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Ageing and Rehabilitation Teaching Stroke Classification Shaarna Shanmugavadivel University of Nottingham, UK Presented at LIMSC, 2007 (Leiden, Netherlands) and AIMS, 2007 (Bristol)

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 2 Whats on the table? Why this project is important – background What the project entailed - project definition How it was carried out – methodology What did we find? – Results Conclusions

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 3 How important is STROKE? THIRD largest cause of death in the UK First stroke- 130,000 people in England and Wales each year equivalent to one stroke every five minutes single leading cause of severe disability in the UK

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 4 Teaching of stroke Core topic on HCE curriculum (4 th yr) BUT clinical diagnosis is not formally taught in introductory lectures tutorials by frequently changing staff at different sites a risk that not all students will gain a core understanding of stroke diagnosis?

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 5 Methods of teaching Tutorial (current) Lectures Clinical sessions (ward-based teaching) Computer-assisted learning (CAL) - Lots of evidence FOR computer assisted learning

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 6 CAL CAL: the process of providing written and visual information in a logical sequence by the computer, the focus of which is on instruction-(Florey 1988) allows a self-paced, self-directed approach promotes deeper and more retentive learning (Coles 1998) immediate feedback and choice to repeat the same tasks until perfected- consistent teaching BUT lack of objective evidence about its effectiveness in terms of the transfer of knowledge to the learner (Sittig et al., 1995)

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 7 AIMS AND OBJECTIVES AIM: to develop and evaluate a teaching package for fourth years on Stroke Classification AIM of CAL package: To understand how to make the diagnosis of stroke using the Oxford Stroke classification

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 8 OBJECTIVES of CAL package: To develop an understanding of the different symptoms and signs seen in stroke To be able to classify the type of stroke using the Oxford Stroke classification To relate the clinical diagnosis to the likely anatomical lesion and pathology To understand the importance of the clinical classification in estimating prognosis

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 9 RESEARCH QUESTIONS Is Stroke diagnosis and classification being taught adequately enough for students to gain a core understanding of the concepts? Is the addition of CAL delivered teaching superior to usual traditional teaching of stroke classification?

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 10 METHOD PHASE 1: Develop an outcome measure, pilot + make CAL 4 domains KNOWLEDGE: MCQ assessment AMOUNT OF TEACHING: on scale 1-5 CONFIDENCE: on scale 1-5 SATISFACTION: on scale 1-5 PHASE 2: Evaluating the CAL

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 11 PHASE 1: pilot study To answer the first research question Power calculation- check sample size to reduce risk of Type ii error Face validity and test-retest reliability using kappa stats All anonymous to avoid bias n=36

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 12 RESULTS OF PILOT How much teaching did you receive? 36.1 % said NONE How confident do you feel with classification? 88.9% said UNCONFIDENT How satisfied are you with the teaching? 57.1 % said DISSATISFIED For the MCQS- MEAN was 36% a soft fail in med school terms!

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 13 POWER CALCULATION A two group t-test with a 0.05 two-sided significance level will have 80% power to detect the difference between a Group 1 mean of 7.2 and a Group 2 mean of 12, assuming that the common standard deviation is 5.3, when the sample sizes in the two groups are 44 and 13, respectively (a total sample size of 57).

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 14 RELIABILITY One forum: assessment completed at beginning and end by same students Cohens un-weighted kappa statistical test observed agreement between the 2 groups: 91.84%, (expected agreement only 27.36%). kappa value >0.4 = acceptable kappa value for this= 0.89 This showed good test-retest reliability of the assessment.

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 15 PHASE 1: making CAL Consists of factual knowledge, real patient videos, assessments Led by Heather Rai http://www.nle.nottingham.ac.uk/websites/stroke/

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 16 PHASE 2: Evaluating the CAL 3 HCE attachments from Oct-Dec 1st two: TUTORIAL ONLY (controls) + 36 from pilot Third: CAL package + TUTORIAL (intervention) Reduces risk of contamination

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 17 RESULTS Control n=76 (92), Intervention n= 23 (28) Attrition due to non attendance and failure to implement assessment Power calc: 44,13

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 18 Primary outcome measure KNOWLEDGE - Mean score out of 20 CONTROL: mean of 9.87 (8.6-11.1) INTERVENTION: mean of 13.26 (10.9-15.6) Normally distributed + equal variances 2-tailed t-test gave mean difference of 3.39 (0.77-6.0), p=0.0116 (p< 0.05)

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 19 Secondary outcome measure Categorical: perceived amount of teaching, confidence and satisfaction Chi-squared test Perceived amount of teaching: 14/23 (60.1%) of intervention group felt they had enough/plenty of teaching compared to 24/76 (31.6%) controls, p = 0.012.

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 20 Secondary outcome measure Confidence: 12/23 (52.2%) of intervention group were confident, compared to 13/76 (17.1%) in the control group, p= 0.0018. Satisfaction: 14/22 (63.6%) students in intervention group were satisfied with teaching, compared to 26/74 (35.1%) of controls group, p=0.017.

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 21 Feedback from CAL 19/19 students enjoyed using the website. 11 left a free-text response 7=100% positive feedback, two= constructive criticism based on areas for improvement and a further two pointed out minor errors Analysis: useful, helpful and enjoyable, especially videos and assessments

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 22 Conclusion The addition of CAL in this study enhanced knowledge acquisition, perceived satisfaction and confidence in diagnosing and classifying Stroke. Students feedback: that this particular CAL could replace the tutorial completely; however, this must be explored by further study.

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 23 References FLOREY C du V(1988) Computer assisted learning in British Medical Schools; Med Educ. May; 22(3): 180-2 COLES (1998) The process of Learning in: Jolly B, Medical education in the Millennium; Oxford University Press, New York VOGEL M, WOOD D (2002) Love it or hate it: Medical students attitudes to computer assisted learning; Med Educ; 36; 214-5 SITTIG DF et al. (1995) Evaluating a computer based experimental learning simulation; Computers in nursing; 13 pp17-24

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Shaarna Shanmugavadivel 3 rd year BMedSci dissertation 24 THANK YOU! Any questions?

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