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Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement

Jennings, Helen; Slade, Mike; Bates, Peter; Munday, Emma; Toney, Rebecca

Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement Thumbnail


Authors

Helen Jennings

MIKE SLADE M.SLADE@NOTTINGHAM.AC.UK
Professor of Mental Health Recovery and Social Inclusion

Peter Bates

Emma Munday

Rebecca Toney



Abstract

Background
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.
Methods
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.
Results
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 o-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 coresearchers, 40 from academic researchers).The process was refined into a best practice framework comprising Preparation, CDA and Application phases.
Conclusions
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.

Journal Article Type Article
Acceptance Date Jun 17, 2018
Online Publication Date Jun 28, 2018
Publication Date Jun 28, 2019
Deposit Date Jun 18, 2018
Publicly Available Date Jun 28, 2018
Journal BMC Psychiatry
Electronic ISSN 1471-244X
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 18
Article Number 213
DOI https://doi.org/10.1186/s12888-018-1794-8
Keywords Patient and Public Involvement (PPI), mental health research, qualitative, collaborative data analysis, co-production
Public URL https://nottingham-repository.worktribe.com/output/942840
Publisher URL https://bmcpsychiatry.biomedcentral.com/articles/10.1186/s12888-018-1794-8

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