Dataset Information

The who and what of validation: an experimental examination of validation and invalidation of specific emotions and the moderating effect of emotion dysregulation.

ABSTRACT:

Background

Theory and research indicate that validation is associated with reductions in negative emotions, whereas invalidation is associated with escalation of negative emotions. However, it remains unclear whether these effects are consistent across emotions, and/or moderated by an individual's levels of emotion dysregulation. The present study experimentally examines the effects of validation and invalidation across emotions and as moderated by emotion dysregulation.

Methods

One hundred twenty-six participants completed a measure of emotion dysregulation, and then listened to a rejection-themed imagery script after which they reported the intensity of several emotions. Participants were then presented with either validating or invalidating feedback about their most intense self-reported emotion, depending on their counterbalancing order. They then repeated the procedure for the other condition. Self-reported negative emotions via continuous rating dial, heart rate (HR), and skin conductance level (SCL) were monitored throughout.

Results

Higher emotion dysregulation was associated with greater increases in self-reported positive emotion when shame or sadness was validated and lesser increases when fear was validated. There were no significant moderating effects of emotion dysregulation in response to invalidation for any emotion on any index.

Conclusions

The effects of validation appear emotion specific and dependent on levels of emotion dysregulation. These findings may help inform more strategic use of validation in psychotherapeutic interventions.

SUBMITTER: Kuo JR

PROVIDER: S-EPMC9116024 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

The who and what of validation: an experimental examination of validation and invalidation of specific emotions and the moderating effect of emotion dysregulation.

Kuo Janice R JR Fitzpatrick Skye S Ip Jennifer J Uliaszek Amanda A

Borderline personality disorder and emotion dysregulation 20220518 1

<h4>Background</h4>Theory and research indicate that validation is associated with reductions in negative emotions, whereas invalidation is associated with escalation of negative emotions. However, it remains unclear whether these effects are consistent across emotions, and/or moderated by an individual's levels of emotion dysregulation. The present study experimentally examines the effects of validation and invalidation across emotions and as moderated by emotion dysregulation.<h4>Methods</h4>O ...[more]

PMID: 35581663

Similar Datasets

Project description:BackgroundVery frequently the same biological system is described by several, sometimes competing mathematical models. This usually creates confusion around their validity, ie, which one is correct. However, this is unnecessary since validity of a model cannot be established; model validation is actually a misnomer. In principle the only statement that one can make about a system model is that it is incorrect, ie, invalid, a fact which can be established given appropriate experimental data. Nonlinear models of high dimension and with many parameters are impossible to invalidate through simulation and as such the invalidation process is often overlooked or ignored.ResultsWe develop different approaches for showing how competing ordinary differential equation (ODE) based models of the same biological phenomenon containing nonlinearities and parametric uncertainty can be invalidated using experimental data. We first emphasize the strong interplay between system identification and model invalidation and we describe a method for obtaining a lower bound on the error between candidate model predictions and data. We then turn to model invalidation and formulate a methodology for discrete-time and continuous-time model invalidation. The methodology is algorithmic and uses Semidefinite Programming as the computational tool. It is emphasized that trying to invalidate complex nonlinear models through exhaustive simulation is not only computationally intractable but also inconclusive.ConclusionBiological models derived from experimental data can never be validated. In fact, in order to understand biological function one should try to invalidate models that are incompatible with available data. This work describes a framework for invalidating both continuous and discrete-time ODE models based on convex optimization techniques. The methodology does not require any simulation of the candidate models; the algorithms presented in this paper have a worst case polynomial time complexity and can provide an exact answer to the invalidation problem.

Dataset Information

The who and what of validation: an experimental examination of validation and invalidation of specific emotions and the moderating effect of emotion dysregulation.

Background

Methods

Results

Conclusions

Publications

The who and what of validation: an experimental examination of validation and invalidation of specific emotions and the moderating effect of emotion dysregulation.

Similar Datasets

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