Effectiveness of journal clubs in translating knowledge into practice: A literature review
Bibliographic record
Abstract
Background and objective: Hamad Medical Corporation nurse leaders established nursing journal clubs in 2014 as an important strategy to involve nurses in translating research into practice and as an effort to provide patients with the highest possible standards of care. Since the implementation of journal clubs in Hamad Medical Corporation (HMC), evaluative research within HMC has not been conducted to examine the effectiveness of this strategy. The aim of this review was to increase decision makers’ knowledge about the effectiveness of journal clubs in translating knowledge into clinical practice and to provide a framework to guide the development of a survey tool that would aide in the evaluation of nursing journal clubs’ effectiveness at Hamad Medical Corporation. A literature search was conducted as an initial step top guide the development of this tool.Methods: A literature search was conducted yielded 13 studies that evaluated the effectiveness of journal clubs after removing all duplicates and applying the inclusion criteria. The Mixed Methods Appraisal Tool-version 2011 was used to evaluate the quality of the included articles. Data was analyzed and extracted from each study and assembled into a summary table.Results: Four themes related to journal clubs’ effectiveness that are important in translating knowledge into practice: encouraging discussion among healthcare professionals, enhancing critical appraisal skills, promoting evidence-based practice knowledge, and impacting clinical practice.Conclusions: This literature review provides information about the four main interrelated themes that contribute to journal clubs’ effectiveness in translating knowledge into practice. This information would be useful to nurse educators at Hamad Medical Corporation and further utilized as a backdrop to the development of a tool to evaluate Hamad Medical Corporation nurses’ perceptions of journal clubs’ effectiveness.
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 | 0.049 | 0.219 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".