Experiences of Advanced Standing Program Nursing Students and Instructors Practicing Transcendental Meditation
Bibliographic record
Abstract
Little is known about the experiences of Advanced Standing Program (ASP) nursing students and instructors who practice Transcendental Meditation® (TM®). The purpose of this qualitative study was to uncover themes from the written descriptions of ASP nursing students and instructors who were taught to practice TM in order to gain a deeper understanding of how this practice might have meaning for and influence their lives and well-being. At the same time, discovering ways that TM could be incorporated into nursing education and practice as an effective stress reduction intervention and opportunity to enhance nursing care. Thematic analysis was employed. Twenty students and three instructors volunteered and were provided with education sessions by certified TM teachers involving the correct way to practice TM twice per day. Written descriptions were collected via written monthly reflective journals over 11 months. Descriptions were analyzed from the journal entries, uncovering major themes describing the experiences of participants when practicing TM and the resulting positive impact on their lives for managing stress, enhancing productivity, and improving relationships. In conclusion, recommendations involve the use of TM to be introduced and implemented as a useful stress reduction intervention tool in nursing programs for students and their instructors.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".