Bibliographic record
Abstract
Literature across health care disciplines has come to acknowledge spiritual care as integral to holistic health promotion. However, caregivers often continue to be reluctant to explore the spiritual dimension of health with their clients. In order to help caregivers feel more prepared to offer spiritual care, the author has drawn upon the interdisciplinary literature to develop the T.R.U.S.T. Model for Inclusive Spiritual Care. This article introduces the T.R.U.S.T. Model and its foundational concept of 'inclusive spiritual care': relevant, non-intrusive care which tends to the spiritual dimension of health by addressing universal spiritual needs, honoring unique spiritual worldviews, and helping individuals to explore and mobilize factors that can help them gain/re-gain a sense of trust in order to promote optimum healing. The article also describes the T.R.U.S.T. Model's origins, underlying assumptions, and its non-prescriptive outline for exploring five topics: 'Traditions', 'Reconciliation', 'Understandings', 'Searching', and 'Teachers'. Guidelines are included for using T.R.U.S.T. to enhance holistic health care, with an emphasis on its use in holistic nursing practice.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.216 | 0.170 |
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".