The Effectiveness of a Virtual Reality Marketing Video on the People Desire to Buy a Product

Virtual Reality technology can provide new experiences and different points of view of activities, events, or products for the users. In line with advances from VR technology, YouTube initiates to support the spread of VR videos by creating a VR feature on their platform. A hundred videos about a dangerous activity, Horror activity, and Marketing video of software or a movie product are found on the YouTube platform. Meanwhile, it is still not yet known how the effectiveness of an advertisement using VR video via the YouTube platform on the people desires to buy a product, especially in Indonesia, which then became the purpose of this study. In carrying out this study, a quantitative study was used by creating a digital questionnaire and distributed it with Google Forms. Then the data obtained will be processed by the respondent demographics and the 4 types of analysis, such as the Validity analysis, the Reliability analysis, the Ranking of VR applications on product promotions, and the Correlation analysis. Afterward, the study found that the B1 and B2 variables refer to Advertising, making it easy for us to understand the product has the most correlation coefficient. Moreover, 80% of the respondents stated that they like the VR advertisement product. It means that people are interested in trying and feel something new in the way VR technology is given to them. Ultimately, the respondents agree that VR advertising has informed them well about the product.

Measuring Internet Gaming Disorder and Gaming Disorder: A Qualitative Content Validity Analysis of Validated Scales

Numerous instruments have been developed to measure gaming-related health problems based on “internet gaming disorder” (IGD) in the third section of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) and “gaming disorder” (GD) in the International Classification of Diseases (11th rev.). However, the criteria in the manuals tend to be operationalized in numerous diverse ways, which can make screening outcomes incomparable. A content validity analysis is needed to reassess the relationships between the diagnostic criteria and the items that operationalize them. The IGD and GD criteria were divided into sematic components. A qualitative content validity analysis was carried out for all items employed by the 17 instruments that claim to measure either construct by their criteria in English. In all but one instrument, the operationalizations did not include all criterion components. There were two main reasons found for this: the components had simply been left out or had been alternatively modified into other components. Criteria that were vaguely described in the manuals were sources of lower content validity items. The study implies that many of the problems in IGD and GD measurement derive from criteria operationalization and original manual descriptions. The conclusion provides practical recommendations that researchers can apply to improve the content validity of their measurement.

THE USE OF THE RASCH MODEL IN ANALYSING THE VALIDITY AND RELIABILITY OF STUDENTS’ COPING STRATEGY SCALE

This research is part of the standardization of the Students' Coping Strategy Scale (SCSS). This study aims to reveal the content validity, empirical validity, and reliability of the SCSS. The non-test instrument consisting of 42 statements from three dimensions: problem-focused coping, emotion-focused coping, and seeking social support. Content validity analysis was carried out by experts to obtain Gregory's content validity coefficient, while the empirical validity and reliability analysis by empirically testing the instrument on 211 respondents and analyzed using the Rasch model approach. The results show that Gregory's content validity coefficient is 0.714, so it needs improvement on some items that are considered unsuitable. Empirical validity analysis using WINSTEPS software shows that three items do not fit the model. The reliability coefficient of the SCSS is 0.99. Thus, the remaining 39 items are appropriate to be used to measure students' coping strategies.

WORK ENVIRONMENT FACTORS IN AFFECTING EMPLOYEE PERFORMANCE

This study aims to determine the effect of the work environment on the performance of the employees of the Public Administration Section of the Pematangsiantar City Regional Secretariat, totaling 28 employees. For the results of the validity analysis, it was found that the results were valid and for reliability the results were reliable. For the results of normality, it is concluded that the data is normally distributed, with a coefficient of determination of 36% while the rest is influenced by other factors and the correlation value of the variables is included in the strong category. The regression equation shows positive equation results and the hypothesis results provide an answer that partially, the work environment has a positive and significant effect on employee performance, because the work environment is the most important factor in achieving employee performance.

A note on the validity of the Schrödinger approximation for the Helmholtz equation

Time-harmonic electromagnetic waves in vacuum are described by the Helmholtz equation Δ ⁢ u + ω 2 ⁢ u = 0 for ⁢ ( x , y , z ) ∈ ℝ 3 . \Delta u+\omega^{2}u=0\quad\text{for }(x,y,z)\in{\mathbb{R}}^{3}. For the evolution of such waves along the z-axis, a Schrödinger equation can be derived through a multiple scaling ansatz. It is the purpose of this paper to justify this formal approximation by proving bounds between this formal approximation and true solutions of the original system. The challenge of the presented validity analysis is the fact that the Helmholtz equation is ill-posed as an evolutionary system along the z-axis.

An Integrated Radiomics Model Incorporating Diffusion-Weighted Imaging and 18F-FDG PET Imaging Improves the Performance of Differentiating Glioblastoma From Solitary Brain Metastases

BackgroundThe effectiveness of conventional MRI (cMRI)-based radiomics in differentiating glioblastoma (GBM) from solitary brain metastases (SBM) is not satisfactory enough. Therefore, we aimed to develop an integrated radiomics model to improve the performance of differentiating GBM from SBM.MethodsOne hundred patients with solitary brain tumors (50 with GBM, 50 with SBM) were retrospectively enrolled and randomly assigned to the training set (n = 80) or validation set (n = 20). A total of 4,424 radiomic features were obtained from contrast-enhanced T1-weighted imaging (CE-T1WI) with the contrast-enhancing and peri-enhancing edema region, T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC), and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) images. The partial least squares (PLS) regression with fivefold cross-validation is used to analyze the correlation between different radiomic features and different modalities. The cross-validity analysis was performed to judge whether a new principal component or a new feature dimension can significantly improve the final prediction effect. The principal components with effective interpretation in all radiomic features were projected to a low-dimensional space (2D in this study). The effective features of the new projection mapping were then sent to the random forest classifier to predict the results. The performance of differentiating GBM from SBM was compared between the integrated radiomics model and other radiomics models or nonradiomics methods using the area under the receiver operating characteristics curve (AUC).ResultsThrough the cross-validity analysis of partial least squares, hundreds of radiomic features were projected into a new two-dimensional space to complete the construction of radiomics model. Compared with the combined radiomics model using DWI + 18F-FDG PET (AUC = 0.93, p = 0.014), cMRI + DWI (AUC = 0.89, p = 0.011), cMRI + 8F-FDG PET (AUC = 0.91, p = 0.015), and single radiomics model using cMRI (AUC = 0.85, p = 0.018), DWI (AUC = 0.84, p = 0.017), and 18F-FDG PET (AUC = 0.85, p = 0.421), the integrated radiomics model (AUC = 0.98) showed more efficient diagnostic performance. The integrated radiomics model (AUC = 0.98) also showed significantly better performance than any single ADC, SUV, or TBR parameter (AUC = 0.57–0.71, p < 0.05). The integrated radiomics model showed better performance in the training (AUC = 0.98) and validation (AUC = 0.93) sets than any other models and methods, demonstrating robustness.ConclusionsWe developed an integrated radiomics model incorporating DWI and 18F-FDG PET, which improved the performance of differentiating GBM from SBM greatly.