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Record W4412050663 · doi:10.56198/k1ea4v29

Immersive Mindfulness: Adolescents’ Meditation Experiences in Maloka VR

2025· article· en· W4412050663 on OpenAlexaff
Cynthie Gaetz, Paula MacDowell, Shahram Fardadvand

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Methods and Impacts
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMeditationMindfulnessMindfulness meditationVirtual realityComputer sciencePsychologyMultimediaHuman–computer interactionCognitive psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Virtual Reality (VR) meditation offers promising solutions to address declining attention spans and enhance cognitive functioning in adolescents. This study evaluates the effectiveness of immersive VR interventions in improving adolescents’ ability to focus their attention. Using the Maloka VR application, participants demonstrated increased focus, engagement, and relaxation after brief meditation sessions. The immersive meditation experience facilitated mindfulness and body awareness, which are essential components for enhancing focus, particularly for individuals with attention-deficit hyperactivity disorder (ADHD). Importantly, findings from this study will inform the development of scalable, school-based VR meditation programs designed to support student well-being, attention training, and self-regulation. By integrating VR meditation into existing wellness initiatives—such as Zen rooms and mental health programming—schools can offer innovative tools to help students manage stress, improve focus, and prepare for cognitively demanding tasks. Future research should explore long-term effects, optimal implementation strategies, and inclusive design principles to ensure equitable access to VR meditation interventions across diverse educational settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.409
Teacher spread0.377 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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