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在协作式定性数据分析中倾听服务使用者研究人员的声音:多种编码的案例。

Hearing the voices of service user researchers in collaborative qualitative data analysis: the case for multiple coding.

机构信息

Department of Mental Health Sciences, University College London, UK; Health Service and Population Research Department, Institute of Psychiatry, King's College, London.

出版信息

Health Expect. 2013 Dec;16(4):e89-99. doi: 10.1111/j.1369-7625.2012.00810.x. Epub 2012 Sep 7.

Abstract

BACKGROUND

Health research is frequently conducted in multi-disciplinary teams, with these teams increasingly including service user researchers. Whilst it is common for service user researchers to be involved in data collection--most typically interviewing other service users--it is less common for service user researchers to be involved in data analysis and interpretation. This means that a unique and significant perspective on the data is absent.

AIM

This study aims to use an empirical report of a study on Cognitive Behavioural Therapy for psychosis (CBTp) to demonstrate the value of multiple coding in enabling service users voices to be heard in team-based qualitative data analysis.

DESIGN

The CBTp study employed multiple coding to analyse service users' discussions of CBT for psychosis (CBTp) from the perspectives of a service user researcher, clinical researcher and psychology assistant. Multiple coding was selected to enable multiple perspectives to analyse and interpret data, to understand and explore differences and to build multi-disciplinary consensus.

RESULTS

Multiple coding enabled the team to understand where our views were commensurate and incommensurate and to discuss and debate differences. Through the process of multiple coding, we were able to build strong consensus about the data from multiple perspectives, including that of the service user researcher.

DISCUSSION

Multiple coding is an important method for understanding and exploring multiple perspectives on data and building team consensus. This can be contrasted with inter-rater reliability which is only appropriate in limited circumstances.

CONCLUSION

We conclude that multiple coding is an appropriate and important means of hearing service users' voices in qualitative data analysis.

摘要

背景

健康研究通常由多学科团队进行,这些团队越来越多地包括服务用户研究人员。虽然服务用户研究人员通常参与数据收集——最典型的是采访其他服务用户——但他们参与数据分析和解释的情况较少。这意味着缺少对数据的独特而重要的视角。

目的

本研究旨在使用一项关于认知行为疗法治疗精神病(CBTp)的研究的实证报告,展示多元编码在团队基础上的定性数据分析中如何使服务用户的声音被听到的价值。

设计

CBTp 研究采用多元编码,从服务用户研究人员、临床研究人员和心理学助理的角度分析服务用户对精神病的认知行为疗法(CBTp)的讨论。选择多元编码是为了使多个视角能够分析和解释数据,理解和探索差异,并建立多学科共识。

结果

多元编码使团队能够理解我们的观点是否一致和不一致,并讨论和辩论差异。通过多元编码的过程,我们能够从多个视角,包括服务用户研究人员的视角,对数据建立强烈的共识。

讨论

多元编码是理解和探索数据的多个视角并建立团队共识的重要方法。这与仅在有限情况下适用的评分者间信度形成对比。

结论

我们得出结论,多元编码是在定性数据分析中倾听服务用户声音的一种合适且重要的方法。

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