Test-retest reliability of the questionnaire in the Sasang constitutional analysis tool (SCAT)

Lee, Jeongyun; Yim, Mi Hong; Kim, Jong Yeol

doi:10.1016/j.imr.2018.02.001

Cited by 13 publications

(12 citation statements)

References 7 publications

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“…Even though there are several questionnaires for Sasang constitution-type diagnosis such as the KS-15 [ 17 ] and SCAT [ 18 ], in the KoGES cohort study, Sasang constitution type was assessed by two independent Korean medicine doctors to increase the accuracy. One Sasang constitution medicine specialist made a diagnosis of the participants' constitution based on analysis of face, voice, and questionnaire (Appendix 1).…”

Section: Methodsmentioning

confidence: 99%

Metabolic Syndrome Prediction Models Using Machine Learning and Sasang Constitution Type

Park

Mun

Lee

2021

Evidence-Based Complementary and Alternative Medicine

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Background. Machine learning may be a useful tool for predicting metabolic syndrome (MetS), and previous studies also suggest that the risk of MetS differs according to Sasang constitution type. The present study investigated the development of MetS prediction models utilizing machine learning methods and whether the incorporation of Sasang constitution type could improve the performance of those prediction models. Methods. Participants visiting a medical center for a health check-up were recruited in 2005 and 2006. Six kinds of machine learning were utilized (K-nearest neighbor, naive Bayes, random forest, decision tree, multilayer perceptron, and support vector machine), as was conventional logistic regression. Machine learning-derived MetS prediction models with and without the incorporation of Sasang constitution type were compared to investigate whether the former would predict MetS with higher sensitivity. Age, sex, education level, marital status, body mass index, stress, physical activity, alcohol consumption, and smoking were included as potentially predictive factors. Results. A total of 750/2,871 participants had MetS. Among the six types of machine learning methods investigated, multiplayer perceptron and support vector machine exhibited the same performance as the conventional regression method, based on the areas under the receiver operating characteristic curves. The naive-Bayes method exhibited the highest sensitivity (0.49), which was higher than that of the conventional regression method (0.39). The incorporation of Sasang constitution type improved the sensitivity of all of the machine learning methods investigated except for the K-nearest neighbor method. Conclusion. Machine learning-derived models may be useful for MetS prediction, and the incorporation of Sasang constitution type may increase the sensitivity of such models.

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Section: Methodsmentioning

confidence: 99%

Metabolic Syndrome Prediction Models Using Machine Learning and Sasang Constitution Type

Park

Mun

Lee

2021

Evidence-Based Complementary and Alternative Medicine

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“…These students have similar characteristics as the respondents of this study, but they did not partake in the study. The two sets of score were correlated using Pearson's Moment Correlation formula and a reliability co-efficient of .81 was gotten; this affirmed that the instrument was reliable for the study (Bolarinwa, 2015;Chiwaridzo et al, 2017;and Lee, Yim & Kim, 2018).…”

Section: Methodsmentioning

confidence: 79%

Factors Responsible for Students’ Unrest in Nigerian Tertiary Institutions: Implications for Counselling Practices

Odebode

2019

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This study, thus, investigated the factors responsible for students’ unrest in Nigerian Tertiary Institutions. Further investigation was also done based on moderating variables of age, gender, and religion if they would have any bearing on the participants’ views. The study was descriptive in nature. The sample consisted of one thousand and two hundred undergraduates, who were selected in six Universities in Nigeria using purposive, simple random, and systematic random techniques. A new questionnaire labelled FRSUQ (Factors Responsible for Students’ Unrest Questionnaire) was developed and used to collect data. The results showed that the factors responsible for students’ unrest in Nigerian Tertiary Institutions are unfavorable Government policies; poor staff-students’ relationship; poor teaching-learning facilities; high tuition fees; and non-responsiveness of University authorities among others. Results also showed that there were no significant differences in the factors responsible for students’ unrest in Nigerian Universities based on age, gender, and religion. KEY WORD: Factors Responsible for; Students’ Unrest; Nigerian Tertiary Institutions; Counsellors. ABSTRAKSI: “Faktor-faktor yang Bertanggung Jawab atas Keresahan Mahasiswa di Lembaga Pendidikan Tinggi Nigeria: Implikasi bagi Praktek Konseling”. Penelitian ini, dengan demikian, menyelidiki faktor-faktor yang bertanggung jawab atas keresahan mahasiswa di Lembaga Pendidikan Tinggi Nigeria. Penyelidikan lebih lanjut juga dilakukan berdasarkan variabel moderasi usia, jenis kelamin, dan agama jika mereka memiliki pandangan yang berbeda terhadap peserta. Penelitian ini bersifat deskriptif. Sampel terdiri dari seribu dua ratus mahasiswa, yang dipilih di enam Universitas di Nigeria menggunakan teknik sampel acak bertujuan, sederhana, dan sistematis. Kuesioner baru berlabel FRSUQ (Kuesioner Faktor-faktor yang Bertanggung Jawab atas Keresahan Mahasiswa) dikembangkan dan digunakan untuk mengumpulkan data. Hasil penelitian menunjukkan bahwa faktor-faktor yang bertanggung jawab atas keresahan mahasiswa di Lembaga Pendidikan Tinggi Nigeria adalah kebijakan Pemerintah yang tidak menguntungkan; hubungan staf-mahasiswa yang lemah; fasilitas belajar-mengajar yang buruk; biaya kuliah yang tinggi; serta tidak responsifnya pihak otoritas Universitas antara lain. Hasil kajian juga menunjukkan bahwa tidak ada perbedaan signifikan dalam faktor-faktor yang bertanggung jawab atas keresahan mahasiswa di Universitas Nigeria berdasarkan usia, jenis kelamin, dan agama. KATA KUNCI: Faktor-faktor yang Bertanggung Jawab atas; Keresahan Mahasiswa; Lembaga Pendidikan Tinggi Nigeria; Pembimbing.About the Author: Dr. Aminat Adeola Odebode is a Lecturer at the Department of Counsellor Education UNILORIM (University of Ilorin), Nigeria. For academic interests, the Author is able to be contacted via e-mail adrress at: odebode.aa@unilorin.edu.ng Suggested Citation: Odebode, Aminat Adeola. (2019). “Factors Responsible for Students’ Unrest in Nigerian Tertiary Institutions: Implications for Counselling Practices” in MIMBAR PENDIDIKAN: Jurnal Indonesia untuk Kajian Pendidikan, Volume 4(2), September, pp.93-102. Bandung, Indonesia: UPI [Indonesia University of Education] Press, ISSN 2527-3868 (print) and 2503-457X (online). Article Timeline: Accepted (July 3, 2019); Revised (August 17, 2019); and Published (September 30, 2019).

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“…The statistics of Cronbach's alpha coefficients (0.924-0.936) and McDonald's omega coefficients (0.885-0.902) are summarized in Table 2, and the Guttman split-half coefficient of the physical concerns, social concerns, and cognitive concerns was 0.938, 0.906, and 0.918, respectively, suggesting that the three factors of ASI-3 had satisfactory reliability. The testretest coefficient for the physical concerns, social concerns, and cognitive concerns was 0.775, 0.596, and 0.730, respectively (P < 0.01), which revealed a moderate correlation between test and retest results (Lee et al, 2018). Moreover, we summarized the reliability parameters of other instruments used in our study in Table 2.…”

Section: Reliabilitymentioning

confidence: 80%

Psychometric Properties of the Chinese Version of Anxiety Sensitivity Index-3 in Women Diagnosed With Breast Cancer

Yan

Zhu

et al. 2020

Front. Psychol.

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Background: Anxiety sensitivity (AS) is a trait-like predisposing factor for the prevalence of anxiety in patients diagnosed with breast cancer. The Anxiety Sensitivity Index-3 (ASI-3) has been widely used in both general and clinical samples for measuring AS. However, the data about its psychometric properties in women with breast cancer are deficient. In addition, there is no evidence proving the measure equivalence of ASI-3 across sociodemographic variables in the specific sample. Thus, the present study examined the psychometric properties and conducted measure equivalence testing of ASI-3 in Chinese women diagnosed with breast cancer.Methods: This study included 815 Chinese women diagnosed with breast cancer. Single group confirmatory factor analysis (CFA) was administrated to detect the factorial validity of ASI-3, and multigroup CFAs were conducted to test the measurement equivalence of ASI-3 across various sociodemographic variables. The reliability of ASI-3 was tested by Cronbach's alpha coefficient, Guttman split-half coefficient, McDonald's omega coefficient, and test-retest coefficient. The standardized factor loadings, construct reliability, and the average variance extracted of factors were used to measure the construct validity of ASI-3, and the partial correlations were conducted to examine the criterion-related validity of ASI-3.Results: The ASI-3 had satisfactory reliability and validity in Chinese women diagnosed with breast cancer; three-factor model fitted the data well in CFA and reached partial strict invariances across age, education, and residence groups. Conclusion:This study explored the psychometric properties and measurement invariance across sociodemographic variables of ASI-3 in Chinese women diagnosed with breast cancer. Our results not only proved that the ASI-3 is an appropriate instrument for measuring AS but also deepened the understanding of ASI-3 in Chinese women with malignancy.

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Test-retest reliability of the questionnaire in the Sasang constitutional analysis tool (SCAT)

Cited by 13 publications

References 7 publications

Metabolic Syndrome Prediction Models Using Machine Learning and Sasang Constitution Type

Metabolic Syndrome Prediction Models Using Machine Learning and Sasang Constitution Type

Factors Responsible for Students’ Unrest in Nigerian Tertiary Institutions: Implications for Counselling Practices

Psychometric Properties of the Chinese Version of Anxiety Sensitivity Index-3 in Women Diagnosed With Breast Cancer

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