THE MIXTURE DISTRIBUTION POLYTOMOUS RASCH MODEL USED TO ACCOUNT FOR RESPONSE STYLES ON RATING SCALES: A SIMULATION STUDY OF PARAMETER RECOVERY AND CLASSIFICATION ACCURACY

Response styles presented in rating scale use have been recognized as an important source of systematic measurement bias in self-report assessment. People with the same amount of a latent trait may be a victim of a biased test score due to the construct's irrelevant effect of response styles. The mixture polytomous Rasch model has been proposed as a tool to deal with the response style problems. This model can be used to classify respondents with different response styles into different latent classes and provides person trait estimates that have been corrected for the effect of a response style. This study investigated how well the mixture partial credit model (MPCM) recovered model parameters under various testing conditions. Item responses that characterized extreme response style (ERS), middle-category response style (MRS), and acquiescent response style (ARS) on a 5-category Likert scale as well as ordinary response style (ORS), which does not involve distorted rating scale use, were generated. The study results suggested that ARS respondents could be almost perfectly classified from other response-style respondents while the distinction between MRS and ORS respondents was most difficult followed by the distinction between ERS and ORS respondents. The classifications were more difficult when the distorted response styles were present in small proportions within the sample. Ten-items and a sample size of 3000 appeared to warrant reasonable threshold and person parameter estimation under the simulated conditions in this study. As the structure of mixture of response styles became more complex, increased sample size, test length, and balanced mixing proportion were needed in order to achieve the same level of recovery accuracy. Misclassification impacted the overall accuracy of person trait estimation. BIC was found to be the most effective data-model fit statistic in identifying the correct number of latent classes under this modeling approach. The model-based correction of score bias was explored with up to four different response-style latent classes. Problems with the estimation of the model including non-convergence, boundary threshold estimates, and label switching were discussed

Adjunctive biomarkers for improving diagnosis of tuberculosis and monitoring therapeutic effects

SummaryObjectivesTo identify host biomarkers associated with latent tuberculosis infection (LTBI), active tuberculosis (TB), and nontuberculous mycobacteria (NTM) diseases to improve diagnosis and effective anti-TB treatment.MethodsActive TB and NTM patients at diagnosis, recent TB contacts, and normal healthy subjects were recruited. Tuberculin skin tests, QuantiFERON-TB Gold In-Tube tests, and multiplex bead arrays with 17 analytes were performed. TB patients were re-evaluated after 2 and 6 months of treatment.ResultsMycobacterium tuberculosis (M. tb) antigen-specific IFN-γ, IL-2, and CXCL10 responses were significantly higher in active TB and LTBI compared with controls (P < 0.01). Only serum VEGF levels varied between the active TB and LTBI groups (AUC = 0.7576, P < 0.001). Active TB and NTM diseases were differentiated by serum IL-2, IL-9, IL-13, IL-17, TNF-α and sCD40L levels (P < 0.05). Increased sCD40L and decreased M. tb antigen-specific IFN-γ levels correlated with sputum clearance of M. tb after 2 months of treatment (P < 0.001).ConclusionsSerum IL-2, IL-9, IL-13, IL-17, TNF-α, sCD40L and VEGF-A levels may be adjunctive biomarkers for differential diagnosis of active TB, LTBI, and NTM disease. Assessment of serum sCD40L and M. tb antigen-specific IFN-γ, TNF-α, and IL-2 levels could help predict successful anti-TB treatment in conjunction with M. tb clearance

Intrinsic nature of visible-light absorption in amorphous semiconducting oxides

To enlighten microscopic origin of visible-light absorption in transparent amorphous semiconducting oxides, the intrinsic optical property of amorphous InGaZnO4 is investigated by considering dipole transitions within the quasiparticle band structure. In comparison with the crystalline InGaZnO 4 with the optical gap of 3.6 eV, the amorphous InGaZnO4 has two distinct features developed in the band structure that contribute to significant visible-light absorption. First, the conduction bands are down-shifted by 0.55 eV mainly due to the undercoordinated In atoms, reducing the optical gap between extended states to 2.8 eV. Second, tail states formed by localized oxygen p orbitals are distributed over ∼0.5 eV near the valence edge, which give rise to substantial subgap absorption. The fundamental understanding on the optical property of amorphous semiconducting oxides based on underlying electronic structure will pave the way for resolving instability issues in recent display devices incorporating the semiconducting oxides. © 2014 Author(s).1881sciescopu

Anti-Inflammatory Effect of Angelica gigas via Heme Oxygenase (HO)-1 Expression

Angelica gigas (AG) is effective against various medical conditions such as bacterial infection, inflammation, and cancer. It contains a number of coumarin compounds and the group of interest is the pyranocoumarin, which comprises decursin and decursinol angelate. This group has an effect on controlling inflammation, which is caused by excessive nitric oxide (NO) production. Heme oxygenases (HOs), particularly HO-1, play a role in regulating the production of NO. Thus, this study aimed to investigate the anti-inflammatory effects of AG by measuring HO-1 expression. Treatments with CH2Cl2 layer and Angelica gigas extract (AGE) showed the highest NO inhibition effects. Decursin, decursinol angelate, and nodakenin were isolated from the CH2Cl2 layer of AGE. Decursin also demonstrated the highest anti-oxidative effect among the coumarins. Although decursin had the best NO inhibition and anti-oxidative effects, the effects of AGE treatment far surpassed that of decursin. This is owing to the combination effect of the coumarins present within AGE, which is a solvent extract of AG. The expression of HO-1 is an effective indicator of the anti-inflammatory effects of AG. Based on the results of the coumarin compounds, HO-1 expression was found to be dose dependent and specific to decursin

Effects of Multicomponent Oriental Integrative Intervention on Cognitive Function, Health Status, Life Satisfaction, and Yangsaeng of Community-Dwelling Elderly

The elderly population in South Korea is rapidly increasing. The elderly living in the community are looking for alternative and complementary methods to improve their healthy longevity and quality of life. This study aimed to examine the effects of Multicomponent Oriental Integrative Intervention on the cognitive function, health status, life satisfaction, and Yangsaeng of the Korean elderly living in the community. A quasi-experimental study design using a pretest&ndash;posttest control group was employed. Study participants were a total of 74 elderly (intervention: n = 37, control: n = 37) in Seoul, South Korea. Multicomponent Oriental Integrative Intervention was scheduled to hold two sessions a week, a total of sixteen sessions in 8 weeks, lasting 60 min per session. The measures were the general characteristics of the study participants, the Korean version of the Mini-Mental State Examination (MMSE-K), the Korean health status measure for the elderly, the Korean elderly life satisfaction scale, and the Yangsaeng measurement tool. Data were collected from March 2022 to May 2022. There were statistically significant differences in cognitive function, health status, life satisfaction, and Yangsaeng between the two groups. Multicomponent Oriental Integrative Intervention might be an effective intervention for improving the cognitive function, health status, life satisfaction, and Yangsaeng of the elderly living in the community. Health care providers need to pay attention to Multicomponent Oriental Integrative Intervention for the elderly living in the community

Healthcare Quality Improvement Analytics: An Example Using Computerized Provider Order Entry

Evaluation of sustainability after quality improvement (QI) projects in healthcare settings is an essential part of monitoring and future QI planning. With limitations in adopting quasi-experimental study design in real-world practice, healthcare professionals find it challenging to present the sustained effect of QI changes effectively. To provide quantitative methodological approaches for demonstrating the sustainability of QI projects for healthcare professionals, we conducted data analyses based on a QI project to improve the computerized provider order entry system to reduce patients’ dosing frequencies in Korea. Data were collected for 5 years: 24-month pre-intervention, 12-month intervention, and 24-month post-intervention. Then, analytic approaches including control chart, Analysis of Variance (ANOVA), and segmented regression were performed. The control chart intuitively displayed how the outcomes changed over the entire period, and ANOVA was used to test whether the outcomes differed between groups. Last, segmented regression analysis was conducted to evaluate longitudinal effects of interventions over time. We found that the impact of QI projects in healthcare settings should be initiated following the Plan–Do–Study–Act cycle and evaluated long-term effects while widening the scope of QI evaluation with sustainability. This study can serve as a guide for healthcare professionals to use a number of statistical methodologies in their QI evaluations