Examining the Efficacy of an Online Program to Cultivate Mindfulness and Self-Compassion Skills (Mind-OP): Randomized Controlled Trial on Amazon’s Mechanical Turk

Objectives: The demand for effective psychological treatments for depression, anxiety, and heightened stress is far outstripping their supply. Accordingly, internet delivered, self-help interventions offer hope to many people, as they can be easily accessed and at a fraction of the price of face-to-face options. Mindfulness and self-compassion are particularly exciting approaches, as evidence suggests interventions that cultivate these skills are effective in reducing depression, anxiety, and heightened stress. We examined the efficacy of a newly developed program that combines mindfulness and self-compassion exercises into a brief self-guided intervention (Mind-OP). The secondary aim of this study was to investigate the feasibility of conducting a randomized-controlled trial entirely on a popular crowdsourcing platform, Amazon’s Mechanical Turk (MTurk). Methods: We randomized 456 participants reporting heightened depression, anxiety, or stress to one of two conditions: the 4-week Mind-OP intervention (n= 227) or to an active control condition (n =229) where participants watched nature videos superimposed onto relaxing meditation music for four consecutive weeks. We administered measures of anxiety, depression, perceived stress, dispositional and state mindfulness, self-compassion, and nonattachment. Results: Intent-to-treat and per-protocol analyses revealed that, compared to participants in the control condition, participants in the Mind-OP intervention condition reported significantly less anxiety and stress at the end of the trial, as well as significantly greater mindfulness, self-compassion, and nonattachment. Conclusions: Mind-OP appears efficacious in reducing anxiety symptoms and perceived stress among MTurk participants. We highlight issues (e.g., attrition) related to feasibility of conducting randomized trials on crowdsourcing platforms such as MTurk.