#9688. The Application of Machine Learning to Online Mindfulness Intervention Data: a Primer and Empirical Example in Compliance Assessment

August 2026publication date
Proposal available till 15-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Developmental and Educational Psychology;
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Abstract:
Objectives: Machine learning models are a promising, yet underutilized tool within the mindfulness field. Accordingly, this work aimed to provide a practical introduction to key machine learning concepts through an illustrative investigation of the association between at-home mindfulness exercise compliance and stress reduction. To further interrogate the currently inconclusive nature of the compliance-outcome association within the mindfulness literature, the illustrative example leveraged a suite of machine learning techniques to highlight the unique affordances and perspectives of the predictive framework. Methods: Foundational information regarding facets of the machine learning analytical process, including model types, data preprocessing, feature engineering, validation, performance evaluation, and model introspection, was presented. With emphasis on providing details and justifications regarding modeling decisions along the way, the work systematically applied these introduced concepts to a real-world data example.
Keywords:
Applied machine learning; Mindfulness; Online intervention; Stress; Tutorial

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