The success of the Saudi Human Genome Program (SHGP), one of the top ten genomic programs worldwide, is highly dependent on the Saudi population embracing the concept of participating in genetic testing. However, genetic data sharing and artificial intelligence (AI) in genomics are critical public issues in medical care and scientific research. The present study was aimed to examine the awareness, knowledge, and attitude of the Saudi society towards the SHGP, the sharing and privacy of genetic data resulting from the SHGP, and the role of AI in genetic data analysis and regulations. Results of a questionnaire survey with 804 respondents revealed moderate awareness and attitude towards the SHGP and minimal knowledge regarding its benefits and applications. Respondents demonstrated a low level of knowledge regarding the privacy of genetic data. A generally positive attitude was found towards the outcomes of the SHGP and genetic data sharing for medical and scientific research. The highest level of knowledge was detected regarding AI use in genetic data analysis and privacy regulation. We recommend that the SHGP’s regulators launch awareness campaigns and educational programs to increase and improve public awareness and knowledge regarding the SHGP’s benefits and applications. Furthermore, we propose a strategy for genetic data sharing which will facilitate genetic data sharing between institutions and advance Personalized Medicine in genetic diseases’ diagnosis and treatment.
Introduction Public awareness regarding COVID-19 plays an important role in controlling the virus’ spread and treating infected people. A high level of awareness among the public will help to implement preventive measures, particularly in the most populated regions, such as Makkah, Saudi Arabia. COVID-19 is an infectious disease and the Saudi Arabian government has taken serious precautions and implemented several preventive measures. In addition, The Ministry of Health (MOH) has launched many awareness campaigns and provided COVID-19 vaccines for free. The objectives To assess the Public's level of health awareness and knowledge toward SARS-CoV-2 and COVID-19 vaccines among residents of Makkah, Saudi Arabia. Methods A cross-sectional study was conducted in the Makkah region from February 23 to March 2, 2021. The questionnaire was generated using a Google form and distributed online through social platforms such as Twitter and WhatsApp. The questionnaire consisted of five sections and six hundred participants have answered and completed all questions. Then, All data were imported into Microsoft Excel and analyzed using the statistical tools SAS version 9.4 and SPSS version 25 software. Results A total of 600 participants from the Makkah region were found to have a high level of awareness and knowledge about all aspects of SARS-CoV-2 and the COVID-19 disease. For example, all participants considered coronavirus to be contagious, and 89.8% of them knew that COVID-19's symptoms are similar to those of seasonal flu. Most respondents showed a high level of awareness regarding the main factors of SARS-CoV-2 transmission. Over 98.7% of respondents were aware of the role of gatherings and events in further spread of the virus. The participants showed a good level of awareness about other preventive measures, such as maintaining social distancing and wearing a mask. However, the respondents considered COVID-19 vaccines to be effective, but some of them were not aware of their side effects, and 38.8% planned to receive a vaccine. Conclusion The residents of Makkah showed a high level of awareness about these aspects; an excellent awareness level was noted for SARS-CoV-2, means of transmission, disease symptoms and prevention of viral spread. On the other hand, the participants had less knowledge regarding COVID-19 vaccines; hence, more effort is required to educate people about the safety and benefits of the vaccines.
Factor Analysis (FA) is the study of variance within a group. Within-Subject Variance (WSV) is affected by multiple features in a study context such as the Experimental Design (ED) or the Sampling Design (SD). The aim of this study is to provide an empirical evaluation of the influence of different aspects of ED and SD on WSV in the context of FA in terms of model precision. The study results showed that the precisions of the overall model fit indices TLI and CFI, as functions of VTF, STV, h2, and their interaction, varied, as did the precisions of the overall model fit indices GFI, AGFI, and RMSEA as functions of VTF, STV, and their interactions. Overall, when the VTF is 4:1 or 7:1, the required STV is 16:1 or above 32:1 or above to show precision in factor solution.
The aim of the current study is to provide improvement evaluation practices in the educational process. A multiple choice test was developed, which was based on content analysis and the test specification table covered some of the vocabulary of the applied statistics course. The test in its final form consisted of 18 items that were reviewed by specialists in the field of statistics to determine their validity. The results determine the relationship between individual responses and the student ability. Most thresholds span the negative section of the ability. Item information curves show that the items provide a good amount of information about a student with lower or moderate ability compared to a student with high ability. In terms of precision, most items were more convenient with lower ability students. The test characteristic curve was plotted according to the change in the characteristics of the examinees. The information obtained by female students appeared to be more than the information obtained by male students and the test provided more information about students who were not studying statistics in an earlier stage compared with students who did. This test clearly indicated that, based on the level of the statistics course, there should be a periodic review of the tests in line with the nature and level of the course materials in order to have a logical judgment about the level of the students’ progress at the level of their ability.
The aim of this study is to provide an empirical evaluation of the influence of different aspects of design in the context of factor analysis in terms of model stability. The overall model stability of factor solutions was evaluated by the examination of the order for testing three levels of Measurement Invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (Δx2) between two groups, and Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and Tucker-Lewis Index (TLI). Factorial invariance results revealed that the stability of the models was varying over increasing levels of measurement as a function of Variable-To-Factor (VTF) ratio, Subject-To-Variable (STV) ratio, and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratios 4:1, 7:1, and 10:1, the models started to show stability over the levels of measurement when the STV ratio was 4:1. Yet, the frequency of stability models over 1000 replications increased (from 77% to 91%) as the STV ratio increased. The models showed more stability at or above 32:1 STV.
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