Exploring pairing of new graduate nurses with mentors: An interpretive descriptive study
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
AIMS AND OBJECTIVES: To explore mentorship pairing practices for new graduate nurses in a tertiary care hospital. BACKGROUND: Many organisations have implemented mentorship transition programmes to decrease new nursing graduate turnover in the first two years of practice. Little is known about mentorship pairing processes. DESIGN: An interpretive descriptive qualitative study was conducted in a multicampus academic health science centre in Ontario, Canada. The COREQ reporting guideline was used. METHODS: Thirty-one semistructured interviews were conducted from July 2018-July 2019 in a multicampus academic health science centre with new nursing graduates, experienced nurses and nurse leaders who participated in the New Graduate Guarantee programme or were involved in the mentor-mentee pairing process in 2016 or 2017. Data collected were analysed using thematic analysis within the groups and triangulated across groups. RESULTS: Neither the new graduates nor the mentors were aware of the pairing processes. Nursing leaders relied on their knowledge of the participants to pair new graduates and mentors with many stating participants' personalities were considered. New graduates and mentors described making an initial connection and socialisation as important themes related to facilitating the pairing process. Organisational influences on pairing included taking breaks together, the location of the final student placement, and the management of workload and scheduling. CONCLUSIONS: Increased awareness and transparency regarding nursing mentorship pairing processes is required. Pairing processes suggested by participants warrant further investigation to determine efficacy. RELEVANCE: Findings reinforce the need to discuss and research nursing specific mentorship pairing processes.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it