks of patients with lung tumors after MWA. These network results will have important implications for future targeted symptom management intervention development. Future research should focus on developing precise interventions for targeting central symptoms and bridge symptoms to promote patients' health.

The biobehavioural pain and movement questionnaire (BioPMovQ): development and psychometric validation of a new questionnaire

Objective

The purpose of this research was to design and psychometrically validate a new instrument (the Biobehavioural Pain and Movement Questionnaire/BioPMovQ), which assesses the relationship between pain and various factors related to motor behaviour from a biobehavioural perspective.

Methods

A mixed-method design combining a qualitative study with an observational and cross-sectional study was employed to develop (content validity) and psychometrically validate (construct validity, reliability and concurrent/discriminant validity) a new instrument. A total of 200 patients with chronic musculoskeletal pain were recruited.

Results

According to the exploratory factor analysis, the final version of the BioPMovQ consists of 16 items distributed across 4 subscales (1, disability, 2, self-efficacy for physical activity; 3, movement avoidance behaviours; and 4, self-perceived functional ability), all with an eigen value greater than 1, explaining 55.79% of the variance. The BioPMovQ showed high internal consistency (Cronbach's α = 0.82; McDonald's ω = 0.83). The intraclass correlation coefficient was 0.86 (95% confidence interval 0.76 to 0.91), which was considered to demonstrate excellent test-retest reliability. The standard error of measurement and minimal detectable change were 3.43 and 8.04 points, respectively. No floor or ceiling effects were identified. There was a positive, significant and moderate magnitude correlation with the Graded Chronic Pain Scale (r = 0.54), kinesiophobia (r = 0.60), pain catastrophising (r = 0.44) and chronic pain self-efficacy (r = -0.31).

Conclusion

The BioPMovQ showed good psychometric properties. Based on the findings of this study, the BioPMovQ can be used in research and clinical practice to assess patients with chronic musculoskeletal pain.

Dimensionality assessment in ordinal data: a comparison between parallel analysis and exploratory graph analysis

In the social sciences, accurately identifying the dimensionality of measurement scales is crucial for understanding latent constructs such as anxiety, happiness, and self-efficacy. This study presents a rigorous comparison between Parallel Analysis (PA) and Exploratory Graph Analysis (EGA) for assessing the dimensionality of scales, particularly focusing on ordinal data. Through an extensive simulation study, we evaluated the effectiveness of these methods under various conditions, including varying sample size, number of factors and their association, patterns of loading magnitudes, and symmetrical or skewed item distributions with assumed underlying normality or non-normality. Results show that the performance of each method varies across different scenarios, depending on the context. EGA consistently outperforms PA in correctly identifying the number of factors, particularly in complex scenarios characterized by more than a single factor, high inter-factor correlations and low to medium primary loadings. However, for datasets with simpler and stronger factor structures, specifically those with a single factor, high primary loadings, low cross-loadings, and low to moderate interfactor correlations, PA is suggested as the method of choice. Skewed item distributions with assumed underlying normality or non-normality were found to noticeably impact the performance of both methods, particularly in complex scenarios. The results provide valuable insights for researchers utilizing these methods in scale development and validation, ensuring that measurement instruments accurately reflect theoretical constructs.

Exploring the factor structure of a Chinese version of the CORE-OM: insights from network approach and bifactor modeling

OBJECTIVE

The Clinical Outcomes in Routine Evaluation (CORE-OM) is a measure of clinical outcomes that has been widely used in mental health research. Nevertheless, the exploration of the factor structure of the CORE-OM yields diverse results. This study aims to explore the factor structure with an innovative method known as exploratory graph analysis (EGA) and supplemented with bifactor modeling.

METHOD

A Chinese version of the CORE-OM was administrated to a total of 1361 clinical college students. We first examined the factor structure of the CORE-OM using EGA, and then compared the model derived by EGA with other models using CFA to find the most reasonable model.

RESULTS

The result of EGA indicated a four-factor model of CORE-OM. The CFA further suggested a bifactor model with a four-factor structure combined with a general factor. The bifactor modeling suggested a significant proportion of shared variance among the variables was attributed to the general factor. The four-factor bifactor model exhibited a satisfactory fit to the data.

CONCLUSION

The results confirm the robustness and parsimonious nature of a four-factor bifactor model for the Chinese version of CORE-OM. It is suitable for measuring intrapersonal psychological distress, positive emotions, interpersonal problems, and risk-related issues among the Chinese population.

Antisocial personality traits relationship with behaviours and beliefs on COVID-19 containment measures: Investigation in a large Brazilian sample

In the COVID-19 context, traits associated with antisociality can decrease concern and awareness about the potential harmfulness of the virus. This study investigated associations of pathological traits of antisocial personality disorder (ASPD) with behaviours and beliefs linked to COVID-19 containment measures. The sample consisted of 2230 Brazilian adults who answered ASPD-related facets of the Personality Inventory for DSM-5 and a questionnaire regarding adherence to COVID-19 containment measures. We applied the DSM-5 ASPD criteria to divide the sample into antisocial and non-antisocial groups. Our findings suggest that individuals meeting the criteria for ASPD tend to exhibit reduced compliance with pandemic control measures and lower adherence to hygiene practices. Moreover, sex, income, and age should be considered potential covariates in research investigating the relationship between antisocial traits and adherence to COVID-19 preventive measures. Altogether, our findings highlight ASPD traits' role in the predisposition to lack of prosocial behaviours of adherence to COVID-19 containment measures.

All the Same? Different Measures of Personality Functioning Are Similar but Distinct. A Comparative Study from a Psychodynamic Perspective Using Exploratory Graph Analysis

Personality functioning (PF) is a central construct in many theories of personality pathology. Based on psychodynamic theories, two screening questionnaires to assess PF are widely used: The Inventory of Personality Organization-16 item version and the Operationalized Psychodynamic Diagnosis-Structure Questionnaire Short Form. This study aimed to explore the similarities and differences of the two questionnaires in a large clinical sample of N = 1636 psychotherapeutic inpatients. Correlation analyses were conducted to examine the associations between the global scores and between the subscales. The study further used Exploratory Graph Analysis (EGA) to explore the dimensionality of the items. The stability of estimates was evaluated using a bootstrap version of EGA (bootEGA). The results indicated that the two questionnaires are highly correlated, yet not multicollinear, and moderate to large correlations were found between their subscales. EGA revealed six dimensions that fairly represented the original subscales. BootEGA showed that the dimensions and items were stable, except for one item that did not load sufficiently on any dimension. The findings suggest that although the questionnaires are highly correlated, their subscales tap into distinct domains of PF. We discuss implications stemming from these findings for clinical and scientific practice.

The "central" importance of loneliness in mental health: A network psychometric study

Loneliness is linked to negative mental health outcomes like depression and social anxiety. However, it is unclear how loneliness and these conditions are connected. This study aims to address two questions: (a) Are there pathways connecting loneliness to these conditions? (b) What symptoms play a role in these pathways? Using network analyses, the study examined a representative sample of 962 adults from the UK (mean age = 46, females = 492). The network analysis revealed four dimensions: depression, social anxiety and two dimensions for loneliness (isolation and social connectedness). Two distinct pathways were identified for the transmission of symptoms between loneliness, social anxiety and depression. The depression-isolation pathway involved a node representing the perceived loss of social connections. The social anxiety-social connectedness pathway was characterised by intimate interaction contexts. These findings suggest that loneliness is associated with different symptom pathways, potentially contributing to comorbidity between loneliness, social anxiety and depression.

Accelerated epigenetic age is associated with whole-brain functional connectivity and impaired cognitive performance in older adults

While chronological age is a strong predictor for health-related risk factors, it is an incomplete metric that fails to fully characterize the unique aging process of individuals with different genetic makeup, neurodevelopment, and environmental experiences. Recent advances in epigenomic array technologies have made it possible to generate DNA methylation-based biomarkers of biological aging, which may be useful in predicting a myriad of cognitive abilities and functional brain network organization across older individuals. It is currently unclear which cognitive domains are negatively correlated with epigenetic age above and beyond chronological age, and it is unknown if functional brain organization is an important mechanism for explaining these associations. In this study, individuals with accelerated epigenetic age (i.e. AgeAccelGrim) performed worse on tasks that spanned a wide variety of cognitive faculties including both fluid and crystallized intelligence (N = 103, average age = 68.98 years, 73 females, 30 males). Additionally, fMRI connectome-based predictive models suggested a mediating mechanism of functional connectivity on epigenetic age acceleration-cognition associations primarily in medial temporal lobe and limbic structures. This research highlights the important role of epigenetic aging processes on the development and maintenance of healthy cognitive capacities and function of the aging brain.

Machine learning-based prediction of heat transfer performance in annular fins with functionally graded materials

This paper presents a study investigating the performance of functionally graded material (FGM) annular fins in heat transfer applications. An annular fin is a circular or annular structure used to improve heat transfer in various systems such as heat exchangers, electronic cooling systems, and power generation equipment. The main objective of this study is to analyze the efficiency of the ring fin in terms of heat transfer and temperature distribution. The fin surfaces are exposed to convection and radiation to dissipate heat. A supervised machine learning method was used to study the heat transfer characteristics and temperature distribution in the annular fin. In particular, a feedback architecture with the BFGS Quasi-Newton training algorithm (trainbfg) was used to analyze the solutions of the mathematical model governing the problem. This approach allows an in-depth study of the performance of fins, taking into account various physical parameters that affect its performance. To ensure the accuracy of the obtained solutions, a comparative analysis was performed using guided machine learning. The results were compared with those obtained by conventional methods such as the homotopy perturbation method, the finite difference method, and the Runge-Kutta method. In addition, a thorough statistical analysis was performed to confirm the reliability of the solutions. The results of this study provide valuable information on the behavior and performance of annular fins made from functionally graded materials. These findings contribute to the design and optimization of heat transfer systems, enabling better heat management and efficient use of available space.

Psychometric network analysis of the Patient Health Questionnaire-4 (PHQ-4) in Paraguayan general population

BACKGROUND

Depression and anxiety are two of the most prevalent and disabling mental disorders worldwide, both in the general population and in outpatient clinical settings.

OBJECTIVE

This study aimed to analyze the psychometric properties of the Patient Health Questionnaire-4 (PHQ-4) based on network analysis metrics.

METHODS

A total of 911 Paraguayans (23.71% women and 76.29% men; mean age 31.25 years, SD = 10.63), selected by non-probabilistic convenience sampling, participated in the study. Network analysis was used to evaluate the internal structure, reliability, and measurement invariance between men and women.

RESULTS

The results revealed that the PHQ-4 is a unidimensional measure through Exploratory Graph Analysis (EGA). Reliability, through structural consistency, identified that 100% of the time, only a single dimension was obtained, and all items remained stable, as they were always replicated within the empirical dimension. The unidimensional structure has shown evidence of configural invariance; therefore, the network structure functioned equally among the different sex groups.

CONCLUSION

The PHQ-4 presented optimal preliminary evidence of validity based on its internal structure, reliability, and invariance between sexes. Therefore, it may be useful as an accurate and brief measure of anxiety and depressive symptoms in the Paraguayan context.

Network Structure and Clustering Analysis Relating to Individual Symptoms of Problematic Internet Use in a Community Adolescent Population

INTRODUCTION

Problematic internet use (PIU) is a psychopathology that includes multiple symptoms and psychological constructs. Because no studies have considered both network structures and clusters among individual symptoms in the context of PIU in a Korean adolescent population, this study aimed to investigate network structures and clustering in relation to PIU symptoms in adolescents.

METHODS

Overall, 73,238 adolescents were included. PIU severity was assessed using a self-rating scale comprising 20 items and 6 subscales, namely, the Internet Addiction Proneness Scale for Youth-Short Form; KS scale. Network structures and clusters among symptoms were analyzed using a Gaussian graphical model and exploratory graph analysis, respectively. Centrality of strength, closeness, and betweenness scores was also calculated.

RESULTS

Our study identified four clusters: disturbance in adaptive functioning, virtual interpersonal relationships, withdrawal, and tolerance. The symptom of confidence served as a node bridging the cluster of virtual interpersonal relationships and other clusters of withdrawal and disturbances of adaptive function. The symptom of craving served as a bridge between the clusters of withdrawal and tolerance with high betweenness centrality.

CONCLUSION

This study identified network structures and clustering among PIU symptoms in adolescents and revealed that positive experiences derived from online interpersonal relationships were an important mechanism underlying PIU. These are novel insights concerning the interconnection among multiple symptoms and related clustering for the mechanism of adolescent PIU in terms of KS-scale PIU assessment.

Internal and external self-affirmation resources: validation and assessment of psychometric properties of the spontaneous self-affirmation measure using structural equation modeling

Introduction

People use coping strategies such as self-affirmation to manage threats to their self-esteem. In empirical research, self-affirmation often involves recalling personal values, strengths, or relationships to restore moral integrity. Research shows it improves attitude adjustment, resolves cognitive dissonance, and enhances well-being. Some studies stress the importance of distinguishing between different aspects of self-affirmation, like strengths or social relations. These aspects align with concepts in psychotherapy that differentiate between internal and external resource activation, benefiting health, self-esteem, and resilience. The aim of the current study was twofold: first, to independently test the three-factor structure of the Spontaneous Self-affirmation Measure (SSAM), and second, to integrate self-affirmation strategies into a broader resource activation framework as resilience factors. It also examined associations with self-esteem and effects of age, gender, and education on spontaneous self-affirmation.

Methods

1,100 participants (72% female, age 18-65) were recruited online. The original three-factor structure of the SSAM (with the factors Strengths, Values and Social relations) was examined using structural equation modeling. Further, a theory driven two-factor structure applying an internal and external resources framework was examined, integrating the factors of the SSAM into the taxonomy of resource activation (Internal resources: Strengths and Values; External resources: Social relations).

Results

The results of confirmatory factor analyses showed that both the original three-factor structure and the complementary two-factor structure with an Internal resources and External resources factor fit the data appropriately. All three factors of the original factor model showed a high reliability (Strengths: ω t = 0.91, Values: ω t = 0.91, Social relations: ω t = 0.92). We also found measurement invariance across age, gender, and education. Furthermore, group differences regarding gender, education and ethnicity in the utilization of spontaneous self-affirmation strategies were apparent. Finally, it was demonstrated that the Internal resources factor of the complementary two-factor model is significantly more strongly correlated with self-esteem than the External Resources factor [z = 12.80, p < 0.001, 95%CIdiff (0.24, 0.33)].

Discussion

The study confirms the validity of both the three-factor and two-factor structures of the SSAM. Integrating self-affirmation into the resource activation framework may facilitate applying findings from self-affirmation studies to clinical contexts.

Symptom clusters in adolescent depression and differential responses of clusters to pharmacologic treatment

OBJECTIVE

Symptoms of depression in adolescents are widely variable, but they are often interactive and clustered. The analysis of interactions and clusters among individual symptoms may help predict treatment outcomes. We aimed to determine clusters of individual symptoms in adolescent depression and their changes in the response to pharmacological treatment.

METHOD

A total of 95 adolescents, aged 12-17 years, with major depressive disorder were included. Participants were treated with escitalopram, and depressive symptoms were assessed at baseline (V1) and 1, 2, 4, 6, and 8 weeks (V6). The severity of depression was assessed using the Children's Depression Rating Scale-Revised. To construct network and clustering structures among symptoms, the Gaussian graphical model and Exploratory Graph Analysis with the tuning parameter to minimize the extended Bayesian information criterion were adopted.

RESULTS

Exploratory Graph Analysis revealed that symptoms of depression comprised four clusters: impaired activity, somatic concerns, subjective mood, and observed affect. The main effect of visit with decreased symptom severity was significant in all four clusters; however, the degree of symptom improvement differed among the four clusters. The effect size of score differences from V1 to V6 was the highest in the subjective mood (Cohen's d = 1.075), and lowest in impaired activity (d = 0.501) clusters.

CONCLUSION

The present study identified four symptom clusters associated with adolescent depression and their differential changes related to antidepressant treatment. This finding suggests that escitalopram was the most effective at improving subjective mood among different clusters. However, other therapeutic modalities may be needed to improve other clusters of symptoms, consequently leading to increased overall improvement of depression in adolescents.

Global cross-cultural validation of a brief measure for identifying potential suicide risk in 42 countries

OBJECTIVES

This study aimed to examine the psychometric properties of the P4 suicide screener in a multinational sample. The primary goal was to evaluate the reliability and validity of the scale and investigate its convergent validity by analyzing its correlation with depression, anxiety, and substance use.

STUDY DESIGN

The study design is a cross-sectional self-report study conducted across 42 countries.

METHODS

A cross-sectional, self-report study was conducted in 42 countries, with a total of 82,243 participants included in the final data set.

RESULTS

The study provides an overview of suicide ideation rates across 42 countries and confirms the structural validity of the P4 screener. The findings indicated that sexual and gender minority individuals exhibited higher rates of suicidal ideation. The P4 screener showed adequate reliability, convergence, and discriminant validity, and a cutoff score of 1 is recommended to identify individuals at risk of suicidal behavior.

CONCLUSIONS

The study supports the reliability and validity of the P4 suicide screener across 42 diverse countries, highlighting the importance of using a cross-cultural suicide risk assessment to standardize the identification of high-risk individuals and tailoring culturally sensitive suicide prevention strategies.

Deciphering the interplay between psychopathological symptoms, sensorimotor, cognitive and global functioning: a transdiagnostic network analysis

BACKGROUND

Understanding the relationship between psychopathology and major domains of human neurobehavioral functioning may identify new transdiagnostic treatment targets. However, studies examining the interrelationship between psychopathological symptoms, sensorimotor, cognitive, and global functioning in a transdiagnostic sample are lacking. We hypothesized a close relationship between sensorimotor and cognitive functioning in a transdiagnostic patient sample.

METHODS

We applied network analysis and community detection methods to examine the interplay and centrality [expected influence (EI) and strength] between psychopathological symptoms, sensorimotor, cognitive, and global functioning in a transdiagnostic sample consisting of 174 schizophrenia spectrum (SSD) and 38 mood disorder (MOD) patients. All patients (n = 212) were examined with the Positive and Negative Syndrome Scale (PANSS), the Heidelberg Neurological Soft Signs Scale (NSS), the Global Assessment of Functioning (GAF), and the Brief Cognitive Assessment Tool for Schizophrenia consisted of trail making test B (TMT-B), category fluency (CF) and digit symbol substitution test (DSST).

RESULTS

NSS showed closer connections with TMT-B, CF, and DSST than with GAF and PANSS. DSST, PANSS general, and NSS motor coordination scores showed the highest EI. Sensory integration, DSST, and CF showed the highest strength.

CONCLUSIONS

The close connection between sensorimotor and cognitive impairment as well as the high centrality of sensorimotor symptoms suggests that both domains share aspects of SSD and MOD pathophysiology. But, because the majority of the study population was diagnosed with SSD, the question as to whether sensorimotor symptoms are really a transdiagnostic therapeutic target needs to be examined in future studies including more balanced diagnostic groups.

The Social Validity of Behavioral Interventions: Seeking Input from Autistic Adults

Many in the autistic community have expressed concerns regarding the use of behavioral interventions with autistic children, suggesting that these interventions may not be socially valid. Though behavioral interventions have evolved to be more naturalistic and child-centered, little structured research has been done to explicitly seek autistic perspectives on the acceptability of specific components of behavioral interventions. Autistic adults (N = 235) were recruited online to take the Autism Intervention Attitudes Scale (AIAS), a questionnaire designed to gather feedback on common intervention goals and practices. Results indicate that participants find goals and practices that highlight quality of life, safety, and autistic interactions acceptable, while those that focus on normalization based on neurotypical standards are not. An exploratory graph analysis revealed three communities of goals ("uncontroversial goals", "controversial goals", and "social goals"). Comparison between naturalistic and structured intervention components additionally showed that autistic participants favored naturalistic strategies. These findings are in line with known criticisms of behavioral intervention from autistic adults, but also provide more information on the specific ways in which behavioral interventions can be reformed. This information can guide professionals in the development of appropriate goals and decisions around intervention planning.

Mental Health and Well-being Measures for Mean Comparison and Screening in Adolescents: An Assessment of Unidimensionality and Sex and Age Measurement Invariance

Adolescence is a period of increased vulnerability for low well-being and mental health problems, particularly for girls and older adolescents. Accurate measurement via brief self-report is therefore vital to understanding prevalence, group trends, screening efforts, and response to intervention. We drew on data from the #BeeWell study (N = 37,149, aged 12-15) to consider whether sum-scoring, mean comparisons, and deployment for screening were likely to show bias for eight such measures. Evidence for unidimensionality, considering dynamic fit confirmatory factor models, exploratory graph analysis, and bifactor modeling, was found for five measures. Of these five, most showed a degree of non-invariance across sex and age likely incompatible with mean comparison. Effects on selection were minimal, except sensitivity was substantially lower in boys for the internalizing symptoms measure. Measure-specific insights are discussed, as are general issues highlighted by our analysis, such as item reversals and measurement invariance.

Network Psychometrics of the 10-Item Perceived Stress Scale Among Patients With High Cardiovascular and Type 2 Diabetes Risk Using Exploratory Graph Analysis

BACKGROUND

No studies have explored the internal structure of the 10-item Perceived Stress Scale in patients with high cardiovascular and diabetes risk.

OBJECTIVE

We scrutinized the dimensionality of the scale in this patient group using exploratory graph analysis, a technique within the developing field of network psychometrics.

METHODS

Analyses were conducted on 200 primary care patients. A bootstrap version of exploratory graph analysis assessed the stability of the dimensions based on structural consistency, item stability, and network loadings.

RESULTS

Exploratory graph analysis revealed a 2-dimensional structure; structural consistency of the first dimension was high (0.863), whereas that for the second was low (0.667). Items belonging to the latter dimension did not cluster consistently with each other (ie, low item stability) and were not strongly associated with any particular dimension (ie, weak network loadings).

CONCLUSION

Exploratory graph analysis offers unique outputs, making it easy to assess the dimensional integrity of scales. Further research is warranted regarding the second dimension of the Perceived Stress Scale.

The Misinformation Susceptibility Test (MIST): A psychometrically validated measure of news veracity discernment

Interest in the psychology of misinformation has exploded in recent years. Despite ample research, to date there is no validated framework to measure misinformation susceptibility. Therefore, we introduce Verification done, a nuanced interpretation schema and assessment tool that simultaneously considers Veracity discernment, and its distinct, measurable abilities (real/fake news detection), and biases (distrust/naïvité-negative/positive judgment bias). We then conduct three studies with seven independent samples (Ntotal = 8504) to show how to develop, validate, and apply the Misinformation Susceptibility Test (MIST). In Study 1 (N = 409) we use a neural network language model to generate items, and use three psychometric methods-factor analysis, item response theory, and exploratory graph analysis-to create the MIST-20 (20 items; completion time < 2 minutes), the MIST-16 (16 items; < 2 minutes), and the MIST-8 (8 items; < 1 minute). In Study 2 (N = 7674) we confirm the internal and predictive validity of the MIST in five national quota samples (US, UK), across 2 years, from three different sampling platforms-Respondi, CloudResearch, and Prolific. We also explore the MIST's nomological net and generate age-, region-, and country-specific norm tables. In Study 3 (N = 421) we demonstrate how the MIST-in conjunction with Verification done-can provide novel insights on existing psychological interventions, thereby advancing theory development. Finally, we outline the versatile implementations of the MIST as a screening tool, covariate, and intervention evaluation framework. As all methods are transparently reported and detailed, this work will allow other researchers to create similar scales or adapt them for any population of interest.

Screening for post-traumatic stress disorder following childbirth using the Peritraumatic Distress Inventory

BACKGROUND

Post-traumatic stress disorder (PTSD) following traumatic childbirth may undermine maternal and infant health, but screening for maternal childbirth-related PTSD (CB-PTSD) remains lacking. Acute emotional distress in response to a traumatic experience strongly associates with PTSD. The Peritraumatic Distress Inventory (PDI) assesses acute distress in non-postpartum individuals, but its use to classify women likely to endorse CB-PTSD is unknown.

METHODS

3039 women provided information about their mental health and childbirth experience. They completed the PDI regarding their recent childbirth event, and a PTSD symptom screen to determine CB-PTSD. We employed Exploratory Graph Analysis and bootstrapping to reveal the PDI's factorial structure and optimal cutoff value for CB-PTSD classification.

RESULTS

Factor analysis revealed two strongly correlated stable factors based on a modified version of the PDI: (1) negative emotions and (2) bodily arousal and threat appraisal. A score of 15+ on the modified PDI produced high sensitivity and specificity: 88 % with a positive CB-PTSD screen in the first postpartum months and 93 % with a negative screen.

LIMITATIONS

In this cross-sectional study, the PDI was administered at different timepoints postpartum. Future work should examine the PDI's predictive utility for screening women as closely as possible to the time of childbirth, and establish clinical cutoffs in populations after complicated deliveries.

CONCLUSIONS

Brief self-report screening concerning a woman's emotional reactions to childbirth using our modified PDI tool can detect those likely to endorse CB-PTSD in the early postpartum. This may serve as the initial step of managing symptoms to ultimately prevent chronic manifestations.

Comparing community detection algorithms in psychometric networks: A Monte Carlo simulation

Identifying the correct number of factors in multivariate data is fundamental to psychological measurement. Factor analysis has a long tradition in the field, but it has been challenged recently by exploratory graph analysis (EGA), an approach based on network psychometrics. EGA first estimates a network and then applies the Walktrap community detection algorithm. Simulation studies have demonstrated that EGA has comparable or better accuracy for recovering the same number of communities as there are factors in the simulated data than factor analytic methods. Despite EGA's effectiveness, there has yet to be an investigation into whether other sparsity induction methods or community detection algorithms could achieve equivalent or better performance. Furthermore, unidimensional structures are fundamental to psychological measurement yet they have been sparsely studied in simulations using community detection algorithms. In the present study, we performed a Monte Carlo simulation using the zero-order correlation matrix, GLASSO, and two variants of a non-regularized partial correlation sparsity induction methods with several community detection algorithms. We examined the performance of these method-algorithm combinations in both continuous and polytomous data across a variety of conditions. The results indicate that the Fast-greedy, Louvain, and Walktrap algorithms paired with the GLASSO method were consistently among the most accurate and least-biased overall.

Improving the Walktrap Algorithm Using K-Means Clustering

The walktrap algorithm is one of the most popular community-detection methods in psychological research. Several simulation studies have shown that it is often effective at determining the correct number of communities and assigning items to their proper community. Nevertheless, it is important to recognize that the walktrap algorithm relies on hierarchical clustering because it was originally developed for networks much larger than those encountered in psychological research. In this paper, we present and demonstrate a computational alternative to the hierarchical algorithm that is conceptually easier to understand. More importantly, we show that better solutions to the sum-of-squares optimization problem that is heuristically tackled by hierarchical clustering in the walktrap algorithm can often be obtained using exact or approximate methods for K-means clustering. Three simulation studies and analyses of empirical networks were completed to assess the impact of better sum-of-squares solutions.

Cognitive restraint, uncontrolled eating, and emotional eating. The Italian version of the Three Factor Eating Questionnaire-Revised 18 (TFEQ-R-18): a three-step validation study

BACKGROUND

The Three Factor Eating Questionnaire-Revised 18 (TFEQ-R-18) is an extensively used questionnaire to measure three transdiagnostic features of eating behavior: cognitive restraint, uncontrolled eating, and emotional eating.

OBJECTIVE

This research aims to investigate the psychometric properties of the Italian version of the TFEQ-R-18 in three large community samples.

METHOD

Cross-sectional research designs were employed. In Study 1 (N = 537), an exploratory graph analysis (EGA) was used to examine item clustering within the TFEQ-R-18. In Study 2 (N = 645), a confirmatory factor analysis (CFA) was conducted to test its structural validity. In Study 3 (N = 346), a MANOVA was employed assessing mean differences across eating disorders (e.g., anorexia nervosa, bulimia nervosa, binge eating disorder).

RESULTS

In Study 1, the EGA accurately identified the three original dimensions of the TFEQ-R-18. Study 2 showed that the Italian TFEQ-R-18 has good fit indexes (CFI = 0.989, RMSEA = 0.064; 90% CI [0.058, 0.070], SRMR = 0.062), and possesses robust psychometric properties. Study 3 reveals distinct, statistically significant differences among eating disorders.

CONCLUSION

The TFEQ-R-18 proves to be a concise and precise tool for measuring transdiagnostic eating behaviors. Its applicability in the Italian context, supported by robust psychometric properties, suggests its utility for both research and clinical purposes. The findings affirm its potential to inform interventions aimed at enhancing psychological health.

LEVEL OF EVIDENCE

Level V, descriptive study.

A Novel, Network-Based Approach to Assessing Romantic-Relationship Quality

How should romantic-relationship quality be approached psychometrically? This is a complicated theoretical and methodological challenge that we begin to address through three studies. In Study 1a, we identified 25 distinct romantic-relationship categories among 754 items from 26 romantic-relationship-quality instruments with a weak Jaccard index (0.38), indicating that the scales' item content was extremely heterogeneous. Study 1b then demonstrated limited structure validity evidence in 43 scale-development-validation articles of 23 of these 26 instruments. Finally, Study 2 surveyed 587 French-speaking participants in a romantic relationship on romantic-relationship quality. Applying a network-based model, we identified four dimensions, three of which are central to relationship quality. The inferences were mostly limited to French-speaking, monogamous, heterosexual women. To resolve challenges detected in the literature, we recommend a multicountry qualitative approach, more diverse sampling, better definitions of romantic-relationship quality, and a dynamic-systems approach to measuring romantic-relationship quality.

Development and Validation of Technology-Facilitated Sexual Violence Perpetration and Victimization Scales Among Adults

Technology-facilitated sexual violence (TFSV) includes different forms of digital violence, such as online gender-based violence, online gender- and sexuality-based violence, digital sexual harassment, online sexual coercion, and nonconsensual pornography. The aim of this study was to design and validate a measure to assess the perpetration and victimization of each dimension of TFSV. The relationships between the different dimensions and differences by gender and sexual orientation were also analyzed. The participants were a sample of 2,486 adults (69% women) from Spain, aged between 16 and 79 (M = 25.95; DT = 9.809) years. The Technology-Facilitated Sexual Violence Scales were found to be valid and reliable instruments, supporting our recommendation for the use of these scales. Network analysis and solution-based exploratory factor analyses showed that the dimensions of online sexual coercion and nonconsensual pornography clustered together. All the perpetration variables were related to sexism. Finally, cis women and nonheterosexual people reported higher victimization scores overall compared to cis men and heterosexuals, respectively, while cis men reported higher perpetration scores overall than cis women.

Adolescent siblings of children with cancer: Resource-based profiles, normalization, and search for meaning in life

INTRODUCTION

Adolescent siblings of children with cancer jointly face the experience of having a brother or sister with cancer and being in the developmental period of adolescence themselves. Based on Hobfoll's conservation of resources theory, we aimed to identify profiles based on two distinct resources: sense of hope (personal resource) and perceived social support (social resource). Both have been found to be vital for optimal functioning during adolescence. Further, we examined differences in these profiles with regard to two distal outcomes: normalization (a coping strategy) and search for meaning in life (a commonly assumed adolescent developmental task).

METHODS

One hundred and eleven Israeli adolescent siblings (aged 13-17) completed self-report measures.

RESULTS

Two distinct resource-based profiles were identified: "high resources" and "low resources." Participants with "high resources" had a higher sense of hope and higher social support; were significantly more likely to live with married parents than with unmarried parents; had marginally fewer siblings; and scored higher on normalization and search for meaning in life than did participants with "low resources."

CONCLUSIONS

The study outcomes highlight the essential role of resources for this population. Such resources seem to be helpful for normalization, a coping strategy whose focus is on facilitating regular family routines, and for the siblings' search for meaning in life. Practitioners who work with families in the context of childhood cancer should aim to help these siblings obtain key resources, such as social support, and to actively pursue their goals.

New psychometric evidence from the Revised Mental Health Inventory (R-MHI-5) in Peruvian adolescents from a network psychometrics approach

BACKGROUND

Mental health is an aspect that has been relegated in recent years, prioritizing physical health care. However, there are more and more mental problems and disorders worldwide. In this context, adolescents are considered at risk for developing psychological difficulties due to the important transition stage they are going through. Given this, an adequate measurement of mental health in the adolescent population is necessary. This research aims to evaluate the internal structure and estimate the reliability of the R-MHI-5.

METHOD

The sample covered 662 adolescents (55.2% men and 44.7% women) aged 12 to 17 years (M = 14.5; SD = 1.6).

RESULTS

Exploratory graph analysis revealed a two-dimensional structure encompassing well-being and psychological distress. Furthermore, confirmatory factor analysis results indicated that a model with two related factors demonstrated superior fit indices (CFI = 0.99; TLI = 0.99; SRMR = 0.04; RMSEA = 0.101) in comparison to a one-dimensional model (CFI = 0.85; TLI = 0.71; SRMR = 0.23; RMSEA = 0.451). Additionally, adequate values were found in the reliability of the dimensions.

CONCLUSION

It is concluded that the R-MHI-5 is an instrument with robust psychometric evidence from the perspective of the EGA and CFA, providing adequate evidence of reliability and validity so that it can be used effectively in future research and prevention and intervention processes. Furthermore, our study is the first to provide psychometric evidence of the scale from a media approach in Peruvian adolescents.

Validation of the Levenson Self-Report Psychopathy (LSRP) scale in the non-institutionalized Lebanese population

BACKGROUND

Psychopathy has been described as "the first personality disorder to be recognized in psychiatry". It has three core features: affective, interpersonal, and behavioral. The Levenson Self-Report Psychopathy (LSRP) scale is used to screen for and measure psychopathy. Our study aims to validate the LSRP as a tool to measure psychopathy in the non-institutionalized Lebanese population.

METHODS

We surveyed Lebanese individuals residing in Lebanon and aged 18 through 65. It was a convenience sample collected via an online survey. 534 Lebanese participants completed the survey and were included in our analyses. Nearly 80% were female, 90% were college educated, and 60% were employed. We used exploratory graph analysis and confirmatory factor analyses to measure internal validity of the LSRP. We also used the HEXACO Personality Inventory-Revised (HEXACO-PI-R), the Subtypes of Antisocial Behavior Questionnaire (STAB), and the Short version of the Urgency, Premeditation (lack of), Perseverance (lack of), Sensation Seeking, Positive Urgency, Impulsive Behavior Scale (S-UPPS-P) to measure external validity of LSRP.

RESULTS

The exploratory graph analysis showed that the LSRP had a three-factor structure (Egocentric, Callous and Antisocial) in the Lebanese population. This three-factor structure (RMSEA = 0.05, CFI = 0.83, SRMR = 0.06) yielded a better fit than the two-factor, and three-factor Brinkley models. The LSRP was negatively correlated with the Honesty-Humility dimension of the HEXACO-PI-R and positively correlated with the STAB and S-UPPS-P subscales.

CONCLUSIONS

The LSRP scale is a valid measure of psychopathy in the Lebanese non-institutionalized population, adding to the currently limited literature addressing psychopathy in the Arab World.

Psychometric properties and measurement invariance of the short form of grit scale in Korean adolescents

This study aimed to identify the factor structure of the Korean version of the Short Grit Scale (Grit-S) and examine its cross-sectional and longitudinal measurement invariance (MI). Data from the Korean Children and Youth Panel Survey 2018 were analyzed, which included two cohorts, comprising 2,327 and 2,325 fourth-year elementary and first-year middle school students, respectively. It was found that the two-factor model fit the data well for the elementary and middle school samples. The results of the cross-sectional MI tests across genders indicated that the full threshold and loading invariance were also supported for the elementary school sample, and the partial threshold and loading invariance were supported for the middle school sample. The analyses of the longitudinal MI revealed that the partial threshold and loading invariance were supported for both samples. The reliability analysis revealed satisfactory McDonald's Omega values for both samples at each time point and moderate stability coefficients over time. Based on these findings, it was concluded that the Korean version of the Grit-S demonstrated satisfactory psychometric properties and exhibited MI across gender and time in Korean adolescents.

Modeling Sequential Dependencies in Progressive Matrices: An Auto-Regressive Item Response Theory (AR-IRT) Approach

Measurement models traditionally make the assumption that item responses are independent from one another, conditional upon the common factor. They typically explore for violations of this assumption using various methods, but rarely do they account for the possibility that an item predicts the next. Extending the development of auto-regressive models in the context of personality and judgment tests, we propose to extend binary item response models-using, as an example, the 2-parameter logistic (2PL) model-to include auto-regressive sequential dependencies. We motivate such models and illustrate them in the context of a publicly available progressive matrices dataset. We find an auto-regressive lag-1 2PL model to outperform a traditional 2PL model in fit as well as to provide more conservative discrimination parameters and standard errors. We conclude that sequential effects are likely overlooked in the context of cognitive ability testing in general and progressive matrices tests in particular. We discuss extensions, notably models with multiple lag effects and variable lag effects.

The dimensional structure of the Camouflaging Autistic Traits Questionnaire (CAT-Q) and predictors of camouflaging in a representative general population sample

OBJECTIVES

Some autistic people "camouflage" their differences by modeling neurotypical behaviors to survive in a neurotypical-dominant social world. It remains elusive whether camouflaging is unique to autism or if it entails similar experiences across human groups as part of ubiquitous impression management (IM). Here we examined camouflaging engagement and theoretical drivers in the general population, drawing on the transactional IM framework and contextualizing findings within both contemporary autism research and the past IM literature.

METHODS

A large representative U.S. general population sample (N = 972) completed this survey study. We combined exploratory item factor analysis and graph analysis to triangulate the dimensional structure of the Camouflaging Autistic Traits Questionnaire (CAT-Q) and examined its correspondence with prior autism-enriched psychometric findings. We then employed hierarchical regression and elastic-net regression to identify the predictors of camouflaging, including demographic (e.g., age, gender), neurodivergence (i.e., autistic and ADHD traits), socio-motivational, and cognitive factors.

RESULTS

We found a three-factor/dimensional structure of the CAT-Q in the general population, nearly identical to that found in previous autism-enriched samples. Significant socio-motivational predictors of camouflaging included greater social comparison, greater public self-consciousness, greater internalized social stigma, and greater social anxiety. These camouflaging drivers overlap with findings in recent autistic camouflaging studies and prior IM research.

CONCLUSIONS

The novel psychometric and socio-motivational evidence demonstrates camouflaging as a shared social coping experience across the general population, including autistic people. This continuity guides a clearer understanding of camouflaging and has key implications for autism scholars, clinicians, and the broader clinical intersecting with social psychology research. Future research areas are mapped to elucidate how camouflaging/IM manifests and functions within person-environment transactions across social-identity and clinical groups.

Stigma and knowledge about autism in Brazil: A psychometric and intervention study

LAY ABSTRACT

To promote the full inclusion of autistic people, we must change the knowledge and attitudes of non-autistic individuals. Unfortunately, access to autism information and support remains limited in Brazil, and stigma is also common. Brazilian researchers reached out to a researcher in the United States to co-develop Brazilian surveys to measure autism stigma and knowledge. Together, they made Brazilian versions of stigma and knowledge surveys which autistic people in the United States had helped make. They also adapted an online autism training used in other countries with help from three Brazilian autistic people and the mother of an autistic child. They used the new measures to see if the autism training improved autism stigma and knowledge among Brazilians. The surveys, called EARPA and ECAT in Brazil, were translated into Portuguese in a previous study. In the first study in this article, 532 Brazilians completed the stigma measure and 510 completed the knowledge measure. The researchers used exploratory graph analysis, which uses the connections between items in a survey to understand which items belong together. Seventy-nine Brazilians participated in the training. They were mostly white, female university students. The EGA showed that the stigma survey measured one big idea while the knowledge survey measured four ideas: diagnosis/cause; socio-communicative development; stimming and special interests; and autism in adulthood. Both scales are promising and may be helpful in future Brazilian and cross-cultural studies about autism. Participants reported more knowledge and less stigma after the autism training, which has been found in other countries too.

Understanding of Depressive Symptomatology across Major Depressive Disorder and Bipolar Disorder: A Network Analysis

Background and Objectives: Depressive symptoms are prominent in both major depressive disorder (MDD) and bipolar disorder (BD). However, comparative research on the network structure of depressive symptoms in these two diagnostic groups has been limited. This study aims to compare the network structure of depressive symptoms in MDD and BD, providing a deeper understanding of the depressive symptomatology of each disorder. Materials and Methods: The Zung Self-Rating Depressive Scale, a 20-item questionnaire, was administered to assess the depressive symptoms in individuals with MDD (n = 322) and BD (n = 516). A network analysis was conducted using exploratory graph analysis (EGA), and the network structure was analyzed using regularized partial correlation models. To validate the dimensionality of the Zung SDS, principal component analysis (PCA) was adopted. Centrality measures of the depressive symptoms within each group were assessed, followed by a network comparison test between the two groups. Results: In both diagnostic groups, the network analysis revealed four distinct categories, aligning closely with the PCA results. "Depressed affect" emerged as the most central symptom in both MDD and BD. Furthermore, non-core symptoms, "Personal devaluation" in MDD and "Confusion" in BD, displayed strong centrality. The network comparison test did not reveal significant differences in the network structure between MDD and BD. Conclusions: The absence of significant differences in the network structures between MDD and BD suggests that the underlying mechanisms of depressive symptoms may be similar across these disorders. The identified central symptoms, including "Depressed affect", in both disorders and the distinct non-core symptoms in each highlight the complexity of the depressive symptomatology. Future research should focus on validating these symptoms as therapeutic targets and incorporate various methodologies, including non-metric dimension reduction techniques or canonical analysis.

Reexploring Problematic Social Media Use and Its Relationship with Adolescent Mental Health. Findings from the "LifeOnSoMe"-Study

Purpose

Previous approaches used to assess problematic social media use risk inflating prevalence numbers and classifying unproblematic social media use as problematic. The main aim of this study was to take an exploratory view as to how different types of activities, experiences, and motivations on social media are associated with problematic mental health outcomes in adolescents.

Patients and Methods

This study is based on a cross-sectional survey of 2023 adolescents (mean age 17.4 years (SD 0.9), 44.4% males) from the year 2020. Exploratory graph analysis and exploratory factor analysis were performed on 28 pre-selected items assessing adolescents' use of social media, to identify underlying potentially problematic factors associated with social media use. Sets of gender-adjusted multiple linear regression analyses were performed to assess the degree to which social media factors predicted depression, anxiety, well-being, and time spent on social media.

Results

Three factors were identified: 1) "subjective overuse", 2) "social obligations", and 3) "source of concern". All three factors showed significant positive associations with mental health problems. The factor "source of concern", which identifies feelings of being overwhelmed and concerned over social media use, had the strongest association to mental health problems and simultaneously the weakest association to time spent on social media.

Conclusion

Three identified factors measuring problematic social media use showed positive associations with mental health problems. This lends support to the notion that problematic social media use is a multidimensional phenomenon and demonstrates the need to move beyond addiction criteria when assessing problematic social media use.

Network structure of symptomatology of adult attention-deficit hyperactivity disorder in patients with mood disorders

Patients with mood disorders commonly manifest comorbid psychiatric disorders, including attention-deficit/hyperactivity disorder (ADHD). However, few studies have evaluated ADHD symptoms in this population. The current study aimed to explore the network structure of ADHD symptomology and identify central symptoms in patients with mood disorders. The Korean version of the Adult ADHD Self-Report Scale was used to assess the overall ADHD symptoms in 1,086 individuals diagnosed with mood disorders (major depressive disorder [n = 373], bipolar I disorder [n = 314], and bipolar II disorder [n = 399]). We used exploratory graph analysis to detect the number of communities, and the network structure was analyzed using regularized partial correlation models. We identified the central ADHD symptom using centrality indices. Network comparison tests were conducted with different subgroups of patients with mood disorders, including three mood diagnosis groups, between the patients who met the diagnostic criteria for ADHD [ADHD-suspected, n = 259] in their self-report and the others [ADHD-non-suspected, n = 827], and groups with high [n = 503] versus low [n = 252] levels of depressive state. The network analysis detected four communities: disorganization, agitation/restlessness, hyperactivity/impulsivity, and inattention. The centrality indices indicated that "feeling restless" was the core ADHD symptom. The result was replicated in the subgroup analyses within our clinically diverse population of mood disorders, encompassing three presentations: Patients with suspected ADHD, patients without suspected ADHD, and patients with a high depressive state. Our findings reveal that "feeling restless" is the central ADHD symptom. The treatment intervention for "feeling restless" may thus play a pivotal role in tackling ADHD symptoms in adult patients with mood disorders.