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Gender, Personality Traits and Experience With Psychiatric Patients as Predictors of Stigma in Italian Psychology Students

机译:性别,人格特征和精神病患者的经历作为意大利心理学专业学生耻辱的预测指标

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A sample of undergraduate Psychology students (n = 1005), prevalently females (82.4%), mean age 20.5 (sd 2.5), was examined regarding their attitudes toward people suffering from mental illness. The survey instrument included a brief form for demographic variables, the Attribution Questionnaire-9 (AQ-9), the Ten Items Personality Inventory (TIPI), and two questions exploring attitudes toward open-door and restraint-free policies in Psychiatry. Higher levels of stigmatizing attitudes were found in males (Pity, Blame, Help, and Avoidance) and in those (76.5%) who had never had any experience with psychiatric patients (Danger, Fear, Blame, Segregation, Help, Avoidance and Coercion). A similar trend was also found in those who don't share the policy of no seclusion/restraint, while subjects who are favorable to open-door policies reported higher Coercion scores. No correlations were found between dimensions of stigma and personality traits. A machine learning approach was then used to explore the role of demographic, academic and personality variables as predictors of stigmatizing attitudes. Agreeableness and Extraversion emerged as the most relevant predictors for blaming attitudes, while Emotional Stability and Openness appeared to be the most effective contributors to Anger. Our results confirmed that a training experience in Psychiatry might successfully reduce stigma in Psychology students. Further research, with increased generalizability of samples and more reliable instruments, should address the role of personality traits and gender on attitudes toward people suffering from mental illness.
机译:调查了他们对心理疾病患者态度的调查,这些样本是心理学专业的本科生(n = 1005),其中女性(82.4%),平均年龄20.5(标准差2.5)。该调查工具包括一个用于人口统计学变量的简短表格,《归因调查表9》(AQ-9),《十项人格量表》(TIPI),以及两个问题,用于探讨对精神病学开放和无约束政策的态度。在男性(可怜,责备,帮助和避免)和从未有过精神病患者经历(危险,恐惧,责备,隔离,帮助,避免和强迫)的男性(76.5%)中发现了较高的污名化态度。 。在那些不实行不隔离/不拘束政策的人中也发现了类似的趋势,而那些倾向于开放政策的受试者报告了更高的强制性分数。在污名的维度和人格特质之间没有发现相关性。然后使用机器学习方法来探索人口统计学,学术和人格变量作为污名化态度的预测因素的作用。令人愉快的态度和外向性成为指责态度最相关的预测因素,而情绪的稳定和开放似乎是愤怒的最有效因素。我们的结果证实,在精神病学方面的培训经验可能会成功地减少心理学专业学生的污名。进一步的研究应通过增加样本的通用性和更可靠的手段来解决人格特质和性别在对待精神疾病患者的态度中的作用。

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