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

Real-Time Self-Regulation of Emotion Networks in Patients with Depression

Many patients show no or incomplete responses to current pharmacological or psychological therapies for depression. Here we explored the feasibility of a new brain self-regulation technique that integrates psychological and neurobiological approaches through neurofeedback with functional magnetic resonance imaging (fMRI). In a proof-of-concept study, eight patients with depression learned to upregulate brain areas involved in the generation of positive emotions (such as the ventrolateral prefrontal cortex (VLPFC) and insula) during four neurofeedback sessions. Their clinical symptoms, as assessed with the 17-item Hamilton Rating Scale for Depression (HDRS), improved significantly. A control group that underwent a training procedure with the same cognitive strategies but without neurofeedback did not improve clinically. Randomised blinded clinical trials are now needed to exclude possible placebo effects and to determine whether fMRI-based neurofeedback might become a useful adjunct to current therapies for depression