Challenges and Opportunities in Rural Nursing Preceptorship: What Multimedia Participant Action Reveals
Bibliographic record
Abstract
Background: Rural health care sites struggle to attract new nurses, owing to a widespread perception that the hardships of rural practice far outweigh the benefits. Preceptorships are a key means of recruiting nursing staff to rural locations, but innovative, firsthand messaging is needed to promote rural preceptorships and nursing careers. Objectives: The researchers sought to elicit compelling, multimedia, firsthand accounts of the challenges and opportunities of rural preceptorship through participant action. Additional goals were to explore the ways in which participants reify their experiences through digital media, and the potential for digitally-based participant action research to empower participants. Methods: The study was designed to engage participants in all phases of research: data collection, analysis, and dissemination of findings. It comprised three phases, each employing participant action methodology: photovoice data collection, collaborative thematic analysis, and authorship of digital stories. Participants: Through purposive and snowball sampling, the researchers recruited seven nursing students and five rural, registered nurses assigned to precept them. Inclusion criteria for the students were enrolment in the senior (final) preceptorship course prior to graduation, and the choice of a rural, semirural or suburban site. No exclusion criteria were warranted owing to the limited cohort of participants. Settings: Data were collected at six acute care sites and one community care site. The sites were rural, semi-rural, and suburban, serving populations ranging from 800 to 18,000, between 42 km and 416 km distant from the students’ primary place of study. Results: It was found that rural preceptorships teach students to accept and manage limitations, while appreciating and capitalizing on opportunities; this finding was equally true for nominally suburban and semi-rural sites included in the study. Emerging from the interviews, challenges, being more concrete, were reflected in photographic data, while opportunities were more abstract and relational. Citing time constraints, most participants declined to author their own digital stories. Conclusions: Digitally based participant action enables nurse preceptors and their students to make a compelling case for rural preceptorships and rural careers. However, digital media may also distort these participants’ experiences, and their involvement in all phases of research may be more burdensome than empowering.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| 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".