Resilience of Nurses in the Context of Professional Integration: An Integrative Review
Bibliographic record
Abstract
Background: Professional integration is a challenging period, which suggests there is a need to strengthen resilience among new nurses. Yet there is little data to help define resilience and identify its determinants and implications. Purpose: To analyze the current literature on resilience in the nursing profession during the career integration period (≤ 2 years of professional experience), its determinants, and how it affects the health and work functioning of new nurses. Methods: An integrative review (Whittemore and Knalf, 2005) of empirical literature (2018–2024) was done based on the Cumulative Index to Nursing and Allied Health (CINAHL), MEDLINE with full text, APA PsycInfo, and Scopus databases. Qualitative and quantitative studies reporting analysis of primary data were selected. Data was obtained and summarized through a system of ongoing comparative analysis. Results: Of a total of 925 listed periodical articles, 17 were selected. The analysis of the literature helped provide a first conceptualization of resilience in nursing during professional integration based on various characteristics. For determinants, the review identified early-career drivers and challenges that fall into two main categories: those concerning health care facility organizational factors, and those of a personal nature. Lastly, it extracted the most commonly cited ways that early-career resilience can affect psychological health and work functioning among new nurses. Discussion and Conclusion: Resilience among new nurses is linked to a number of professional environmental and personal factors that in turn reflect various signs of psychological health and work functioning. A focus on early-career resilience could help new nurses stay healthy and fully functional and ultimately aid in their professional integration and long-term career prospects.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".