Hatha Yoga and Executive Function: A Systematic Review
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Recent reviews have documented the beneficial effects of seated meditation on executive function (EF). However, there has yet to be a comprehensive review on the effects of Hatha yoga, a moving meditation, on EF. OBJECTIVE: To examine the empirical literature on the effects of Hatha yoga on EF. METHODS: MEDLINE, Scopus, and PsycINFO databases were searched for experimental studies (between- or within-subject designs) testing the effects of Hatha yoga (acute bouts, short-term interventions, longer-term interventions) on EF. RESULTS: A total of 11 published studies met eligibility criteria: Three studies involved healthy adults, 2 studies involved healthy older adults (n = 2), 1 study involved children and adolescents, and 5 studies involved medical (n = 4) or forensic (n = 1) populations. In healthy adults, 2 of 3 studies suggested that acute bouts of Hatha yoga improved EF; however, 1 study using a short-term intervention found no improvements in EF. Among healthy older adults, 1 study provided evidence that Hatha yoga improves EF. In child/adolescent samples, 1 study supported the contention that Hatha yoga improves EF after short-term interventions. Among medical populations, EF improved in patients with type 2 diabetes mellitus and in 1 of 3 studies involving patients with multiple sclerosis. The sole study involving impulsive prisoners showed positive effects on EF with a short-term intervention. CONCLUSION: Hatha yoga shows promise of benefit for EF in healthy adults, children, adolescents, healthy older adults, impulsive prisoners, and medical populations (with the exception of multiple sclerosis). However, more good-quality studies that evaluate the efficacy of Hatha yoga's effects on EF are essential to build on this evidence base.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it