Nurse practitioner student preceptor orientation via a Wiki
Bibliographic record
Abstract
Nurse practitioner education programs have always partnered with nurse practitioners (NPs) to serve as preceptors for students completing clinical requirements of their graduate level nurse practitioner programs. In this model faculty rely on nurse practitioners for the clinical education of nurse practitioner students. Therefore, the preceptor role is a crucial element of NP education particularly in distance learning programs. Orientation to the role is essential to ensure educational competencies are achieved. Nursing faculty struggle with implementation of orientation that is efficient and meets the needs of all preceptors for all clinical courses. Orientation requirements to the nurse practitioners’ role as preceptor can be a barrier to acquiring and retaining preceptors. The purpose of this study was to acquire information from NP preceptors regarding willingness to participate in a NP preceptor orientation program, the type of information they desired in a NP preceptor orientation, and the preferred delivery system for this information. Former preceptors from our school of nursing’s database were sent an online survey with 15 questions regarding orientation for NP preceptors. Descriptive statistics were used to summarize preceptor needs and preceptor barriers. Qualitative findings from written comments found many preceptors perceive school of nursing faculty organizational support is vital in terms of how positively they view their role as a preceptor and their willingness to participate in an orientation program. The results of the survey were used to re-design nurse practitioner preceptor orientation in our school of nursing. The WIKI online method was chosen due to its ease of information dissemination, which met the administrative needs of faculty; and its convenience and availability, which met the accessibility needs of preceptors.
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.
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".