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Indices of Change: Analysing the Indexical Properties of Data from Psychotherapy Case Work to Discern Patterns of Therapeutic Change Over Time

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Computer Supported Qualitative Research (ISQR 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 621))

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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.

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Author information

Authors and Affiliations

  1. School of Healthcare, University of Leeds, Baines Wing, Leeds, LS2 9TJ, UK

    John Hills, Jane Cahill & John Lees

  2. University of Western Australia, Perth, Australia

    Dawn Freshwater

Authors
  1. John Hills
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  2. Jane Cahill
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  3. John Lees
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  4. Dawn Freshwater
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Corresponding author

Correspondence to John Hills .

Editor information

Editors and Affiliations

  1. Education and Psychology Department, University of Aveiro, Aveiro, Portugal

    António Pedro Costa

  2. Information Systems Department, University of Minho, Guimarães, Portugal

    Luís Paulo Reis

  3. Education and Psychology Department, University of Aveiro, Aveiro, Portugal

    Francislê Neri de Souza

  4. Education and Psychology Department, University of Aveiro, Aveiro, Portugal

    António Moreira

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Hills, J., Cahill, J., Lees, J., Freshwater, D. (2018). Indices of Change: Analysing the Indexical Properties of Data from Psychotherapy Case Work to Discern Patterns of Therapeutic Change Over Time. In: Costa, A., Reis, L., Souza, F., Moreira, A. (eds) Computer Supported Qualitative Research. ISQR 2017. Advances in Intelligent Systems and Computing, vol 621. Springer, Cham. https://doi.org/10.1007/978-3-319-61121-1_36

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  • DOI: https://doi.org/10.1007/978-3-319-61121-1_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61120-4

  • Online ISBN: 978-3-319-61121-1

  • eBook Packages: EngineeringEngineering (R0)

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