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A Dynamic Autocatalytic Network Model of Therapeutic Change Ganesh, Kirthana; Gabora, Liane
Abstract
Psychotherapy involves the modification of a client’s worldview to reduce distress and enhance well-being. We take a human dynamical systems approach to modeling this process, using Reflexively Autocatalytic foodset-derived (RAF) networks. RAFs have been used to model the self-organization of adaptive networks associated with the origin and early evolution of both biological life, as well as the evolution and development of the kind of cognitive structure necessary for cultural evolution. The RAF approach is applicable in these seemingly disparate cases because it provides a theoretical framework for formally describing under what conditions systems composed of elements that interact and ‘catalyze’ the formation of new elements collectively become integrated wholes. In our application, the elements are mental representations, and the whole is a conceptual network. The initial components—referred to as foodset items—are mental representations that are innate, or were acquired through social learning or individual learning (of pre-existing information). The new elements—referred to as foodset-derived items—are mental representations that result from creative thought (resulting in new information). In clinical psychology, a client’s distress may be due to, or exacerbated by, one or more beliefs that diminish self-esteem. Such beliefs may be formed and sustained through distorted thinking, and the tendency to interpret ambiguous events as confirmation of these beliefs. We view psychotherapy as a creative collaborative process between therapist and client, in which the output is not an artwork or invention but a more well-adapted worldview and approach to life on the part of the client. In this paper, we model a hypothetical albeit representative example of the formation and dissolution of such beliefs over the course of a therapist–client interaction using RAF networks. We show how the therapist is able to elicit this worldview from the client and create a conceptualization of the client’s concerns. We then formally demonstrate four distinct ways in which the therapist is able to facilitate change in the client’s worldview: (1) challenging the client’s negative interpretations of events, (2) providing direct evidence that runs contrary to and counteracts the client’s distressing beliefs, (3) using self-disclosure to provide examples of strategies one can use to diffuse a negative conclusion, and (4) reinforcing the client’s attempts to assimilate such strategies into their own ways of thinking. We then discuss the implications of such an approach to expanding our knowledge of the development of mental health concerns and the trajectory of the therapeutic change.
Item Metadata
Title |
A Dynamic Autocatalytic Network Model of Therapeutic Change
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Creator | |
Contributor | |
Publisher |
Multidisciplinary Digital Publishing Institute
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Date Issued |
2022-04-13
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Description |
Psychotherapy involves the modification of a client’s worldview to reduce distress and enhance well-being. We take a human dynamical systems approach to modeling this process, using Reflexively Autocatalytic foodset-derived (RAF) networks. RAFs have been used to model the self-organization of adaptive networks associated with the origin and early evolution of both biological life, as well as the evolution and development of the kind of cognitive structure necessary for cultural evolution. The RAF approach is applicable in these seemingly disparate cases because it provides a theoretical framework for formally describing under what conditions systems composed of elements that interact and ‘catalyze’ the formation of new elements collectively become integrated wholes. In our application, the elements are mental representations, and the whole is a conceptual network. The initial components—referred to as foodset items—are mental representations that are innate, or were acquired through social learning or individual learning (of pre-existing information). The new elements—referred to as foodset-derived items—are mental representations that result from creative thought (resulting in new information). In clinical psychology, a client’s distress may be due to, or exacerbated by, one or more beliefs that diminish self-esteem. Such beliefs may be formed and sustained through distorted thinking, and the tendency to interpret ambiguous events as confirmation of these beliefs. We view psychotherapy as a creative collaborative process between therapist and client, in which the output is not an artwork or invention but a more well-adapted worldview and approach to life on the part of the client. In this paper, we model a hypothetical albeit representative example of the formation and dissolution of such beliefs over the course of a therapist–client interaction using RAF networks. We show how the therapist is able to elicit this worldview from the client and create a conceptualization of the client’s concerns. We then formally demonstrate four distinct ways in which the therapist is able to facilitate change in the client’s worldview: (1) challenging the client’s negative interpretations of events, (2) providing direct evidence that runs contrary to and counteracts the client’s distressing beliefs, (3) using self-disclosure to provide examples of strategies one can use to diffuse a negative conclusion, and (4) reinforcing the client’s attempts to assimilate such strategies into their own ways of thinking. We then discuss the implications of such an approach to expanding our knowledge of the development of mental health concerns and the trajectory of the therapeutic change.
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Subject | |
Genre | |
Type | |
Language |
eng
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Date Available |
2022-04-29
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Provider |
Vancouver : University of British Columbia Library
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Rights |
CC BY 4.0
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DOI |
10.14288/1.0413165
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URI | |
Affiliation | |
Citation |
Entropy 24 (4): 547 (2022)
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Publisher DOI |
10.3390/e24040547
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty; Researcher
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
CC BY 4.0