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

Ageing and Rehabilitation

Teaching Stroke Classification

Shaarna Shanmugavadivel University of Nottingham, UK

Presented at LIMSC, 2007 (Leiden, Netherlands) and AIMS, 2007 (Bristol)

Shaarna Shanmugavadivel 3rd year BMedSci dissertation

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What’s 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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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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Teaching of stroke

Core topic on HCE curriculum (4th 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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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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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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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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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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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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METHOD

PHASE 1: Develop an outcome measure, pilot + make CAL

4 domainsKNOWLEDGE: MCQ assessmentAMOUNT OF TEACHING: on scale 1-5CONFIDENCE: on scale 1-5SATISFACTION: on scale 1-5

PHASE 2: Evaluating the CAL


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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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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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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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RELIABILITY

One forum: assessment completed at beginning and end by same students

Cohen’s 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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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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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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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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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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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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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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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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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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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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THANK YOU!

Any questions?

Documents

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