Nuances and Uncertainties Regarding Hypnotic Inductions: Toward a Theoretically Informed Praxis.

Inductions are widely considered the starting point of hypnosis, yet their actual role is poorly understood and often oversimplified. Drawing on research into suggestibility, spontaneous experience, brain activity, and cognition, this article argues that the value of inductions is more nuanced and uncertain than commonly assumed. Some components of standard inductions clearly boost suggestibility, while others show no clear benefit. The effect of inductions on suggestibility varies depending on the type of suggestion and how it is measured, and the reasons for this variability remain unknown. Examining these effects through the lens of individual differences in high hypnotic suggestibility and componential models may open new research directions. The article advocates for practical, theory-driven optimization of inductions.

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Abstract

Although most definitions of hypnosis consider inductions as the initial stage in a hypnosis protocol, knowledge of inductions remains poor and uninformed by recent developments in theory and research. It is frequently argued that inductions play a critical role in hypnotic responding or, by contrast, are largely interchangeable and unimportant. Drawing on the literature on suggestibility, spontaneous phenomenology, neurophysiology, and cognition, this article argues that the value of inductions, as well as the potential value of inductions, is more nuanced and uncertain. Certain components of standard inductions appear to be efficacious in enhancing suggestibility, whereas others do not have any clear benefits. The impact of inductions on suggestibility seems to vary across suggestions and modes of assessment with the sources of this variability being unknown. Considering these effects, and the broader impact of inductions on spontaneous conscious states and cognition, through the lens of heterogeneity in high hypnotic suggestibility and componential models of hypnotic suggestibility may offer novel research avenues in this area. The article concludes by arguing for the practical and theory-driven optimization of inductions.