Weight Discrimination Research Articles

We Are All Ballooning: Multimedia Critical Discourse Analysis of ‘Measure Up’ and ‘Swap It, Don’t Stop It’ Social Marketing Campaigns

We Are All Ballooning: Multimedia Critical Discourse Analysis of ‘Measure Up’ and ‘Swap It, Don’t Stop It’ Social Marketing Campaigns

Robust object tracking based on weighted subspace reconstruction error with forward: backward tracking criterion

It is a challenging task to develop an effective and robust object tracking method due to factors such as severe occlusion, background clutters, abrupt motion, illumination variation, and so on. A tracking algorithm based on weighted subspace reconstruction error is proposed. The discriminative weights are defined based on minimizing reconstruction error with a positive dictionary while maximizing reconstruction error with a negative dictionary. Then a confidence map for candidates is computed through the subspace reconstruction error. Finally, the location of the target object is estimated by maximizing the decision map which combines the discriminative weights and subspace reconstruction error. Furthermore, the new evaluation method based on a forward–backward tracking criterion is used to verify the proposed method and demonstrates its robustness in the updating stage and its effectiveness in the reduction of accumulated errors. Experimental results on 12 challenging video sequences show that the proposed algorithm performs favorably against 12 state-of-the-art methods in terms of accuracy and robustness.

Toward Probabilistic Diagnosis and Understanding of Depression Based on Functional MRI Data Analysis with Logistic Group LASSO.

Diagnosis of psychiatric disorders based on brain imaging data is highly desirable in clinical applications. However, a common problem in applying machine learning algorithms is that the number of imaging data dimensions often greatly exceeds the number of available training samples. Furthermore, interpretability of the learned classifier with respect to brain function and anatomy is an important, but non-trivial issue. We propose the use of logistic regression with a least absolute shrinkage and selection operator (LASSO) to capture the most critical input features. In particular, we consider application of group LASSO to select brain areas relevant to diagnosis. An additional advantage of LASSO is its probabilistic output, which allows evaluation of diagnosis certainty. To verify our approach, we obtained semantic and phonological verbal fluency fMRI data from 31 depression patients and 31 control subjects, and compared the performances of group LASSO (gLASSO), and sparse group LASSO (sgLASSO) to those of standard LASSO (sLASSO), Support Vector Machine (SVM), and Random Forest. Over 90% classification accuracy was achieved with gLASSO, sgLASSO, as well as SVM; however, in contrast to SVM, LASSO approaches allow for identification of the most discriminative weights and estimation of prediction reliability. Semantic task data revealed contributions to the classification from left precuneus, left precentral gyrus, left inferior frontal cortex (pars triangularis), and left cerebellum (c rus1). Weights for the phonological task indicated contributions from left inferior frontal operculum, left post central gyrus, left insula, left middle frontal cortex, bilateral middle temporal cortices, bilateral precuneus, left inferior frontal cortex (pars triangularis), and left precentral gyrus. The distribution of normalized odds ratios further showed, that predictions with absolute odds ratios higher than 0.2 could be regarded as certain.

Obesity, perceived weight discrimination, and psychological well-being in older adults in England

ObjectiveTo examine whether the adverse effect of obesity on psychological well‐being can be explained by weight discrimination.MethodsThe study sample included 5056 older (≥50 y) men and women living in England and participating in the English Longitudinal Study of Ageing. Participants reported experiences of weight discrimination in everyday life and completed measures of quality of life (CASP‐19 scale), life satisfaction (Satisfaction With Life Scale), and depressive symptoms (eight‐item CES‐D scale). Height and weight were objectively measured, with obesity defined as BMI ≥30 kg/m2. Mediation analyses were used to test the role of perceived weight discrimination in the relationship between obesity and each psychological factor.ResultsObesity, weight discrimination, and psychological well‐being were all significantly inter‐related. Mediation models revealed significant indirect effects of obesity through perceived weight discrimination on quality of life (β = −0.072, SE = 0.008), life satisfaction (β = −0.038, SE = 0.008), and depressive symptoms (β = 0.057, SE = 0.008), with perceived weight discrimination explaining approximately 40% (range: 39.5‐44.1%) of the total association between obesity and psychological well‐being.ConclusionsPerceived weight discrimination explains a substantial proportion of the association between obesity and psychological well‐being in English older adults. Efforts to reduce weight stigma in society could help to reduce the psychological burden of obesity.

Seeing the other side: Perspective taking and the moderation of extremity

Recognizing the reasonableness of others' positions is important for conflict reduction, but is notoriously hard. We tested a perspective-taking approach to decreasing attitude entrenchment. Participants were held accountable in a task in which they wrote about a controversial issue from the perspective of a partner with an opposing viewpoint. This approach was effective at changing views on controversial issues—in Study 1 on weight discrimination, an issue participants were unlikely to have thought much about, and in Study 2 on abortion, where beliefs tend to be more deeply held. Studies 3 and 4 showed this change only took place under conditions where participants met the individual with an opposing view in person, and where that individual would see the perspective-taking effort. These results suggest that it is possible to reduce attitude entrenchment by encouraging people to think about the opposing perspective of another, as long as there is real contact and accountability.

A supervised dictionary learning and discriminative weighting model for action recognition

In this paper, we propose a supervised dictionary learning algorithm for action recognition in still images followed by a discriminative weighting model. The dictionary is learned based on Local Fisher Discrimination which takes into account the local manifold structure and discrimination information of local descriptors. The label information of local descriptors is considered in both dictionary learning and sparse coding stage which generates a supervised sparse coding algorithm and makes the coding coefficients discriminative. Instead of using spatial pyramid features, sliding window-based features with max-pooling are computed from coding coefficients. And then a discriminative weighting model combining a max-margin classifier is proposed using the features. Both the weighting coefficients and model parameters can be jointly learned using the same way in Multiple Kernel Learning algorithm. We validate our model on the following action recognition datasets: Willow 7 human actions dataset, People Playing Music Instrument (PPMI) dataset, and Sports dataset. To show the generality of our model, we also validate it on Scene15 dataset. The experiment results show that only with single scale local descriptors, our algorithm is comparable to some state-of-the-art algorithms.

Motor and sensory effects of ipsilesional upper extremity hypothermia and contralesional sensory training for chronic stroke patients

As hypothermia by immersion can reduce the sensory nerve conduction velocity, this study hypothesized that the reduction of sensory input to the ipsilesional upper extremity (UE) using cryotherapy would reduce the inhibitory activity of the contralesional hemisphere in chronic stroke subjects.Objective:In this study, hypothermia was applied by immersing the ipsilesional UE in association with sensory training of the contralesional UE of stroke patients to assess the immediate (e.g. sensorimotor function, hemodynamics, and levels of comfort) and long-term (sensory and motor performances of the UEs) effects.Methods:The sample included 27 stroke patients allocated into group 1 (n = 14), which received conventional physiotherapy for the affected UE, and group 2 (n = 13), which underwent 10 sessions of immersion hypothermia of the ipsilesional wrist and hand. Assessments were performed pre- and post-treatment and at follow-up using esthesiometry, the Fugl–Meyer Assessment (FMA), the Nottingham Sensory Assessment, functional tests, tactile and weight discrimination, motor sequence, level of comfort, and hemodynamic parameters.Results:The immediate effects of hypothermia using immersion of the ipsilesional UE in association with sensory training of the contralesional UE were hemodynamic stability during and after hypothermia, the absence of sensory abnormalities in the contralesional UE, hypoesthesia in the ipsilesional extremity (dermatomes C6 and C8) (P < 0.05), the maintenance of acceptable levels of comfort, and good patient compliance to the technique. The long-term effects included significant increases in scores on tests performed without functional vision, in scores on blindfolded functional tests, and in tactile localization and joint position sense for the contralesional hand in group 2 as well as the maintenance of these gains at long-term follow-up (5 weeks). Improvement was also found in the tactile function of the C6 and C7 dermatomes of the contralesional hand (P < 0.05).Conclusions:The use of immersion hypothermia on the ipsilesional UE in association with sensory training of the contralesional UE improved motor function and sensitivity in the contralesional UE of individuals with chronic stroke. Immersion hypothermia of the ipsilesional UE in chronic stroke patients is a safe, practical, inexpensive, and easily applied technique.

Modelling and structural characteristics analysis of gene networks for prostate cancer.

Analysing structure of gene networks is an important way to understand regulatory mechanisms of organism at the molecular level. In this work, gene mutual information networks are constructed based on gene expression profiles in prostate tissues with and without cancer. In order to contrast structural difference of normal and diseased networks, curves of four structural parameters are given with the change of thresholds. Then threshold discrimination intervals and discrimination weights are defined. A method of finding structural key genes with significant degree-difference is proposed. The finding of key genes will help the biomedical scientists to further research the pathogenesis of prostate cancer. Finally randomisation test is performed to prove that these structural parameters can distinguish normal and prostate cancer in their structures compared with these results in real data.

Weight stigma mediates the association between BMI and self-reported health.

Weight stigma is pervasive in the United States. We tested the hypothesis that stigma may be a mechanism through which obesity negatively affects self-reported health. Two studies examined whether perceived weight-based discrimination and concerns over weight stigma mediated the association between BMI and self-reported psychological health (Study 1) and physical health (Study 2). In 2 online studies, adult community members completed measures of stigma-relevant mediators (perceived weight discrimination, weight stigma concerns) and provided their height and weight. In Study 1 (N = 171) participants also completed measures of psychological health (depression, self-esteem, quality of life), whereas participants in Study 2 (N = 194) also completed a measure of self-reported physical health. Process modeling was used to simultaneously test for mediation through perceived discrimination and stigma concerns independently as well as for serial mediation through both variables. Across both studies, we hypothesized and found support for serial mediation such that BMI was indirectly related to poorer self-reported health through its effect on perceived discrimination and concerns about stigma. Additionally, concerns about stigma mediated the association between BMI and health independent of perceived discrimination. Weight stigma is an important mediator of the association between BMI and self-reported health. Furthermore, results indicate that concerns about facing stigma in the future mediate the link between perceived past experiences of discrimination and psychological and physical health.

Comparing Ranking Methods for Tensor Components in Multilinear and Concurrent Subspace Analysis with Applications in Face Images

In the area of multi-dimensional image databases modeling, the multilinear principal component analysis (MPCA) and concurrent subspace analysis (CSA) approaches were independently proposed and applied for mining image databases. The former follows the classical principal component analysis (PCA) paradigm that centers the sample data before subspace learning. The CSA, on the other hand, performs the learning procedure using the raw data. Besides, the corresponding tensor components have been ranked in order to identify the principal tensor subspaces for separating sample groups for face image analysis and gait recognition. In this paper, we first demonstrate that if CSA receives centered input samples and we consider full projection matrices then the obtained solution is equal to the one generated by MPCA. Then, we consider the general problem of ranking tensor components. We examine the theoretical aspects of typical solutions in this field: (a) Estimating the covariance structure of the database; (b) Computing discriminant weights through separating hyperplanes; (c) Application of Fisher criterium. We discuss these solutions for tensor subspaces learned using centered data (MPCA) and raw data (CSA). In the experimental results we focus on tensor principal components selected by the mentioned techniques for face image analysis considering gender classification as well as reconstruction problems.

Weight stigma "gets under the skin"-evidence for an adapted psychological mediation framework: a systematic review.

Research consistently shows a negative view of individuals with obesity in the general public and in various other settings. Stigma and discrimination can be considered chronic stressors, as these factors have a profound impact on the psychological well-being of the affected individuals. This article proposes a framework that entails a mediation of the adverse effects of discrimination and stigmatization on mental well-being through elevated psychological risk factors that are not unique to weight but that could affect overweight and normal-weight individuals alike. A systematic review was conducted to assess the prevalence of psychological risk factors, such as self-esteem and coping, in individuals with obesity. Forty-six articles were assessed and included for detailed analysis. The number of studies on these topics is limited to certain dimensions of psychological processes. The best evaluated association of obesity and psychosocial aspects is seen for self-esteem. Most studies establish a negative association of weight and self-esteem in children and adults. All studies with mediation analysis find a positive mediation through psychological risk factors on mental health outcomes. This review shows that elevated psychological risk factors are existent in individuals with obesity and that they may be a mediator between weight discrimination and pathopsychological outcomes.

Visual Tracking via Weighted Local Cosine Similarity.

In this paper, we propose a novel weighted local cosine similarity (WLCS) and apply it to visual tracking. First, we present the local cosine similarity to measure the similarities between the target template and candidates, and provide some theoretical insights on it. Second, we develop an objective function to model the discriminative ability of local components, and use a quadratic programming method to solve the objective function and to obtain the discriminative weights. Finally, we design an effective and efficient tracker based on the WLCS method and a simple update manner within the particle filter framework. Experimental results on several challenging image sequences show that the proposed tracker achieves better performance than other competing methods.

Weight-Biased Health Professionals and the Effects on Overweight Patients

A significant number of Americans are obese. Weight bias and negative attitudes have been documented among medical professionals, and these may cause obese patients to avoid seeking health care, leading to undiagnosed pathology. Some physicians lack adequate resources and patient counseling skills when addressing patient weight management. This may lead to continued weight problems and associated complications for the patient. Many physicians do not address patient obesity with urgency and determination, even though most physicians consider obesity a widespread, problematic disease. The purpose of this literature review is to assess weight discrimination and negative attitudes among health professionals and how those attitudes affect quality of care for overweight patients. Through these generalizations, sonographers can become aware of their own biases, which may lead to poor patient care.

Sparse regularization techniques provide novel insights into outcome integration processes

By exploiting information that is contained in the spatial arrangement of neural activations, multivariate pattern analysis (MVPA) can detect distributed brain activations which are not accessible by standard univariate analysis. Recent methodological advances in MVPA regularization techniques have made it feasible to produce sparse discriminative whole-brain maps with highly specific patterns. Furthermore, the most recent refinement, the Graph Net, explicitly takes the 3D-structure of fMRI data into account. Here, these advanced classification methods were applied to a large fMRI sample (N=70) in order to gain novel insights into the functional localization of outcome integration processes. While the beneficial effect of differential outcomes is well-studied in trial-and-error learning, outcome integration in the context of instruction-based learning has remained largely unexplored. In order to examine neural processes associated with outcome integration in the context of instruction-based learning, two groups of subjects underwent functional imaging while being presented with either differential or ambiguous outcomes following the execution of varying stimulus–response instructions. While no significant univariate group differences were found in the resulting fMRI dataset, L1-regularized (sparse) classifiers performed significantly above chance and also clearly outperformed the standard L2-regularized (dense) Support Vector Machine on this whole-brain between-subject classification task. Moreover, additional L2-regularization via the Elastic Net and spatial regularization by the Graph Net improved interpretability of discriminative weight maps but were accompanied by reduced classification accuracies. Most importantly, classification based on sparse regularization facilitated the identification of highly specific regions differentially engaged under ambiguous and differential outcome conditions, comprising several prefrontal regions previously associated with probabilistic learning, rule integration and reward processing. Additionally, a detailed post-hoc analysis of these regions revealed that distinct activation dynamics underlay the processing of ambiguous relative to differential outcomes. Together, these results show that L1-regularization can improve classification performance while simultaneously providing highly specific and interpretable discriminative activation patterns.

Perceived weight discrimination in England: a population-based study of adults aged ⩾50 years.

Background:Despite a wealth of experimental studies on weight bias, little is known about weight discrimination at the population level. This study examined the prevalence and socio-demographic correlates of perceived weight discrimination in a large population-based sample of older adults.Methods:Data were from 5307 adults in the English Longitudinal Study of Ageing; a population-based cohort of men and women aged ⩾50 years. Weight discrimination was reported for five domains (less respect/courtesy; treated as less clever; poorer treatment in medical settings; poorer service in restaurants/stores; threatened/harassed) at wave 5 (2010–2011). Height and weight were measured at wave 4 (2008–2009). We used logistic regression to test the odds of weight discrimination in relation to weight status, age, sex, wealth, education and marital status.Results:Perceived weight discrimination in any domain was reported by 4.6% of participants, ranging from 0.8% in the normal-weight participants through 0.9, 6.7, 24.2 and 35.1% in individuals who were overweight or met criteria for class I, II and III obesity. Overall, and in each situation, odds of perceived weight discrimination were higher in younger and less wealthy individuals. There was no interaction between weight status and any socio-demographic variable. Relative to normal-weight participants, odds ratios for any perceived weight discrimination were 1.13 (95% confidence interval 0.53–2.40) in those who were overweight, 8.86 (4.65–16.88) in those with class I obesity, 35.06 (18.30–67.16) in class II obese and 56.43 (27.72–114.87) in class III obese.Conclusions:Our results indicate that rates of perceived weight discrimination are comparatively low in individuals who are overweight or have class I obesity, but for those with class II/III obesity, >10% had experienced discrimination in each domain, and >20% had been treated with less respect or courtesy. These findings have implications for public policy and highlight the need for effective interventions to promote equality.

Perceived weight discrimination and changes in weight, waist circumference, and weight status.

ObjectiveTo examine associations between perceived weight discrimination and changes in weight, waist circumference, and weight status.MethodsData were from 2944 men and women aged ≥50 years participating in the English Longitudinal Study of Ageing. Experiences of weight discrimination were reported in 2010-2011 and weight and waist circumference were objectively measured in 2008-2009 and 2012-2013. ANCOVAs were used to test associations between perceived weight discrimination and changes in weight and waist circumference. Logistic regression was used to test associations with changes in weight status. All analyses adjusted for baseline BMI, age, sex, and wealth.ResultsPerceived weight discrimination was associated with relative increases in weight (+1.66 kg, P < 0.001) and waist circumference (+1.12 cm, P = 0.046). There was also a significant association with odds of becoming obese over the follow-up period (OR = 6.67, 95% CI 1.85-24.04) but odds of remaining obese did not differ according to experiences of weight discrimination (OR = 1.09, 95% CI 0.46-2.59).ConclusionsOur results indicate that rather than encouraging people to lose weight, weight discrimination promotes weight gain and the onset of obesity. Implementing effective interventions to combat weight stigma and discrimination at the population level could reduce the burden of obesity.

Effect of ice massage on lower extremity functional performance and weight discrimination ability in collegiate footballers.

Background:Cryotherapy, in the form of ice massge is used to reduce inflammation after acute musculoskeletal injury or trauma. The potential negative effects of ice massage on proprioception are unknown, despite equivocal evidence supporting its effectivenessObjectives:The purpose of the study was to test the influence of cooling on weight discrimination ability and hence the performance in footballers.Patients and Methods:The study was of same subject experimental design (pretest-posttest design). Thirty male collegiate football players, whose mean age was 21.07 years, participated in the study. The participants were assessed for two functional performance tests, single leg hop test and crossed over hop test and weight discrimination ability before and after ice massage for 5 minutes on hamstrings muscle tendon.Results:Pre cooling scores of Single Leg Hop Test of the dominant leg in the subjects was 166.65 (± 10.16) cm and post cooling scores of the dominant leg was 167.25 (± 11.77) cm. Pre cooling scores of Crossed Over Hop Test of the dominant leg in the subjects was 174.14 (± 8.60) cm and post cooling scores of the dominant leg was 174.45 (± 9.28) cm. Pre cooling scores of Weight Discrimination Differential Threshold of the dominant leg in the subjects was 1.625 ± 1.179 kg compared with post cooling scores of the dominant leg 1.85 (± 1.91) kg. Pre cooling scores of single leg hop and crossed over hop test of the dominant leg in the subjects compared with post cooling scores of the dominant leg showed no significant differences and it was also noted that the weight discrimination ability (weight discrimination differential threshold) didn’t show any significant difference. All the values are reported as mean ± SD.Conclusions:This study provides additional evidence that proprioceptive acuity in the hamstring muscles (biceps femoris) remains largely unaffected after ice application to the hamstrings tendon (biceps femoris).

Weight and health-related quality of life: The moderating role of weight discrimination and internalized weight bias

ObjectivesObesity is an increasingly prevalent public health concern, with associated medical comorbidities and impairment in health-related quality of life (HRQoL). Obese women are frequently victims of weight-related discrimination. The HRQoL impairments among obese people could be related to this discrimination and to internalized weight bias.DesignWe examined the potential moderating role of discrimination (from others) and self-directed (internalized) weight-based discrimination in the association between body mass index (BMI) and HRQoL. MethodsEighty-one women (mean age=41.1years; mean BMI=43.40kg/m2, 97% Caucasian) completed valid and reliable measures of weight bias internalization (weight bias internalization scale), perceived discrimination by others (everyday discrimination scale) and both physical and mental HRQoL (SF-36 Health Survey). Multiple regression analysis was used to test whether internalized weight bias or discrimination moderated the association between BMI and the summary scores for physical and mental HRQoL, controlling for age. ResultsSignificant associations were found between BMI and discrimination (r=.36, p=.002), between internalized weight bias and both mental (r=.61, p<.001) and physical HRQoL (r=.45, p<.001), and between discrimination and physical HRQoL (r=.29, p=.014). A statistically significant interaction was found between BMI and internalized weight bias (b=−.21, SE=.10, p<0.05) in accounting for the variance in physical HRQoL. ConclusionsThe association between higher BMI and poorer physical HRQoL was found only in individuals reporting high levels of internalized weight bias. Self-discrimination among overweight individuals may be a critical factor in their physical health impairment.

Short text keyphrase extraction with hypergraphs

Graph-based ranking for keyphrase extraction has become an important approach for measuring saliency scores in text due to its ability to capture the context. By modeling words as vertices and the co-occurrence relation between words as edges, the importance of words is measured from the whole graph. However, graphs by nature can only capture the pair-wise relation between vertices. Therefore, it is not clear if graphs can capture high-order relations of more than two words. In this paper, we propose to use a hypergraph to capture high-order relations appearing in short documents, and use such information to infer better ranking of words. Additionally, we model the temporal and social attributes of short documents and discriminative weights of words into the hypergraph as weights which give us the ability of capturing recent and topical keyphrases. Furthermore, to rank vertices in the proposed hypergraph, we propose a probabilistic random walk that takes into account weights of both vertices and hyperedges. We show the effectiveness of our approach by conducting extensive experiments over two different data sets which demonstrate the robustness of the proposed approach.

Discriminative likelihood score weighting based on acoustic-phonetic classification for speaker identification

In this paper, a new discriminative likelihood score weighting technique is proposed for speaker identification. The proposed method employs a discriminative weighting of frame-level log-likelihood scores with acoustic-phonetic classification in the Gaussian mixture model (GMM)-based speaker identification. Experiments performed on the Aurora noise-corrupted TIMIT database showed that the proposed approach provides meaningful performance improvement with an overall relative error reduction of 15.8% over the maximum likelihood-based baseline GMM approach.