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1.
Perspect Psychol Sci ; : 17456916211014183, 2021 Nov 30.
Artigo em Inglês | MEDLINE | ID: mdl-34846952

RESUMO

When it originated in the late 19th century, psychometrics was a field with both a scientific and a social mission: Psychometrics provided new methods for research into individual differences and at the same time considered these methods a means of creating a new social order. In contrast, contemporary psychometrics-because of its highly technical nature and its limited involvement in substantive psychological research-has created the impression of being a value-free discipline. In this article, we develop a contrasting characterization of contemporary psychometrics as a value-laden discipline. We expose four such values: that individual differences are quantitative (rather than qualitative), that measurement should be objective in a specific sense, that test items should be fair, and that the utility of a model is more important than its truth. Our goal is not to criticize psychometrics for supporting these values but rather to bring them into the open and to show that they are not inevitable and are in need of systematic evaluation.

2.
Methods ; 2021 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-34793976

RESUMO

Identifying the different influences of symptoms in dynamic psychopathology models may hold promise for increasing treatment efficacy in clinical applications. Dynamic psychopathology models study the behavioral patterns of symptom networks, where symptoms mutually enforce each other. Interventions could be tailored to specific symptoms that are most effective at lowering symptom activity or that hinder the further development of psychopathology. Simulating interventions in psychopathology network models fits in a novel tradition where symptom-specific perturbations are used as in silico interventions. Here, we present the NodeIdentifyR algorithm (NIRA) to identify the projected most efficient, symptom-specific intervention target in a network model (i.e., the Ising model). We implemented NIRA in a freely available R package. The technique studies the projected effects of symptom-specific interventions by simulating data while symptom parameters (i.e., thresholds) are systematically altered. The projected effect of these interventions is defined in terms of the expected change in overall symptom activity across simulations. With this algorithm, it is possible to study (1) whether symptoms differ in their projected influence on the behavior of the symptom network and, if so, (2) which symptom has the largest projected effect in lowering or increasing overall symptom activation. As an illustration, we apply the algorithm to an empirical dataset containing Post-Traumatic Stress Disorder symptom assessments of participants who experienced the Wenchuan earthquake in 2008. The most important limitations of the method are discussed, as well as recommendations for future research, such as shifting towards modeling individual processes to validate these types of simulation-based intervention methods.

3.
Psychol Methods ; 2021 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-34735175

RESUMO

Over the past decade, there has been a surge of empirical research investigating mental disorders as complex systems. In this article, we investigate how to best make use of this growing body of empirical research and move the field toward its fundamental aims of explaining, predicting, and controlling psychopathology. We first review the contemporary philosophy of science literature on scientific theories and argue that fully achieving the aims of explanation, prediction, and control requires that we construct formal theories of mental disorders: theories expressed in the language of mathematics or a computational programming language. We then investigate three routes by which one can use empirical findings (i.e., data models) to construct formal theories: (a) using data models themselves as formal theories, (b) using data models to infer formal theories, and (c) comparing empirical data models to theory-implied data models in order to evaluate and refine an existing formal theory. We argue that the third approach is the most promising path forward. We conclude by introducing the abductive formal theory construction (AFTC) framework, informed by both our review of philosophy of science and our methodological investigation. We argue that this approach provides a clear and promising way forward for using empirical research to inform the generation, development, and testing of formal theories both in the domain of psychopathology and in the broader field of psychological science. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

4.
Sci Rep ; 11(1): 19463, 2021 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-34593931

RESUMO

In the wake of the COVID-19 pandemic, physical distancing behavior turned out to be key to mitigating the virus spread. Therefore, it is crucial that we understand how we can successfully alter our behavior and promote physical distancing. We present a framework to systematically assess the effectiveness of behavioral interventions to stimulate physical distancing. In addition, we demonstrate the feasibility of this framework in a large-scale natural experiment (N = 639) conducted during an art fair. In an experimental design, we varied interventions to evaluate the effect of face masks, walking directions, and immediate feedback on visitors' contacts. We represent visitors as nodes, and their contacts as links in a contact network. Subsequently, we used network modelling to test for differences in these contact networks. We find no evidence that face masks influence physical distancing, while unidirectional walking directions and buzzer feedback do positively impact physical distancing. This study offers a feasible way to optimize physical distancing interventions through scientific research. As such, the presented framework provides society with the means to directly evaluate interventions, so that policy can be based on evidence rather than conjecture.


Assuntos
Comportamento , COVID-19/prevenção & controle , COVID-19/psicologia , Distanciamento Físico , Adulto , Retroalimentação , Feminino , Humanos , Masculino , Máscaras , Pessoa de Meia-Idade , Modelos Teóricos , Política Pública , Inquéritos e Questionários , Adulto Jovem
5.
Lancet Psychiatry ; 8(11): 991-1000, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34627532

RESUMO

Urbanisation and common mental disorders (CMDs; ie, depressive, anxiety, and substance use disorders) are increasing worldwide. In this Review, we discuss how urbanicity and risk of CMDs relate to each other and call for a complexity science approach to advance understanding of this interrelationship. We did an ecological analysis using data on urbanicity and CMD burden in 191 countries. We found a positive, non-linear relationship with a higher CMD prevalence in more urbanised countries, particularly for anxiety disorders. We also did a review of meta-analytic studies on the association between urban factors and CMD risk. We identified factors relating to the ambient, physical, and social urban environment and showed differences per diagnosis of CMDs. We argue that factors in the urban environment are likely to operate as a complex system and interact with each other and with individual city inhabitants (including their psychological and neurobiological characteristics) to shape mental health in an urban context. These interactions operate on various timescales and show feedback loop mechanisms, rendering system behaviour characterised by non-linearity that is hard to predict over time. We present a conceptual framework for future urban mental health research that uses a complexity science approach. We conclude by discussing how complexity science methodology (eg, network analyses, system-dynamic modelling, and agent-based modelling) could enable identification of actionable targets for treatment and policy, aimed at decreasing CMD burdens in an urban context.


Assuntos
COVID-19/psicologia , Transtornos Mentais/epidemiologia , Saúde Mental/normas , Saúde da População Urbana/normas , Adulto , Transtornos de Ansiedade/diagnóstico , Transtornos de Ansiedade/epidemiologia , COVID-19/diagnóstico , COVID-19/epidemiologia , COVID-19/virologia , Transtorno Depressivo/diagnóstico , Transtorno Depressivo/epidemiologia , Ecossistema , Feminino , Indicadores Básicos de Saúde , Humanos , Masculino , Transtornos Mentais/diagnóstico , Transtornos Mentais/psicologia , Transtornos Mentais/terapia , Saúde Mental/tendências , Metanálise como Assunto , Prevalência , SARS-CoV-2/genética , Análise de Rede Social , Transtornos Relacionados ao Uso de Substâncias/diagnóstico , Transtornos Relacionados ao Uso de Substâncias/epidemiologia , Análise de Sistemas , Saúde da População Urbana/tendências
6.
Neurosci Biobehav Rev ; 130: 81-90, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34324918

RESUMO

In recent years, there has been an increase in applications of network science in many different fields. In clinical neuroscience and psychopathology, the developments and applications of network science have occurred mostly simultaneously, but without much collaboration between the two fields. The promise of integrating these network applications lies in a united framework to tackle one of the fundamental questions of our time: how to understand the link between brain and behavior. In the current overview, we bridge this gap by introducing conventions in both fields, highlighting similarities, and creating a common language that enables the exploitation of synergies. We provide research examples in autism research, as it accurately represents research lines in both network neuroscience and psychological networks. We integrate brain and behavior not only semantically, but also practically, by showcasing three methodological avenues that allow to combine networks of brain and behavioral data. As such, the current paper offers a stepping stone to further develop multi-modal networks and to integrate brain and behavior.


Assuntos
Encéfalo , Neurociências , Humanos
7.
PLoS One ; 16(7): e0254496, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34329316

RESUMO

OBJECTIVE: Within the network approach to psychopathology, cross-sectional partial correlation networks have frequently been used to estimate relationships between symptoms. The resulting relationships have been used to generate hypotheses about causal links between symptoms. In order to justify such exploratory use of partial correlation networks, one needs to assume that the between-subjects relationships in the network approximate systematic within-subjects relationships, which are in turn the results of some within-subjects causal mechanism. If this assumption holds, relationships in the network should be mirrored by relationships between symptom changes; if links in networks approximate systematic within-subject relationships, change in a symptom should relate to change in connected symptoms. METHOD: To investigate this implication, we combined longitudinal data on the Borderline Personality Disorder Severity Index from four samples of borderline personality disorder patients (N = 683). We related parameters from baseline partial correlation networks of symptoms to relationships between change trajectories of these symptoms. RESULTS: Across multiple levels of analysis, our results showed that parameters from baseline partial correlation networks are strongly predictive of relationships between change trajectories. CONCLUSIONS: By confirming its implication, our results support the idea that cross-sectional partial correlation networks hold a relevant amount of information about systematic within-subjects relationships and thereby have exploratory value to generate hypotheses about the causal dynamics between symptoms.


Assuntos
Transtorno da Personalidade Borderline/psicologia , Adolescente , Adulto , Estudos Transversais , Feminino , Humanos , Masculino , Psicopatologia
8.
Schizophr Bull ; 2021 Jul 27.
Artigo em Inglês | MEDLINE | ID: mdl-34313767

RESUMO

Psychotic and autistic symptoms are related to social functioning in individuals with psychotic disorders (PD). The present study used a network approach to (1) evaluate the interactions between autistic symptoms, psychotic symptoms, and social functioning, and (2) investigate whether relations are similar in individuals with and without PD. We estimated an undirected network model in a sample of 504 PD, 572 familial risk for psychosis (FR), and 337 typical comparisons (TC), with a mean age of 34.9 years. Symptoms were assessed with the Autism Spectrum Quotient (AQ; 5 nodes) and the Community Assessment of Psychic Experiences (CAPE; 9 nodes). Social functioning was measured with the Social Functioning Scale (SFS; 7 nodes). We identified statistically significant differences between the FR and PD samples in global strength (P < .001) and network structure (P < .001). Our results show autistic symptoms (social interaction nodes) are negatively and more closely related to social functioning (withdrawal, interpersonal behavior) than psychotic symptoms. More and stronger connections between nodes were observed for the PD network than for FR and TC networks, while the latter 2 were similar in density (P = .11) and network structure (P = .19). The most central items in strength for PD were bizarre experiences, social skills, and paranoia. In conclusion, specific autistic symptoms are negatively associated with social functioning across the psychosis spectrum, but in the PD network symptoms may reinforce each other more easily. These findings emphasize the need for increased clinical awareness of comorbid autistic symptoms in psychotic individuals.

9.
Sci Data ; 8(1): 179, 2021 07 15.
Artigo em Inglês | MEDLINE | ID: mdl-34267219

RESUMO

In the absence of a vaccine, social distancing behaviour is pivotal to mitigate COVID-19 virus spread. In this large-scale behavioural experiment, we gathered data during Smart Distance Lab: The Art Fair (n = 839) between August 28 and 30, 2020 in Amsterdam, the Netherlands. We varied walking directions (bidirectional, unidirectional, and no directions) and supplementary interventions (face mask and buzzer to alert visitors of 1.5 metres distance). We captured visitors' movements using cameras, registered their contacts (defined as within 1.5 metres) using wearable sensors, and assessed their attitudes toward COVID-19 as well as their experience during the event using questionnaires. We also registered environmental measures (e.g., humidity). In this paper, we describe this unprecedented, multi-modal experimental data set on social distancing, including psychological, behavioural, and environmental measures. The data set is available on figshare and in a MySQL database. It can be used to gain insight into (attitudes toward) behavioural interventions promoting social distancing, to calibrate pedestrian models, and to inform new studies on behavioural interventions.

10.
Front Psychiatry ; 12: 640658, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33815173

RESUMO

Inspired by modeling approaches from the ecosystems literature, in this paper, we expand the network approach to psychopathology with risk and protective factors to arrive at an integrated analysis of resilience. We take a complexity approach to investigate the multifactorial nature of resilience and present a system in which a network of interacting psychiatric symptoms is targeted by risk and protective factors. These risk and protective factors influence symptom development patterns and thereby increase or decrease the probability that the symptom network is pulled toward a healthy or disorder state. In this way, risk and protective factors influence the resilience of the network. We take a step forward in formalizing the proposed system by implementing it in a statistical model and translating different influences from risk and protective factors to specific targets on the node and edge parameters of the symptom network. To analyze the behavior of the system under different targets, we present two novel network resilience metrics: Expected Symptom Activity (ESA, which indicates how many symptoms are active or inactive) and Symptom Activity Stability (SAS, which indicates how stable the symptom activity patterns are). These metrics follow standard practices in the resilience literature, combined with ideas from ecology and physics, and characterize resilience in terms of the stability of the system's healthy state. By discussing the advantages and limitations of our proposed system and metrics, we provide concrete suggestions for the further development of a comprehensive modeling approach to study the complex relationship between risk and protective factors and resilience.

11.
Psychometrika ; 86(1): 327-343, 2021 03.
Artigo em Inglês | MEDLINE | ID: mdl-33770319

RESUMO

In this article, we present the findings of an oral history project on the past, present, and future of psychometrics, as obtained through structured interviews with twenty past Psychometric Society presidents. Perspectives on how psychometrics should be practiced vary strongly. Some presidents are psychology-oriented, whereas others have a more mathematical or statistical approach. The originally strong relationship between psychometrics and psychology has weakened, and contemporary psychometrics has become a diverse and multifaceted discipline. The presidents are confident psychometrics will continue to be relevant but believe psychometrics needs to become better at selling its strong points to relevant research areas. We recommend for psychometrics to cherish its plurality and make its goals and priorities explicit.


Assuntos
Psicometria
12.
BMC Psychiatry ; 21(1): 119, 2021 02 27.
Artigo em Inglês | MEDLINE | ID: mdl-33639891

RESUMO

BACKGROUND: Understanding complex associations between psychopathology and chronic illness is instrumental in facilitating both research and treatment progress. The current study is the first and only network-based study to provide such an encompassing view of unique associations between a multitude of mental and physical health-related domains. METHODS: The current analyses were based on the Singapore Mental Health Study, a cross-sectional study of adult Singapore residents. The study sample consisted of 6616 respondents, of which 49.8% were male and 50.2% female. A network structure was constructed to examine associations between psychopathology, alcohol use, gambling, major chronic conditions, and functioning. RESULTS: The network structure identified what we have labeled a Cartesian graph: a network visibly split into a psychopathological domain and a physical health domain. The borders between these domains were fuzzy and bridged by various cross-domain associations, with functioning items playing an important role in bridging chronic conditions to psychopathology. CONCLUSIONS: Current results deliver a comprehensive overview of the complex relation between psychopathology, functioning, and chronic illness, highlighting potential pathways to comorbidity.


Assuntos
Transtornos Mentais , Psicopatologia , Adulto , Doença Crônica , Comorbidade , Estudos Transversais , Feminino , Humanos , Masculino , Transtornos Mentais/epidemiologia , Singapura/epidemiologia
13.
Clin Psychol Psychother ; 28(5): 1065-1078, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-33606318

RESUMO

A fundamental question in psychotherapy is whether interventions should target client problems (i.e., problem-focused approaches) or client strengths (i.e., strength-focused approaches). In this study, we first propose to address this question from a network perspective on schema modes (i.e., healthy or dysfunctional patterns of co-occurring emotions, cognitions, and behaviours). From this perspective, schema modes mutually influence each other (e.g., healthy modes reduce dysfunctional modes). Recent evidence suggests that changes in modes that are strongly associated to other modes (i.e., central modes) could be associated with greater treatment effects. We therefore suggest research should investigate the relative centrality of healthy and dysfunctional modes. To make an exploratory start, we investigated the cross-sectional network structure of schema modes in a clinical (comprising individuals diagnosed with paranoid, narcissistic, histrionic, and Cluster C personality disorders) and non-clinical sample. Results showed that, in both samples, the Healthy Adult was significantly less central than several dysfunctional modes (e.g., Undisciplined Child and Abandoned and Abused Child). Although our study cannot draw causal conclusions, this finding could suggest that weakening dysfunctional modes (compared to strengthening the Healthy Adult) might be more effective in decreasing other dysfunctional modes. Our study further indicates that several schema modes are negatively associated, which could suggest that decreasing one might increase another. Finally, the Healthy Adult was among the modes that most strongly discriminated between clinical and non-clinical individuals. Longitudinal and experimental research into the network structure of schema modes is required to further clarify the relative influence of schema modes.


Assuntos
Transtornos da Personalidade , Psicoterapia , Adulto , Criança , Estudos Transversais , Emoções , Nível de Saúde , Humanos , Transtornos da Personalidade/terapia
14.
Schizophr Bull ; 47(4): 1018-1028, 2021 07 08.
Artigo em Inglês | MEDLINE | ID: mdl-33595089

RESUMO

BACKGROUND: The high prevalence of obsessive-compulsive symptoms (OCS) among subjects at Ultra-High Risk (UHR) for psychosis is well documented. However, the network structure spanning the relations between OCS and symptoms of the at risk mental state for psychosis as assessed with the Comprehensive Assessment of At Risk Mental States (CAARMS) has not yet been investigated. This article aimed to use a network approach to investigate the associations between OCS and CAARMS symptoms in a large sample of individuals with different levels of risk for psychosis. METHOD: Three hundred and forty-one UHR and 66 healthy participants were included, who participated in the EU-GEI study. Data analysis consisted of constructing a network of CAARMS symptoms, investigating central items in the network, and identifying the shortest pathways between OCS and positive symptoms. RESULTS: Strong associations between OCS and anxiety, social isolation and blunted affect were identified. Depression was the most central symptom in terms of the number of connections, and anxiety was a key item in bridging OCS to other symptoms. Shortest paths between OCS and positive symptoms revealed that unusual thought content and perceptual abnormalities were connected mainly via anxiety, while disorganized speech was connected via blunted affect and cognitive change. CONCLUSIONS: Findings provide valuable insight into the central role of depression and the potential connective component of anxiety between OCS and other symptoms of the network. Interventions specifically aimed to reduce affective symptoms might be crucial for the development and prospective course of symptom co-occurrence.

15.
Perspect Psychol Sci ; 16(4): 756-766, 2021 07.
Artigo em Inglês | MEDLINE | ID: mdl-33593167

RESUMO

This article aims to improve theory formation in psychology by developing a practical methodology for constructing explanatory theories: theory construction methodology (TCM). TCM is a sequence of five steps. First, the theorist identifies a domain of empirical phenomena that becomes the target of explanation. Second, the theorist constructs a prototheory, a set of theoretical principles that putatively explain these phenomena. Third, the prototheory is used to construct a formal model, a set of model equations that encode explanatory principles. Fourth, the theorist investigates the explanatory adequacy of the model by formalizing its empirical phenomena and assessing whether it indeed reproduces these phenomena. Fifth, the theorist studies the overall adequacy of the theory by evaluating whether the identified phenomena are indeed reproduced faithfully and whether the explanatory principles are sufficiently parsimonious and substantively plausible. We explain TCM with an example taken from research on intelligence (the mutualism model of intelligence), in which key elements of the method have been successfully implemented. We discuss the place of TCM in the larger scheme of scientific research and propose an outline for a university curriculum that can systematically educate psychologists in the process of theory formation.


Assuntos
Teoria Psicológica , Psicologia/métodos , Projetos de Pesquisa , Humanos , Inteligência
16.
Multivariate Behav Res ; 56(2): 256-287, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-31782672

RESUMO

Pairwise network models such as the Gaussian Graphical Model (GGM) are a powerful and intuitive way to analyze dependencies in multivariate data. A key assumption of the GGM is that each pairwise interaction is independent of the values of all other variables. However, in psychological research, this is often implausible. In this article, we extend the GGM by allowing each pairwise interaction between two variables to be moderated by (a subset of) all other variables in the model, and thereby introduce a Moderated Network Model (MNM). We show how to construct MNMs and propose an ℓ1-regularized nodewise regression approach to estimate them. We provide performance results in a simulation study and show that MNMs outperform the split-sample based methods Network Comparison Test (NCT) and Fused Graphical Lasso (FGL) in detecting moderation effects. Finally, we provide a fully reproducible tutorial on how to estimate MNMs with the R-package mgm and discuss possible issues with model misspecification.


Assuntos
Distribuição Normal , Simulação por Computador
17.
Multivariate Behav Res ; 56(2): 175-198, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-31617420

RESUMO

Networks are gaining popularity as an alternative to latent variable models for representing psychological constructs. Whereas latent variable approaches introduce unobserved common causes to explain the relations among observed variables, network approaches posit direct causal relations between observed variables. While these approaches lead to radically different understandings of the psychological constructs of interest, recent articles have established mathematical equivalences that hold between network models and latent variable models. We argue that the fact that for any model from one class there is an equivalent model from the other class does not mean that both models are equally plausible accounts of the data-generating mechanism. In many cases the constraints that are meaningful in one framework translate to constraints in the equivalent model that lack a clear interpretation in the other framework. Finally, we discuss three diverging predictions for the relation between zero-order correlations and partial correlations implied by sparse network models and unidimensional factor models. We propose a test procedure that compares the likelihoods of these models in light of these diverging implications. We use an empirical example to illustrate our argument.


Assuntos
Modelos Estatísticos , Modelos Teóricos
18.
Behav Res Ther ; 149: 104011, 2021 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-34998034

RESUMO

In recent years, network approaches to psychopathology have sparked much debate and have had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there are many important challenges in moving from theory to empirical research and clinical practice and vice versa. Therefore, in this article, we bring together different points of view on psychological networks by methodologists and clinicians to give a critical overview on these challenges, and to present an agenda for addressing these challenges. In contrast to previous reviews, we especially focus on methodological issues related to temporal networks. This includes topics such as selecting and assessing the quality of the nodes in the network, distinguishing between- and within-person effects in networks, relating items that are measured at different time scales, and dealing with changes in network structures. These issues are not only important for researchers using network models on empirical data, but also for clinicians, who are increasingly likely to encounter (person-specific) networks in the consulting room.

19.
PLoS One ; 15(12): e0243298, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33320901

RESUMO

The network approach to psychological phenomena advances our understanding of the interrelations between autism and well-being. We use the Perceived Causal Relations methodology in order to (i) identify perceived causal pathways in the well-being system, (ii) validate networks based on self-report data, and (iii) quantify and integrate clinical expertise in autism research. Trained clinicians served as raters (N = 29) completing 374 cause-effects ratings of 34 variables on well-being and symptomatology. A subgroup (N = 16) of raters chose intervention targets in the resulting network which we found to match the respective centrality of nodes. Clinicians' perception of causal relations was similar to the interrelatedness found in self-reported client data (N = 323). We present a useful tool for translating clinical expertise into quantitative information enabling future research to integrate this in scientific studies.


Assuntos
Transtorno Autístico/psicologia , Felicidade , Adolescente , Adulto , Idoso , Transtorno Autístico/terapia , Criança , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Autorrelato
20.
Perspect Psychol Sci ; 15(2): 444-468, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-32040935

RESUMO

Emotions are part and parcel of the human condition, but their nature is debated. Three broad classes of theories about the nature of emotions can be distinguished: affect-program theories, constructionist theories, and appraisal theories. Integrating these broad classes of theories into a unifying theory is challenging. An integrative psychometric model of emotions can inform such a theory because psychometric models are intertwined with theoretical perspectives about constructs. To identify an integrative psychometric model, we delineate properties of emotions stated by emotion theories and investigate whether psychometric models account for these properties. Specifically, an integrative psychometric model of emotions should allow (a) identifying distinct emotions (central in affect-program theories), (b) between- and within-person variations of emotions (central in constructionist theories), and (c) causal relationships between emotion components (central in appraisal theories). Evidence suggests that the popular reflective and formative latent variable models-in which emotions are conceptualized as unobservable causes or consequences of emotion components-cannot account for all properties. Conversely, a psychometric network model-in which emotions are conceptualized as systems of causally interacting emotion components-accounts for all properties. The psychometric network model thus constitutes an integrative psychometric model of emotions, facilitating progress toward a unifying theory.


Assuntos
Emoções , Modelos Psicológicos , Teoria Psicológica , Psicometria , Humanos
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