نبذة مختصرة : The presentation will present a proposed psychological study of the link between stigmatizing beliefs and depression vulnerability. Stigma, defined broadly as a perception of being flawed because of a socially-unacceptable characteristic (Blaine, 2000), accompanies a variety of mental health problems (Britt, 2000). One study suggests a link between stigma and vulnerability to depression (Britt et al., 2008). Recent research has distinguished between two kinds of stigma: public stigma, prejudicial views about a stigmatized group believed to be endorsed by the general public (Corrigan, 2004) and self-stigma, "reduction of an individual’s self-esteem or self-worth caused by the individual self-labeling herself or himself as someone who is socially unacceptable" (Vogel, Wade & Haake, 2006). The proposed study will examine whether public stigma and self-stigma play a role in predicting depression proneness. Considering the detrimental effects self-stigma has demonstrated on those with mental illness (Vogel, Wade & Haake, 2006), it is hypothesized that self-stigmatizing beliefs will be as predictive of depression proneness as those regarding public stigma. That is, given stressors, individuals who hold self-stigmatizing beliefs are hypothesized to be more likely to be found to be depression-prone. This finding would run counter to existing work regarding the stigma-mental health relationship by shifting the model from reactive to proactive, one that would identify persons who are prone to depression because of stigma. Background study of the topic is ongoing, and application to UM’s Institutional Review Board is in progress. Study will utilize a within-subjects survey design in which subjects will be asked to complete the Depression Stigma Scale, the Depression Proneness Rating Scale, and the Perceived Stress Scale. It is hoped that these measures will shed light on any relationships that exist between stigma and depression proneness. It is projected that data collection will be underway at the time of the ...
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