Who engages? Machine learning insights into digital mindfulness-based intervention for generalized anxiety disorder.

Study at a glance

Characteristics	Observational cohort Peer reviewed
Population	Adults with generalized anxiety disorder using a digital mindfulness-based intervention
Topics	Anxiety Meditation
Key findings	Machine learning identified baseline characteristics that predict engagement with the digital mindfulness-based intervention, indicating that engagement is not uniform and may be influenced by individual factors. The authors propose that these insights can inform personalized approaches to enhance adherence.

Other observational and cohort studies on anxiety, most cited first.

Study	Year	Design	Participants
Effectiveness of a meditation-based stress reduction program in the treatment of anxiety disorders Patients with generalized anxiety disorder or panic disorder with or without agoraphobia	1992	Observational cohort	n = 22
Antidepressant effects of a single dose of ayahuasca in patients with recurrent depression: a preliminary report Patients with a depressive disorder	2015	Observational study
Patterning of Cognitive and Somatic Processes in the Self-Regulation of Anxiety: Effects of Meditation versus Exercise Regular practitioners of physical exercise or meditation	1978	Retrospective study	n = 77
Dynamic coupling of whole-brain neuronal and neurotransmitter systems Healthy humans	2020	Observational study
Psychedelics not linked to mental health problems or suicidal behavior: A population study Randomly selected United States adults	2015	Observational cohort	n = 135,095