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Nov 2018 DOI 10.14302/issn.2474-3585.jpmc-18-2345
Habibeh AhmadipourCorresponding author
Social Determinants of Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Background: lifestyle modification is known as the cornerstone for prevention and treatment of chronic diseases. To promote individual’s lifestyle, the first step is to measure their lifestyle by a valid and reliable tool. The aim of present study was to evaluate psychometric properties of the Persian version of Healthy Lifestyle and Personal Control Questionnaire (HLPCQ). Method: A crosssectional study carried out on 300 medical students in Kerman University of Medical Sciences, Iran. Data collected using a questionnaire contained demographic data and Persian version of HLPCQ. The reliability of the questionnaire determined using Cronbach’s alpha and intra class correlation coefficient (ICC). The construct validity of the questionnaire evaluated by exploratory and confirmatory factor analysis. Data were analyzed by SPSS version 19 and Lisrel 8.8. Results: Internal consistency of HLPCQ was 0.78 using Cronbach’s alpha and 0.80 by ICC. In confirmatory factor analysis, the scale had acceptable goodness of fit indices. Conclusions: The Persian version of HLPCQ had excellent psychometric properties and can be used in in primary health care settings.
Jun 2014 DOI 10.14302/issn.2324-7339.jcrhap-12-158
Ross RatchneewanCorresponding author
College of Nursing, Kent State University, Kent, OH 44242
It is important to measure depressive symptoms in HIV-infected individuals because depressive symptoms have been found to be correlated with faster progression to AIDS. Worldwide, the CES-D has been used to assess depressive symptoms and examined for its construct validity. However, no previous studies have investigated the CES-D’s construct validity among HIV-infected perinatal women. Therefore, the objective of this study was to examine the construct validity of the CES-D using both explanatory and confirmatory factor analysis among HIV-positive perinatal women in Thailand. Results showed that, overall, the CES-D is a 4-factor instrument with good construct validity and can be used to evaluate depressive symptoms among HIV-positive perinatal Thai women. However, some items from our study loaded differently on the 4 factors from Radloff’s model. Finally, the CES-D can be used as a general-factor scale without being compromised.
Nov 2020 DOI 10.14302/issn.2577-2279.ijha-20-3591
Pal BaidyanathCorresponding author
Biological Anthropology Unit, Indian Statistical Institute, Kolkata, India
Objectives Aim of the study was to develop a ‘composite body size score’ (CBSS) using anthropometric traits to estimate body size and to assess the nutritional status of each study individual on the basis of CBSS. Materials and Methods Data on seventeen anthropometric traits were collected from 710 individuals (Male, Female) from fishermen community inhabiting coastal villages of West Bengal, India. For estimating body sizes, Structural Equation Model (SEM) was constructed with Path Analysis (PA). Later, second order Confirmatory Factor Analysis (CFA) was applied on SEM to determine CBSS. It was hypothesized in the models that CBSS is composed with three sets of latent variables viz., linear, circular and skinfold, constructed from anthropometric traits. Applying new derived optimal cut off points of CBSS was used to determine lean, normal and robust body sizes. Individuals with negative values of CBSS were categorised as lean body size,. Positive values of CBSS were categorised into two categories- normal and robust body size. Results On the basis of CBSS, result showed that 50.6%, 48.8% and 0.6% of the individuals were categorised under lean, normal and robust body size respectively. Females showed relatively higher percent of lean body size i.e. under nutrition (73.8%) compared to males (26.2%). Conclusion The hypothesized model estimate more accurate composite body size score, based on anthropometric traits. All the traits are highly significant on the model. The lean body size category can be use in predicting ‘Undernutrition’.