Nurses' attitudes towards older people care: An integrative review
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To examine hospital nurses' attitudes towards caring for older adults and delineate associated factors contributing to their attitudes. BACKGROUND: Population ageing is of international significance. A nursing workforce able to care for the ageing population is critical for ensuring quality older adult care. A synthesis of research related to nurses' attitudes towards older adult care is important for informing care quality and the nursing workforce issues. METHODS: A systematic integrative review process guided the review. Cumulative Index of Nursing and Allied Health Literature and Medline databases were searched for primary research published between 2005-2017. A total of 1,690 papers were screened with 67 papers read in-depth and eight selected for this review that met the inclusion/exclusion criteria. RESULTS: Nurses' held coexisting positive and negative attitudes towards generic and specific aspects of older adult care. Negative attitudes, in particular, were directed at the characteristics of older adults, their care demands or reflected in nurses' approaches to care. Across jurisdictions, work environment, education, experience and demographics emerged as influences on nurses' attitudes. CONCLUSION: There is a paucity of research examining nurses' attitudes towards older adult care. The limited evidence indicates that attitudes towards older people care are complex and contradictory. Influences on nurses' attitudes need further study individually and collectively to build a strong evidence base. Interventional studies are needed as are the development of valid and reliable instruments for measuring nurses' attitudes towards older adult care. RELEVANCE TO CLINICAL PRACTICE: Bolstering postgraduate gerontological preparation is critical for promoting nurses' attitudes towards older adult care. Creating age-friendly work environments, including appropriate resource allocation, is important to support older people care and facilitate positive nursing attitudes.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".