Nonpharmacological nursing interventions for the management of patient fatigue: a literature review
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To identify and describe nonpharmacological interventions for the management of fatigue that are within the scope of nursing practice. BACKGROUND: Fatigue is a complex multidimensional symptom experienced by patients with varying diagnoses. Limited details are available on the nature of nursing interventions to manage fatigue, which preclude fidelity of implementation in day-to-day practice. DESIGN: Literature review. METHODS: Multiple databases were searched for publications reporting on the evaluation of nurse-delivered interventions for the management of fatigue. Data were extracted on study and intervention characteristics and results pertaining to the effects of the intervention on fatigue. RESULTS: The studies (n = 16) evaluated eight interventions: psycho-education, cognitive behavioural therapy, exercise, acupressure, relaxation, distraction, energy conservation and activity management, and a combination of exercise, education and support. CONCLUSION: Psycho-education was evaluated in several studies and demonstrated effectiveness when delivered in both acute and community settings. RELEVANCE TO CLINICAL PRACTICE: This review focused on interventions that are within the scope of nursing practice for the management of fatigue. The findings provide nurses with an overview of the effectiveness of interventions they may use in their day-to-day practice to help patients manage fatigue. A detailed description of interventions found effective is provided to assist nurses in translating evidence into practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".