Career decisions and aspirations of early‐career nurses: Insights from a qualitative interpretative description study
Bibliographic record
Abstract
AIM: To explore the career decisions and aspirations of early-career registered nurses in New Brunswick, Canada. DESIGN: A qualitative study using an interpretive description approach was conducted. METHODS: Semi-structured one-on-one interviews were conducted with a purposive sample of nurses (n = 22) currently working in New Brunswick, Canada, with up to 5 years of experience from February to April 2022. RESULTS: Participants described diverse career paths and aspirations. Personal factors affecting these included the desire for meaningful work, career satisfaction, work-life balance, spending time with family, working in a preferred location, and finances. Professionally, working conditions were the dominant factor influencing early-career nurses' career decisions and aspirations. Participants described how short staffing, safety, support, and scheduling influenced their day-to-day work, mental and physical health, job and career satisfaction, and intent to leave. CONCLUSION: The findings highlighted the abundant and diverse career opportunities available to nurses early in their careers. Early-career nurses are interested in finding nursing positions with a high degree of person-job fit and value opportunities for ongoing professional education and growth. IMPACT: This study in New Brunswick, Canada, explores early-career nurses' career decisions and aspirations during nursing shortages and the pandemic, emphasizing the importance of person-job fit. Recommendations include improving working conditions and career pathways to enhance the sustainability of the nursing profession. REPORTING METHOD: Standards for Reporting Qualitative Research (SRQR). PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".