Several governments have implemented strict measures in order to reduce the spread of COVID-19, such as lockdown measures. However, these measures have brought negative consequences at an individual level by increasing the psychological distress already exacerbated by the pandemic. In the present study, we evaluated the role of cognitive emotion regulation strategies and variables related to social support, hobbies, seeking information related to COVID-19, perceived risk of infection, and age on the levels of anxiety and depression during the lockdown in a sample of 663 Spanish-speaking adults. By using multiple regression analyses with a backward model selection procedure, 26% of the variance in anxiety was predicted by specific cognitive emotion regulation strategies, perceived risk of infection, number of hobbies, and seeking information about COVID-19. A similar procedure was used to build a model predicting depression. The resulting model predicted 38% of the variance in depression, and included specific emotion regulation strategies and age. Significant differences were found in the use of emotion regulation strategies and the experience of anxiety and depression between men and women, with women experiencing higher levels of both anxiety and depression. Based on our results, recommendations are provided for improving coping with stressful events where lockdown measures are taken.

Background: Decisions made by disordered gamblers are markedly inflexible. However, whether anomalies in learning from feedback are gambling-specific, or extend beyond gambling contexts, remains an open question. More generally, addictive disorders –including gambling disorder– have been proposed to be facilitated by individual differences in learning-driven decision-making inflexibility. Individual differences in decision-making inflexibility have been studied in the lab with the Affective Probabilistic Reversal Learning Task (PRLT). In this task, participants are first asked to learn which of two choice options is more advantageous, on the basis of trial-by-trial feedback, but, once preferences are established, reward contingencies are reversed, so that the advantageous option becomes disadvantageous and vice versa. Inflexibility is revealed by a less effective reacquisition of preferences after reversal, which can be distinguished from more generalized acquisition deficits.Methods: In the present study, we compared PRLT performance across two groups of 25 treatment-seeking patients with an addictive disorder and reported gambling problems, and 25 matched controls [18 Males/7 Females in both groups, Mage(SDage) = 25.24 (8.42) and 24.96 (7.90), for patients and controls, respectively]. Beyond testing for differences in the shape of PRLT learning curves across groups, the specific effect of gambling symptoms’ severity was also assessed in the group of patients. In order to surpass previous methodological problems, full acquisition and reacquisition curves were fitted using generalized mixed-effect models. Results: Results showed that (1) controls learned more efficiently than patients in all phases of the task, and were more likely to make correct choices by the end of each task phase, regardless of contingency (and so there were no specific signs of decision-making inflexibility in the group of patients); (2) gambling severity in the group of patients was specifically associated with more inefficient learning in phases with reversed contingencies (i.e., decision-making inflexibility). Conclusion: Decision-making inflexibility, as revealed by difficulty to reacquire decisional preferences based on feedback after contingency reversals, seems to be specifically associated with gambling problems, but not necessarily with a substance-use disorder diagnosis. This result aligns with gambling disorder models in which domain-general compulsivity is linked to vulnerability to develop gambling-specific problems with exposure to gambling opportunities.