Publications by authors named "Miguel A Nunez-Benitez"

Purpose: Currently, information on the psychometric properties of the Medical outcomes study-social support survey (MOS-SSS) for patients with chronic disease in primary health care, suggests problems in the dimensionality, specifically predominant unidimensionality in a multidimensional measure. The aim of this study was to determine the internal structure (dimensionality, measurement invariance and reliability) and association with other variables.

Methods: A total of 470 patients with chronic disease from a Family Medicine Unit at the Instituto Mexicano del Seguro Social, IMSS, with a mean age of 51.

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Introduction: Vitiligo is an incurable, slowly progressive skin condition, the prevalence of which ranges from 0.4 to 2.0%.

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There is evidence in the literature that anonymity when investigating individual variables could increase the objectivity of the measurement of some psychosocial constructs. However, there is a significant gap in the literature on the theoretical and methodological usefulness of simultaneously assessing the same measurement instrument across two groups, with one group remaining anonymous and a second group revealing identities using names. Therefore, the aim of this study was to compare the psychometric characteristics of a measure of depressive symptoms in two groups of adolescents as a consequence of identification or anonymity at the time of answering the measuring instrument.

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The internal structure of the Multidimensional Scale of Perceived Social Support (MSPSS) in adolescents has been evaluated with some factorial analysis methodologies but not with bifactor exploratory structural equation modeling (ESEM), and possibly the inconsistency in the internal structure was dependent on these approaches. The objective of the study was to update evidence regarding its internal structure of MSPSS, by means of a detailed examination of its multidimensionality The participants were 460 adolescents from an educational institution in the Callao region, Lima, Peru. The structure was modeled using unidimensional, three-factor and bifactor models with confirmatory factor analysis (CFA) and ESEM approaches.

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