Bibliographic record
Abstract
AIM: To report an analysis of the concept of mindfulness. BACKGROUND: Mindfulness is an emerging concept in health care that has significant implications for a variety of clinical populations. Nursing uses this concept in limited ways, and subsequently requires conceptual clarity to further identify its significance, use and applications in nursing. DESIGN: Mindfulness was explored using Rodgers evolutionary method of concept analysis. DATA SOURCES: For this analysis, a sample of 59 English theoretical and research-based articles from the Cumulative Index to Nursing and Allied Health Literature database were obtained. The search was conducted between all-inclusive years of the database, 1981-2012. REVIEW METHODS: Data were analysed with particular focus on the attributes, antecedents, consequences, references and related terms that arose in relation to mindfulness in the nursing literature. RESULTS: The analysis found five intricately connected attributes: mindfulness is a transformative process where one develops an increasing ability to 'experience being present', with 'acceptance', 'attention' and 'awareness'. Antecedents, attributes and consequences appeared to inform and strengthen one another over time. Mindfulness is a significant concept for the discipline of nursing with practical applications for nurse well-being, the development and sustainability of therapeutic nursing qualities and holistic health promotion. CONCLUSION: It is imperative that nurse well-being and self-care become a more prominent focus in nursing research and education. Further development of the concept of mindfulness could support this focus, particularly through rigorous qualitative methodologies.
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 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".