Development and Testing of a Literature Search Protocol for Evidence Based Nursing: An Applied Student Learning Experience
Bibliographic record
Abstract
Objective – The study aimed to develop a search protocol and evaluate reviewers' satisfaction with an evidence-based practice (EBP) review by embedding a library science student in the process. Methods – The student was embedded in one of four review teams overseen by a professional organization for oncology nurses (ONS). A literature search protocol was developed by the student following discussion and feedback from the review team. Organization staff provided process feedback. Reviewers from both case and control groups completed a questionnaire to assess satisfaction with the literature search phases of the review process. Results – A protocol was developed and refined for use by future review teams. The collaboration and the resulting search protocol were beneficial for both the student and the review team members. The questionnaire results did not yield statistically significant differences regarding satisfaction with the search process between case and control groups. Conclusions – Evidence-based reviewers' satisfaction with the literature searching process depends on multiple factors and it was not clear that embedding an LIS specialist in the review team improved satisfaction with the process. Future research with more respondents may elucidate specific factors that may impact reviewers' assessment.
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 | 0.556 | 0.687 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".