Cover -- Title Page -- Copyright -- Contents -- Foreword to the first edition by Professor Sir David Weatherall -- Preface to the first edition: do you need to read this book? -- Preface to the fifth edition -- Acknowledgements -- Chapter 1 Why read papers at all? -- Does 'evidence-based medicine' simply mean 'reading papers in medical journals'? -- Why do people sometimes groan when you mention evidence-based medicine? -- Decision-making by anecdote -- Decision-making by press cutting -- Decision-making by GOBSAT (good old boys sat around a table) -- Decision-making by cost-minimisation -- Before you start: formulate the problem -- Exercise 1 -- References -- Chapter 2 Searching the literature -- What are you looking for? -- Levels upon levels of evidence -- Synthesised sources: systems, summaries and syntheses -- Pre-appraised sources: synopses of systematic reviews and primary studies -- Specialised resources -- Primary studies - tackling the jungle -- One-stop shopping: federated search engines -- Asking for help and asking around -- Online tutorials for effective searching -- References -- Chapter 3 Getting your bearings: what is this paper about? -- The science of 'trashing' papers -- Three preliminary questions to get your bearings -- Randomised controlled trials -- Cohort studies -- Case-control studies -- Cross-sectional surveys -- Case reports -- The traditional hierarchy of evidence -- A note on ethical considerations -- References -- Chapter 4 Assessing methodological quality -- Was the study original? -- Whom is the study about? -- Was the design of the study sensible? -- Was systematic bias avoided or minimised? -- Randomised controlled trials -- Non-randomised controlled clinical trials -- Cohort studies -- Case-control studies -- Was assessment 'blind'? -- Were preliminary statistical questions addressed? -- Sample size.

Duration of follow-up -- Completeness of follow-up -- Summing up -- References -- Chapter 5 Statistics for the non-statistician -- How can non-statisticians evaluate statistical tests? -- Have the authors set the scene correctly? -- Have they determined whether their groups are comparable, and, if necessary, adjusted for baseline differences? -- What sort of data have they got, and have they used appropriate statistical tests? -- If the statistical tests in the paper are obscure, why have the authors chosen to use them, and have they included a reference? -- Have the data been analysed according to the original study protocol? -- Paired data, tails and outliers -- Were paired tests performed on paired data? -- Was a two-tailed test performed whenever the effect of an intervention could conceivably be a negative one? -- Were 'outliers' analysed with both common sense and appropriate statistical adjustments? -- Correlation, regression and causation -- Has correlation been distinguished from regression, and has the correlation coefficient ('r-value') been calculated and interpreted correctly? -- Have assumptions been made about the nature and direction of causality? -- Probability and confidence -- Have 'p-values' been calculated and interpreted appropriately? -- Have confidence intervals been calculated, and do the authors' conclusions reflect them? -- The bottom line -- Have the authors expressed the effects of an intervention in terms of the likely benefit or harm that an individual patient can expect? -- Summary -- References -- Chapter 6 Papers that report trials of drug treatments and other simple interventions -- 'Evidence' and marketing -- Making decisions about therapy -- Surrogate endpoints -- What information to expect in a paper describing a randomised controlled trial: the CONSORT statement.

Getting worthwhile evidence out of a pharmaceutical representative -- References -- Chapter 7 Papers that report trials of complex interventions -- Complex interventions -- Ten questions to ask about a paper describing a complex intervention -- References -- Chapter 8 Papers that report diagnostic or screening tests -- Ten men in the dock -- Validating diagnostic tests against a gold standard -- Ten questions to ask about a paper that claims to validate a diagnostic or screening test -- Likelihood ratios -- Clinical prediction rules -- References -- Chapter 9 Papers that summarise other papers (systematic reviews and meta-analyses) -- When is a review systematic? -- Evaluating systematic reviews -- Meta-analysis for the non-statistician -- Explaining heterogeneity -- New approaches to systematic review -- References -- Chapter 10 Papers that tell you what to do (guidelines) -- The great guidelines debate -- How can we help ensure that evidence-based guidelines are followed? -- Ten questions to ask about a clinical guideline -- References -- Chapter 11 Papers that tell you what things cost (economic analyses) -- What is economic analysis? -- Measuring costs and benefits of health interventions -- Ten questions to ask about an economic analysis -- Conclusion -- References -- Chapter 12 Papers that go beyond numbers (qualitative research) -- What is qualitative research? -- Evaluating papers that describe qualitative research -- Conclusion -- References -- Chapter 13 Papers that report questionnaire research -- The rise and rise of questionnaire research -- Ten questions to ask about a paper describing a questionnaire study -- References -- Chapter 14 Papers that report quality improvement case studies -- What are quality improvement studies - and how should we research them?.

Ten questions to ask about a paper describing a quality improvement initiative -- Conclusion -- References -- Chapter 15 Getting evidence into practice -- Why are health professionals slow to adopt evidence-based practice? -- How much avoidable suffering is caused by failing to implement evidence? -- How can we influence health professionals' behaviour to promote evidence-based practice? -- What does an 'evidence-based organisation' look like? -- How can we help organisations develop the appropriate structures, systems and values to support evidence-based practice? -- References -- Chapter 16 Applying evidence with patients -- The patient perspective -- PROMs -- Shared decision-making -- Option grids -- n of 1 trials and other individualised approaches -- References -- Chapter 17 Criticisms of evidence-based medicine -- What's wrong with EBM when it's done badly? -- What's wrong with EBM when it's done well? -- Why is 'evidence-based policymaking' so hard to achieve? -- References -- Appendix 1 Checklists for finding, appraising and implementing evidence -- Appendix 2 Assessing the effects of an intervention -- Index.

The best-selling introduction to evidence-based medicine In a clear and engaging style, How to Read a Paper demystifies evidence-based medicine and explains how to critically appraise published research and also put the findings into practice. An ideal introduction to evidence-based medicine, How to Read a Paper explains what to look for in different types of papers and how best to evaluate the literature and then implement the findings in an evidence-based, patient-centred way. Helpful checklist summaries of the key points in each chapter provide a useful framework for applying the principles of evidence-based medicine in everyday practice. This fifth edition has been fully updated with new examples and references to reflect recent developments and current practice. It also includes two new chapters on applying evidence-based medicine with patients and on the common criticisms of evidence-based medicine and responses. How to Read a Paper is a standard text for medical and nursing schools as well as a friendly guide for everyone wanting to teach or learn the basics of evidence-based medicine.

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