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Record Nr. |
UNINA9911019851203321 |
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Autore |
Greenhalgh Trisha M |
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Titolo |
How to read a paper : the basics of evidence-based healthcare / / Trisha Greenhalgh, Paul Dijkstra |
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Pubbl/distr/stampa |
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Newark : , : John Wiley & Sons, Incorporated, , 2025 |
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©2025 |
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ISBN |
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9781394206926 |
1394206925 |
9781394206933 |
1394206933 |
9781394206919 |
1394206917 |
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Edizione |
[Seventh edition.] |
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Descrizione fisica |
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1 online resource (351 pages) |
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Collana |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Evidence-based medicine |
Medical literature - Evaluation |
Medicine - Research - Evaluation |
Medical literature |
Clinical medicine - Decision making |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Cover -- Title Page -- Copyright Page -- Dedication Page -- Contents -- Foreword to the first edition by Professor Sir David Weatherall -- Preface to the seventh edition -- Preface to the first 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 healthcare? -- 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 -- Exercises based on this chapter -- References -- Chapter 2 Searching the literature -- The information jungle -- What are you looking for? -- |
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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 -- PubMed -- SPORTDiscus -- Google Scholar -- One-stop shopping: federated search engines -- Using artificial intelligence to search the literature -- Asking for help and asking around -- Online tutorials for effective searching -- Exercises based on this chapter -- References -- Chapter 3 Getting your bearings: what is this paper about? -- The science of 'trashing' papers -- Three preliminary questions to get your bearings -- Question one: Why was the study needed and what was the research question? -- Question two: What was the research design? -- Question three: Was the research design appropriate to the question? -- What are randomised controlled trials and why do they matter? -- What are cohort studies? -- What are case-control studies? -- What are cross-sectional surveys? -- What are case reports? -- The traditional hierarchy of evidence. |
Exercises based on this chapter -- References -- Chapter 4 Assessing methodological quality -- Was the study original? -- Who is the study about? -- Was the design of the study sensible? -- Was bias avoided or minimised? -- Sources of bias in randomised controlled trials -- Sources of bias in non-randomised controlled clinical trials -- Sources of bias in cohort studies -- Sources of bias in case-control studies -- Was assessment 'blind'? -- Were preliminary statistical questions addressed? -- Sample size -- Duration of follow-up -- Completeness of follow-up -- A note on ethical considerations -- Summing up -- Exercises based on this chapter -- 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 do they have 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 (quantifying the chance of benefit and harm) -- Have the authors expressed the effects of an intervention in terms of the likely benefit or harm that an individual patient can expect? -- Summary -- Exercises based on this chapter -- References -- Chapter 6 Papers that report clinical trials of simple interventions -- What is a clinical trial? -- Drug trials: '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 from pharmaceutical representatives -- A note on vaccine trials -- Exercises based on this chapter -- References -- Chapter 7 Papers that report trials of complex interventions -- |
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Complex interventions -- Ten questions to ask about a paper describing a complex intervention -- Question one: What is the problem for which this complex intervention is seen as a possible solution? -- Question two: What was done in the developmental phase of the research to inform the design of the complex intervention? -- Question three: What were the core and non-core components of the intervention? -- Question four: What was the theoretical mechanism of action of the intervention? -- Question five: What outcome measures were used and were they sensible? -- Question six: What were the findings? -- Question seven: What process evaluation was done and what were the key findings? In particular, to what extent was the intervention implemented as planned ('implementation fidelity')? -- Question eight: If the findings were negative, to what extent can this be explained by implementation failure and/or inadequate optimisation of the intervention?. |
Question nine: If the findings varied across different subgroups, to what extent have the authors explained this by refining their theory of change? -- Question ten: What further research do the authors believe is needed and is this belief justified? -- References -- Chapter 8 Papers that report diagnostic or screening tests -- Ten suspects 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 -- Question one: Is this test potentially relevant to my patients and my practice? -- Question two: Has the test been compared with a true gold standard? -- Question three: Did this validation study include an appropriate spectrum of participants? -- Question four: Has work-up (verification) bias been avoided? -- Question five: Has expectation bias been avoided? -- Question six: Was the test shown to be reproducible both within and between observers? -- Question seven: What are the features of the test as derived from this validation study? -- Question eight: Were confidence intervals given for sensitivity, specificity and other features of the test? -- Question nine: Has a sensible 'normal range' been derived from these results? -- Question ten: Has this test been placed in the context of other potential tests in the diagnostic sequence for the condition? -- Likelihood ratios -- Clinical prediction models -- Exercises based on this chapter -- References -- Chapter 9 Papers that summarise other papers (systematic reviews and meta-analyses) -- When is a review systematic? -- Evaluating systematic reviews: five questions to ask -- Question one: What is the important clinical question that the review addressed? -- Question two: Was a thorough search carried out of the appropriate database(s) and were other potentially important sources explored?. |
Question three: Was risk of bias of individual studies assessed and the studies weighted accordingly? -- Question four: How sensitive are the results to the way the review has been performed? -- Question five: Have the numerical results been interpreted with common sense and due regard to the broader aspects of the problem? -- Meta-analysis for the non-statistician -- Explaining heterogeneity -- New approaches to systematic review -- Exercises based on this chapter -- References -- Chapter 10 Papers that advise you what to do (guidelines) -- The great guidelines debate -- Ten questions to ask about a clinical guideline -- Question one: Did the preparation and publication of this guideline involve a significant conflict of interest? -- Question two: Is the guideline concerned with an appropriate topic and does it state clearly the target group it applies to? -- Question three: Did the guideline development panel include: (1) an expert in the topic area -- (2) a specialist in the methods of secondary research (e.g. meta-analyst, health economist) and (3) |
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a person affected by the condition? -- Question four: Have the subjective judgements of the development panel been made explicit and are they justified? -- Question five: Have all the relevant data been scrutinised and rigorously evaluated? -- Question six: Has the evidence been properly synthesised and are the guideline's conclusions in keeping with the data on which they are based? -- Question seven: Does the guideline address variations in medical practice and other controversial areas (e.g. optimum care in response to genuine or perceived underfunding)? -- Question eight: Is the guideline clinically relevant, comprehensive and flexible? -- Question nine: Does the guideline take into account what is acceptable to, affordable by and practically possible for patients?. |
Question ten: Does the guideline include recommendations for its own dissemination, implementation and regular review?. |
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Sommario/riassunto |
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"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"-- |
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