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Record W2475111967 · doi:10.18438/b8w618

Medical School Librarians Need More Training to Support their Involvement in Evidence Based Medicine Curricula

2016· article· en· W2475111967 on OpenAlexvenueaboutno aff
Aislinn Conway

Bibliographic record

VenueEvidence Based Library and Information Practice · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumMedical educationCurriculum developmentFaculty developmentProfessional developmentPerceptionPsychologyQualitative researchScheduleSoftware deploymentInformation literacyMedicinePedagogyComputer scienceSociology

Abstract

fetched live from OpenAlex

Objective – To describe the self-perceived role of librarians in developing evidence based medicine (EBM) curricula and identify their current and desired level of training to support these activities. Design – Multi-institutional qualitative study. Setting – Nine medical schools in Canada and the United States of America. Subjects – Nine librarians identified by medical school faculty as central to the provision of EBM training for medical students at their institution. Methods – The researchers designed a semi-structured interview schedule based on a review of the literature and their own experiences as librarians teaching EBM. The topics covered were; librarians’ perceptions of their roles in relation to the curriculum, the training required to enable them to undertake these roles, and their professional development needs. The interviews were conducted by telephone and then audio-recorded and transcribed verbatim. The authors present five main themes; curricular design, curricular deployment, curricular assessment, educational training, and professional development. Profiles were developed for each participant based on the latter two themes and from this information common characteristics were identified. Main Results – The participants described the importance of collaboration with faculty and student bodies when designing a curriculum. Information literacy instruction and specifically literature searching and forming a research question were taught by all of the participants to facilitate curricular deployment. Some of the librarians were involved or partly involved in curricular assessment activities such as formulating exam questions or providing feedback on assignments. Educational training of participants varied from informal observation to formal workshops offered by higher education institutions. All librarians indicated a willingness to partake in professional development focused on teaching and EBM. The subjects’ perceptions of their roles are supported by Dorsch and Perry’s themes of the librarian’s role in curricular design, deployment, and assessment. The educational training received by participants included formal training and experiential and self-directed learning activities. Finally, the librarians identified their professional development needs going forward. The majority of participants indicated that they would like to attend workshops run by universities or the Medical Library Association. Others wanted to invite and host guest speakers at their own institutions. Librarians identified financial restraints and geographic location as barriers to attending professional development events. Conclusion – Librarians can be actively involved in the delivery of EBM instruction in medical schools. However, they require additional educational opportunities to enable them to develop in this role. Online training could be a viable option for self-directed learning to overcome financial and geographic constraints.

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0070.006
Open science0.0010.005
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0110.003

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 head0.139
GPT teacher head0.447
Teacher spread0.308 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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