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Record W2012733915 · doi:10.1186/1472-6920-10-72

Hunter disease eClinic:interactive, computer-assisted, problem-based approach to independent learning about a rare genetic disease

2010· article· en· W2012733915 on OpenAlexafffundabout
Fatma Al‐Jasmi, Laura Moldovan, Joe TR Clarke

Bibliographic record

VenueBMC Medical Education · 2010
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoLMC Diabetes & Endocrinology (Canada)
FundersHospital for Sick Children
KeywordsSoftwareDiseaseComputer scienceMultimediaVirtual patientMedical educationMedicineWorld Wide WebHuman–computer interactionPathologyOperating system

Abstract

fetched live from OpenAlex

BACKGROUND: Computer-based teaching (CBT) is a well-known educational device, but it has never been applied systematically to the teaching of a complex, rare, genetic disease, such as Hunter disease (MPS II). AIM: To develop interactive teaching software functioning as a virtual clinic for the management of MPS II. IMPLEMENTATION AND RESULTS: The Hunter disease eClinic, a self-training, user-friendly educational software program, available at the Lysosomal Storage Research Group (http://www.lysosomalstorageresearch.ca), was developed using the Adobe Flash multimedia platform. It was designed to function both to provide a realistic, interactive virtual clinic and instantaneous access to supporting literature on Hunter disease. The Hunter disease eClinic consists of an eBook and an eClinic. The eClinic is the interactive virtual clinic component of the software. Within an environment resembling a real clinic, the trainee is instructed to perform a medical history, to examine the patient, and to order appropriate investigation. The program provides clinical data derived from the management of actual patients with Hunter disease. The eBook provides instantaneous, electronic access to a vast collection of reference information to provide detailed background clinical and basic science, including relevant biochemistry, physiology, and genetics. In the eClinic, the trainee is presented with quizzes designed to provide immediate feedback on both trainee effectiveness and efficiency. User feedback on the merits of the program was collected at several seminars and formal clinical rounds at several medical centres, primarily in Canada. In addition, online usage statistics were documented for a 2-year period. Feedback was consistently positive and confirmed the practical benefit of the program. The online English-language version is accessed daily by users from all over the world; a Japanese translation of the program is also available. CONCLUSIONS: The Hunter disease eClinic employs a CBT model providing the trainee with realistic clinical problems, coupled with comprehensive basic and clinical reference information by instantaneous access to an electronic textbook, the eBook. The program was rated highly by attendees at national and international presentations. It provides a potential model for use as an educational approach to other rare genetic diseases.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.022
GPT teacher head0.344
Teacher spread0.322 · 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 teacher head, not a consensus.

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

Citations18
Published2010
Admission routes3
Has abstractyes

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