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Record W4405039437 · doi:10.1182/blood-2024-200444

Development of an Electronic Learning Module for CAR-T Education in Canadian Hematology Residents

2024· article· en· W4405039437 on OpenAlexaffabout
Grace Zhang, Gwynivere A Davies, Kylie Lepic, Amaris Balitsky

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsHamilton Health SciencesJuravinski Cancer CentreMcMaster University
Fundersnot available
KeywordsHematologyMedicineInternal medicineMedical education

Abstract

fetched live from OpenAlex

Introduction: Chimeric antigen receptor T-cell (CAR-T) therapy is a novel treatment for multiple hematologic malignancies. There are currently six approved CAR-T products in Canada and this therapy is provided in a select number of academic centres. While this therapy has shown promising efficacy, it is associated with unique toxicities which requires prompt recognition and management. As CAR-T therapy access increases, there is a growing need to ensure that physicians overseeing this therapy have received appropriate education and training. Canadian hematology graduate trainees experience variable exposure to CAR-T therapy management, mainly dependent on experiential learning. This can lead to gaps in trainee education. Electronic learning modules (ELMs) are an educational intervention that provide an accessible, flexible and interactive learning experience supporting adult learning principles, which have the potential to address such potential gaps in training. We present our process of developing a needs-driven novel CAR-T therapy ELM for hematology trainees in Canada. Methods: In March 2023, an online environmental scan was performed to identify the need for CAR-T education programs tailored to Canadian hematology trainees. Next, to determine optimal ELM content and delivery, a needs assessment survey was distributed online to Canadian hematology trainees in June 2023. The survey contained 10 items and included multiple choice, free text, and Likert scale questions addressing the following domains: 1) pre-existing CAR-T education, 2) content knowledge needs, 3) ideal features and parameters of a CAR-T ELM, 4) preferred learning methods, and 5) preferred assessment methods. A draft ELM was developed based on these results and with input from CAR-T therapy content experts. We conducted semi-structured focus groups of recently graduated Canadian hematology trainees to pilot the ELMs' module content, length, visuals, and delivery. The focus groups were conducted between January and February 2024. The qualitative analysis of transcripts was iterative until thematic saturation was reached. The ELM was modified based on focus group feedback to produce the final ELM product. Results: An environmental scan identified no open-access CAR-T ELMs that address the Canadian practice environment. Additionally, there were no online learning programs directed at hematology trainees. Sixty participants were approached and 17 completed the needs assessment, with representation from 72% of adult hematology residency programs in Canada. Most residents (71%) had some teaching around CAR-T, even if their residency training was not based at a CAR-T centre. 65% of residents had assessed a patient for CAR-T therapy eligibility, and 71% of residents had experience managing acute toxicities of CAR-T therapy. However, only 35% had experience assessing patients for potential bridging therapy prior to CAR-T, and less than 30% had provided long-term follow-up care following CAR-T therapy. Participants felt they would at least moderately benefit from learning more about all aspects of CAR-T therapy, and significantly benefit from learning more about patient selection, bridging, and acute and long-term toxicities. The preferred ELM length was 1-2 hours. To assess knowledge acquisition, participants strongly preferred a written quiz format over OSCE-style assessment. Eight participants took part in three focus groups to provide feedback on the ELM. Major themes of positive feedback included: 1) overall visual design, 2) user-friendliness of interface, 3) module content and length, and 4) availability and relevance of practice questions. Points of constructive feedback included adding in-line references and reference summaries, highlighting key information to draw attention, and providing proof of module completion for educational credit. Conclusion: A mixed methods research design was successfully employed to develop an electronic learning module for CAR-T education in Canadian hematology residents. The next step, which is currently in progress, is to evaluate the efficacy of this educational intervention across multiple levels using Kirkpatrick's training evaluation model. Future goals include disseminating the ELM through the Cellular Therapy and Transplant Canada website.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.386

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.003

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 head0.004
GPT teacher head0.225
Teacher spread0.220 · 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 designObservational
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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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