Is it a (fe)male pain? Portuguese nurses' and laypeople's gendered representations of common pains

Abstract

This study identified different gendered patterns of common pains, which may have important implications for (wo)men's pain experiences and how these are interpreted by others.

Trends and consequences of the technocratic paradigm of childbirth in Portugal: A population-based analysis of birth conditions and social characteristics of parents

“…MCA transforms categorical input variables using an optimal scaling procedure and, consequently, assigns optimal quantifications to the categories of those input variables and symmetrically scores to the objects (cases). Using the optimal quantifications of the categories or the scores of the objects as coordinates, MCA represents categories or objects as points in subspace with the minimum number of dimensions (axes or factors) possible, in particular, bidimensional graphs (39)(40)(41). The privileged associations are emphasised by geometric proximity of the categories in the factorial plan and, from the configurations designed by those associations, different patterns can be defined.…”

Meat, beyond the plate. Data-driven hypotheses for understanding consumer willingness to adopt a more plant-based diet

“…After determining the inter-rater agreement value we performed a multiple correspondence analysis (MCA) and a hierarchical cluster analysis (HCA). MCA was used to explore the interrelationships between the categorical variables (Greenacre, 2007) and the HCA was performed in order to validate the MCA pattern solution (Hair, Black, Babin, & Anderson, 2010), while using MCA standardized object scores as input variables (Bernardes et al, 2014). The HCA was suited by a k-means algorithm (nonhierarchical clustering method).…”

Clinical profiles of stigma experiences, self-esteem and social relationships among people with schizophrenia, depressive, and bipolar disorders

“…Then, a cluster analysis (Hair et al, 2010) was used in order to group individuals according to their clinical profiles. MCA standardized object scores were used as input variables and a k-means algorithm was implemented (Bernardes et al, 2014;Dumais et al, 2011;Ramos and Carvalho, 2011). All statistical analyses were conducted using SPSS version 20.0.…”