Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement.
Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement.
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DOI：
10.1186/s12888-018-1794-8
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发表时间：
2018-06-28
期刊：
影响因子：
4.4
通讯作者：
Toney R
中科院分区：
文献类型：
--
作者：
Jennings H;Slade M;Bates P;Munday E;Toney R
精神卫生研究中的患者和公众参与（PPI）正在增加，特别是在早期（资助前）阶段。生产者价格指数在较后阶段，包括在分析定性数据时，不太一致。本研究的目的是开发一种方法，让PPI的合作研究人员与学术研究人员合作分析定性心理健康研究数据，试点和完善这种方法，并创建一个定性心理健康研究的协作数据分析（CDA）的最佳实践框架。在恢复学院的RECOLLECT研究的背景下，协作数据分析研究的关键文献综述进行，以确定成功的CDA的方法和建议。制定了一种全面发展分析方法，然后在RECOLLECT中进行了试点，随后完善和制定了一个最佳做法框架。从10个纳入的出版物中，确定了四种CDA方法：（1）咨询，（2）开发，（3）应用和（4）编码框架的开发和应用。成功的CDA的四个特点被发现：CDA过程是共同产生的; CDA过程是现实的时间和资源; CDA过程的需求是PPI合作研究人员管理;和组的期望和动态有效管理。一个四次会议的CDA过程进行了试点，共同制作一个编码框架的基础上收集的定性数据在RECOLLECT和创建一个心理健康服务用户定义的变化模型相关的恢复学院。正式和非正式的反馈显示了积极的参与。CDA过程涉及额外的80人-天的时间（40人来自PPI的合作研究人员，40人来自学术研究人员）。该过程被细化为一个最佳实践框架，包括准备，CDA和应用阶段。本研究开发了一种类型学的方法，以协作分析的定性数据在精神卫生研究，确定从现有的证据的特征，成功的参与，并开发，试点和完善的第一个最佳实践框架的定性数据的协作分析。这个框架有可能支持有意义的PPI在定性心理健康研究的背景下进行数据分析，这是以前被忽视的研究周期的核心部分。
Patient and Public Involvement (PPI) in mental health research is increasing, especially in early (pre-funding) stages. PPI is less consistent in later stages, including in analysing qualitative data. The aims of this study were to develop a methodology for involving PPI co-researchers in collaboratively analysing qualitative mental health research data with academic researchers, to pilot and refine this methodology, and to create a best practice framework for collaborative data analysis (CDA) of qualitative mental health research. In the context of the RECOLLECT Study of Recovery Colleges, a critical literature review of collaborative data analysis studies was conducted, to identify approaches and recommendations for successful CDA. A CDA methodology was developed and then piloted in RECOLLECT, followed by refinement and development of a best practice framework. From 10 included publications, four CDA approaches were identified: (1) consultation, (2) development, (3) application and (4) development and application of coding framework. Four characteristics of successful CDA were found: CDA process is co-produced; CDA process is realistic regarding time and resources; demands of the CDA process are manageable for PPI co-researchers; and group expectations and dynamics are effectively managed. A four-meeting CDA process was piloted to co-produce a coding framework based on qualitative data collected in RECOLLECT and to create a mental health service user-defined change model relevant to Recovery Colleges. Formal and informal feedback demonstrated active involvement. The CDA process involved an extra 80 person-days of time (40 from PPI co-researchers, 40 from academic researchers). The process was refined into a best practice framework comprising Preparation, CDA and Application phases. This study has developed a typology of approaches to collaborative analysis of qualitative data in mental health research, identified from available evidence the characteristics of successful involvement, and developed, piloted and refined the first best practice framework for collaborative analysis of qualitative data. This framework has the potential to support meaningful PPI in data analysis in the context of qualitative mental health research studies, a previously neglected yet central part of the research cycle.
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影响因子：
--
作者：
Baxter, Susan;Muir, Delia;Baird, Wendy
通讯作者：
Baird, Wendy
影响因子：
1.2
作者：
Cotterell, Phil
通讯作者：
Cotterell, Phil
影响因子：
3.2
作者：
Baart, Ingrid L. M. A.;Abma, Tineke A.
通讯作者：
Abma, Tineke A.
DOI：
10.1111/hex.12295
发表时间：
2016-06
期刊：
Health expectations : an international journal of public participation in health care and health policy
影响因子：
--
作者：
Boaz A;Biri D;McKevitt C
通讯作者：
McKevitt C
影响因子：
4
作者：
Gale NK;Heath G;Cameron E;Rashid S;Redwood S
通讯作者：
Redwood S