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根据维罗纳编码情绪序列定义(VR-CoDES)识别的线索和关注点的患者验证:一种基于视频和访谈的方法。

Patient validation of cues and concerns identified according to Verona coding definitions of emotional sequences (VR-CoDES): a video- and interview-based approach.

机构信息

Oslo University College, Faculty of Nursing, Norway.

出版信息

Patient Educ Couns. 2011 Feb;82(2):156-62. doi: 10.1016/j.pec.2010.04.036. Epub 2010 Jun 8.

Abstract

OBJECTIVE

A challenging but main task for clinicians is to identify patients' concerns related to their medical conditions. The study aim was to validate a new coding scheme for identifying patients' cues and concerns.

METHODS

12 videotaped consultations between nurses and pain patients were coded according to the Verona Coding Scheme for Emotional Sequences (VR-CoDES). During a metainterview each patient watched his/her own video interview with the researcher to confirm or disconfirm the identified cues and concerns. A directive or an open format was applied. Quantitative and qualitative data analyses were performed.

RESULTS

Patients' confirmation in relation to the coding gave a sensitivity of 0.95 and specificity of 0.99 in the directive format and a sensitivity of 0.99 and specificity of 0.70 applying the open format. Through a qualitative analysis 83% of researcher-identified cues and concerns were validated. 17% were not confirmed or uncertain.

CONCLUSION

The VR-CoDES seems to capture what are experienced as real concerns to patients, and proves to be a coding scheme with a high degree of ecological validity.

PRACTICE IMPLICATIONS

The VR-CoDES provides a valid framework for detecting patients' cues and concerns, and should be explored as a training tool to develop clinicians' empathic accuracy.

摘要

目的

对于临床医生来说,一项具有挑战性但主要的任务是识别与患者病情相关的患者关注点。本研究旨在验证一种用于识别患者线索和关注点的新编码方案。

方法

根据维罗纳情绪序列编码方案(VR-CoDES),对护士与疼痛患者之间的 12 段录像咨询进行编码。在元访谈中,每位患者与研究人员一起观看自己的视频访谈,以确认或否定识别出的线索和关注点。使用指令或开放式格式进行定量和定性数据分析。

结果

患者对编码的确认在指令格式下具有 0.95 的灵敏度和 0.99 的特异性,在开放式格式下具有 0.99 的灵敏度和 0.70 的特异性。通过定性分析,83%的研究人员识别出的线索和关注点得到了验证。17%的线索和关注点未得到确认或存在不确定性。

结论

VR-CoDES 似乎捕捉到了患者实际关注的问题,证明是一种具有高度生态有效性的编码方案。

实践意义

VR-CoDES 为检测患者的线索和关注点提供了一个有效的框架,应作为一种培训工具来探索,以提高临床医生的共情准确性。

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