Predictors of Self-Stigma in Schizophrenia: New Insights Using Mobile Technologies.
Predictors of Self-Stigma in Schizophrenia: New Insights Using Mobile Technologies.
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DOI：
10.1080/15504263.2012.723311
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发表时间：
2012-10
影响因子：
2.2
通讯作者：
Corrigan PW
中科院分区：
文献类型：
--
作者：
Ben-Zeev D;Frounfelker R;Morris SB;Corrigan PW
自我污名对严重精神疾病患者的康复有显著的负面影响，但其变化过程尚不清楚。个体的自我污名水平可能会随着时间的推移而变化，并随着外部/背景（即，位置、活动、社交公司）和内部（即，精神症状、情绪）因素。本研究的目的是检查自我污名化的信念和这些因素之间的关系，因为它们发生在精神分裂症患者的日常生活中。移动的技术被用来纵向跟踪自我耻辱，精神病症状，消极影响，积极影响，活动，并立即社会和物理环境的瞬间水平在24个精神分裂症患者，每天多次，超过一周的时间。多水平模型分析表明，当前的活动与自我污名的变化相关（χ2= 10.53，p <0.05），而当前的地理位置和社会陪伴与自我污名的变化无关。时滞分析发现，消极情感（β=0.11，p<0.01）和精神病症状严重程度（β=0.16，p<0.01）的增加预示着自我污名化信念强度的增加。精神病性症状是自我污名增加的前因和后果（β=0.08，p<0.01）。我们的研究结果支持了一个框架，将自我污名理解为一种基于内部状态和外部环境变化而变化的体验。移动的技术是研究自我污名的有效方法，并有可能用于提供临床干预。
Self-stigma has significant negative impact on the recovery of individuals with severe mental illness, but its varying course is not well understood. Individual levels of self-stigma may vary over time and fluctuate in response to both external/contextual (i.e., location, activity, social company) and internal (i.e., psychiatric symptoms, mood) factors. The aim of this study was to examine the relationship between self-stigmatizing beliefs and these factors, as they occur in the daily life of individuals with schizophrenia. Mobile technologies were used to longitudinally track momentary levels of self-stigma, psychotic symptoms, negative affect, positive affect, activity, and immediate social and physical environment in twenty-four individuals with schizophrenia, multiple times daily, over a one-week period. Multilevel modeling showed that participants’ current activity was associated with changes in self-stigma (χ2= 10.53, p <0.05), but immediate location and social company were not. Time-lagged analyses found that increases in negative affect (β=0.11, p<0.01) and psychotic symptom severity (β=0.16, p<0.01) predicted increases in the intensity of self-stigmatizing beliefs. Psychotic symptoms were found to be both an antecedent and a consequence (β=0.08, p<0.01) of increased self-stigma. Our findings support a framework for understanding self-stigma as an experience that changes based on alterations in internal states and external circumstances. Mobile technologies are an effective methodology to study self-stigma and have potential to be used to deliver clinical interventions.
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