Yebing Yang

Bifactor item response theory model of acute stress response.

Background Better understanding of acute stress responses is important for revision of DSM-5. However, the latent structure and relationship between different aspects of acute stress responses haven’t been clarified comprehensively. Bifactor item response model may help resolve this problem. Objective The purpose of this study is to develop a statistical model of acute stress responses, based on data from earthquake rescuers using Acute Stress Response Scale (ASRS). Through this model, we could better understand acute stress responses comprehensively, and provide preliminary information for computerized adaptive testing of stress responses. Methods Acute stress responses of earthquake rescuers were evaluated using ASRS, and state/trait anxiety were assessed using State-trait Anxiety Inventory (STAI). A hierarchical item response model (bifactor model) was used to analyze the data. Additionally, we tested this hierarchical model with model fit comparisons with one-dimensional and five-dimensional models. The correlations among acute stress responses and state/trait anxiety were compared, based on both the five-dimensional and bifactor models. Results Model fit comparisons showed bifactor model fit the data best. Item loadings on general and specific factors varied greatly between different aspects of stress responses. Many symptoms (40%) of physiological responses had positive loadings on general factor, and negative loadings on specific factor of physiological responses, while other stress responses had positive loadings on both general and specific factors. After extracting general factor of stress responses using bifactor analysis, significant positive correlations between physiological responses and state/trait anxiety (r = 0.185/0.112, p<0.01) changed into negative ones (r = −0.177/−0.38, p<0.01). Conclusion Our results demonstrated bifactor structure of acute stress responses, and positive and negative correlations between physiological responses and stress responses suggested physiological responses could have negative feedback on severity of stress responses. This finding has not been convincingly demonstrated in previous research.

A Real Data Simulation Study of Computerized Adaptive Testing of Chinese Soldier Personality Questionnaire

A real data simulation study of computerized adaptive testing (CAT) of Chinese soldier personality questionnaire (CSPQ) was conducted to find out the feasibility of using count-down method to realize the CAT of personality questionnaire. The data was from 100,125 normal Chinese young people. All participants were male, and the mean age of the individuals was 18.3 (range 16-21, SD = 2.5). The data included two parts, one part was collected in 2005 including 47,550 subjects, the other was collected in 2006 including 52,575 subjects. The first part was used to compute the frequencies of item endorsement and the scalability coefficient H. According to the results three item presentation orders were determined. And the second part was used to compare these presentation orders. Results showed that the original order had the worst efficiency, the other two orders had similar results. But all orders can bring great improvement to efficiencies. From this study we can see count-down method can be used in the CAT of CSPQ. At last the test was divided into two stages. Items, which belong to at least two dimensions, were presented first, then the rest items were presented according to the third order. And under the two-stage testing, new method to realize CAT of CSPQ was put forward. But this is just a simulation study, the item savings and validity of the CAT of CSPQ have to be investigated in the further real testing.