scholarly journals Influence of Biomedical Factors on the Five Viscera Score (FVS) on Middle-Aged and Elderly Individuals: Application of Structural Equation Modeling

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Taro Tomura ◽  
Kouichi Yoshimasu ◽  
Shunji Sakaguchi ◽  
Kanami Tsuno ◽  
Shigeki Takemura ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Medical Data ◽  
Equation Modeling ◽  
Age Group ◽  
Middle Aged ◽  
Elderly Individuals ◽  
Objective Evidence ◽  
Significant Difference

The five viscera score (FVS) is a diagnostic scale for traditional Chinese medicine (TCM). The purposes of current study are to elucidate the characteristics of FVS obtained from middle-aged to elderly individuals and to investigate the validity of FVS using biological medical data of middle-aged and elderly individuals. Structural equation modeling (SEM) was used to conduct assessments between FVS and medical data. Eighty men and 99 women participated in this study, whose mean ages (SD) were 58 ± 7 years in both genders showing no significant difference. FVS of women was significantly higher than that of men in the spleen of the 50s (P=0.019) and liver of the 60s age group (P=0.030). By SEM, the following biomedical factors were found to influence viscera: gender, diastolic blood pressure, and HDL-C for the liver; GLU, GOT, andγ-GTP for the spleen; age, BMI, and HCRP for the lungs; and HbA1c and creatinine clearance for the kidneys. These results provide objective evidence that FVS can be used for TCM diagnosis in middle-aged and elderly individuals.

scholarly journals Hubungan Motivasi Belajar IPA, Pengetahuan Awal IPA, Dan Hasil Belajar IPA, Serta Identifikasi Perbedaan Hubungan Berdasar Perspektif Pesisir

2018 ◽  
Vol 6 (02) ◽  
pp. 127-139
Author(s):  
Siti Aisiyah ◽  
Anik Anekawati ◽  
Nisfil Maghfiroh Meita
Keyword(s):  
Structural Equation Modeling ◽  
Prior Knowledge ◽  
Structural Equation ◽  
Living Environment ◽  
Learning Motivation ◽  
Equation Modeling ◽  
Learning Achievement ◽  
Significant Difference ◽  
Good Learning ◽  
The Relationship

Students of Junior High School 2 Saronggi come from coastal and non-coastal areas. The differences in the living environment will bring out a different experiences, which in turn form a diverse prior knowledge because there is a correlation between the students' experience and prior knowledge. Prior knowledge of students shows readiness to receive lessons. A student who is ready to accept learning will influence learning achievement positively. Good learning readiness results in a high of self-confidence and will focus on learning which is a characteristic of high learning motivation, therefore, it will achieve good learning achievement. The purpose of this study is to determine the relationship among learning motivation, prior knowledge, and learning achievement, and identify differences in the relationship among three variables between coastal and non-coastal students. The method in this study using experimental design One-Short Case Study, while the method of data analysis using the analysis of structural equation modeling (SEM). The results showed that there were significant correlations between the prior knowledge and learning achievement, between the prior knowledge and learning motivation, between learning motivation and learning achievement, and there was the significant difference in the relationship among learning motivation, prior knowledge and learning achievement between coastal and non-coastal students.   Keywords: Science learning outcomes, learning motivation, science knowledge, SEM Abstrak Siswa SMPN 2 Saronggi berasal dari daerah pesisir dan bukan pesisir. Perbedaan lingkungan tempat tinggal akan menumbuhkan pengalaman yang berbeda, yang selanjutnya membentuk pengetahuan awal yang beragam, karena terdapat keterkaitan antara pengalaman dan pengetahuan awal siswa. Pengetahuan awal siswa menggambarkan kesiapan untuk menerima pelajaran. Siswa yang siap untuk menerima pembelajaran akan mempengaruhi hasil belajar secara positif. Kesiapan belajar yang baik memunculkan rasa percaya diri yang tinggi dan akan fokus untuk belajar yang merupakan ciri motivasi belajar tinggi, sehingga akan mencapai hasil belajar yang baik. Tujuan penelitian ini untuk mengetahui hubungan motivasi belajar IPA, pengetahuan awal IPA, dan hasil belajar IPA, serta mengidentifikasi perbedaan hubungan ketiga variabel tersebut antara siswa pesisir dan bukan pesisir. Metode pada penelitian ini menggunakan eksperimen dengan desain One-Short Case Stud, sedangkan metode analisis data menggunakan  analisis structural equation modeling (SEM). Hasil penelitian menunjukkan bahwa adanya hubungan yang signifikan antara pengetahuan awal IPA dan hasil belajar IPA, antara pengetahuan awal IPA dan motivasi belajar IPA, antara motivasi belajar IPA dan hasil belajar IPA, dan terdapat perbedaan yang signifikan hubungan motivasi belajar IPA, pengetahuan awal IPA dan hasil belajar IPA antara siswa pesisir dan bukan peisisir.

scholarly journals The Relationship between Patient Safety Climate and Medical Error Reporting Rate among Iranian Hospitals Using a Structural Equation Modeling

2020 ◽  
Vol 30 (3) ◽  
Author(s):  
Mostefa Shahabinejad ◽  
Hadi Khoshab ◽  
Kazem Najafi ◽  
Aboutalem Haghshenas
Keyword(s):  
Patient Safety ◽  
Structural Equation Modeling ◽  
Medical Error ◽  
Structural Equation ◽  
Safety Climate ◽  
Error Reporting ◽  
Equation Modeling ◽  
Patient Safety Climate ◽  
Significant Difference ◽  
The Relationship

BACKGROUND: Improving patient safety is a global health imperative, and patient safety climate is one of the components one that plays an important role in promoting patient safety. Medical error reporting is a way through which it can be evaluated and prevented in the future. The aim of this study was to assess the relationship between patient safety climate and medical error reporting in military and civilian hospitals.METHODS: This research was conducted by using structural equation modeling in the selected hospitals of Iran in 2018. The study community consisted of 200 nurses in the military and 400 nurses in the civilian hospitals. By using Structural Equation Modeling, the relationship between patient safety climate and the rate of medical error reporting in the hospitals was measured by a questionnaire. Data was analyzed using SPSS 17 and LISREL 8.8 software.RESULTS: The mean score of patient safety climate was moderate in the hospitals. There was no significant relationship between the rate of medical error reporting and patient safety climate, while a significant difference was found between patient safety climate score and age, sex, job category, and type of hospital (P < 0.05).CONCLUSION: The results suggested that patient safety climate and the rate of reporting errors were not favorable in the studied hospitals, while there was a difference between safety climate dimensions.

scholarly journals HUBUNGAN ANTARA RAWAN BOSAN DAN KEMUDAHAN TERTIDUR DENGAN MICROSLEEP SAAT MENGEMUDI

2021 ◽  
Vol 4 (3) ◽  
pp. 729
Author(s):  
Arjun Indru Moorjani ◽  
Leksmono Suryo Putranto
Keyword(s):  
Structural Equation Modeling ◽  
Epworth Sleepiness Scale ◽  
Structural Equation ◽  
Sem Analysis ◽  
Equation Modeling ◽  
Analysis Method ◽  
Falling Asleep ◽  
Significant Difference ◽  
Scale Scores ◽  
Boredom Proneness

One of the most common types of sleepiness experienced by drivers is microsleep. Microsleep causes the driver to lose control of his or her vehicle, resulting in accidents that could be fatal. This study aims to determine the effect of boredom proneness and the driver's level of ease of falling asleep on the frequency of occurrence of microsleep while driving. Boredom proneness and ease of falling asleep were measured using questions adopted from the Boredom proneness Scale and Epworth Sleepiness Scale, respectively, while microsleep was calculated using a questionnaire to determine the frequency of microsleep experienced by the driver. The research data were analyzed using the Structural Equation Modeling (SEM) analysis method to calculate the correlation value between research variables. The results of the analysis show that boredom proneness and ease of falling asleep are significantly and positively correlated with the likelihood of someone experiencing microsleep while driving, where boredom proneness is also positively and significantly correlated with ease of falling asleep. There was no significant difference found in the Boredom proneness Scale scores, Epworth Sleepiness Scale scores, and frequency of experiencing microsleep whilst driving between the genders ABSTRAKSalah satu jenis kantuk yang paling sering dialami oleh pengemudi dalam berkendara adalah microsleep. Microsleep mengakibatkan pengemudi kehilangan kontrol akan kendaraannya, sehingga berakibat sangat fatal terhadap keselamatan berkendara. Penelitian ini bertujuan untuk mengetahui pengaruh boredom proneness (kecenderungan merasa bosan) dan tingkat kemudahan tertidur pengemudi terhadap frekuensi terjadinya microsleep pada saat berkendara. Boredom proneness dan kemudahan tertidur masing-masing diukur menggunakan pertanyaan-pertanyaan yang diadopsi dari Boredom proneness Scale dan Epworth Sleepiness Scale, sedangkan microsleep dihitung menggunakan kuesioner untuk menentukan frekuensi microsleep yang dialami pengemudi. Data penelitian dianalisa menggunakan metode analisis Structural Equation Modeling (SEM) untuk menghitung nilai korelasi antar variabel penelitian. Hasil analisis menunjukkan bahwa boredom proneness dan kemudahan tertidur berkorelasi secara signifikan dan positif terhadap kemungkinan seseorang mengalami microsleep saat mengemudi, dimana boredom proneness juga berkorelasi secara positif dan signifikan terhadap kemudahan tertidur. Tidak ditemukan perbedaan signifikan pada tingkat kecenderungan pengemudi merasa bosan (boredom proneness), mudah tertidur, dan mengalami microsleep di antara jenis kelamin. Mereka yang berusia di bawah 30 tahun ditemukan lebih mudah untuk merasa bosan, sehingga lebih rentan untuk mengalami microsleep pada saat mengemudi.

Correspondence Between the General Ability to Discriminate Sensory Stimuli and General Intelligence

2010 ◽  
Vol 31 (1) ◽  
pp. 46-56 ◽  
Author(s):  
Christine Sandra Meyer ◽  
Priska Hagmann-von Arx ◽  
Sakari Lemola ◽  
Alexander Grob
Keyword(s):  
Structural Equation Modeling ◽  
Strong Correlation ◽  
Structural Equation ◽  
Equation Modeling ◽  
General Intelligence ◽  
Age Group ◽  
Discrimination Factor ◽  
Sensory Stimuli ◽  
Sensory Discrimination ◽  
General Ability

For more than a century the veracity of Spearman’s postulate that there is a nearly perfect correspondence between general intelligence and general sensory discrimination has remained unresolved. Most studies have found significant albeit small correlations. However, this can be used neither to confirm nor dismiss Spearman’s postulate, a major weakness of previous research being that only single discrimination capacities were considered rather than general discrimination. The present study examines Spearman’s hypothesis with a sample of 1,330 5- to 10-year-old children, using structural equation modeling. The results support Spearman’s hypothesis with a strong correlation (r = .78). Results are discussed in terms of the validity of the general sensory discrimination factor. In addition, age-group-specific analyses explored the age differentiation hypothesis.

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