Predictors of new graduate nurses’ health over the first 4 years of practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: To examine predictors of Canadian new graduate nurses' health outcomes over 1 year. DESIGN: A time-lagged mail survey was conducted. METHOD: = 406) responded to a mail survey at two time points: November 2012-March 2013 (Time 1) and May-July 2014 (Time 2). Multiple linear regression (mental and overall health) and logistic regression (post-traumatic stress disorder risk) analyses were conducted to assess the impact of Time 1 predictors on Time 2 health outcomes. RESULTS: Both situational and personal factors were significantly related to mental and overall health and post-traumatic stress disorder risk. Regression analysis identified that cynicism was a significant predictor of all three health outcomes, while occupational coping self-efficacy explained unique variance in mental health and work-life interference explained unique variance in post-traumatic stress disorder risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it