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

Health Expect

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

Published: December 2013

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5060679PMC
http://dx.doi.org/10.1111/j.1369-7625.2012.00810.xDOI Listing

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