|Course code MEDI6020||Units 10||Level 6000||Faculty of Health and MedicineSchool of Medicine and Public Health|
This subject is designed to invest candidates with the intellectual and arithmetic skills to understand and calculate various statistics pertinent to the evaluation of the reliability, validity and efficacy techniques relevant to the diagnosis and treatment of pain. Furthermore, candidates will be instructed as to how to evaluate (and compose) literature on pain treatment. This subject does not preclude enrollment in other subjects.
Not available in 2014
|Previously offered in 2008, 2007, 2006, 2005, 2004|
|Objectives||To be able to analyse and determine the reliability and validity of a diagnostic tests for pain, in terms of Kappa scores, sensitivity, specificity, likelihood ratiios, pre-test and post-test odds and probabilities.|
To be able to assess the efficacy of a treatment for pain:
1. by being familiar the possible statistical tools although not necessarily able to coompute statistics inaided.
2. by being able to identify critical issues seminal to the quality of a research paper on treatment.
To be able to compose and present a written critique of a selected article.
|Content||Definition of Truth:|
Truth in Diagnosis - Reliability, Validity (concept, content, face, construct, therapeutic utility)
Truth in Treatment - Efficacy, sensitivity analysis, confidence intervals, met-analysis, ANOVAs, survival curves, number needed to treat, systematic reviews, odds ratios.
How to read or write a paper on pain. The importance of:
source population, selection bias, drop out, observer bias, security of blinding, power calculation, tests of statistical significance (chi-square, Fisher's exact test, survival analysis), VAS, psychological measures, cost-effectiveness, study sample, control group, intention to treat analysis, recall bias, independent observer, type I and type II errors, disability, treatment satisfaction, inception period, comparability, outcome measures, blinding, compliance, categorical vs continuous data, clinical significance (snesitivity analysis, NNT), health care utilisation, complications
|Assumed Knowledge||Undergraduate competence in arithmetic and algebra.|
|Modes of Delivery||Distance Learning : IT Based|
Distance Learning : Paper Based
|Teaching Methods||Email Discussion Group|
Self Directed Learning
|Contact Hours||Email Discussion Group: for 10 hour(s) per Week for Full Term|