The Perception and Practice of Evidence Based Library and Information Practice Among Iranian Medical Librarians
Bibliographic record
Abstract
Objective – Evidence based library and information services help to link best evidence with decision making in library practice. Current library and information science practice operates in both a knowledge and evidence-based environment. Health service librarians provide information services in an evidence based health care context to improve patient care. But the evidence based practice movement has influenced many fields of human knowledge, including librarianship. Therefore, this study seeks to answer the following questions: 1) What are the perceptions of Iranian medical librarians regarding the use of an evidence based approach in their decision making processes? 2) Do Iranian medical librarians apply an evidence based approach in their professional work? 3) How do Iranian medical librarians practice an evidence based approach? 4) What are the barriers and limitations for Iranian medical librarians who engage in evidence based library and information practice (EBLIP)?
 
 Methods – This study utilized a survey to discover medical librarians’ attitudes and perceptions towards the use of an evidence based approach to library practice in Iran. Data was collected using a structured questionnaire to identify medical librarians’ attitudes toward EBLIP.
 
 Results – The findings of the study indicate that Iranian medical librarians are aware of EBLIP and that they utilize an evidence based approach towards their LIS work. They practice the five steps of an evidence based answering cycle in formulating, locating, assessing, applying, and redefining questions. However, they have less knowledge about levels of evidence, research methodologies, and critical appraisal. 
 
 Conclusions – Medical librarians in Iran are familiar with the concept of an evidence based approach. More training is needed in some elements of evidence based practice to improve their approach to evidence based library and information practice.
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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 | 0.008 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.660 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".