Integrating a Career Planning and Development Program into the Baccalaureate Nursing Curriculum: Part I. Impact on Students’ Career Resilience
Bibliographic record
Abstract
Student nurses often embark on their professional careers with a lack of the knowledge and confidence necessary to navigate them successfully. An ongoing process of career planning and development (CPD) is integral to developing career resilience, one key attribute that may enable nurses to respond to and influence their ever-changing work environments with the potential outcome of increased job satisfaction and commitment to the profession. A longitudinal mixed methods study of a curriculum-based CPD program was conducted to determine the program's effects on participating students, new graduate nurses, and faculty. This first in a series of three papers about the overall study's components reports on undergraduate student outcomes. Findings demonstrate that the intervention group reported higher perceived career resilience than the control group, who received the standard nursing curriculum without CPD. The program offered students the tools and resources to become confident, self-directed, and active in shaping their engagement in their academic program to help achieve their career goals, whereas control group students continued to look uncertainly to others for answers and direction. The intervention group recognized the value of this particular CPD program and both groups, albeit differently, highlighted the key role that faculty played in students' career planning.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".