scholarly journals Psychometric evaluation of the Smartphone for Clinical Work Scale to measure nurses’ use of smartphones for work purposes

2018 ◽  
Vol 25 (8) ◽  
pp. 1018-1025
Author(s):  
John Robert Bautista ◽  
Sonny Rosenthal ◽  
Trisha Tsui-Chuan Lin ◽  
Yin-Leng Theng
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Predictive Validity ◽  
Structural Equation ◽  
Instant Messaging ◽  
Work Productivity ◽  
Psychometric Evaluation ◽  
Clinical Work ◽  
Equation Modeling ◽  
Five Factors

Abstract Objective This study reports the development and psychometric evaluation of the Smartphone for Clinical Work Scale (SCWS) to measure nurses’ use of smartphones for work purposes. Methods Items were developed based on literature review and a preliminary study. After expert consultations and pilot testing, a 20-item scale was administered in January-June 2017 to 517 staff nurses from 19 tertiary-level general hospitals in Metro Manila, Philippines. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to evaluate construct validity. Structural equation modeling (SEM) was used to test the predictive validity of SCWS on perceived work productivity. Results EFA results show that 15 out of 20 items loaded on five factors: communication with clinicians via call and text, communication with doctors via instant messaging, information seeking, communication with nurses via instant messaging, and communication with patients via call and text. CFA results suggest that the five factors that form SCWS have adequate fit to the data, thus supporting construct validity. SEM results suggest predictive validity since SCWS was positively associated with perceived work productivity. Conclusions The 15-item SCWS showed satisfactory psychometric properties for use in future studies. These studies can focus on identifying factors associated with nurses’ use of smartphones for work purposes.

scholarly journals Perceived Inventory of Technological Competency as Caring in Nursing (PITCCN): Psychometric Evaluation

2019 ◽  
Vol 4 (2) ◽  
pp. 1 ◽  
Author(s):  
Hirokazu Ito ◽  
Tetsuya Tanioka ◽  
Mie Miyamoto ◽  
Misao Miyagawa ◽  
Yuko Yasuhara ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Psychometric Evaluation ◽  
Equation Modeling ◽  
Index Test ◽  
Chi Square ◽  
Technological Competency ◽  
Fit Index

Background: The theory of Technological Competency as Caring in Nursing (TCCN) was developed by Locsin (2005) to guide the expression of “technological competency as caring in nursing” among practicing nurses. While the Technological Competency as Caring in Nursing Instrument (TCCNI) was developed and translated into other languages, no instrument measuring the TCCN among Japanese nurses was developed and tested. Thus, the Perceived Inventory of Technological Competency of Caring in Nursing (PITCCN) was developed and improved. Aim: The aim of this study was to validate the PITCCN using construct validity through structural equation modeling (SEM). Methods: The PITCCN is a four-factor questionnaire. The PITCCN was distributed to four hospitals (402 nurses) from selected Shikoku District in Japan. The theoretical model was tested using confirmatory factor analysis (CFA). Exploratory factor analysis and CFA via a SEM were used to justify construct validity, and Cronbach’s alpha coefficient was determined to establish reliability of constructs using SPSS and AMOS 25.0. Results: Finding shows that the chosen fit index test like Tucker Lewis Index (TLI), Goodness of Fit Index (GFI), and Normed Fit Index (NFI) are greater than 0.80 as set by the requirement. The values of the chi-square/degree of freedom (CMIN/DF), Comparative Fit Index (CFI), Incremental Fit Index (IFI), and Root Mean Square of Error Approximation (RMSEA) showed acceptable to good fit. Conclusion: GFI of the structure model was acceptable.

scholarly journals Individual differences in avoiding feelings of disgust: Development and construct validity of the disgust avoidance questionnaire

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248219
Author(s):  
Paula von Spreckelsen ◽  
Nienke C. Jonker ◽  
Jorien Vugteveen ◽  
Ineke Wessel ◽  
Klaske A. Glashouwer ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Convergent Validity ◽  
Structural Equation ◽  
Factor Model ◽  
Self Report ◽  
Equation Modeling ◽  
Future Research ◽  
Cognitive Avoidance ◽  
Behavioral Avoidance

We developed and examined the construct validity of the Disgust Avoidance Questionnaire (DAQ) as a measure of people’s inclination to prevent experiencing disgust (disgust prevention) and to escape from the experience of disgust (disgust escape). In a stepwise item-reduction (Study 1; N = 417) using Exploratory Factor Analysis (EFA) based on a 4-subscale distinction (behavioral prevention, cognitive prevention, behavioral escape, cognitive escape), we selected 17 items from a pool of potential items. In order to incorporate the conceptual overlap between dimensions of disgust avoidance, focus (prevention vs. escape), and strategy (behavioral avoidance vs. cognitive avoidance), we specified an adapted model. In this model, we allowed each item to load on one type of dimension and one type of strategy, resulting in four overlapping factors (prevention, escape, behavioral avoidance, cognitive avoidance). Evaluation of this overlapping 4-factor model (Study 2; N = 513) using Exploratory Structural Equation Modeling (ESEM) and Confirmatory Factor Analysis (CFA) showed promising model fit indices, factor loadings, factor correlations, and reliability estimates for three of the four factors (prevention, behavioral avoidance, cognitive avoidance). Those three subscales also showed good convergent validity. In contrast, the results related to the escape factor may call the suitability of self-report to assess disgust escape into question. In light of the exploratory nature of the project, future examinations of the DAQ’s validity and applicability to more diverse samples are essential. A critical next step for future research would be to examine the DAQ’s criterion validity and the distinctive roles of the DAQ subscales in (clinical) psychological constructs and processes.

The Construct Validity of the Tripartite Classification of Attitudes

1979 ◽  
Vol 16 (1) ◽  
pp. 88-95 ◽  
Author(s):  
Richard P. Bagozzi ◽  
Alice M. Tybout ◽  
C. Samuel Craig ◽  
Brian Sternthal
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Predictive Validity ◽  
Convergent Validity ◽  
Structural Equation ◽  
Discriminant Validity ◽  
Tripartite Model ◽  
Normative Beliefs ◽  
Attitude Measures

The convergent, discriminant, and predictive validity of the tripartite model of attitudes is investigated. On the basis of a structural equation methodology, evidence is obtained for convergent validity. Moreover, a factor analysis of the attitude measures and measures of perceived extraneous events and personal and social normative beliefs provides evidence for discriminant validity. Finally, evidence for predictive validity based on actual and intended behaviors is found to be mixed. The implications of these findings for research pertaining to the prediction of consumer behavior are discussed.

scholarly journals Preprint: Individual Differences in Avoiding Feelings of Disgust: Development and Construct Validity of the Disgust Avoidance Questionnaire

2020 ◽  
Author(s):  
Paula von Spreckelsen ◽  
Nienke Jonker ◽  
Jorien Vugteveen ◽  
Ineke Wessel ◽  
Klaske A. Glashouwer ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Convergent Validity ◽  
Structural Equation ◽  
Factor Model ◽  
Self Report ◽  
Equation Modeling ◽  
Future Research ◽  
Cognitive Avoidance ◽  
Behavioral Avoidance

We developed and examined the construct validity of the Disgust Avoidance Questionnaire (DAQ) as a measure of people’s inclination to prevent experiencing disgust (disgust prevention) and to escape from the experience of disgust (disgust escape). In a stepwise item-reduction (sample 1; n = 417) using Exploratory Factor Analysis (EFA) based on a 4-subscale distinction (behavioral prevention, cognitive prevention, behavioral escape, cognitive escape), we selected 17 items from a pool of potential items (step 1). In order to incorporate the conceptual overlap between dimensions of disgust avoidance, focus (prevention vs. escape), and strategy (behavioral avoidance vs. cognitive avoidance), we specified an adapted model. In this model, we allowed each item to load on one type of dimension and one type of strategy, resulting in four overlapping factors (prevention, escape, behavioral avoidance, cognitive avoidance). Evaluation of this overlapping 4-factor model (sample 2; n = 513) using Exploratory Structural Equation Modeling (ESEM) and Confirmatory Factor Analysis (CFA) showed promising model fit indices, factor loadings, factor correlations, and reliability estimates for three of the four factors (prevention, behavioral avoidance, cognitive avoidance; step 2). Those three subscales also showed good convergent validity (step 3; sample 2). In contrast, the results related to the escape factor question the suitability of self-report to assess disgust escape. In light of the exploratory nature of the project, future examination of the DAQ’s validity is essential. A critical next step for future research would be to examine the DAQ’s criterion validity and the distinctive roles of the DAQ subscales in (clinical) psychological constructs and processes.

scholarly journals Development and Validation of Instrument to Measure Thinking Patterns: A Structural Equation Modeling Analysis

2020 ◽  
Vol 13 (1) ◽  
pp. 58-66
Author(s):  
Ali Maksum ◽  
Fifukha D. Khory
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
State University ◽  
Validity And Reliability ◽  
Cognitive Reflection Test ◽  
Five Factors ◽  
Modeling Analysis ◽  
Fit Index

Background: As an instrument that measures thinking processes, the cognitive reflection test still has a number of problems, especially in terms of its validity and reliability. Aims: This research aimed to develop instruments to identify patterns of thinking that meet psychometric requirements. Methods and Results: Participants in the research were 727 students from the State University of Surabaya, including 322 (44%) men and 405 (56%) women with a mean age of 19.17 years. The first examination using exploratory factor analysis showed that the scale of thinking patterns, which we later called Intuitive-Reflective Scale (IRS), had a conceptual relations structure consisting of 5 factors with a loading factor of .40 - .80. The five factors explained 52.57% of the total variance and had Cronbach’s Alpha reliability of .71. The second examination using confirmatory factor analysis based on structural equation modeling proved that the IRS had factors structure that was consistent with the results of the first examination and was a significant predictor of academic performance. Conclusion: Hypothesized factor structure fits with empirical data based on the comparative fit index of .96 and root mean square error of approximation of .07.

scholarly journals Store Image Attributes and Customer Satisfaction in Supermarkets in Campo Grande-MS

2013 ◽  
Vol 12 (4) ◽  
pp. 85-107 ◽  
Author(s):  
Eluiza Alberto de Morais Watanabe ◽  
Dario De Oliveira Lima-Filho ◽  
Cláudio Vaz Torres
Keyword(s):  
Factor Analysis ◽  
Data Analysis ◽  
Consumer Satisfaction ◽  
Structural Equation ◽  
Equation Modeling ◽  
Store Image ◽  
Five Factors ◽  
The Impact ◽  
The Relationship ◽  
Positive Effect

The aim of this study was to investigate the relationship between image attributes and consumer satisfaction in supermarkets. Specifically, we sought to: a) identify the variables which make up the image attributes of supermarkets and group them into factors, and b) assess the impact of image attributes on consumer satisfaction. We conducted a quantitative study, which met quotas by region and city income class, among 400 individuals from Campo Grande, MS, southwest Brazil, who were responsible for purchasing supermarket products for their families. Exploratory Factor Analysis (EFA) and Structural Equation Modeling were used for the data analysis. The results revealed that the attributes are grouped into five factors. The constructs environment and promotions were not considered significant in determining satisfaction, while the attributes employees, product and price had a positive effect on satisfaction, with the latter having the greatest impact.DOI: 10.5585/remark.v12i4.2561

scholarly journals Validity and Reliability of a COVID-19 Stigma Scale Using Exploratory and Confirmatory Factor Analysis in a Sample of Egyptian Physicians: E16-COVID19-S

2021 ◽  
Vol 18 (10) ◽  
pp. 5451
Author(s):  
Aya Mostafa ◽  
Nayera S. Mostafa ◽  
Nashwa Ismail
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Construct Validity ◽  
Psychometric Properties ◽  
Exploratory Factor Analysis ◽  
Internal Consistency ◽  
Structural Equation ◽  
Equation Modeling ◽  
Stigma Scale ◽  
Confirmatory Factor

Introduction: To date, a universal validated and specific tool for assessing coronavirus disease 2019 (COVID-19) stigma among healthcare workers is lacking. We adapted a SARS stigma scale that was developed using the Berger HIV scale for use as a COVID-19 stigma scale and evaluated its psychometric properties among Egyptian physicians. Methods: We administered the 17-item SARS stigma scale in an anonymous online questionnaire among 509 Egyptian physicians recruited via convenience sampling during a cross-sectional study in June 2020. Exploratory factor analysis was performed on half of the sample. Confirmatory factor analysis of the resulting model was done using structural equation modeling on the other half. Scale reliability was examined using Cronbach’s alpha for internal consistency. Convergent construct validity was assessed using regression models to examine the association between the adapted COVID-19 stigma scale and relevant factors. Results: Exploratory factor analysis yielded 16 items (E16-COVID19-S) that supported a three-factor structure: personalized stigma (8 items); concerns of disclosure and public attitudes (5 items); and negative experiences (3 items). Cronbach’s α was 0.909 for the total scale and 0.907, 0.663, and 0.789 for the three subscales. E16-COVID19-S was confirmed to have good model fit (comparative fit index = 0.964; root mean squared error of approximation = 0.056). E16-COVID19-S was independently associated with physicians’ younger age, lower qualification, working in an isolation hospital, and self-stigma, whether the scale was treated as categorical or continuous. Conclusions: E16-COVID19-S exhibited good internal consistency and construct validity among this sample of Egyptian physicians. These adequate psychometric properties make the E16-COVID19-S scale appropriate for use by researchers and practitioners.

Celebrity Worship Among University Students in Malaysia

2011 ◽  
Vol 16 (4) ◽  
pp. 334-342 ◽  
Author(s):  
Viren Swami ◽  
Tomas Chamorro-Premuzic ◽  
Khairul Mastor ◽  
Fatin Hazwani Siran ◽  
Mohammad Mohsein Mohammad Said ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Attitude Scale ◽  
Equation Modeling ◽  
Future Research ◽  
The West ◽  
Factor Solution ◽  
Movie Stars ◽  
Three Factor

The present study examined conceptual issues surrounding celebrity worship in a Malay-speaking population. In total, 512 Malay and 269 Chinese participants from Malaysia indicated who their favorite celebrity was and completed the Celebrity Attitude Scale (CAS) as well as a range of demographic items. Results showed that the majority of Malay and Chinese participants selected pop stars and movie stars as their favourite celebrities, mirroring findings in Western settings. In addition, exploratory factor analysis revealed a three-factor solution of the CAS that was consistent with previous studies conducted in the West. Structural equation modeling further revealed that participant’s age was negatively associated with celebrity worship and that self-rated attractiveness was positively associated with celebrity worship. Overall, the present results suggest that celebrity worship in Malaysia may be driven by market and media forces, and future research may well be guided by use of the CAS.

A Comparison of Reliability Estimation Based on Confirmatory Factor Analysis and Exploratory Structural Equation Models

2021 ◽  
pp. 001316442110089
Author(s):  
Yuanshu Fu ◽  
Zhonglin Wen ◽  
Yang Wang
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Reliability Estimation ◽  
Model Fit ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Reliability Estimates ◽  
Confirmatory Factor ◽  
Composite Reliability

Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is often found to be substantially better than that of ICM-CFA. The present study first illustrated the method used to estimate composite reliability under ESEM and then compared the difference between ESEM and ICM-CFA in terms of composite reliability estimation under various indicators per factor, target factor loadings, cross-loadings, and sample sizes. The results showed no apparent difference in using ESEM or ICM-CFA for estimating composite reliability, and the rotation type did not affect the composite reliability estimates generated by ESEM. An empirical example was given as further proof of the results of the simulation studies. Based on the present study, we suggest that if the model fit of ESEM (regardless of the utilized rotation criteria) is acceptable but that of ICM-CFA is not, the composite reliability estimates based on the above two models should be similar. If the target factor loadings are relatively small, researchers should increase the number of indicators per factor or increase the sample size.

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