676 resultados para Body-image Dissatisfaction


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[returning interception?]

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[returning interception?]

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[from article that appeared in Journal of Physical Education, Nov-Dec. 1956]

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Thesis (Master's)--University of Washington, 2016-06

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Research with adults has shown a preference for average-weight female figures with waist-to-hip ratios (WHR) of 0.7, and average weight male figures with waist-to-hip ratios of 0.9. This study investigated the development of preferences for WHR sizes as well as preferences for specific body weights. Five-hundred eleven children ranging in age from 6 to 17 were presented with drawings of 12 male and 12 female silhouettes varying in weight and WHR and asked to select one they thought looked the nicest or most attractive. The youngest children showed preferences for the underweight figures, changing to consistent preferences for the average weight figures in the teenage years. The developmental curves for waist-to-hip ratio preferences were linear, changing gradually over time to become more adult-like. Potential developmental models for the development of preferences for specific body shapes are considered in relation to these data.

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The research developed in this thesis explores the sensing and inference of human movement in a dynamic way, as opposed to conventional measurement systems, that are only concerned with discrete evaluations of stimuli in sequential time. Typically, conventional approaches are used to infer the dynamic movement of the body; such as vision and motion tracking devices, with either a human diagnosis or complex image processing algorithm to classify the movement. This research is therefore the first of its kind to attempt and provide a movement classifying algorithm through the use of minimal sensing points, with the application for this novel system, to classify human movement during a golf swing. There are two main categories of force sensing. Firstly, array-type systems consisting of many sensing elements, and are the most commonly researched and commercially available. Secondly, reduced force sensing element systems (RFSES) also known as distributive systems have only been recently exploited in the academic world. The fundamental difference between these systems is that array systems handle the data captured from each sensor as unique outputs and suffer the effects of resolution. The effect of resolution, is the error in the load position measurement between sensing elements, as the output is quantized in terms of position. This can be compared to a reduced sensor element system that maximises that data received through the coupling of data from a distribution of sensing points to describe the output in discrete time. Also this can be extended to a coupling of transients in the time domain to describe an activity or dynamic movement. It is the RFSES that is to be examined and exploited in the commercial sector due to its advantages over array-based approaches such as reduced design, computational complexity and cost.

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Two experiments examined the effect of metastereotype valence on high and low identifiers' judgments of an outgroup. As high identifiers are strongly emotionally invested in the ingroup, we expected that such group members would feel angry when they activate negative metastereotypes which would correspondingly lead to less favourable evaluation of the outgroup. We further expected this pattern to be particularly visible when high identifiers could communicate their dissatisfaction to an outgroup (but not an ingroup) audience presumably to persuade the outgroup to reevaluate their attitudes toward the ingroup. We did not expect low identifiers to reflect the valence of metastereotypes in their outgroup attitudes and judgments, given their weak emotional ties with the ingroup and because such members are likely to feel that metastereotypes do not apply to them personally. Results from two experiments (Study 1, N = 78; Study 2, N = 80) supported these predictions and are discussed in light of the implications of metastereotyping for intergroup relations. © 2012 Canadian Psychological Association.

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General note: Title and date provided by Bettye Lane.

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X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].

Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.

As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization.

More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.

With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled.

Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4.

With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes.

Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization.

Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.

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Depuis le début du XXIe siècle, un type particulier d’images a envahi l’espace public constitué par Internet : il s’agit des images principales de profil, ces images que les utilisateurs de sites de réseaux sociaux choisissent pour les représenter auprès des autres individus connectés. Comme le plus souvent il s’agit d’une image du corps de celui ou celle qui s’affiche ainsi, il est intéressant de s’intéresser à cette pratique en la rattachant à des pratiques plus anciennes. Dans un premier temps, cette étude présente donc une perspective socio-historique en notant la ressemblance de la pratique de l’image principale de profil avec celle de l’autoportrait et du portrait commandé. Cela permet de remarquer plusieurs points de rupture ou d’inflexion dans l’usage de ce type d’images, mais aussi d’en dégager les usages sociaux typiques. Ensuite, l’observation d’un lieu particulier d’Internet permet de tirer les conclusions suivantes : si l’usage principal de ces images est facile à expliquer, elles servent à symboliser une présence dans des lieux non accessibles aux corps sensibles, ces images montrent toujours des éléments qui permettent de déduire une position sociale et elles sont fondamentalement identiques aux images produites avant Internet. Ensuite, l’étude de ces images montre qu’il y a un véritable continuum dans la manière de dévoiler son intimité qui permet d’affirmer que la frontière entre public et privé n’existe pas sur Internet. Finalement, ces images montrent une absence de canon quant à leur production et une multiplicité des façons de se mettre en scène qui laissent à penser qu’elles sont devenues des symboles à part entière dans la communication qui peut s’établir entre des étrangers sur Internet.