The COVID-19 pandemic is far more than a health crisis: it has unpredictably changed our whole way of life. As suggested by the analysis of economic data on sales, this dramatic scenario has also heavily impacted individuals’ spending levels. To better understand these changes, the present study focused on consumer behavior and its psychological antecedents. Previous studies found that crises differently affect people’s willingness to buy necessities products (i.e., utilitarian shopping) and non-necessities products (i.e., hedonic shopping). Therefore, in examining whether changes in spending levels were associated with changes in consumer behavior, we adopted a fine-grained approach disentangling between necessities and non-necessities. We administered an online survey to 3833 participants (age range 18–64) during the first peak period of the contagion in Italy. Consumer behavior toward necessities was predicted by anxiety and COVID-related fear, whereas consumer behavior toward non-necessities was predicted by depression. Furthermore, consumer behavior toward necessities and non-necessities was predicted by personality traits, perceived economic stability, and self-justifications for purchasing. The present study extended our understanding of consumer behavior changes during the COVID-19 pandemic. Results could be helpful to develop marketing strategies that consider psychological factors to meet actual consumers’ needs and feelings.

Virtual Reality (VR) has been gaining increasing attention as a potential ecological and effective intervention system for treating Mild Cognitive Impairment (MCI). However, it remains unclear the efficacy and effectiveness of VR-based cognitive rehabilitation therapy (VR-CRT) in comparison with cognitive rehabilitation therapy (CRT). Consequently, a systematic review on Pubmed, Scopus, PsycInfo, and Web Of Science was conducted to assess the state of the art of the literature published between 2003 and April 2023. Only articles that adopted CRT as control group and that included some measure of at least one domain among overall cognitive function, executive function and functional status were included. Participants needed to be older adults aged 65 or over with a diagnosis of MCI. The risk of bias and the quality of evidence were assessed using the Version 2 of the Cochrane risk-of-bias tool for randomized trials. Initially, 6503 records were considered and screened after removing duplicates (n = 1321). Subsequently, 81 full texts were assessed for eligibility. Four articles met the inclusion criteria but 2 of them were merged as they were describing different outcomes of the same research project. Consequently, 3 overall studies with a total of 130 participants were included in the final analysis. Due to the high heterogeneity in the methodology and outcome measures employed, it was not possible to conduct a meta-analysis. Included studies used semi-immersive (k = 2) and full-immersive (k = 1) VR systems in their research. Two articles evaluated overall cognitive function through the MoCA together with specific tests for executive functions (n = 69), while one study adopted a comprehensive neuropsychological battery to evaluate both cognitive function and executive function (n = 61). Finally, one study evaluated functional status through instrumental activities of daily living (n = 34). A However, the limited number of studies, the small sample size, and the potential issues with the quality and methodology of these studies that emerged from the risk of bias assessment may raise doubts about the reliability of their results. Nevertheless, although scarce, results of the present review suggest that VR-CRT may be paramount in treating MCI for its additional ecological and adaptive advantages, as all of the studies highlighted that it was at least as effective as conventional CRT for all the outcome measures. Therefore, more rigorous research that compares VR-CRT and CRT is needed to understand the degree to which VR-CRT is effective with older adults with MCI and the potential role of immersion to influence its efficacy. Indeed, these preliminary findings highlight the need for the development of standardized VR protocols, as the integration of such technology into clinical practice may help improve the quality of life and cognitive outcomes for this growing demographic.

Extensive possibilities of applications have rendered emotion recognition ineluctable and challenging in the fields of computer science as well as in human-machine interaction and affective computing. Fields that, in turn, are increasingly requiring real-time applications or interactions in everyday life scenarios. However, while extremely desirable, an accurate and automated emotion classification approach remains a challenging issue. To this end, this study presents an automated emotion recognition model based on easily accessible physiological signals and deep learning (DL) approaches. As a DL algorithm, a Feedforward Neural Network was employed in this study. The network outcome was further compared with canonical machine learning algorithms such as random forest (RF). The developed DL model relied on the combined use of wearables and contactless technologies, such as thermal infrared imaging. Such a model is able to classify the emotional state into four classes, derived from the linear combination of valence and arousal (referring to the circumplex model of affect’s four-quadrant structure) with an overall accuracy of 70% outperforming the 66% accuracy reached by the RF model. Considering the ecological and agile nature of the technique used the proposed model could lead to innovative applications in the affective computing field.

Previous studies consistently showed age-related differences in temporal judgment and temporal memory. Importantly, emotional valence plays a crucial role in older adults’ information processing. In this study, we examined the effects of emotions at the intersection between time and memory, analysing age-related differences in a temporal source memory task. Twenty-five younger adults (age range 18–35), 25 old adults (age range 65–74), and 25 old–old adults (age range 75–84) saw a series of emotional pictures in three sessions separated by a one-day rest period. In the fourth session, participants were asked to indicate in which session (1, 2, or 3) they saw each picture. Results showed that old–old adults tended to collocate negative pictures distant in time, while positive stimuli were remembered as more recent than real, compared to neutral pictures. To a lower extent, people over 65 showed the same pattern of results. In contrast, emotional valence did not affect younger adults’ temporal positioning of stimuli. Current findings fit well with the Socio-Emotional Selectivity Theory’s assumptions and extended the literature on the positivity effect to temporal source memory.

We investigated people’s preferences in COVID-19 vaccine allocation priority, comparing different social categories based on age and occupation. Vaccine allocation preferences were related to perce...

Background: Cognitive biases are popular topics in psychology and marketing, as they refer to systematic cognitive tendencies in human thinking that deviate from logical and rational reasoning. The framing effect (FE) and the decoy effect (DE) are examples of cognitive biases that can influence decision making and consumer preferences. The FE involves how options are presented, while the DE involves the addition of a third option that influences the choice between the other two options. Methods: We investigated the interaction between the FE and the DE in the case of both incongruent (ID) and congruent (CD) decoys in a sample of undergraduates (n = 471). The study had a two (positive vs. negative valence) × three (original, congruent decoy, incongruent decoy) within-subject design. Results: The ID option reduces the FE in both positive- and negative-framed conditions compared to the controls, while adding the CD option increases the FE only in the positive-framed condition. Additionally, the inclusion of the CD option enhances the level of decision confidence, whereas no significant differences were found in the ID condition. Conclusions: Our findings gave new insights into the interplay between two of the most frequent cognitive biases.