Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement
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 i...
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| Format: | Article |
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BioMed Central
2018
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| Online Access: | https://eprints.nottingham.ac.uk/52454/ |
| _version_ | 1848798729306374144 |
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| author | Jennings, Helen Slade, Mike Bates, Peter Munday, Emma Toney, Rebecca |
| author_facet | Jennings, Helen Slade, Mike Bates, Peter Munday, Emma Toney, Rebecca |
| author_sort | Jennings, Helen |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T20:24:24Z |
| format | Article |
| id | nottingham-52454 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:24:24Z |
| publishDate | 2018 |
| publisher | BioMed Central |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-524542020-05-04T19:43:02Z https://eprints.nottingham.ac.uk/52454/ 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 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. BioMed Central 2018-06-28 Article PeerReviewed Jennings, Helen, Slade, Mike, Bates, Peter, Munday, Emma and Toney, Rebecca (2018) Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement. BMC Psychiatry . ISSN 1471-244X Patient and Public Involvement (PPI) mental health research qualitative collaborative data analysis co-production https://bmcpsychiatry.biomedcentral.com/articles/10.1186/s12888-018-1794-8 doi:10.1186/s12888-018-1794-8 doi:10.1186/s12888-018-1794-8 |
| spellingShingle | Patient and Public Involvement (PPI) mental health research qualitative collaborative data analysis co-production 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 |
| title | Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement |
| title_full | Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement |
| title_fullStr | Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement |
| title_full_unstemmed | Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement |
| title_short | Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement |
| title_sort | best practice framework for patient and public involvement (ppi) in collaborative data analysis of qualitative mental health research: methodology development and refinement |
| topic | Patient and Public Involvement (PPI) mental health research qualitative collaborative data analysis co-production |
| url | https://eprints.nottingham.ac.uk/52454/ https://eprints.nottingham.ac.uk/52454/ https://eprints.nottingham.ac.uk/52454/ |