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Using Gagne’s “Instructional Design” to teach clinically applicable knowledge in small groups

ABSTRACT: Background Anesthesia trainees are expected to perform tasks under non-direct supervision as soon as possible in their clinical training. Often they rely on only superficial rote learning, which might lead to medical errors. We have developed a lesson plan that is based on this educational need using Gagné’s Instructional Design for the example of teaching the complex preoperative management of diabetic patients. Our aim was to use Gagne’s approach successfully for the teaching of non-procedural skills. Methods We implemented a comprehensive lesson plan that was developed on the example of a clinical pattern – the preoperative assessment of diabetic patients - using Gagné’s systematic nine-step model of instruction design. After the lesson, we analysed the trainees’ opinions with the use of a standardized questionnaire. Results Nine trainees with 2.1 ± 0.8 years of anesthesia experience attended the lesson. The assessment of knowledge revealed in 82% the correct answers to the treatment options, and the residents’ overall view on the lecture concept were 4.8 ± 0.3 for lecture concept and realization and 4.7 ± 0.5 regarding motivation, participation and climate. Conclusions Applying Gagné’s Instructional Design model guides seems to effectively guide the development of a comprehensive lesson plan to teach non-procedural skills in a small group setting.

SUBMITTER: Berger-Estilita J

PROVIDER: S-EPMC7431410 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Project description:BackgroundClassification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed.MethodsGenomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared.ResultsReplication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for 'copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined 'high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves.ConclusionsMolecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.

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Using Gagne’s “Instructional Design” to teach clinically applicable knowledge in small groups

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