Exploring aspects of the cognitive behavioural model of physical hoarding in relation to digital hoarding behaviours

Exploration of vulnerability factors of digital hoarding behavior among university students and the moderating role of maladaptive perfectionism

In light of the rapidly evolving digital landscape, there is an increasing need to explore digital hoarding behavior. This need is driven by concerns regarding its intricate psychological foundations and its impact on individuals within our technology-centric society. This research investigates the influence of various factors, including the fear of missing out, emotional attachment, information overload, and decision fatigue, on digital hoarding behaviors among university students in Iran. Additionally, the study examines the moderating role of maladaptive perfectionism in these relationships. The study involved 275 university students (mean age = 21.62 years; standard deviation = 2.28 years; 65.6% female) selected from four universities in Iran. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results revealed that the fear of missing out, emotional attachment, information overload, and decision fatigue significantly predict university students' digital hoarding behavior. Moreover, the findings highlighted the moderating effect of maladaptive perfectionism on the association between emotional attachment and digital hoarding behavior. This suggests that individuals with higher levels of maladaptive perfectionism exhibit amplified digital hoarding tendencies when emotionally attached to their digital data. This study provides a deeper understanding of the relationship between psychological factors and digital hoarding tendencies. These findings have practical implications for educational institutions and mental health professionals, as they can help in developing targeted strategies and interventions to manage digital hoarding behavior in university freshmen and promote healthier digital habits.

Storing, Not Reading: Investigating the Link Between Upward Social Comparison via Social Media and Digital Hoarding Behavior in Chinese Youth

Background

Digital hoarding has emerged as a pervasive psychological phenomenon and behavioral challenge among contemporary youth. This study focused on exploring the relationship between upward social comparison via social media, fear of missing out (FoMO), mindfulness, digital hoarding behavior, and its underlying mechanisms.

Methods

A total of 927 young people participated in this cross-sectional study. Research instruments included the Social Comparison Scale, the Fear of Missing Out Scale, the Mindfulness Measure, and the Digital Hoarding Behavior Questionnaire. The data analysis comprised descriptive statistics and correlation analyses. Advanced analyses were conducted using Model 4 for mediation and Model 8 for moderation from the PROCESS macro.

Results

(1) Upward social comparison via social media was a strong predictor of digital hoarding behavior, even after controlling for variables such as gender, age, and education. (2) FoMO mediated the relationship between upward social comparison via social media and digital hoarding. (3) Mindfulness moderated both the direct effect of upward social comparison via social media on digital hoarding and the first segment of the mediating role of FoMO.

Discussion

The study further clarified the antecedents and psychological mechanisms that drive digital hoarding behavior. The findings contribute new perspectives for understanding the emerging concept of digital hoarding, while providing empirical evidence and valuable guidance for encouraging young adults to use social media responsibly and reduce impulsive hoarding tendencies.

Artificial Intelligence and Precision Medicine: A Perspective

This article aims to present how the advanced solutions of artificial intelligence and precision medicine work together to refine medical management. Multi-omics seems the most suitable approach for biological analysis of data on precision medicine and artificial intelligence. We searched PubMed and Google Scholar databases to collect pertinent articles appearing up to 5 March 2021. Genetics, oncology, radiology, and the recent coronavirus disease (COVID-19) pandemic were chosen as representative fields addressing the cross-compliance of artificial intelligence (AI) and precision medicine based on the highest number of articles, topicality, and interconnectedness of the issue. Overall, we identified and perused 1572 articles. AI is a breakthrough that takes part in shaping the Fourth Industrial Revolution in medicine and health care, changing the long-time accepted diagnostic and treatment regimens and approaches. AI-based link prediction models may be outstandingly helpful in the literature search for drug repurposing or finding new therapeutical modalities in rapidly erupting wide-scale diseases such as the recent COVID-19.