What’s in a Definition? <i>Holistic Nursing, Integrative Health Care</i> , and <i>Integrative Nursing</i> : Report of an Integrated Literature Review
Bibliographic record
Abstract
Background: Nurses and others have used various terms to describe our caring/healing approach to practice. Because terms used can influence our image of ourselves and the image others have of us, we sought to clarify their meanings. Questions: How are the terms holistic nursing, integrative health care, and integrative nursing defined or described? Do we identify with these definitions/descriptions? Are the various terms the same or are they distinct? Method: We conducted an integrated review of peer-reviewed literature following the process described by Whittemore and Knafl. Using standard search methods, we reviewed full texts of 94 published papers and extracted data from 58 articles. Findings: Holistic describes “whole person care” often acknowledging body–mind–spirit. Holistic nursing defines a disciplinary practice specialty. The term integrative refers to practice that includes two or more disciplines or distinct approaches to care. Both terms, integrative and holistic, are associated with alternative/complementary modalities and have similar philosophical and/or theoretical underpinnings. Conclusions: There is considerable overlap between holistic nursing and integrative nursing. The relationship of integrative nursing to integrative health care is unclear based solely on definitions. Consideration of terms used provides opportunities for reflection, collaboration, and growth.
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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 | 0.035 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.025 | 0.027 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.022 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".