Hills, JW orcid.org/0000-0002-6852-8261, Cahill, J, Lees, J orcid.org/0000-0002-1225-9007 et al. (1 more author) (2018) Indices of Change: Analysing the Indexical Properties of Data from Psychotherapy Case Work to Discern Patterns of Therapeutic Change Over Time. In: Costa, AP, Reis, LP, Souza, FND and Moreira, A, (eds.) Computer Supported Qualitative Research: Second International Symposium on Qualitative Research (ISQR 2017). Advances in Intelligent Systems and Computing, 621 . Springer Verlag , pp. 418-424. ISBN 978-3-319-61120-4
Abstract
With reference to semiotic theory, a form of data analysis is proposed that explicitly unpacks the indexical properties of data from psychotherapy case studies. The approach is observed to happen within the therapeutic hour as a co-production between the client and their therapist. Thus analysing the data in this way seeks to address two common charges against traditional research into psychotherapy processes: that it fails to capture the true value of the therapy and lacks the sensitivity to measure outcomes. Two case vignettes will demonstrate the utility of this approach in lived context, with meaning emerging as therapy continues.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | (c) 2018, Springer International Publishing AG. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-61121-1_36 |
Keywords: | psychotherapy; case study research; practitioner research; change process research; semiotics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Healthcare (Leeds) > Nursing Mental Health (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Jul 2017 11:37 |
Last Modified: | 21 Jun 2018 00:39 |
Status: | Published |
Publisher: | Springer Verlag |
Series Name: | Advances in Intelligent Systems and Computing |
Identification Number: | 10.1007/978-3-319-61121-1_36 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:119080 |