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减少健康差距:理解医疗保健专业人员和患者特征对治疗的意外影响。

Reducing Health Disparities: Understanding the Unintended Effects of Health Care Professional and Patient Characteristics on Treatment.

作者信息

Nazione Samantha, Nazione Anthony

出版信息

J Am Osteopath Assoc. 2018 Jun 1;118(6):376-383. doi: 10.7556/jaoa.2018.081.

DOI:10.7556/jaoa.2018.081
PMID:29809254
Abstract

CONTEXT

The responsibility-affect-helping model proposes that helping behavior is a function of perceived responsibility and affect.

OBJECTIVE

To examine the effect of medical students' degree (DO or MD) and gender on attitudes toward patients and how these factors could act as moderators in the responsibility-affect-helping model.

METHODS

This 2×3 experimental study included third- and fourth-year osteopathic (ie, DO) and allopathic (ie, MD) medical students. Students were given a survey that included the medical record and photograph of a fictitious male patient with diabetes and a message from the patient regarding his diet nonadherence. The patients differed in race (black or white) and the cause of diet nonadherence (healthy foods don't taste good, no reason given, or inability to access healthy foods). Survey items measured students' perception of the patient's responsibility for his nonadherence, level of anger, intention to help, level of sympathy, and ethnocentrism. Data were analyzed using a multivariate analysis of covariance with ethnocentrism as a covariate.

RESULTS

Of 1520 potential students, 231 were included in the study. Mean (SD) responsibility scale scores showed that DO students viewed the patient who gave dislike of healthy food or no reason for their diet nonadherence as more responsible for his nonadherence than did MD students (4.69 [0.99] vs 3.93 [1.00] and 4.35 [0.88] vs 3.65 [1.01], respectively). Conversely, mean (SD) responsibility scores showed that DO students viewed patients who indicated lack of access to healthy food as his reason for diet nonadherence as less responsible for his nonadherence than did MD students (2.45 [0.94] vs 2.59 [1.08]) (F2,228=3.21, P<.05, η2=.03). Furthermore, female students perceived patients to be less responsible for their diet nonadherence than did male students (3.28 [1.22] vs 3.88 [1.22]) (F2,228=8.87, P<.01, η2=.04). Ethnocentrism was consistently a significant covariate for students' perception of patient characteristics, predicted patient behaviors, perception of the patient's responsibility for his nonadherence, students' level of anger, students' intention to help, and students' level of sympathy.

CONCLUSION

Survey results showed that DO students perceived patients who reported dislike of healthy food or no reason for diet nonadherence as more responsible for their health issue and patients who indicated lack of access to healthy food as less responsible for their nonadherence than did MD students. Additionally, female students perceived patients to be less responsible for their health issue than did male students. Results of the current study indicate that physician demographic factors could be taken into account as proxy variables when using the responsibility-affect-helping model in the health care field.

摘要

背景

责任 - 情感 - 帮助模型提出,帮助行为是感知责任和情感的函数。

目的

研究医学生学位(医学博士或医学博士)和性别对患者态度的影响,以及这些因素如何在责任 - 情感 - 帮助模型中作为调节变量。

方法

这项2×3实验研究纳入了三年级和四年级的整骨疗法(即医学博士)和对抗疗法(即医学博士)医学生。学生们收到一份调查问卷,其中包括一名虚构的患有糖尿病的男性患者的病历和照片,以及患者关于其饮食不依从的信息。患者在种族(黑人或白人)和饮食不依从的原因(健康食品不好吃、未给出原因或无法获得健康食品)方面存在差异。调查项目测量了学生对患者不依从行为的责任感知、愤怒程度、帮助意愿、同情程度和种族中心主义。使用以种族中心主义为协变量的多变量协方差分析对数据进行分析。

结果

在1520名潜在学生中,231名被纳入研究。平均(标准差)责任量表得分显示,医学博士学生认为那些不喜欢健康食品或未说明饮食不依从原因的患者对自己的不依从行为负有更大责任,而医学博士学生则不然(分别为4.69[0.99]对3.93[1.00]和4.35[0.88]对3.65[1.01])。相反,平均(标准差)责任得分显示,医学博士学生认为那些表示无法获得健康食品是其饮食不依从原因的患者对自己的不依从行为负有较小责任,而医学博士学生则不然(2.45[0.94]对2.59[1.08])(F2,228 = 3.21,P <.05,η2 =.03)。此外,女学生认为患者对其饮食不依从行为的责任比男学生小(3.28[1.22]对3.88[1.22])(F2,228 = 8.87,P <.01,η2 =.04)。种族中心主义一直是学生对患者特征的感知、预测患者行为、对患者不依从行为的责任感知、学生的愤怒程度、学生的帮助意愿和学生的同情程度的重要协变量。

结论

调查结果显示,与医学博士学生相比,医学博士学生认为那些报告不喜欢健康食品或未说明饮食不依从原因的患者对自己的健康问题负有更大责任,而那些表示无法获得健康食品的患者对自己的不依从行为负有较小责任。此外,女学生认为患者对自己健康问题的责任比男学生小。本研究结果表明,在医疗保健领域使用责任 - 情感 - 帮助模型时,可以将医生的人口统计学因素作为代理变量考虑在内。

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