Understanding Motivational Interviewing: an Evolutionary Perspective

Autor: Abilio C. de Almeida Neto
Rok vydání: 2017
Předmět:
Zdroj: Evolutionary Psychological Science. 3:379-389
ISSN: 2198-9885
Popis: Motivational interviewing (MI) is a well-known scientifically tested method of affecting behavior change in humans. In MI, interventionists are instructed not to directly provide clients with advice to change as it is often ineffective. Instead, they are trained to direct the client’s cognition towards modifying the target behavior. The delivery of MI-based interventions in diverse areas of behavior modification is based on the efficacy data that demonstrate that they influence behavior but without an integrative theoretical basis necessary for comprehensive understanding. This article uses an evolutionary framework to identify potential mediators of the effects of MI on behavior. Specifically, it argues that the techniques used in MI are adaptively significant, signaling to the client that he/she is social hierarchically and physically safe. By not directly providing advice to change and by enhancing the client’s perception of social support, the interventionist is not perceived as attempting to impose social-hierarchical discipline. This, in turn, bypasses the unconsciously primed, evolutionary salient human trait of psychological reactance, which is argued, in this paper, to have evolved, in part, to facilitate the maintenance of social dominance hierarchies. This non-socially threatening environment created by MI allows the human cortex to process information and engage in cognitive reasoning and decision making without strong influence from unconscious instinctual subcortical processes that ruled behavior prior to cortical evolution. Understanding the adaptive significance of counseling strategies that facilitate successful outcomes allows for greater insight into the underlying mechanisms by which these strategies impact on behavior, which may assist in the design and refinement of behavior modification programs.ᅟ
Databáze: OpenAIRE