An Integrative Review of Patient Education During Inpatient Hematopoietic Stem Cell Transplantation
Bibliographic record
Abstract
PROBLEM IDENTIFICATION: Patients undergoing hematopoietic stem cell transplantation (HSCT) have significant learning needs that nurses must provide. The review question was "What teaching methods and strategies have been examined to deliver education to patients undergoing HSCT?" LITERATURE SEARCH: The review was conducted in November 2022 using the following databases: Scopus®, Embase®, MEDLINE®, CINAHL®, PsycINFO®, and ERIC. The search comprised two main concepts: HSCT and patient education. DATA EVALUATION: The search yielded 1,458 records after duplicates were removed, and 3 studies were included in this review. The studies were critically appraised using the Mixed Methods Appraisal Tool and deemed to be of moderate quality. SYNTHESIS: Problem-solving training was the teaching method used in all three studies. Satisfaction was noted among patients and those delivering the intervention. The effect of the training on information retention or application was not measured. IMPLICATIONS FOR PRACTICE: Additional research is needed to explore how to best educate patients undergoing HSCT while hospitalized. Structured teaching methods may have a sound theoretical basis and warrant additional investigation using more rigorous research methods.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".