A modern network approach to revisiting the positive and negative affective schedule (PANAS) construct validity

Introduction: The factor structure of the Positive and Negative Affective Schedule (PANAS) is still a topic of debate. There are several reasons why using Exploratory Graph Analysis (EGA) for scale validation is advantageous and can help understand and resolve conflicting results in the factor analytic literature. Objective: The main objective of the present study was to advance the knowledge regarding the factor structure underlying the PANAS scores by utilizing the different functionalities of the EGA method. EGA was used to (1) estimate the dimensionality of the PANAS scores, (2) establish the stability of the dimensionality estimate and of the item assignments into the dimensions, and (3) assess the impact of potential redundancies across item pairs on the dimensionality and structure of the PANAS scores. Method: This assessment was carried out across two studies that included two large samples of participants. Results and Conclusion: In sum, the results are consistent with a two-factor oblique structure.Fil: Flores Kanter, Pablo Ezequiel. Universidad Empresarial Siglo XXI; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Garrido, Luis Eduardo. Pontificia Universidad Católica Madre y Maestra; República DominicanaFil: Moretti, Luciana Sofía. Universidad Empresarial Siglo XXI; Argentina. Pontificia Universidad Católica Madre y Maestra; República Dominicana. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Medrano, Leonardo. Universidad Empresarial Siglo XXI; Argentina. Pontificia Universidad Católica Madre y Maestra; República Dominicana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Datset for Internal structure of Beck’s Hopelessness Scale: Analyzing method effects using the CT-C(M–1) model

The factor structure of the Beck Hopelessness Scale (BHS) has long been a topic of debate in psychometrics. Recently, studies have examined the method factor’s role in the factor structure of the BHS, but the models used to study the method’s effect have severe limitations and new models are needed. One such model is the correlated trait–correlated methods minus one (CT-C(M-1)), a powerful modeling approach that gives the trait factor an unambiguous meaning and avoids anomalous results associated with fully symmetrical bifactor modeling. The present work compares the fit of the CT-C(M-1) model to that of the models proposed in the previous literature to verify the convergent validity of the CT-C(M-1) model and its discriminatory capacity by taking suicidal ideation as the criterion variable. This study used a large and heterogeneous open-mode online sample of Argentinian people (N = 2,164). The results indicated that the CT-C(M-1) model with positive words as referenced items achieves the best fit. The factorial scores derived from this model demonstrate good predictive and discriminating capabilities

Datset for A Modern Network Approach to Revisiting the PANAS Structure

In order to provide greater clarity on the factor structure of the PANAS, this paper purpose of applying a new network psychometric approach called Exploratory Graph Analysis (EGA)

Datset for A Modern Network Approach to Revisiting the PANAS Structure

In order to provide greater clarity on the factor structure of the PANAS, this paper purpose of applying a new network psychometric approach called Exploratory Graph Analysis (EGA)

Datset for A Modern Network Approach to Revisiting the PANAS Structure

In order to provide greater clarity on the factor structure of the PANAS, this paper purpose of applying a new network psychometric approach called Exploratory Graph Analysis (EGA)

Datset for Internal structure of Beck Hopelessness Scale: An analysis of method effects using the CT-C(M–1) model

The construct validity in relation to the dimensionality or factor structure of the Beck Hopelessness Scale (BHS) has long been debated in psychometrics. Irrelevant variance due to item wording (method effects) can distort the factor structure, and recent studies have examined the method factor’s role in the factor structure of the BHS. However, the models used to control the method effects have severe limitations, and new models are needed. One such model is the correlated trait-correlated method minus one (CT-C(M-1)), which is a powerful approach that gives the trait factor an unambiguous meaning and prevents the anomalous results associated with fully symmetrical bifactor modeling. The present work compares the fit and factor structure of the CT-C(M-1) model to bifactor models proposed in previous literature and evaluates the convergent validity of the CT-C(M-1) model and its discriminatory capacity by taking suicidal ideation as the criterion variable. This study used a large and heterogeneous open mode online sample of Argentinian people (N = 2,164). For this study, the adapted Beck Hopelessness Scale (BHS) version for the Argentinian population was used (Mikulic et al., 2009). This scale comprises 20 items with a dichotomous reply format (i.e., true or false) and is used to evaluate the respondent’s negative expectations for the future. In addition, the version of the Inventory of Suicide Orientation-30 (ISO-30) validated by Fernandez-Liporace and Casullo (2006) in Argentina was used for this study. The instrument measures the respondent’s level of agreement with certain statements using a four-point Likert scale (with responses ranging from 1, “I strongly disagree” to 4, “I strongly agree”). From the inventory, only the questions that were related to the dimension of SI were included (e.g., “In order to stop things from getting worse, I believe suicide is the solution”). Within the ISO-30 scale, the suicidal ideation factor is the one that has shown the highest consistency and evidence of measurement validity in the literature on the internal structure of the scale (Vecco et al., 2021). In the present research, the high-SI and no-SI groups were identified based on the scores obtained from the ISO-30 SI subscale (possible range values = 4–16). A total score of 4 (i.e., the participant marked “strongly disagree” on all items) was considered to indicate an absence of SI, while a score of 16 (i.e., the participant marked “strongly agree” on all items) indicated a high SI. Individuals scoring in the middle range were not included in the analyses. The results indicated that the CT-C(M-1) model with positive words as referenced items achieves the most adequate factor structure. The factorial scores derived from this model demonstrate good predictive and discriminating capabilities

Data for: Cognitive Processes in Stressful Situations: Proposal and Validation of Bottom-up and Top-down Emotion Regulation Models

Background: The Cognitive Emotion Regulation Questionnaire (CERQ) is a purpose-built tool for measuring the use of CERS in negative or stressful situations ore for coping propose. Nevertheless, inconsistencies and controversies about its general validity, especially in regards to its constructs validity, continue to exist for this cognitive emotion regulation measure. Some form to resolve these controversies it´s considerate different measures models in function of the specifics CERQ factors implicated. Objective: The principal objective of the present research is to empirically test these measures models in a large and heterogeneous argentine sample. Methods: To this end, a computerized version of the CERQ scale was used, and psychometrics statistical procedures of construct validity (confirmatory factor analysis), measurement invariance, and criterion validity (correlation with affective variables), were applied. Results and Conclusions: The empirical evidence supports the applicability of a bifactor model to maladaptive CERQ factors and an oblique or hierarchical model for adaptative CERQ factors. These results open the gate to the use and applicability of CERQ to measure repetitive negative thinking as a coping style response and provided evidence in favor of a computerized or electronic version of the CERQ, which broadens and facilitates its application in various research and clinical contexts

Datset for Construct Validity of Beck's Hopelessness Scale (BHS): Analysis trough S-1 Bifactor Model in a Large Argentine Sample.

Despite the fact that The Beck Hopelessness Scale (BHS) has been widely used and considerate an instrument recognized for its predictive capabilities of suicidal ideation and attempt; its factor structure is still a topic of debate. It becomes necessary to propose models for resolving these disputes. One of such approach is the bifactor S-1 model. This is a power modeling approach that gives a G an unambiguous meaning and avoids anomalous results associated to fully symmetrical modeling. The main objective of this work is to verify the fit of a bifactor S-1 model for BHS, contrasted with other models that contemplate methods effects too. We take a sample of 2,164 Argentines through an open mode on-line sample method. The results indicate that the S-1 bifactor model with positive word as referenced items achieves the best and optimal fit indices. The complementary receiver operating characteristic curve shows that the area under the curve obtained gives an optimal precision for discriminating between people with high and no suicidal ideations. These results allow to give clarity on the factorial structure of the BHS, showing evidence in favor of the construct validity of a computerized version of the BHS

Data for: Cognitive Processes in Stressful Situations: Proposal and Validation of Bottom-up and Top-down Emotion Regulation Models

Background: The Cognitive Emotion Regulation Questionnaire (CERQ) is a purpose-built tool for measuring the use of CERS in negative or stressful situations ore for coping propose. Nevertheless, inconsistencies and controversies about its general validity, especially in regards to its constructs validity, continue to exist for this cognitive emotion regulation measure. Some form to resolve these controversies it´s considerate different measures models in function of the specifics CERQ factors implicated. Objective: The principal objective of the present research is to empirically test these measures models in a large and heterogeneous argentine sample. Methods: To this end, a computerized version of the CERQ scale was used, and psychometrics statistical procedures of construct validity (confirmatory factor analysis), measurement invariance, and criterion validity (correlation with affective variables), were applied. Results and Conclusions: The empirical evidence supports the applicability of a bifactor model to maladaptive CERQ factors and an oblique or hierarchical model for adaptative CERQ factors. These results open the gate to the use and applicability of CERQ to measure repetitive negative thinking as a coping style response and provided evidence in favor of a computerized or electronic version of the CERQ, which broadens and facilitates its application in various research and clinical contexts

Datset for Internal structure of Beck’s Hopelessness Scale: Analyzing method effects using the CT-C(M–1) model

The factor structure of the Beck Hopelessness Scale (BHS) has long been a topic of debate in psychometrics. Recently, studies have examined the method factor’s role in the factor structure of the BHS, but the models used to study the method’s effect have severe limitations and new models are needed. One such model is the correlated trait–correlated methods minus one (CT-C(M-1)), a powerful modeling approach that gives the trait factor an unambiguous meaning and avoids anomalous results associated with fully symmetrical bifactor modeling. The present work compares the fit of the CT-C(M-1) model to that of the models proposed in the previous literature to verify the convergent validity of the CT-C(M-1) model and its discriminatory capacity by taking suicidal ideation as the criterion variable. This study used a large and heterogeneous open-mode online sample of Argentinian people (N = 2,164). The results indicated that the CT-C(M-1) model with positive words as referenced items achieves the best fit. The factorial scores derived from this model demonstrate good predictive and discriminating capabilities.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV