Uncertainty about future events may lead to worry, anxiety, even inability to function. The highly related concept—intolerance of uncertainty (IU)—emerged in the early 1990s, which is further developed into a transdiagnostic risk factor in multiple forms of anxiety disorders. Interests in uncertainty and intolerance of uncertainty have rapidly increased in recent years; little is known about the construct and phenomenology of uncertainty and IU and the association between them. In an attempt to reveal the nature of two concepts, we reviewed broad literature surrounding uncertainty and intolerance of uncertainty (IU). We followed the process in which the whole IU theory developed and extended, including two aspects: (1) from uncertainty to intolerance of uncertainty and (2) definition of uncertainty and intolerance of uncertainty, and further concluded uncertainty fuels to negative emotions, biased expectancy, and inflexible response. Secondly, this paper summarized the experimental research concerning uncertainty and IU, consisted of three parts: (1) uncertainty-based research, (2) measurements of IU, and (3) domain-specific IU. Lastly, we pointed out what remains unknown and needed to be investigated in future research. This result provides a comprehensive overview in this domain, enhancing our understanding of uncertainty and IU and contributing to further theoretical and empirical explorations.

Background: Major depressive disorder (MDD) is an affective disorder that is harmful to both physical and mental health. Abnormal self-knowledge, which refers to abnormal judgments about oneself, is a core symptom of depression. However, little research has summarized how and why patients with MDD differ from healthy individuals in terms of self-knowledge. Objective: To gain a better understanding of MDD, we reviewed previous studies that focused on the behavioral and neurological changes of self-knowledge in this illness. Main Findings: On the behavioral level, depressed individuals exhibited negative self-knowledge in an explicit way, while more heterogeneous patterns were reported in implicit results. On the neurological level, depressed individuals, as compared with non-depressed controls, showed abnormal self-referential processing in both early perception and higher cognitive processing phases during the Self-Referential Encoding Task. Furthermore, fMRI studies have reported aberrant activity in the medial prefrontal cortex area for negative self-related items in depression. These results revealed several behavioral features and brain mechanisms underlying abnormal self-knowledge in depression. Future Studies: The neural mechanism of implicit self-knowledge in MDD remains unclear. Future research should examine the importance of others' attitudes on the self-concept of individuals with MDD, and whether abnormal self-views may be modified through cognitive or pharmacological approaches. In addition, differences in abnormal self-knowledge due to genetic variation between depressed and non-depressed populations remain unconfirmed. Importantly, it remains unknown whether abnormal self-knowledge could be used as a specific marker to distinguish healthy individuals from those with MDD. Conclusion: This review extends our understanding of the relationship between self-knowledge and depression by indicating several abnormalities among individuals with MDD and those who are at risk for this illness.

Smartphone Addiction is a social issue caused by excessive smartphone use, affecting decision-making processes. Current research on the risky decision-making abilities of smartphone addicts is limited. This study used the functional Near-Infrared Spectroscopy (fNIRS) brain imaging technique and a Sequential Risk-Taking Task experimental paradigm to investigate the decision-making behavior and brain activity of smartphone addicts under varying risk levels. Using a mixed experimental design, the research assessed decision-making ability and brain activation levels as dependent variables across two groups (addiction and control), two risk amounts (high and low), and two outcomes (gain and loss). The study included 42 participants, with 25 in the addiction group and 17 in the control group. Results indicated that risk level significantly impacted the decision-making ability of smartphone addicts, with high-risk levels leading to weaker decision-making ability and increased risk-taking. However, at low-risk levels, decision-making abilities between addicts and healthy individuals showed no significant difference. Furthermore, brain imaging results using fNIRS revealed stronger brain activation in the dorsolateral Prefrontal Cortex (dlPFC) region for smartphone addicts under loss outcome conditions, with no significant differences between the two groups in terms of brain activation at varying risk volumes. These findings are critical in promoting healthy smartphone use, guiding clinical treatment, and advancing brain mechanism research.