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Ribeiro Santiago PH, Soares GH, Quintero A, Jamieson L. Comparing the Clique Percolation algorithm to other overlapping community detection algorithms in psychological networks: A Monte Carlo simulation study. Behav Res Methods 2024; 56:7219-7240. [PMID: 38693441 PMCID: PMC11362237 DOI: 10.3758/s13428-024-02415-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/27/2024] [Indexed: 05/03/2024]
Abstract
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.
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Affiliation(s)
| | - Gustavo Hermes Soares
- Adelaide Dental School, The University of Adelaide, Level 4, 50 Rundle Mall, Rundle Mall Plaza, Adelaide, Australia
| | - Adrian Quintero
- ICFES - Colombian Institute for Educational Evaluation, Bogotá, Colombia
| | - Lisa Jamieson
- Adelaide Dental School, The University of Adelaide, Level 4, 50 Rundle Mall, Rundle Mall Plaza, Adelaide, Australia
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2
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Sun X, Liang D, Wu Y. 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. J Pers Assess 2024:1-12. [PMID: 39231311 DOI: 10.1080/00223891.2024.2397819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 07/25/2024] [Accepted: 08/11/2024] [Indexed: 09/06/2024]
Abstract
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.
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Affiliation(s)
- Xiaoqi Sun
- Institute of Interdisciplinary Studies, Hunan Normal University
- Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University
- Department of Psychology, Faculty of Educational Sciences, Hunan Normal University
| | - Dan Liang
- Department of Psychology, Faculty of Educational Sciences, Hunan Normal University
| | - Yunxia Wu
- Department of Psychology, Faculty of Educational Sciences, Hunan Normal University
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3
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Garcia-Pardina A, Abad FJ, Christensen AP, Golino H, Garrido LE. Dimensionality assessment in the presence of wording effects: A network psychometric and factorial approach. Behav Res Methods 2024; 56:6179-6197. [PMID: 38379114 DOI: 10.3758/s13428-024-02348-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/22/2024] [Indexed: 02/22/2024]
Abstract
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.
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Affiliation(s)
| | - Francisco J Abad
- Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, Madrid, Spain
| | | | - Hudson Golino
- Department of Psychology, University of Virginia, Charlottesville, VA, USA
| | - Luis Eduardo Garrido
- School of Psychology, Pontificia Universidad Católica Madre y Maestra, Abraham Lincoln esq. Simón Bolívar, Santo Domingo, Dominican Republic.
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Polner B, Jamalabadi H, van Kemenade BM, Billino J, Kircher T, Straube B. Speech-Gesture Matching and Schizotypal Traits: A Network Approach. Schizophr Bull 2024:sbae134. [PMID: 39046822 DOI: 10.1093/schbul/sbae134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/27/2024]
Abstract
BACKGROUND AND HYPOTHESIS Impaired speech-gesture matching has repeatedly been shown in patients with schizophrenia spectrum disorders. Here, we tested the hypothesis that schizotypal traits in the general population are related to reduced speech-gesture matching performance and reduced self-reports about gesture perception. We further explored the relationships between facets of schizotypy and gesture processing in a network model. STUDY DESIGN Participants (1094 mainly healthy adults) were presented with concrete or abstract sentences accompanied with videos showing related or unrelated gestures. For each video, participants evaluated the alignment between speech and gesture. They also completed self-rating scales about the perception and production of gestures (Brief Assessment of Gesture scale) and schizotypal traits (Schizotypal Personality Questionnaire-Brief 22-item version). We analyzed bivariate associations and estimated a non-regularized partial Spearman correlation network. We characterized the network by analyzing bridge centrality and controllability metrics of nodes. STUDY RESULTS We found a negative relationship between both concrete and abstract gesture-speech matching performance and overall schizotypy. In the network, disorganization had the highest average controllability and it was negatively related to abstract speech-gesture matching. Bridge centralities indicated that self-reported production of gestures to enhance communication in social interactions connects self-reported gesture perception, schizotypal traits, and gesture processing task performance. CONCLUSION The association between impaired abstract speech-gesture matching and disorganization supports a continuum between schizophrenia and schizotypy. Using gestures to facilitate communication connects subjective and objective aspects of gesture processing and schizotypal traits. Future interventional studies in patients should test the potential causal pathways implied by this network model.
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Affiliation(s)
- Bertalan Polner
- Institute of Psychology, ELTE, Eötvös Loránd University, Budapest, Hungary
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Bianca M van Kemenade
- Center for Psychiatry, Justus Liebig University Giessen, Giessen, Germany
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Marburg, Germany, and Justus Liebig University Giessen, Giessen, Germany
| | - Jutta Billino
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Marburg, Germany, and Justus Liebig University Giessen, Giessen, Germany
- Experimental Psychology, Lifespan Neuropsychology, Justus Liebig University Giessen, Giessen, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Marburg, Germany, and Justus Liebig University Giessen, Giessen, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Marburg, Germany, and Justus Liebig University Giessen, Giessen, Germany
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Caycho-Rodríguez T, Travezaño-Cabrera A, Ventura-León J, Vilca LW, Baños-Chaparro J, Yupanqui-Lorenzo DE, Valencia PD, Torales J, Carbajal-León C, Lobos-Rivera ME, Reyes-Bossio M, Barrios I, Jaimes-Alvarez F, Lee SA. New Psychometric Evidence of the Grief Impairment Scale (GIS) in People Who Have Experienced the Death of a Loved One From a Network Psychometric Approach in Two Latin American Countries. OMEGA-JOURNAL OF DEATH AND DYING 2024:302228241256828. [PMID: 38820211 DOI: 10.1177/00302228241256828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2024]
Abstract
This study aimed to evaluate the psychometric properties of the Grief Impairment Scale (GIS) using a network psychometric model. A total of 1048 individuals from Peru and El Salvador participated. A network psychometric model was used to determine internal structure, reliability, and cross-country invariance. The results indicate that the GIS items were grouped into a single network structure through Exploratory Graph Analysis. Reliability was estimated by structural consistency, and it was found that when replicating the network structure within an empirical dimension, a single network structure was consistently obtained, and all items remained stable. Furthermore, the network structure was invariant, thus functioning similarly across the different country groups. In conclusion, the GIS presented solid psychometric evidence of validity based on its internal structure, reliability, and cross-country invariance. Therefore, the GIS is a psychometrically sound measure of functional impairment symptoms due to grief for Peruvian and Salvadoran individuals.
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Affiliation(s)
| | | | - José Ventura-León
- Facultad de Ciencias de la Salud, Universidad Privada del Norte, Lima, Perú
| | - Lindsey W Vilca
- South American Center for Education and Research in Public Health, Universidad Norbert Wiener, Lima, Perú
| | | | | | - Pablo D Valencia
- Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de Mexico, Tlanepantla de Baz, Mexico
| | - Julio Torales
- Cátedra de Psicología Médica, Facultad de Ciencias Médicas, Universidad Nacional de Asunción, San Lorenzo, Paraguay
- Instituto Regional de Investigación en Salud, Universidad Nacional de Caaguazú, Coronel Oviedo, Paraguay
- Facultad de Ciencias Médicas, Universidad Sudamericana, Pedro Juan Caballero, Paraguay
| | - Carlos Carbajal-León
- Escuela de Psicología, Facultad de Ciencias de la Comunicación, Turismo y Psicología, Universidad de San Martín de Porres, Lima, Perú
| | | | - Mario Reyes-Bossio
- Facultad de Psicología, Universidad Peruana de Ciencias Aplicadas, Lima, Peru
| | - Iván Barrios
- Instituto Regional de Investigación en Salud, Universidad Nacional de Caaguazú, Coronel Oviedo, Paraguay
- Cátedra de Bioestadística, Facultad de Ciencias Médicas, Santa Rosa del Aguaray Campus, Universidad Nacional de Asunción, Santa Rosa del Aguaray, Paraguay
| | | | - Sherman A Lee
- Department of Psychology, Christopher Newport University, Christopher Newport University, Newport News, VI, USA
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Wang X, Yang M, Ren L, Wang Q, Liang S, Li Y, Li Y, Zhan Q, Huang S, Xie K, Liu J, Li X, Wu S. Burnout and depression in college students. Psychiatry Res 2024; 335:115828. [PMID: 38518519 DOI: 10.1016/j.psychres.2024.115828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 02/17/2024] [Accepted: 02/25/2024] [Indexed: 03/24/2024]
Abstract
Research on burnout has garnered considerable attention since its inception. However, the ongoing debate persists regarding the conceptual model of burnout and its relationship with depression. Thus, we conducted a network analysis to determine the dimensional structure of burnout and the burnout-depression overlap. The Maslach Burnout Inventory-Student Survey and Patient Health Questionnaire-9 were used to measure burnout and depression among 1096 college students. We constructed networks for burnout, depression, and a burnout-depression co-occurrence network. The results showed that cynicism symptom was the most central to the burnout network. In the co-occurrence network, depressive symptoms ("anhedonia", "fatigue") and burnout symptom ("doubting the significance of studies") were the most significant in causing burnout-depression comorbidity. Community detection revealed three communities within burnout symptoms, aligning closely with their three dimensions identified through factor analysis. Additionally, there was no overlap between burnout and depression. In conclusion, our findings support a multidimensional structure of burnout, affirming it as a distinct concept separate from depression. Cynicism, rather than exhaustion, plays the most important role in burnout and the burnout-depression comorbidity.
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Affiliation(s)
- Xianyang Wang
- Department of Military Medical Psychology, Air Force Medical University, 710032, Xi'an, Shaanxi, China
| | - Mengyuan Yang
- Department of Military Medical Psychology, Air Force Medical University, 710032, Xi'an, Shaanxi, China
| | - Lei Ren
- Military Psychology Section, Logistics University of PAP, 300309, Tianjin, China; Military Mental Health Services & Research Center, 300309, Tianjin, China
| | - Qingyi Wang
- School of Basic Medicine, Air Force Medical University, 710032, Xi'an, Shaanxi, China
| | - Shuyi Liang
- Department of Military Medical Psychology, Air Force Medical University, 710032, Xi'an, Shaanxi, China
| | - Yahong Li
- Air Force Hospital of Central Theater Command, 037006, Datong, Shanxi, China
| | - Yu Li
- Academic Affair Office, Air Force Medical University, 710032, Xi'an, Shaanxi, China
| | - Qingchen Zhan
- Department of Military Medical Psychology, Air Force Medical University, 710032, Xi'an, Shaanxi, China
| | - Shen Huang
- Xi'an Research Institute of High Technology, 710000, Xi'an, Shaanxi, China
| | - Kangning Xie
- School of Military Biomedical Engineering, Air Force Medical University, 710032, Xi'an, Shaanxi, China
| | - Jianjun Liu
- Department of Outpatient, 986 Hospital of Air Force, 710054, Xi'an, Shaanxi, China
| | - Xinhong Li
- Department of General Practice, Second Affiliated Hospital of Air Force Medical University, 710038, Xi'an, Shaanxi, China.
| | - Shengjun Wu
- Department of Military Medical Psychology, Air Force Medical University, 710032, Xi'an, Shaanxi, China.
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Grunden N, Phillips NA. A network approach to subjective cognitive decline: Exploring multivariate relationships in neuropsychological test performance across Alzheimer's disease risk states. Cortex 2024; 173:313-332. [PMID: 38458017 DOI: 10.1016/j.cortex.2024.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 11/17/2023] [Accepted: 02/02/2024] [Indexed: 03/10/2024]
Abstract
Subjective cognitive decline (SCD) is characterized by subjective concerns of cognitive change despite test performance within normal range. Although those with SCD are at higher risk for developing further cognitive decline, we still lack methods using objective cognitive measures that reliably distinguish SCD from cognitively normal aging at the group level. Network analysis may help to address this by modeling cognitive performance as a web of intertwined cognitive abilities, providing insight into the multivariate associations determining cognitive status. Following previous network studies of mild cognitive impairment (MCI) and Alzheimer's dementia (AD), the current study centered upon the novel visualization and analysis of the SCD cognitive network compared to cognitively normal (CN) older adult, MCI, and AD group networks. Cross-sectional neuropsychological data from CIMA-Q and COMPASS-ND cohorts were used to construct Gaussian graphical models for CN (n = 122), SCD (n = 207), MCI (n = 210), and AD (n = 79) groups. Group networks were explored in terms of global network structure, prominent edge weights, and strength centrality indices. CN and SCD group networks were contrasted using the Network Comparison Test. Results indicate that CN and SCD groups did not differ in univariate cognitive performance or global network structure. However, measures of strength centrality, principally in executive functioning and processing speed, showed a CN-SCD-MCI gradient where subtle differences within the SCD network suggest that SCD is an intermediary between CN and MCI stages. Additional results may indicate a distinctiveness of network structure in AD, a reversal in network influence between age and general cognitive status as clinical impairment increases, and potential evidence for cognitive reserve. Together, these results provide evidence that network-specific metrics are sensitive to cognitive performance changes across the dementia risk spectrum and can help to objectively distinguish SCD group cognitive performance from that of the CN group.
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Affiliation(s)
- Nicholas Grunden
- Department of Psychology, Concordia University, Montréal, Canada; Canadian Consortium on Neurodegeneration in Aging (CCNA), Canada; Centre for Research on Brain, Language and Music (CRBLM), Montréal, Canada; Centre for Research in Human Development (CRDH), Montréal, Canada
| | - Natalie A Phillips
- Department of Psychology, Concordia University, Montréal, Canada; Canadian Consortium on Neurodegeneration in Aging (CCNA), Canada; Centre for Research on Brain, Language and Music (CRBLM), Montréal, Canada; Centre for Research in Human Development (CRDH), Montréal, Canada.
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8
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Stefana A, Fusar-Poli P, Vieta E, Gelso CJ, Youngstrom EA. Development and validation of an 8-item version of the Real Relationship Inventory-Client form. Psychother Res 2024:1-17. [PMID: 38497741 DOI: 10.1080/10503307.2024.2320331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 02/08/2024] [Indexed: 03/19/2024] Open
Abstract
OBJECTIVE To develop and validate a very brief version of the 24-item Real Relationship Inventory-Client (RRI-C) form. METHOD Two independent samples of individual psychotherapy patients (Nsample1 = 700, Nsample2 = 434) completed the RRI-C along with other measures. Psychometric scale shortening involved exploratory factor analysis, item response theory analysis, confirmatory factor analysis (CFA), and multigroup CFA. Reliability and convergent and discriminant validity of the scale and subscales were also assessed. RESULTS The 8-item RRI-C (RRI-C-SF) preserves the two-factor structure: Genuineness (k = 4, α = .86) and Realism (k = 4, α = .87), which were correlated at r = .74. CFA provided the following fit indices for the bifactor model: X2/df = 2.16, CFI = .99, TLI = .96, RMSEA = .07, and SRMR = .03. Multigroup CFA showed that the RRI-C-SF was invariant across in-person and remote session formats. The RRI-C-SF demonstrated high reliability (α = .91); high correlation with the full-length scale (r = .96); and excellent convergent and discriminant validity with measures of other elements of the therapeutic relationship, personality characteristics, current mental health state, and demographic-clinical variables. Clinical change benchmarks were calculated to serve as valuable tools for both research and clinical practice. CONCLUSION The RRI-C-SF is a reliable measure that can be used for both research and clinical purposes. It enables a nuanced assessment of the genuineness and the realism dimensions of the real relationship.
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Affiliation(s)
- Alberto Stefana
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Paolo Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Hospital Clinic, IDIBAPS, CIBERSAM, University of Barcelona, Barcelona, Spain
| | - Charles J Gelso
- Department of Psychology, University of Maryland, College Park, MA, USA
| | - Eric A Youngstrom
- Institute for Mental and Behavioral Health Research, Nationwide Children's Hospital and Department of Psychiatry, The Ohio State University, Columbus, OH, USA
- Helping Give Away Psychological Science, 501c3
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Brusco M, Steinley D, Watts AL. Improving the Walktrap Algorithm Using K-Means Clustering. MULTIVARIATE BEHAVIORAL RESEARCH 2024; 59:266-288. [PMID: 38361218 PMCID: PMC11014777 DOI: 10.1080/00273171.2023.2254767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
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.
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Kenett YN, Cardillo ER, Christensen AP, Chatterjee A. Aesthetic emotions are affected by context: a psychometric network analysis. Sci Rep 2023; 13:20985. [PMID: 38017110 PMCID: PMC10684561 DOI: 10.1038/s41598-023-48219-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 11/22/2023] [Indexed: 11/30/2023] Open
Abstract
Aesthetic emotions are defined as emotions arising when a person evaluates a stimulus for its aesthetic appeal. Whether these emotions are unique to aesthetic activities is debated. We address this debate by examining if recollections of different types of engaging activities entail different emotional profiles. A large sample of participants were asked to recall engaging aesthetic (N = 167), non-aesthetic (N = 160), or consumer (N = 172) activities. They rated the extent to which 75 candidate aesthetic emotions were evoked by these activities. We applied a computational psychometric network approach to represent and compare the space of these emotions across the three conditions. At the behavioral level, recalled aesthetic activities were rated as the least vivid but most intense compared to the two other conditions. At the network level, we found several quantitative differences across the three conditions, related to the typology, community (clusters) and core nodes (emotions) of these networks. Our results suggest that aesthetic and non-aesthetic activities evoke emotional spaces differently. Thus, we propose that aesthetic emotions are distributed differently in a multidimensional aesthetic space than for other engaging activities. Our results highlight the context-specificity of aesthetic emotions.
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Affiliation(s)
- Yoed N Kenett
- Faculty of Data and Decision Sciences, Technion - Israel Institute of Technology, 3200003, Haifa, Israel.
| | - Eileen R Cardillo
- Penn Center for Neuroaesthetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexander P Christensen
- Department of Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN, USA
| | - Anjan Chatterjee
- Penn Center for Neuroaesthetics, University of Pennsylvania, Philadelphia, PA, USA
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