246 Timothy J. Beck and Jacob W. Glazier
Networking Care around Mental Health
The social, economic, and cultural developments outlined above have
heralded the development of various new transdisciplinary frameworks to
account for increasing concerns with the DSM and its underlying
biomedical model of mental health. Examples of these emerging
frameworks include the Research Domain Criteria (RDoC) project created
by the National Institute of Mental Health (Research, 2019) and various
computational network approaches (e.g., McNally, 2016). With the latter,
disorders are conceived as the effects of identified symptoms rather than
the other way around. With these new network models of
psychopathology, diagnoses are understood as the sum total of all observed
relations between symptoms. In this way, individual behaviors and thought
patterns can be tracked through computer generated models (McNally,
2016). Individual behaviors are represented as nodes within these complex
systems, with diagnoses understood as the patterns formed by each
constellation of nodes.
In terms of the organization of both treatments and conceptual
frameworks, mental health services have thus become considerably more
decentralized in ways that nonetheless rely on standardized diagnostic
procedures. This poses obvious problems for movements toward
decolonization, as the same vocabulary of pathology used by the DSM or
ICD is distributed through data compiled across geographical boundaries
without regard for local narratives and structures of meaning-making.
However, insofar as services today must be rendered across widely
different types of social settings, a standardized vocabulary with flexible
rules for inclusion seems necessary given the practical realities created
through deinstitutionalization.
Providing a more optimistic take on the concerns raised by McGuire
above, and the future of deinstitutionalization more generally, Richard
McNally (2016) suggests, “[a]dvances in quantitative methods,
computational power, and mobile technology will pay if clinical
researchers can use idiographic network methods to guide therapeutic
intervention in the coming years” (p. 102). The goal with such network