IES Database.

Ibogaine, an indole alkaloid derived from the root bark of Tabernanthe iboga, has long been used in traditional Bwiti healing rituals and shows promise for treating opioid dependence and neurological conditions, but existing psychometric tools fail to capture its distinctive subjective/oneiric (dream-like) effects. To address this gap, we developed the 70-item Ibogaine Experience Scale (IES) through an iterative process informed by a prior qualitative study (n = 20) that identified eight experiential domains. A preliminary 144-item version was completed on site with a mobile device within 48 hours of treatment by 499 participants across two clinical settings—cohort neuropsychiatric treatments (n = 381) and substance use disorder treatments (n = 118). We employed exploratory graph analysis, parallel analysis on polychoric correlations, and iterative item‐reduction (Gulliksen’s Pool, MIREAL, MSA) to refine the scale. Semi-confirmatory factor analysis used Robust Unweighted Least Squares (RULS) with LOSEFER correction, oblimin rotation, and multiple fit indices (CFI, NNFI, GFI, AGFI, RMSR, WRMR). Cronbach’s α, McDonald’s ω, H indices, EAP reliability, FDI, ORION, SR, and EPTD assessed internal consistency and factorial quality. The final structure comprises seven factors—Narrative and symbolic visions; Visual changes; Discomfort and challenge; Cosmic/Archetypal Visions; Introspection and personal transformation; Somatosensory hypersensitivity and physiological activation; Dissociation—explaining 53.9% of variance, with excellent fit (CFI = .991; GFI = .983; RMSR = .041; WRMR = .038) and high internal consistency (α = .948; ω = .946; subscale ω = .65–.91). Two subscales exhibited small gender effects. The IES provides a reliable, phenomenologically rich instrument for quantifying ibogaine’s distinctive subjective effects. It supports research and clinical assessment by capturing the multidimensional, oneiric/dream-like nature of the ibogaine experience. Future work should confirm this structure in independent, culturally diverse cohorts and explore predictive links between IES domains and therapeutic outcomes.