scholarly journals Exploratory and Confirmatory Factor Analysis of the Jefferson Scale of Empathy among Chinese Medical Students

2019 ◽  
Author(s):  
Xuyu Chen ◽  
Li Ran ◽  
Yaohua Gu ◽  
Yuting Zhang ◽  
Wenwen Wu ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Medical Students ◽  
Confirmatory Factor Analysis ◽  
Goodness Of Fit ◽  
Medical Training ◽  
Equation Modeling ◽  
Emotional Detachment ◽  
Confirmatory Factor ◽  
Chinese Medical Students ◽  
Jefferson Scale Of Empathy

Abstract Background: Empathy is critical for medical training, clinical practice, even the future professionalism of medical students. The Jefferson scale of empathy- Students version (JSE-S) was developed for estimating empathy among medical students and it’s a psychometrically sound instrument. The purpose of the study is to develop a validated translation of JSE-S that used by Chinese medical students and to confirm the psychometric properties, underlying component and latent variable structure of the Chinese JSE-S. Methods: The JSE-S was translated into Chinese based on standardized guidelines. The sample was divided to two parts. The first half of the data was used for exploratory factor analysis (EFA) using principal component analysis(PCA) with oblique rotation(promax), and the latter was used for confirmatory factor analysis(CFA) using structural equation modeling(SEM). Results: 749 questionnaires (94.81%) were eligible. Cronbach’s alpha coefficient of the JSE-S for the entire sample was 0.89. EFA indicated that three-component solution was acceptable, and the three components are "Perspective Taking", "Compassionate Care" and "Emotional Detachment" respectively. Item 18 was proposed to move to the third factor. CFA indicated that the three-factors model showed an acceptable goodness of fit. Conclusions: Reliability and validity of the Chinese JSE-S were satisfactory among Chinese medical students. The results supporting the underlying factor structure of the Chinese JSE-S.

scholarly journals Mengakomodasi Efek Metode dalam Pengujian Validitas Konstruk Melalui Analisis Faktor Konfirmatori

2017 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Wahyu Widhiarso
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Equation Modeling ◽  
Fit Indices ◽  
Method Effect ◽  
Confirmatory Factor ◽  
Method Effects ◽  
Item Writing

Literatures in the field of psychometrics recommend researchers to employvarious of methods on measuring individual attributes. Ideally,each methods are complementary and measuresthe construct designed to be measured. However, some problems arise when among the methods is unique and unrelated to the construct being measured. The uniqueness of method can lead what is called the method effect. In testing construct validity using confirmatory factor analysis, the emergence of this effect tend to reducing the goodness of fit indices of the model. There are many ways to solve these problem, one of themis controling the method effects and accommodate it to the model. This paper introduces how to accommodate method effecton the confirmatory factor analysis using structural equation modeling. In the application section, author identify the emergence of method effects due to the differences item writing direction (favorable-unfavorable). The analysis showed that method effectemerge from different writing direction.

scholarly journals ANALYSIS AND RESULTS: CONFIRMATORY FACTOR ANALYSIS THE MALAY VERSION OF DREEM INVENTORY WITH MEDICAL STUDENTS OF UNISZA, KUALA TERENGGANU, MALAYSIA

2017 ◽  
Vol 10 (12) ◽  
pp. 338
Author(s):  
Mainul Haque ◽  
Muhamad Saiful Bahri Yusoff ◽  
Md. Anwarul Azim Majumder ◽  
Zainal Zulkifli ◽  
Farah Hanani Binti Mohd Nasir
Keyword(s):  
Factor Analysis ◽  
Medical Students ◽  
Confirmatory Factor Analysis ◽  
Psychometric Properties ◽  
Goodness Of Fit ◽  
Factor Model ◽  
Cross Sectional Study ◽  
Model Fit ◽  
Cross Sectional ◽  
Confirmatory Factor

  Objectives: The DREEM inventory has been universally established as a generic instrument to assess health-related educational programs. There were some apprehensions regarding the psychometric properties of the DREEM raised in last few years. This study evaluated first ever the psychometric properties of the Bahasa Melayu version of the DREEM in a sample of Malaysian medical students.Methods: A cross-sectional study was carried and universal sampling method was applied. Researchers selected 1-5th-year medical students of Universiti Sultan Zainal Abidin, Malaysia, as study subjects. Researchers collected data through a guided self-administered questionnaire during a face-to-face session.Results: Confirmatory factor analysis (CFA) showed that the one factor model of DREEM-M (Model A), consisting 50 items were not fit, indicating it was a multidimensional instrument. On further CFA, it appeared that the proposed five-factor structure was not fit (Model B) as all the goodness-of-fit indices did not signify a model fit.Conclusions: The study findings revealed that the DREEM inventory 50-item inventory failed to achieve a model fit, but it demonstrated a high of internal consistency. The proposed 19-item DREEM-M revealed good model fit.

scholarly journals Psychometric properties of a Chinese version of the Fraboni Scale of Ageism: evidence from medical students sample

2020 ◽  
Author(s):  
Jun-Yao Fan ◽  
Hui-Min Zhao ◽  
Yue-Ting Liu ◽  
Ling-Lin Kong ◽  
Jing Mao ◽  
...  
Keyword(s):  
Older Adults ◽  
Factor Analysis ◽  
Medical Students ◽  
Confirmatory Factor Analysis ◽  
Construct Validity ◽  
Content Validity ◽  
Intraclass Correlation ◽  
Chinese Version ◽  
Confirmatory Factor ◽  
Chinese Medical Students

Abstract Background The increasing of older adults has led to enormous demand for medical care. However, as a group with unique needs and characteristics, older adults are often discriminated against in the medical field. In this paper, we aimed to translate the Fraboni Scale of Ageism (FSA) into Chinese and examine its construct validity, content validity, and reliability in Chinese mainland medical students. In order to evaluate the prevalence of ageism in Chinese medical students and prompt medical college to adopt necessary teaching methods to mitigate ageism in medical students. Methods By Brislin's translation guidelines, FSA was translated to Chinese. The convenient sampling method was used to select samples for this survey, including 1,974 students from two medical schools in central and north China. Construct validity was verified by the exploratory and confirmatory factor analysis. The content validity index (CVI) was used to assess content validity. The Cronbach's alpha coefficients and intraclass correlation coefficient (ICC) were used to estimate reliability. Results The alpha coefficients for FSA (Chinese version) was 0.81 and ICC was 0.87. The CVI was 0.93. Three factors were identified by exploratory factor analysis explaining 34.84% of the total variance and a three-factor model was confirmed to fit by confirmatory factor analysis. Conclusions FSA (Chinese version) is a reliable and valid scale for measuring discrimination degree against the older adults in Chinese medical students.

scholarly journals Student’s Inventory of Professionalism (SIP): A Tool to Assess Attitudes towards Professional Development Based on Palliative Care Undergraduate Education

2019 ◽  
Vol 16 (24) ◽  
pp. 4925 ◽  
Author(s):  
Antonio Noguera ◽  
María Arantzamendi ◽  
Jesús López-Fidalgo ◽  
Alfredo Gea ◽  
Alberto Acitores ◽  
...  
Keyword(s):  
Professional Development ◽  
Palliative Care ◽  
Factor Analysis ◽  
Medical Students ◽  
Confirmatory Factor Analysis ◽  
Personal Growth ◽  
Goodness Of Fit ◽  
Self Report ◽  
Care Teaching ◽  
Confirmatory Factor

Introduction: Quality medical education, centered on a patient’s needs, is crucial to develop the health professionals that our society requires. Research suggests a strong contribution of palliative care education to professionalism. The aim of this study was to design and validate a self-report inventory to measure student’s professional development. Method: Sequential exploratory strategy mixed method. The inventory is built based on the themes that emerged from the analysis of four qualitative studies about nursing and medical students’ perceptions related to palliative care teaching interventions (see Ballesteros et al. 2014, Centeno et al. 2014 and 2017, Rojí et al. 2017). The structure and psychometrics of the inventory obtained is tested in two different surveys with two different groups of medical students. Inventory reliability and construct validity are tested in the first survey group. To verify the inventory structure, a confirmatory factor analysis is performed in a second survey group. Results: The inventory has 33 items and seven dimensions: a holistic approach, caring for and understanding the patient, personal growth, teamwork, decision-making, patient evaluation, and being a health care professional. Cronbach’s-alpha was 0.73–0.84 in all seven domains, ICC: 0.95. The confirmatory factor analysis comparative fit index (CFI) was 1 with a standardized root mean square Index 0.088 (SRMR) and obtained a 0.99 goodness-of-fit R-square coefficient. Conclusions: this new inventory is grounded on student’s palliative care teaching experiences and seems to be valid to assess student’s professional development.

scholarly journals RGLS and RLS in Covariance Structure Analysis

2021 ◽  
Author(s):  
Bang Quan Zheng
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Least Squares ◽  
Goodness Of Fit ◽  
Weight Matrix ◽  
Equation Modeling ◽  
Covariance Structure Analysis ◽  
Factor Analysis Model ◽  
Monte Carlo Simulation Study ◽  
Confirmatory Factor

This paper assesses the performance of regularized generalized least squares (RGLS) and reweighted least squares (RLS) methodologies in a confirmatory factor analysis model. Normal theory maximum likelihood (ML) and GLS statistics are based on large sample statistical theory. However, violation of asymptotic sample size is ubiquitous in real applications of structural equation modeling (SEM), and ML and GLS goodness-of-fit tests in SEM often make incorrect decisions on the true model. The novel methods RGLS and RLS aim to correct the over-rejection by ML and under-rejection by GLS. Proposed by Arruda and Bentler (2017), RGLS replaces a GLS weight matrix with a regularized one. Rediscovered by Hayakawa (2019), RLS replaces this weight matrix with one that derives from an ML function. Both of these methods outperform ML and GLS when samples are small, yet no studies have compared their relative performance. A confirmatory factor analysis Monte Carlo simulation study with normal data was carried out to examine the statistical performance of these two methods at different sample sizes. Based on empirical rejection frequencies and empirical distributions of test statistics, we find that RLS and RGLS have equivalent performance when N≥70; whereas when N<70, RLS outperforms RGLS. Both methods clearly outperform ML and GLS with N≤400.

scholarly journals Measurement properties and confirmatory factor analysis of the Jefferson Scale of Empathy in Italian medical students

2014 ◽  
Vol 3 (6) ◽  
pp. 419-430 ◽  
Author(s):  
Paolo Leombruni ◽  
Mariangela Di Lillo ◽  
Marco Miniotti ◽  
Angelo Picardi ◽  
Guido Alessandri ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Medical Students ◽  
Confirmatory Factor Analysis ◽  
Measurement Properties ◽  
Confirmatory Factor ◽  
Jefferson Scale Of Empathy

scholarly journals Efek Mediasi Variabel Motivasi pada Pengaruh Komitmen Organisasi dan Disiplin Kerja Terhadap Kinerja Pegawai

2021 ◽  
Vol 6 (10) ◽  
pp. 5232
Author(s):  
Nasruddin Nasruddin ◽  
Surajiyo Surajiyo ◽  
Suhaipa Suhaipa ◽  
Herman Paleni
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Equation Modeling ◽  
Confirmatory Factor

Komitmen seorang pegawai merupakan hasil (resultante) dari dukungan dan penghargaan yang diberikan organisasi pada pegawai. Penelitian ini bertujuan untuk memperoleh hasil tentang pengaruh Komitmen Organisasi Terhadap Motivasi Pegawai, Disiplin Kerja Terhadap Motivasi Pegawai, Komitmen Organisasi Terhadap Kinerja Pegawai, Disiplin Kerja Terhadap Kinerja Pegawai, Motivasi Pegawai Terhadap Kinerja Pegawai, Motivasi dapat memediasi pengaruh komitmen organisasi terhadap kinerja pegawai, dan Motivasi dapat memediasi pengaruh disiplin kerja terhadap kinerja pegawai pada Lembaga Pemasyarakatan Narkotika Kelas II Lubuklinggau (Muara Beliti). Tahapan penelitian dengan melakukan observasi, pengelompokkan data hasil observasi, mengidentifikasi masalah, merumuskan masalah, penelusuran referensi/literatur, membuat kerangka berpikir dan hipotesis, menentukan teknik pengumpulan data, penentuan populasi dan sampel, membuat instrumen penelitian atau kuesioner, melakukan penyebaran kuesioner, menganalisis data dari hasil jawaban 96 pegawai ASN di Lembaga Pemasyarakatan Narkotika Klas IIA Lubuklinggau (Muara Beliti) menggunakan teknik analisis Structural Equation Modeling (SEM) dengan alat bantu komputer menggunakan program Lisrel 8.70. Adapun langkah-langkah Structural Equation Modeling (SEM) yang dilakukan Confirmatory Factor Analysis (CFA), Identifikasi model, modifikasi model dan menguji kecocokan model (Goodness-of-Fit). Hasil penelitian menunjukkan nilai koefesien pengaruh langsung komitmen organisasi terhadap motivasi pegawai sebesar 0,43, dan nilai t hitung sebesar 3,35. Karena nilai t hitung sebesar 3.35 > 1,96, maka komitmen organisasi berpengaruh signifikan terhadap motivasi pegawai. Dengan demikian dapat diinterpretasikan semakin tinggi komitmen organisasi, maka semakin tinggi motivasi pegawai

Confirmatory Factor Analysis of the Long and Short Forms of the Worry Domains Questionnaire

2009 ◽  
Vol 25 (4) ◽  
pp. 239-243
Author(s):  
Roberto Nuevo ◽  
Andrés Losada ◽  
María Márquez-González ◽  
Cecilia Peñacoba
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Goodness Of Fit ◽  
Factorial Validity ◽  
Fit Indices ◽  
Short Forms ◽  
Confirmatory Factor ◽  
Positive Correlations ◽  
Future Work

The Worry Domains Questionnaire was proposed as a measure of both pathological and nonpathological worry, and assesses the frequency of worrying about five different domains: relationships, lack of confidence, aimless future, work, and financial. The present study analyzed the factor structure of the long and short forms of the WDQ (WDQ and WDQ-SF, respectively) through confirmatory factor analysis in a sample of 262 students (M age = 21.8; SD = 2.6; 86.3% females). While the goodness-of-fit indices did not provide support for the WDQ, good fit indices were found for the WDQ-SF. Furthermore, no source of misspecification was identified, thus, supporting the factorial validity of the WDQ-SF scale. Significant positive correlations between the WDQ-SF and its subscales with worry (PSWQ), anxiety (STAI-T), and depression (BDI) were found. The internal consistency was good for the total scale and for the subscales. This work provides support for the use of the WDQ-SF, and potential uses for research and clinical purposes are discussed.

512 Confirmatory Factor Analysis of the Sleep Inertia Questionnaire in a Clinical Sample with Sleep Disorders

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A201-A202
Author(s):  
Kristina Puzino ◽  
Susan Calhoun ◽  
Allison Harvey ◽  
Julio Fernandez-Mendoza
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Construct Validity ◽  
Sleep Disorders ◽  
Goodness Of Fit ◽  
Criterion Validity ◽  
Clinical Samples ◽  
Sleep Inertia ◽  
Confirmatory Factor ◽  
Sensitivity Specificity

Abstract Introduction The Sleep Inertia Questionnaire (SIQ) was developed and validated in patients with mood disorders to evaluate difficulties with becoming fully awake after nighttime sleep or daytime naps in a multidimensional manner. However, few data are available regarding its psychometric properties in clinical samples with sleep disorders. Methods 211 patients (43.0±16.4 years old, 68% female, 17% minority) evaluated at the Behavioral Sleep Medicine (BSM) program of Penn State Health Sleep Research & Treatment Center completed the SIQ. All patients were diagnosed using ICSD-3 criteria, with 111 receiving a diagnosis of chronic insomnia disorder (CID), 48 of a central disorder of hypersomnolence (CDH), and 52 of other sleep disorders (OSD). Structural equation modelling was used to conduct confirmatory factor analysis (CFA) of the SIQ. Results CFA supported four SIQ dimensions of “physiological”, “cognitive”, “emotional” and “response to” (RSI) sleep inertia with adequate goodness-of-fit (TLI=0.90, CFI=0.91, GFI=0.85, RMSEA=0.08). Internal consistency was high (α=0.94), including that of its dimensions (physiological α=0.89, cognitive α=0.94, emotional α=0.67, RSI α=0.78). Dimension inter-correlations were moderate to high (r=0.42–0.93, p<0.01), indicating good construct validity. Convergent validity showed moderate correlations with Epworth sleepiness scale (ESS) scores (r=0.38) and large correlations with Flinders fatigue scale (FFS) scores (r=0.65). Criterion validity showed significantly (p<0.01) higher scores in subjects with CDH (69.0±16.6) as compared to those with CID (54.4±18.3) or OSD (58.5±20.0). A SIQ cut-off score ≥57.5 provided a sensitivity/specificity of 0.77/0.65, while a cut-off score ≥61.5 provided a sensitivity/specificity of 0.71/0.70 to identify CDH vs. ESS<10 (AUC=0.76). Conclusion The SIQ shows satisfactory indices of reliability and construct validity in a clinically-diverse sleep disorders sample. Its criterion validity is supported by its divergent association with hypersomnia vs. insomnia disorders, as well as its adequate sensitivity/specificity to identify patients with CDH. The SIQ can help clinicians easily assess the complex dimensionality of sleep inertia and target behavioral sleep treatments. Future studies should confirm the best SIQ cut-off score by including good sleeping controls, while clinical studies should determine its minimal clinically important difference after pharmacological or behavioral treatments. Support (if any):

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