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Innovative Moments in Group Therapy: Analyzing voices of group change.

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Title: Innovative Moments in Group Therapy: Analyzing voices of group change.
Authors: Garcia-Martínez, J. (AUTHOR), Maestre-Castillo, D. (AUTHOR), Payán-Bravo, M. A. (AUTHOR), Fernández-Navarro, P. (AUTHOR)
Source: Journal of Constructivist Psychology. Apr-Jun2021, Vol. 34 Issue 2, p195-206. 12p.
Subjects: Group psychotherapy, Social groups, Mental illness, Social interaction
Abstract: The Innovative Moments Coding System has been used for studying therapeutic change. However, there has hardly been any research on its application in group therapy and on how new I-positions emerge in groups. Based on the literature review on group therapy, constructivist therapy, and the dialogical self theory this article proposes three new types of innovative moments to study the complex interaction present in group interventions. These innovative moments group types are illustrated by contrasting two cases, Ángel and Zacarías, in a group that is centered on recovering from self-stigma in patients with a severe mental disorder. The results show a different group innovative moment profile in these two cases. This adaptation of the innovative moments model can be used to track how different voices from different participants interact and are integrated in the group dynamics. Lastly, this article also highlights some clinical implications for group work and group change from a dialogical perspective. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Constructivist Psychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Innovative Moments in Group Therapy: Analyzing voices of group change.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Constructivist+Psychology%22">Journal of Constructivist Psychology</searchLink>. Apr-Jun2021, Vol. 34 Issue 2, p195-206. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Group+psychotherapy%22">Group psychotherapy</searchLink><br /><searchLink fieldCode="DE" term="%22Social+groups%22">Social groups</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+illness%22">Mental illness</searchLink><br /><searchLink fieldCode="DE" term="%22Social+interaction%22">Social interaction</searchLink>
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  Data: The Innovative Moments Coding System has been used for studying therapeutic change. However, there has hardly been any research on its application in group therapy and on how new I-positions emerge in groups. Based on the literature review on group therapy, constructivist therapy, and the dialogical self theory this article proposes three new types of innovative moments to study the complex interaction present in group interventions. These innovative moments group types are illustrated by contrasting two cases, Ángel and Zacarías, in a group that is centered on recovering from self-stigma in patients with a severe mental disorder. The results show a different group innovative moment profile in these two cases. This adaptation of the innovative moments model can be used to track how different voices from different participants interact and are integrated in the group dynamics. Lastly, this article also highlights some clinical implications for group work and group change from a dialogical perspective. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Constructivist Psychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Apr-Jun2021
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