scholarly journals Cognitive-Processing Bias in Chinese Student Teachers with Strong and Weak Professional Identity

2017 ◽  
Vol 8 ◽  
Author(s):  
Xin-qiang Wang ◽  
Jun-cheng Zhu ◽  
Lu Liu ◽  
Xiang-yu Chen
Keyword(s):  
Professional Identity ◽  
Student Teachers ◽  
Cognitive Processing ◽  
Chinese Student ◽  
Processing Bias ◽  
Cognitive Processing Bias

scholarly journals Mental health status of Chinese residents during the COVID-19 epidemic

2020 ◽  
Author(s):  
Wen Jiang ◽  
Xuerong Liu ◽  
Jingxuan Zhang ◽  
Zhengzhi Feng
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Depressive Symptoms ◽  
Cognitive Processing ◽  
Multiple Logistic Regression Analysis ◽  
Anxiety Symptoms ◽  
Multiple Logistic Regression ◽  
Processing Bias ◽  
Cognitive Processing Bias

Abstract Background: To investigate the mental health status of Chinese residents during the epidemic of COVID-19, as well as to identify the positive and negative factors and regulatory effect of negative cognitive processing bias on mental health.Methods: A total of 60199 residents in China were surveyed via an internet-based survey containing a general questionnaire, such as the self-rating depression scale, the state anxiety inventory, and the negative cognitive processing bias questionnaire. An ordered multiple logistic regression analysis model was used to analyze the collected data. Results: The survey revealed mild, moderate, and severe depressive symptoms in 62.65%, 11.33%, and 6.14% participants, respectively, and mild, moderate, and severe anxiety symptoms in 33.21%, 41.27%, and 22.99% participants, respectively. Multiple logistic regression analysis showed that factors, such as female gender, being older than 55 years, high school education level, medical staff, marital conflicts, negative attention bias, rumination, and death growth rate, positively affected depression and anxiety symptoms. The good family functionality, democratic working atmosphere, and a myriad of social activities negatively affected the level of depressive and anxiety symptoms.Conclusion: Chinese residents exhibited a high prevalence of anxiety and depressive symptoms during the epidemic. Thus, psychological interventions should focus on the vulnerable groups, and cognitive training should focus on reducing the negative cognitive processing bias. This might be an effective way to alleviate the mental stress of the general public during the COVID-19 pandemic.

Anxiety and Ambiguity: It’s All Open to Interpretation

2002 ◽  
Vol 24 (3) ◽  
pp. 239-253 ◽  
Author(s):  
Martin Eubank ◽  
Dave Collins ◽  
Nick Smith
Keyword(s):  
Cognitive Processing ◽  
Negative Mood ◽  
Ambiguous Word ◽  
Ambiguous Information ◽  
Ambiguous Words ◽  
Modified Stroop ◽  
Processing Bias ◽  
Cognitive Processing Bias ◽  
Mood Condition ◽  
Negative Mood Condition

Beck’s (1976) theoretical account of emotional vulnerability predicts that individuals who are vulnerable to anxiety will exhibit a cognitive processing bias for the threatening interpretation of ambiguous information. As anxiety direction (Jones, 1995) may best account for individual differences, the aim of this study was to establish whether such processing bias is a function of anxiety interpretation. Anxiety facilitators and debilitators underwent a modified Stroop test by reacting to neutral and ambiguous word types in neutral, positive, and negative mood conditions. A significant 3-way interaction, F(4, 60) = 3.02, p < .05, was evident, with the reaction time of facilitators being slowest for ambiguous words in the positive mood condition and debilitators being slowest for ambiguous words in the negative mood condition. The findings illustrate the important role that anxiety interpretation plays in the mechanism involved in the processing of ambiguous information.

scholarly journals Mental health status of Chinese residents during the COVID-19 epidemic

2020 ◽  
Author(s):  
Wen Jiang ◽  
Xuerong Liu ◽  
Jingxuan Zhang ◽  
Zhengzhi Feng
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Depressive Symptoms ◽  
Health Status ◽  
Cognitive Processing ◽  
Multiple Logistic Regression Analysis ◽  
Multiple Logistic Regression ◽  
Processing Bias ◽  
Cognitive Processing Bias

Abstract Background: To investigate the mental health status of Chinese residents during the epidemic of COVID-19, identify the positive and negative factors and explore the regulatory effects of negative cognitive processing bias on mental health.Methods: Using a general questionnaire, such as the self-rating depression scale, the state anxiety inventory, and the negative cognitive processing bias questionnaire, an internet-based survey was conducted on 60199 residents in China. An ordered multiple logistic regression analysis model was used to analyze the collected data. Results: The survey showed that the incidences of mild, moderate, and severe depressive symptoms were 62.65%, 11.33%, and 6.14%, respectively, and that of mild, moderate and severe anxiety symptoms were 33.21%, 41.27%, and 22.99%, respectively. The results of ordered multiple logistic regression analysis showed that factors, such as female gender, age more than 55 years elderly, high school education level, medical staff, marital conflicts, negative attention bias, rumination, and death rate positively affected the level of depressive and anxiety symptoms. The good family functionality, democratic working atmosphere, and a myriad of social activities negatively affected the level of depressive and anxiety symptoms.Conclusion: The Chinese residents exhibited a high prevalence of anxiety and depressive symptoms during the epidemic. Thus, psychological interventions should focus on the vulnerable groups, and cognitive training should focus on reducing the negative cognitive processing bias that might be an effective way to alleviate the mental stress of the general public during the COVID-19 pandemic.

scholarly journals Mental health status of Chinese residents during the COVID-19 epidemic

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wen Jiang ◽  
Xuerong Liu ◽  
Jingxuan Zhang ◽  
Zhengzhi Feng
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Depressive Symptoms ◽  
Cognitive Processing ◽  
Multiple Logistic Regression Analysis ◽  
Anxiety Symptoms ◽  
Multiple Logistic Regression ◽  
Processing Bias ◽  
Cognitive Processing Bias

Abstract Background To investigate the mental health status of Chinese residents during the epidemic of COVID-19, as well as to identify the positive and negative factors and regulatory effect of negative cognitive processing bias on mental health. Methods A total of 60,199 residents in China were surveyed via an internet-based survey containing a general questionnaire, such as the self-rating depression scale, the state anxiety inventory, and the negative cognitive processing bias questionnaire. An ordered multiple logistic regression analysis model was used to analyze the collected data. Results The survey revealed mild, moderate, and severe depressive symptoms in 62.65, 11.33, and 6.14% participants, respectively, and mild, moderate, and severe anxiety symptoms in 33.21, 41.27, and 22.99% participants, respectively. Multiple logistic regression analysis showed that factors, such as female gender, being older than 55 years, high school education level, medical staff, marital conflicts, negative attention bias, rumination, and death growth rate, positively affected depression and anxiety symptoms. The good family functionality, democratic working atmosphere, and a myriad of social activities negatively affected the level of depressive and anxiety symptoms. Conclusion Chinese residents exhibited a high prevalence of anxiety and depressive symptoms during the epidemic. Thus, psychological interventions should focus on the vulnerable groups, and cognitive training should focus on reducing the negative cognitive processing bias. This might be an effective way to alleviate the mental stress of the general public during the COVID-19 pandemic.

scholarly journals Mental health status of Chinese residents during the COVID-19 epidemic

2020 ◽  
Author(s):  
Wen Jiang ◽  
Xuerong Liu ◽  
Jingxuan Zhang ◽  
Jia Wang ◽  
Zhengzhi Feng
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Health Status ◽  
Cognitive Processing ◽  
Logistic Regression Analysis ◽  
Multiple Logistic Regression Analysis ◽  
Multiple Logistic Regression ◽  
Processing Bias ◽  
Cognitive Processing Bias

Abstract Background: To investigate the mental health status of Chinese residents during the epidemic of COVID-19 and identify the positive and negative factors affecting mediating effects of negative cognitive processing bias on mental health. Methods: Using a general questionnaire, such as the self-rating depression scale, the state anxiety inventory, and the negative cognitive processing bias questionnaire, an internet-based survey was conducted on 60199 residents in China. An ordered multiple logistic regression analysis model was used to analyze the collected data. Results: The survey showed that the incidences of mild, moderate, and severe depression were 62.65%, 11.33%, and 6.14%, respectively, and that of mild, moderate and severe anxiety were 33.21%, 41.27%, and 22.99%, respectively. The results of ordered multiple logistic regression analysis showed that factors, such as female gender, age more than 55 years elderly, high school education level, medical staff, marital conflicts, negative attention bias, rumination, and death rate positively affected the level of depression and anxiety. The good family functionality, democratic working atmosphere, and a myriad of social activities negatively affected the level of depression and anxiety.Conclusion: The Chinese residents exhibited a high prevalence of anxiety and depression during the epidemic. Thus, psychological interventions should focus on the vulnerable groups, and cognitive training should focus on reducing the negative cognitive processing bias that might be an effective way to alleviate the mental stress of the general public during the COVID-19 pandemic.

scholarly journals Mental health status of Chinese residents during the COVID-19 epidemic

2020 ◽  
Author(s):  
Wen Jiang ◽  
Xuerong Liu ◽  
Jingxuan Zhang ◽  
Zhengzhi Feng
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Depressive Symptoms ◽  
Cognitive Processing ◽  
Multiple Logistic Regression Analysis ◽  
Anxiety Symptoms ◽  
Multiple Logistic Regression ◽  
Processing Bias ◽  
Cognitive Processing Bias

Abstract Background: To investigate the mental health status of Chinese residents during the epidemic of COVID-19, as well as to identify the positive and negative factors and regulatory effect of negative cognitive processing bias on mental health.Methods: A total of 60199 residents in China were surveyed via an internet-based survey containing a general questionnaire, such as the self-rating depression scale, the state anxiety inventory, and the negative cognitive processing bias questionnaire. An ordered multiple logistic regression analysis model was used to analyze the collected data. Results: The survey revealed mild, moderate, and severe depressive symptoms in 62.65%, 11.33%, and 6.14% participants, respectively, and mild, moderate, and severe anxiety symptoms in 33.21%, 41.27%, and 22.99% participants, respectively. Multiple logistic regression analysis showed that factors, such as female gender, being older than 55 years, high school education level, medical staff, marital conflicts, negative attention bias, rumination, and death growth rate, positively affected depression and anxiety symptoms. The good family functionality, democratic working atmosphere, and a myriad of social activities negatively affected the level of depressive and anxiety symptoms.Conclusion: Chinese residents exhibited a high prevalence of anxiety and depressive symptoms during the epidemic. Thus, psychological interventions should focus on the vulnerable groups, and cognitive training should focus on reducing the negative cognitive processing bias. This might be an effective way to alleviate the mental stress of the general public during the COVID-19 pandemic.

Sign in / Sign up

Export Citation Format

Share Document