Category: Cognitive Science / Cognitive Processes

Symposium

Probabilistic and Operant Learning Tendencies in GAD: Deficits in Positive Reinforcement Response

Friday, November 17
3:30 PM - 5:00 PM
Location: Cobalt 502, Level 5, Cobalt Level

Keywords: GAD (Generalized Anxiety Disorder) | Cognitive Biases / Distortions | Cognitive Vulnerability
Presentation Type: Symposium

Studies suggest that those with GAD may have differential learning tendencies compared to the nonanxious, such as deficits in learning outcome probabilities and learning by positive reinforcement. Those with GAD have problems estimating the probability of future events based on past consequences. Excessive worrying in GAD is linked to higher rated likelihoods for the occurrence of negative events compared to controls (Berenbaum et al., 2007) and GAD worry is inaccurate (85-91% of GAD worries do not come true; Borkovec et al., 1999). Furthermore, worry in GAD increases affective and somatic distress and is perpetuated by cycles of negative reinforcement, continually blocking positive experience. Those with GAD are also less likely to register or savor rewards because positive affect may leave them vulnerable to greater undesirable negative emotional shifts (Newman & Llera, 2011). Thus, those with GAD may have differential learning tendencies in positive reinforcement and gauging outcome probabilities compared to controls.


This study used a computerized implicit cognitive task with probabilistic reinforcement to determine if such tendencies existed. Thus far, 59 GAD and 98 non-GAD participants have taken a modified version of the Probabilistic Learning Task (PLT). In our PLT, participants chose between stimuli with specific probabilities of reinforcement, learning over time which of each pair had the highest probability. Correct choices in the negative condition removed an angry face, whereas those in the positive condition made a happy face appear. Analyses used multilevel modeling and factorial ANOVAs.


Preliminary results with this sub-sample showed that compared to non-GADs, the probabilistic learning of those with GAD was both slower over time and less accurate both implicitly and explicitly, regardless of condition (t(597.41) = −2.20, p = 0.028). Marginally significant explicit learning effects suggested that those with GAD had poorer learning via positive reinforcement than did non-GADs, especially when reward probability was high (F(1, 156) = 3.44, p = 0.066). Final results at ABCT 2017 will draw on an increased sample size for adequate power.

Lucas S. LaFreniere

Doctoral Student
The Pennsylvania State University

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