8 research outputs found

    Social support experiences when growing up with a parent with Huntington’s disease

    No full text
    Background Social support is a strong protector factor against the many negative effects stress and adversity in childhood can have on short- and long-term health. However, for young people who are exposed to adversity because their parent suffers from severe neurodegenerative disease, such as Huntington’s disease (HD), support from close caregiving relationships can be compromised. This study aimed to investigate what current and past experiences young people who grow up with a parent with HD have with social support outside the parent–child context.Methods A total of 36 semi-structured qualitative interviews with individuals who had current and past experiences growing up with a parent with HD were analysed using thematic analysis.Findings Relationships were experienced as supportive when they provided a sense of love, care, or belonging; when they provided coping skills; and when they reduced or alleviated stressors at home. Barriers to receiving and accepting support included their parent’s and others’ lack of acknowledgement and understanding about their situation and the young people’s own need to protect themselves or their family from support they feared could cause harm.Conclusion Our findings highlight the many important roles persons other than caregivers can have in helping young people who grow up with the distress and adversity of having a parent with a severe disease, such as HD. The findings suggest that by sustaining positive and adaptive emotions and/ or changing distressing emotions, social support help and can compensate for a lack of support in their caregiving relationships. In order for others to be experienced as supportive, the many barriers this vulnerable group may encounter must be addressed and overcome. Most importantly, support providers must understand how HD affects young people

    Body image and quality of life in adolescents with craniofacial conditions

    No full text
    © Copyright 2017 American Cleft Palate-Craniofacial Association. Objective: To evaluate body image in adolescents with and without craniofacial conditions and to examine relationships between body image and quality of life. Design: Case-control design. Setting: A pediatric hospital's craniofacial center and primary care practices. Participants: Seventy adolescents with visible craniofacial conditions and a demographically matched sample of 42 adolescents without craniofacial conditions. Main Outcome Measure: Adolescents completed measures of quality of life and body image including satisfaction with weight, facial and overall appearance, investment in appearance (importance of appearance to self-worth), and body image disturbance (appearance-related distress and impairment in functioning). Results: Adolescents with craniofacial conditions reported lower appearance investment (P < .001) and were more likely to report concerns about facial features (P < .02) compared with nonaffected youth. Females in both groups reported greater investment in appearance, greater body image disturbance, and lower weight satisfaction compared with males (P < .01). Within both groups, greater body image disturbance was associated with lower quality of life (P < .01). The two groups did not differ significantly on measures of quality of life, body image disturbance, or satisfaction with appearance. Conclusions: Body image and quality of life in adolescents with craniofacial conditions are similar to nonaffected youth. Relationships between body image and quality of life emphasize that appearance perceptions are important to adolescents' well-being regardless of whether they have a facial disfigurement. Investment in one's appearance may explain variations in body image satisfaction and serve as an intervention target, particularly for females

    Advances in Geometric Statistics for Manifold Dimension Reduction

    No full text
    International audienceGeometric statistics aim at shifting the classical paradigm for inference from points in a Euclidean space to objects living in a non-linear space, in a consistent way with the underlying geometric structure considered. In this chapter, we illustrate some recent advances of geometric statistics for dimension reduction in manifolds. Beyond the mean value (the best 0-dimensional summary statistics of our data), we want to estimate higher dimensional approximation spaces fitting our data. We first define a family of natural parametric geometric subspaces in manifolds that generalize the now classical geodesic subspaces: barycentric subspaces are implicitly defined as the locus of weighted means of k + 1 reference points with positive or negative weights summing up to one. Depending on the definition of the mean, we obtain the Fréchet, Karcher or Exponential Barycentric subspaces (FBS/KBS/EBS). The completion of the EBS, called the affine span of the points in a manifold is the most interesting notion as it defines complete sub-(pseudo)-spheres in constant curvature spaces. Barycentric subspaces can be characterized very similarly to the Euclidean case by the singular value decomposition of a certain matrix or by the diagonalization of the covariance and the Gram matrices. This shows that they are stratified spaces that are locally manifolds of dimension k at regular points. Barycentric subspaces can naturally be nested by defining an ordered series of reference points in the manifold. This allows the construction of inductive forward or backward properly nested sequences of subspaces approximating data points. These flags of barycen-tric subspaces generalize the sequence of nested linear subspaces (flags) appearing in the classical Principal Component Analysis. We propose a criterion on the space of flags, the accumulated unexplained variance (AUV), whose optimization exactly lead to the PCA decomposition in Euclidean spaces. This procedure is called barycentric subspace analysis (BSA). We illustrate the power of barycentric subspaces in the context of cardiac imaging with the estimation, analysis and reconstruction of cardiac motion from sequences of images
    corecore