Academic Medical Library Services Contribute to Scholarship in Medical Faculty and Residents
Bibliographic record
Abstract
A Review of: Quesenberry, A. C., Oelschlegel, S., Earl, M., Leonard, K., & Vaughn, C. J. (2016). The impact of library resources and services on the scholarly activity of medical faculty and residents. Medical Reference Services Quarterly, 35(3), 259-265. http://dx.doi.org/10.1080/02763869.2016.1189778 Abstract Objective – To assess the impact of academic medical library services and resources on information-seeking behaviours during the academic efforts of medical faculty and residents. Design – Value study derived from a 23-item survey. Setting – Public medical residency program and training hospital in Tennessee, USA. Subjects – 433 faculty and residents currently employed by or completing residency in an academic medical centre. Methods – Respondents completed a 23-question survey about their use of library resources and services in preparation for publishing, presenting, and teaching. The library services in the survey included literature searches completed by librarians and document delivery for preparation of publications, presentations, and lecture material. The survey also included questions about how resources were being accessed in preparation for scholarship. The survey sought information on whether respondents published articles or chapters or presented papers or posters in the previous three years. If respondents answered in the affirmative to one of the aforementioned methods of scholarship, they were provided with further questions about how they access library resources and whether they sought mediated literature search and document delivery services in preparation for their recent presentations and publications. The survey also included questions concerning what types of scholarly activity prompt faculty and residents to use online library resources. Main Results – The study was provided to 433 subjects, including 220 faculty and 213 residents, contacted through an email distribution list. The response rate to the survey was 15% (N=65). Residents comprised 35% of the respondents, and faculty at each of the three levels of tenure comprised 60%. The remaining 5% of respondents included PhD and non-clinical faculty within the graduate school. Over 50% of respondents reported use of library services in preparation for publishing and presenting. These library services were literature searches, document delivery, and accessing online resources. Faculty and residents reported use of PubMed first (71%) and most often, with 56% of respondents reporting weekly use, followed by Google or Google Scholar, with 20% of respondents reporting its use first and 23% of respondents reporting weekly use. However, regarding responses to the question concerning how journal articles are accessed, “using a search engine” was chosen most often, at almost 65%, followed by (in order) clicking library links in a database, contacting the library directly, searching the list of library e-journals, clicking publisher links in a database, using personal subscriptions, searching the library catalog, and using bookmarks saved in a web browser. Based on survey responses, faculty reported higher use of library services and resources than residents; however, residents reported higher use of library services and resources when preparing posters and papers for conferences and professional meetings. In addition, several comments spoke to the importance of the library for scholarly activity, many indicating the critical role of library assistance or resources in their academic accomplishments. Conclusion – This study provides evidence in support of library resources and services for medical faculty and residents, which contributes to discussions of the contributions of medical libraries. As hospital libraries close and academic medical libraries see reductions in budgets, this study contributes to the value of a library’s presence, as well as the role of the health sciences librarian in medical research and scholarly communication. This academic medical library was reported to be first and most often used, in comparison with other resources or none, in preparation for publication and presenting. The results of this and similar studies can contribute to the generalizability of its findings relating to the value of medical libraries. In addition, PubMed, UpToDate, and Google were the resources used most often by respondents, along with search engines and library links in databases. These findings can be incorporated into future outreach, marketing, and instructional curriculum for this library’s users. The survey results also provide additional support for the library’s role in the academic research lifecycle, and free-text comments about the critical role of library services furthered those findings. The authors state that further research is necessary for improving awareness of library resources and services in the role of scholarship at institutions.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.009 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.005 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".