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Record W1582314035 · doi:10.18438/b8p34h

Development and Testing of a Literature Search Protocol for Evidence Based Nursing: An Applied Student Learning Experience

2011· article· en· W1582314035 on OpenAlexvenueno aff
Andy Hickner, Christopher R. Friese, Margaret Irwin

Bibliographic record

VenueEvidence Based Library and Information Practice · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Process (computing)Medical educationPsychologyControl (management)Best practiceBest evidenceComputer scienceMedicineAlternative medicine

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.081
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.266
GPT teacher head0.516
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2011
Admission routes1
Has abstractyes

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