VALIDATION OF EXPERIMENTAL METHODOLOGY FOR STATE MINDFULNESS INDUCTION IN A CONTROLLED LABORATORY SETTING
Bibliographic record
Abstract
The exponential growth of mindfulness' popularity in both experimental and applied fields of psychology has revealed serious gaps in the relevant research methodology and theoretical groundwork which, in turn, has undermined the inferences about the beneficial nature of mindfulness.One of the methodological gaps is a lack of formally validated mindfulness induction procedures.The present research aimed to address this issue by experimentally validating a 5-minute body-centered guided meditation as an effective method of mindfulness induction in a laboratory setting.The induction method was designed by an independent professional yoga and meditation teacher; it was designed to be brief, simple, body-centered, and not affiliated with any specific tradition of mindfulness practice.A four-group randomized-control pretestposttest study design was used in this study.Ninety-nine participants were recruited from the Cleveland State University student body.The Toronto Mindfulness Scale was used for the pretest and posttest assessments of state mindfulness.State mindfulness was measured twice in each group: (1) before and (2) either immediately after or 30 minutes after the induction procedure.The induction method was effective in increasing state mindfulness immediately after the mindfulness induction.The induction effect dissipated, but did not fully disappear, by the 30-minute mark.The control condition (sitting down and attending to one's thoughts and physical sensations) served as a low but stable mindfulness induction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.053 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".