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Record W2903430593 · doi:10.2147/amep.s181874

An effective and novel method for teaching applied facial anatomy and related procedural skills to esthetic physicians

2018· article· en· W2903430593 on OpenAlex
Narendra Kumar, Eqram Rahman, Philip J. Adds

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAdvances in Medical Education and Practice · 2018
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsnot available
FundersMonash UniversityMcGill University
KeywordsLikert scalePsychomotor learningIntraclass correlationMedical educationMedicineTeaching methodPsychologyCognitionMedical physicsMathematics educationClinical psychologyPsychometricsDevelopmental psychology

Abstract

fetched live from OpenAlex

BACKGROUND: An understanding of facial anatomy is crucial for the safe practice of nonsurgical facial esthetic procedures. Contextual learning, aided with instructional design, enhances the trainees' overall learning experience and retention, and makes a positive impact on the performance of procedural skills. The present study aimed to develop a teaching approach based on Bloom's taxonomy involving cognitive, affective, and psychomotor learning domains. MATERIALS AND METHODS: The practicability of Assess & Aware, Demonstrate, Decode, Act & Accomplish, Perform, Teach & Test (ADDAPT), a new approach to teaching applied facial anatomy and procedural skills to esthetic physicians in a large group setting, was evaluated in this study. Study participants were from two cohorts (n=124) who underwent 2 days of applied anatomy training in Singapore. Pre- and post-course multiple choice questions and objective structured practical examination were conducted to measure the effectiveness and applicability of the teaching model. Expert raters, table demonstrators, and participants rated the steps involved in the ADDAPT model on an 11-point Likert scale. RESULTS: <0.001). Inter-rater agreement, expressed as the intraclass correlation coefficient, was 0.91 (95% CI: 0.62-0.98) for expert raters and 0.90 (95% CI: 0.78-0.97) for table demonstrators, which reflects the real strength of sound educational practice. The trainees well accepted the model and found the sessions intellectually stimulating. Trainees' feedback stated that the learning experience was enhanced by the repeated observation and constructive feedback provided by the tutors. CONCLUSION: The ADDAPT model is practical to instruct a large group of trainees in clinical anatomy and procedural skill training. This approach to instructional design may be feasible and transferable to other areas of psychomotor skill training in medical education.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.367
Teacher spread0.365 · 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