Evaluation of hospital staff’s perceived quality of librarian-mediated literature searching services
Bibliographic record
Abstract
Objective: The research evaluated the perceived quality of librarian-mediated literature searching services at one of Canada’s largest acute care teaching hospitals for the purpose of continuous quality improvement and investigation of relationships between variables that can impact user satisfaction.Methods: An online survey was constructed using evidence-based methodologies. A systematic sample of staff and physicians requesting literature searches at London Health Sciences Centre were invited to participate in the study over a one-year period. Data analyses included descriptive statistics of closed-ended questions and coding of open-ended questions.Results: A range of staff including clinicians, researchers, educators, leaders, and analysts submitted a total of 137 surveys, representing a response rate of 71%. Staff requested literature searches for the following “primary” purposes: research or publication (34%), teaching or training (20%), informing a policy or standard practice (16%), patient care (15%), and “other” purposes (15%). While the majority of staff (76%) submitted search requests using methods of written communication, including email and search request forms, staff using methods of verbal communication, including face-to-face and telephone conversations, were significantly more likely to be extremely satisfied with the librarian’s interpretation of the search request (p=0.004) and to rate the perceived quality of the search results as excellent (p=0.005). In most cases, librarians followed up with staff to clarify the details of their search requests (72%), and these staff were significantly more likely to be extremely satisfied with the librarian’s interpretation of the search request (p=0.002).Conclusions: Our results demonstrate the limitations of written communication in the context of librarian-mediated literature searching and suggest a multifaceted approach to quality improvement efforts. This article has been approved for the Medical Library Association’s Independent Reading Program.
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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 | 0.063 | 0.208 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".