The present study investigated how trait anxiety influenced the formation of a self-frame and decision making. Participants (N = 1044) responded to the Trait Anxiety Inventory. Those with trait anxiety scores AE1 Z score from the sample mean (N = 328) were recalled to respond to the self-frame questionnaire. The results suggested that trait anxiety differences could result in differences in the editing of decision-making information, thereby influencing the risky choice. Compared with the low trait anxiety group, participants from the high trait anxiety group showed a greater tendency to use negative vocabulary to construct their self-frame and tended to choose conservative plans. Self-frame suppressed the influence of trait anxiety on decision making. These results further confirmed the hypothesis that individual differences in personality traits might influence the processing of information in a framed decision task.

BackgroundThe relationship between anxiety and depression in pain patients has not been clarified comprehensively. Previous research has identified a common factor in anxiety and depression, which may explain why depression and anxiety are strongly correlated. However, the specific clinical features of anxiety and depression seem to pull in opposite directions.ObjectiveThe purpose of this study is to develop a statistical model of depression and anxiety, based on data from pain patients using Hospital Anxiety and Depression Scale (HADS). This model should account for the positive correlation between depression and anxiety in terms of a general factor and also demonstrate a latent negative correlation between the specific factors underlying depression and anxiety.MethodsThe anxiety and depression symptoms of pain patients were evaluated using the HADS and the severity of their pain was assessed with the visual analogue scale (VAS). We developed a hierarchical model of the data using an IRT method called bifactor analysis. In addition, we tested this hierarchical model with model fit comparisons with unidimensional, bidimensional, and tridimensional models. The correlations among anxiety, depression, and pain severity were compared, based on both the bidimensional model and our hierarchical model.ResultsThe bidimensional model analysis found that there was a large positive correlation between anxiety and depression (r = 0.638), and both scores were significantly positively correlated with pain severity. After extracting general factor of distress using bifactor analysis, the specific factors underlying anxiety and depression were weakly but significantly negatively correlated (r = −0.245) and only the general factor was significantly correlated with pain severity. Compared with the three first-order models, the bifactor hierarchical model had the best model fit.ConclusionOur results support the hypothesis that apart from distress, anxiety and depression are inversely correlated. This finding has not been convincingly demonstrated in previous research.

In this study, the relationships among psychological health and self-efficacy, social support, and coping strategies soon after a devastating natural disaster was explored using path analysis, in order to provide guidelines for early psychological intervention. Participants comprised 172 senior middle-school students, in the stricken area of the May 2008 earthquake in Wenchuan, China, of whom 167 completed the scales. Three different models were tested consecutively and compared. According to the model that provided the best fit to the data, emotion-focused coping significantly predicted psychological problems, while subjective social support and problem-focused coping significantly predicted self-efficacy. The results showed that soon after a disaster, the most important mediating factor for people is emotional regulation.

"512 PIM" was an effective psychological intervention for military rescuers in reducing symptoms of PTSD, anxiety and depression after a crisis.

In this study we developed a scale to provide a tool for accurate assessment of acute stress response (ASR). We determined the dimensions and symptom clusters of ASR according to a review of the literature and through interviews with psychologists, and then compiled corresponding items, using these to compose the Acute Stress Response Scale (ASRS). We also investigated the construct validity, concurrent validity, test-retest reliability, and internal consistency reliability of this scale. The final version of the scale included 6 dimensions and 25 symptom clusters with comparatively satisfactory indices of validity and reliability, indicating that the ASRS can lay the foundation for the detection and objective and accurate assessment of ASR.