Nurses’ integrity and coping strategies: An integrative review
Bibliographic record
Abstract
INTRODUCTION: Integrity is one of the core values in nursing that needs to be maintained by nurses in practice. However, the complexity in the nursing milieu can pose threats to integrity. An understanding of the common threats and coping strategies might assist nurses in preserving integrity in everyday practice. AIMS AND OBJECTIVES: To review and synthesis the concept of integrity in nursing and identify common threats and coping strategies. METHODS: Whittemore and Knafl's integrative review method was implemented. A search was performed in Scopus, Medline, Embase, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, and Proquest Health and Medical electronic databases published in English between 2000-2017. Two reviewers independently assessed eligibility for inclusion. Methodological appropriateness for the included studies was assessed using the critical appraisal skills programme. The constant comparative method of grounded theory was used to analyse and synthesise data from seven peer-reviewed articles. RESULTS: Two major conceptions of integrity were identified. These included the sense of wholeness with regard to personal-professional concerns and ethical-moral conducts. Five entities, self, patients, teamwork and work culture, the nature of work, and organisation, were identified as interweaving elements that may induce threats to integrity. When integrity is threatened, nurses use two key strategies to survive: adjusting and compensating. An emergent framework to facilitate understanding of nurses' threats to integrity is discussed. CONCLUSIONS: A threat to nurses' integrity takes form when there is an unmitigated gap between a nurse's expectation and reality. While the expectation comes from within the nurse, the reality materialises out of the complex interplays that occur in the healthcare workforce. Maintaining integrity demands a continual strive to balance personal expectations, professional concerns and nursing realities.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".