JMIR Publications

ABSTRACT

Background:

The resurgence of research and public interest in the positive psychological effects of psychedelics, together with advancements in digital data collection techniques, have brought forth a new type of research design, gathering large-scale naturalistic data from psychedelic users prospectively, i.e. before and after use of a psychedelic compound. A methodological limitation of such studies is their high attrition rate, caused by participants who stop responding after initial study enrolment. Importantly, study dropout can introduce systematic biases that may affect the interpretability of results.

Objective:

Based on a previously collected sample (N=654), we here investigated potential determinants of study attrition in prospective psychedelic online research.

Methods:

Logistic regression models were used to examine demographic, psychological trait and state, and psychedelic-specific predictors of dropout. Predictors were assessed 2 weeks before, one day after, and 2 weeks after the psychedelic experience, with attrition being defined as non-completion of the key endpoint 4 weeks post experience.

Results:

Predictors of attrition were found among demographic variables, including age and educational level, as well as personality traits, specifically low conscientiousness and high extraversion. Contrary to prior hypotheses, neither baseline attitudes towards psychedelics nor the intensity of acute challenging experiences were predictive of dropout.

Conclusions:

. Baseline predictors of attrition identified here are consistent with those found in longitudinal studies from other scientific disciplines, suggesting their transdisciplinary relevance. Moreover, the lack of an association between attrition and psychedelic advocacy or negative drug experiences in the present sample contextualises concerns about problematic biases in these and related data.