医疗咨询中积极信息的剖析:22个随机试验中信息的成分分析

J. Howick, E. Lyness, C. Albury, K. Smith, H. Dambha‐Miller, Mohana Ratnapalan, J. Vennik, Stephanie Hughes, J. Bostock, L. Morrison, C. Mallen, H. Everitt, Sue Dean, T. Levett-Jones, S. Ivynian, P. Little, F. Bishop
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引用次数: 5

摘要

背景:患者希望从他们的保健医生诚实和希望。最近一项对22项随机试验的系统回顾发现,传递积极信息的医疗从业人员可以改善患者的治疗效果,尤其是减轻疼痛。然而,在这些试验中,积极信息的语言和非语言成分差异很大,这对以人为本的护理的实施构成了障碍。目的:本研究探讨在回顾试验中积极信息的共同组成部分。方法:我们从最近的系统综述中提取了22项试验中用于传递积极信息的口头和非口头语言。三位独立的研究人员使用内容分析对这些信息的组成部分进行编码。结果:我们样本中的积极信息有2到18种不同的成分。这些被集中在5个方面:明确积极的结果,使信息个性化,利用联系和意义,提供一个支持性的心理背景和提供一个理由。在一半的研究中,信息通过重复得到强化。在这些集群中,积极信息的最常见组成部分是具体效果的建议(18项研究)和个性化配方(15项研究)。大多数研究没有充分描述积极信息的组成部分。结论:随机试验中的积极信息是复杂的干预措施,其中大多数包括对具体效果的强烈建议,自信地提出,并与个体患者个人相关。未来的积极信息试验应报告这些干预措施的所有组成部分。
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Anatomy of positive messages in healthcare consultations: component analysis of messages within 22 randomised trials
Background: Patients desire both honesty and hope from their healthcare practitioners. A recent systematic review of 22 randomised trials found that healthcare practitioners who deliver positive messages improve patient outcomes, most notably by reducing pain. However, the verbal and non-verbal components of positive messages within these trials varied greatly, which presents a barrier to the implementation of person-centered care. Objective: This study investigates common components of positive messages within the reviewed trials. Methods: We extracted the verbal and non-verbal language used to deliver positive messages in 22 trials from a recent systematic review. Three independent researchers coded the components of the messages using content analysis. Results: Positive messages in our sample had between 2 and 18 different components. These were clustered into 5 areas: specifying the positive outcomes, making the message personal, drawing on associations and meanings, providing a supportive psychological context and providing a rationale. Messages were reinforced through repetition in half the studies. Within the clusters, the most common components of positive messages were suggestions of specific effects (18 studies) and personalised formulations (15 studies). Most studies did not describe the components of positive messages adequately. Conclusions: Positive messages within randomized trials are complex interventions, with most including strong suggestions about specific effects, presented confidently and made personally relevant to the individual patient. Future trials of positive messages should report all components of these interventions.
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