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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
For two decades, Understanding Clinical Papers has been helping students and professionals understand the research that supports evidence-based practice. Now in its fourth edition, this popular introductory textbook covers every major aspect of reading and evaluating clinical research literature, from identifying the aims and objectives of a paper to analysing the data with different multivariable methods. Numerous excerpts from actual clinical research papers make learning real and immediate, supported by a unique visual approach that reinforces key points and connects examples with the chapter material. The fourth edition includes extensively revised content throughout, including four brand-new chapters covering qualitativestudies, Poisson regression, studies of complex interventions, and research using previously collected data. New and updated material discusses the difference between clinical and statistical significance, the consequences of multiple testingand methods of correction, howtopic guides are used to explore and explain participants' experiences, standardised guidelines for writing trials and reviews, and much more. Offering clear explanations of important research-related topics, this reader-friendly resource: * Offers a clear, concise, and accessible approach to learning how to read and analyse clinical research literature * Features new coverage of qualitativeresearch, includingdescriptive studies, sampling and populations,and identifying, summarising, and measuring qualitative characteristics * Provides new material on missing data, sub-group analysis, feasibility and pilot studies, cluster randomised trials, and adaptive trial designs * Includes new tables, abstracts, and excerpts from recent clinical research literature Understanding Clinical Papers is essential reading for all healthcare professionals and students, particularly those involved in clinical work and medical research, as well as general readers wanting to improve their understanding of research literature.
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Table of Contents
Cover
Title Page
Copyright Page
Preface to the First Edition
Preface to the Second Edition
SOME NOTES ON STATISTICAL SOFTWARE
WRITING PAPERS FOR CLINICAL JOURNALS
Preface to the Third Edition
Preface to the Fourth Edition
PART I: Setting the Scene: Who Did What, and Why
CHAPTER 1: Some Preliminaries
WHO WROTE THE PAPER?
IN WHAT SORT OF JOURNAL DOES THE PAPER APPEAR?
WHO (AND WHAT) IS ACKNOWLEDGED?
CHAPTER 2: The Abstract and Introduction
THE ABSTRACT
THE INTRODUCTION
ETHICAL CONSIDERATIONS
CHAPTER 3: The Aims and Objectives
HYPOTHESES
OBJECTIVES THAT ARE NOT HYPOTHESIS TESTING
STUDIES WITH UNCLEAR OBJECTIVES
PART II: Design Matters: What Type of Study Is It?
CHAPTER 4: Descriptive Studies
QUALITATIVE RESEARCH
TYPES OF QUALITATIVE STUDY
CHAPTER 5: Descriptive Studies
CASE REPORTS
CASE SERIES
CROSS‐SECTIONAL STUDIES
LONGITUDINAL STUDIES
CHAPTER 6: Analytic Studies
ECOLOGICAL STUDIES
CROSS‐SECTIONAL, TWO‐GROUP STUDIES
CASE–CONTROL STUDIES
COHORT ANALYTIC STUDIES
VARIATIONS IN CASE–CONTROL AND COHORT DESIGNS
COMPARING AND CONTRASTING CASE–CONTROL AND COHORT STUDIES
‘STROBE' GUIDELINES
CHAPTER 7: Intervention Studies
TRIALS
RANDOM ALLOCATION AND ITS CONCEALMENT
CONSENT AND RANDOMIZATION IN TRIALS
PLACEBOS OR TREATMENT‐AS‐USUAL
PRAGMATIC AND EXPLANATORY TRIALS
INTENTION‐TO‐TREAT ANALYSIS
FEASIBILITY AND PILOT STUDIES
CLUSTER RANDOMIZED TRIALS
ADAPTIVE TRIAL DESIGN
CONSORT GUIDELINES
CHAPTER 8: Mixed Methods Research
CHAPTER 9: Studies of Complex Interventions
CHAPTER 10: Systematic Review and Meta‐Analysis
SYSTEMATIC REVIEW
PUBLICATION AND OTHER BIASES
THE FUNNEL PLOT
HETEROGENEITY
COMBINING THE STUDIES
‘PRISMA' GUIDELINES
SYSTEMATIC REVIEW OF NON‐TRIALS RESEARCH
CHAPTER 11: Systematic Review of Qualitative Studies
PART III: The Cast: Finding Out About the Subjects of the Research
CHAPTER 12: The Research Setting
CHAPTER 13: Populations and Samples in Quantitative Research
SAMPLING
SAMPLE SIZE AND POWER
CHAPTER 14: Research Using Already‐Collected Data
SOURCES OF ALREADY‐COLLECTED DATA
PROBLEMS WITH ALREADY‐COLLECTED DATA
MISSING DATA IN ALREADY‐COLLECTED DATASETS
CONFOUNDING IN ALREADY‐COLLECTED DATA
CHAPTER 15: The Sample in Qualitative Research
THE NATURE OF SAMPLES IN QUALITATIVE RESEARCH
SAMPLE SIZE IN QUALITATIVE RESEARCH
SAMPLING FOR QUALITATIVE RESEARCH
CHAPTER 16: Identifying and Defining Cases
CHAPTER 17: Controls and Comparisons
PART IV: Establishing the Facts: Starting with Basic Observations
CHAPTER 18: Identifying the Characteristics of Quantitative Data
TYPES OF VARIABLE – TYPES OF DATA
IDENTIFYING DATA TYPE
SHAPES OF DISTRIBUTIONS
CHAPTER 19: Summarizing the Characteristics of Quantitative Data
SUMMARY MEASURES OF LOCATION
SUMMARY MEASURES OF SPREAD
CHAPTER 20: Identifying and Summarising the Characteristics of Qualitative Data
CHAPTER 21: Measuring the Characteristics of Participants
INFORMATION AND MEASUREMENT BIAS
BIAS ARISING FROM MISSING VALUES
CHAPTER 22: Measuring the Characteristics of Participants
CHAPTER 23: Diagnostic Tests
THE MEASURES
THE SENSITIVITY VERSUS SPECIFICITY TRADE‐OFF – THE RECEIVER OPERATING CHARACTERISTIC (ROC) CURVE
CHAPTER 24: Measurement Scales
THE MEASUREMENT PROBLEM
WHAT ARE MEASUREMENT SCALES?
WHEN AUTHORS USE DATA FROM MEASUREMENT SCALES
DEVELOPMENT OF A NEW MEASUREMENT SCALE
SCALE CONSTRUCTION
DESIRABLE PROPERTIES OF SCALES
CHAPTER 25: Exploring and Explaining
PART V: Establishing More of the Facts: Some Common Ways of Describing Results
CHAPTER 26: Fractions, Proportions, and Rates
CHAPTER 27: Risks and Odds
RISK
ODDS
CHAPTER 28: Ratios of Risks and Odds
RISK RATIO
ODDS RATIO
CLINICAL TRIALS AND ‘NUMBERS NEEDED TO TREAT'
PART VI: Analysing the Data: Estimation and Hypothesis Testing
CHAPTER 29: Confidence Intervals for Means, Proportions, and Medians
WHAT IS A CONFIDENCE INTERVAL?
CONFIDENCE INTERVALS FOR DIFFERENCES IN TWO MEANS
CONFIDENCE INTERVALS AND CLINICAL EFFECTIVENESS
CONFIDENCE INTERVALS FOR DIFFERENCES IN TWO PERCENTAGES
CONFIDENCE INTERVALS FOR DIFFERENCES IN TWO MEDIANS
CHAPTER 30: Confidence Intervals for Ratios
CONFIDENCE INTERVALS FOR ODDS RATIOS
CONFIDENCE INTERVALS FOR RISK RATIOS
CONFIDENCE INTERVALS FOR HAZARD RATIOS
CHAPTER 31: Testing Hypotheses – The
p
‐value
ASSESSING THE EVIDENCE AGAINST THE HYPOTHESIS – THE
P
‐VALUE
MAKING THE WRONG DECISION – TYPES OF ERROR
HYPOTHESIS TESTS AND CONFIDENCE INTERVALS COMPARED
TWO‐TAILED VERSUS ONE‐TAILED TESTS
MATCHED VERSUS INDEPENDENT GROUPS
TRANSFORMING DATA
FINALLY
PART VII: Analysing the Data: Multivariable Methods
CHAPTER 32: Measuring Association
MEASURING ASSOCIATION
THE CORRELATION COEFFICIENT
CHAPTER 33: Measuring Agreement
MEASURING AGREEMENT WITH NOMINAL DATA
INTERPRETING
κ
AGREEMENT WITH ORDINAL DATA: WEIGHTED κ
MEASURING AGREEMENT WITH METRIC DATA
CHAPTER 34: Linear Regression
WHY REGRESSION?
LINEAR REGRESSION
ESTIMATING THE REGRESSION COEFFICIENTS – ORDINARY LEAST SQUARES ESTIMATION
MEASURING THE STATISTICAL SIGNIFICANCE OF THE REGRESSION PARAMETERS
MODEL‐BUILDING AND VARIABLE SELECTION
AUTOMATED (OR STEPWISE) VARIABLE SELECTION
MANUAL VARIABLE SELECTION METHODS
INTERPRETING THE REGRESSION COEFFICIENTS
GOODNESS‐OF‐FIT
DUMMY (OR DESIGN) VARIABLES
TESTING THE ASSUMPTIONS OF THE LINEAR REGRESSION MODEL
EFFECT MODIFICATION AND INTERACTION
SUMMARY
ANALYSIS OF VARIANCE (ANOVA)
MULTIVARIATE STATISTICS
CHAPTER 35: Logistic Regression
THE LOGISTIC REGRESSION MODEL
VARIABLE SELECTION AND MODEL ESTIMATION
INTERPRETATION AND STATISTICAL SIGNIFICANCE OF THE REGRESSION COEFFICIENTS
DUMMY VARIABLES
GOODNESS‐OF‐FIT
EFFECT MODIFICATION – INTERACTION
MODEL DIAGNOSTICS
CHAPTER 36: Poisson Regression
PREAMBLE
POISSON REGRESSION
GOODNESS‐OF‐FIT
ZERO‐INFLATED POISSON REGRESSION
NEGATIVE BINOMIAL REGRESSION
ZERO‐INFLATED NEGATIVE BINOMIAL REGRESSION (ZNIB)
CHAPTER 37: Measuring Survival
THE KAPLAN–MEIER METHOD – MEDIAN SURVIVAL TIME
THE LOG‐RANK TEST
LOG‐RANK TEST FOR TREND
THE PROPORTIONAL HAZARDS (OR COX'S) REGRESSION MODEL
CHAPTER 38: Analysing Qualitative Data
PART VIII: Reading Between the Lines: How Authors use Text, Tables, and Pictures to Tell You the Story
CHAPTER 39: Results in Text and Tables
RAW RESULTS AND COOKED FINDINGS
INTERESTING FINDINGS
LEGENDS AND BRACKETS
DASHES
CHAPTER 40: Results in Pictures
WHY USE CHARTS AND FIGURES?
SHAPE OF DISTRIBUTIONS
CHAPTER 41: The Discussion and Conclusions
References
Index
End User License Agreement
List of Tables
Chapter 31
Table 31.1 A few of the more common statistical tests.
List of Illustrations
Chapter 1
Figure 1.1 Authors and research centres listed at the start of a research pa...
Figure 1.2 Paper written by multiple authors on behalf of several research g...
Figure 1.3 Acknowledgement of statistical, financial, and other support at t...
Chapter 2
Figure 2.1 An example of a structured Abstract – this one from a trial of tw...
Figure 2.2 An unstructured Abstract accompanied by a list of Keywords indica...
Figure 2.3 Explaining the background to a research study.
Figure 2.4 Introduction explaining the rationale for the study.
Figure 2.5 Ethical considerations in a study involving adults with a learnin...
Chapter 3
Figure 3.1 Statement of a study's main hypothesis.
Figure 3.2 A study with two hypotheses.
Figure 3.3 The (structured) Abstract of a qualitative study, starting with a...
Figure 3.4 The aim of the qualitative study.
Figure 3.5 New subgroup analysis in report of an RCT.
Chapter 4
Figure 4.1 A qualitative study examining views and experience of tests and i...
Figure 4.2 Grounded theory as the theoretical basis for a study examining pa...
Figure 4.3 A qualitative study employing ethnographic (participant observati...
Figure 4.4 A qualitative study involving focus groups and individual intervi...
Chapter 5
Figure 5.1 Types of research study design.
Figure 5.2 Extract from case series of bouncy castle injuries.
Figure 5.3 Extract from cross‐sectional study about bouncy castle injuries....
Figure 5.4 Prevalence of a clinical feature, determined in a cross‐sectional...
Figure 5.5 Extract from a cross‐sectional (incidence) study about frequency ...
Figure 5.6 Use of a survey method in a cross‐sectional study.
Chapter 6
Figure 6.1 Findings from an ecological study about smoking and domestic fire...
Figure 6.2 Extract from table of summary statistics from cross‐sectional stu...
Figure 6.3 A case–control study examining the relation between cannabis use ...
Figure 6.4 A retrospective cohort analytic study examining the relation betw...
Figure 6.5 Prospective cohort analytic study examining the relation between ...
Chapter 7
Figure 7.1 Summary of a randomized controlled trial investigating an interve...
Figure 7.2 Summary of a randomized controlled trial evaluating the effect of...
Figure 7.3 Extract from a randomized controlled trial, describing the use of...
Figure 7.4 A flow chart to illustrate Zelen's procedure for post‐randomizati...
Figure 7.5 Summary of a randomized controlled trial evaluating the effect of...
Figure 7.6 Extract from a pragmatic trial comparing face‐to‐face consultatio...
Figure 7.7 Abstract for a randomized controlled feasibility study examining ...
Figure 7.8 Extracts from the Methods section of a cluster randomised control...
Chapter 8
Figure 8.1 Concurrent use of qualitative and quantitative approaches to data...
Figure 8.2 A sequential approach to data collection is combined with a concu...
Figure 8.3 Results from qualitative and quantitative research studies can be...
Chapter 9
Figure 9.1 Description of a complex intervention.
Figure 9.2 Representation of the development of a complex intervention and i...
Figure 9.3 Use of a composite outcome measure in a systematic review.
Figure 9.4 Process evaluation in an RCT.
Chapter 10
Figure 10.1 Abstract describing the rationale and methods for a systematic r...
Figure 10.2 Cochrane Review of local treatments for skin warts showing that ...
Figure 10.3 Funnel plot used to check for publication bias in a meta‐analysi...
Figure 10.4 L'Abbé plot showing outcomes from 37 placebo‐controlled trials o...
Figure 10.5 Forest plot showing comparison of dietary saturated fatty acid r...
Chapter 11
Figure 11.1 Statement of review objective and search strategy in a study exp...
Figure 11.2 Example of synthesis of qualitative, quantitative, and mixed‐met...
Figure 11.3 Example of a qualitative review that used meta‐ethnography to ad...
Chapter 12
Figure 12.1 A national survey of deaths from suicide and their relation to t...
Figure 12.2 Reporting from a National Case Register of the rare disease, var...
Figure 12.3 Results from a population‐based study of self‐harm.
Figure 12.4 A service‐based study, undertaken in a specialist clinic, of com...
Chapter 13
Figure 13.1 A study which describes two random samples.
Figure 13.2 A systematic sample of patients attending clinics on particular ...
Figure 13.3 Sample size calculation in a clinical trial.
Chapter 14
Figure 14.1 Cohort study based upon already‐collected primary care data (CPR...
Figure 14.2 Data on self‐reported self‐harm from a national survey.
Figure 14.3 Outcome study based upon linking already‐collected datasets, wit...
Figure 14.4 Missing data in a birth cohort study used to estimate outcomes a...
Chapter 15
Figure 15.1 Sampling purposively – for diversity in an observational study a...
Figure 15.2 Sample characteristics chosen for maximum variation and sample s...
Figure 15.3 Clarifying the unit of analysis: not 15 participants, but 65 ‘di...
Figure 15.4 Example of a sampling matrix; in this case one which might have ...
Chapter 16
Figure 16.1 Inclusion and exclusion criteria applied to recruits into a tria...
Figure 16.2 Flow chart describing the participants in a randomized controlle...
Chapter 17
Figure 17.1 Comparison results from a clinical population with published pop...
Figure 17.2 A case control study comparing exposure to influenza vaccine in ...
Figure 17.3 Non‐random selection of intervention and control groups in a tri...
Chapter 18
Figure 18.1 Types of data.
Figure 18.2 Types of data used to describe the baseline characteristics of s...
Figure 18.3 Types of data used in a study comparing Foley catheter versus pr...
Figure 18.4 A positively skewed histogram showing the number (frequency) of ...
Figure 18.5 Normally distributed Jamaican birthweight data.
Chapter 19
Figure 19.1 Hypothetical normally distributed systolic blood pressure (b.p.)...
Figure 19.2 A small part of a baseline table describing the characteristics ...
Figure 19.3 Baseline characteristics in an acute back pain study.
Chapter 20
Figure 20.1 A study of patients' aggression, where the boundaries of the dat...
Figure 20.2 A study of neighbourhood influences on physical activity in olde...
Figure 20.3 Use of photos to elicit responses in a semi‐structured interview...
Figure 20.4 The unit of analysis may be a significant utterance, phrase, or ...
Chapter 21
Figure 21.1 Summary and part of a table from a randomized controlled trial, ...
Figure 21.2 Baseline or casemix measures from a clinical trial.
Figure 21.3 Blinding patients and staff so that measures made later can be m...
Figure 21.4 Blinding people who are extracting case note information to the ...
Figure 21.5 Dealing with missing values in a clinical trial.
Chapter 22
Figure 22.1 Martin et al. (2019),
Figure 22.2 Diversity as a characteristic of the participants in a study of ...
Chapter 23
Figure 23.1 Diagnostic plots showing: Panel (a) Sympathetic skin response (S...
Figure 23.2 Three ROC curves from a study to predict future diabetes when as...
Chapter 24
Figure 24.1 Extract from a paper reporting the development of a new scale to...
Figure 24.2 The scale properties of validity and reliability in a scale to m...
Figure 24.3 Extract from a study in which the authors examine the concurrent...
Figure 24.4 Demonstrating construct validity, from a paper on the use of SF‐...
Figure 24.5 Authors' comment on the correlations between scale scores from t...
Figure 24.6 Using
κ
to examine the test–retest (reliability) property o...
Chapter 25
Figure 25.1 Use of tailored topic guides in a study exploring experiences of...
Figure 25.2 Use of a predetermined set of questions (a topic guide) in a stu...
Chapter 26
Figure 26.1 Summary of a descriptive study setting out rates and proportions...
Chapter 27
Figure 27.1 Terminology in common use when describing the chance of tossing ...
Figure 27.2 A plausible result from two tosses of a coin.
Figure 27.3 Determining risk in a cohort study.
Figure 27.4 Determining odds (expressed as one odds relative to another) in ...
Chapter 28
Figure 28.1 Summary and extract from the Results section of a cohort analyti...
Figure 28.2 Summary and extract from the Results section of a case–control s...
Figure 28.3 Summary from a clinical trial where the main findings are set ou...
Chapter 29
Figure 29.1 Confidence intervals from a study comparing annual with twice‐ye...
Figure 29.2 95% confidence intervals for the mean difference in outcomes fro...
Figure 29.3 Four possible 95% confidence intervals for the difference betwee...
Figure 29.4 Comparison of outcomes in patients between a multidisciplinary i...
Figure 29.5 From Hartley et al. (2018),
Chapter 30
Figure 30.1 The adjusted odds ratios, stratified by income, for the prevalen...
Figure 30.2 Relative risks (risk ratios) from a large cohort study (47 000 m...
Chapter 31
Figure 31.1 A hypothetical 2 × 2 contingency table showing sample frequencie...
Figure 31.2 Use of the
χ
2
test in a comparison of additional catheter‐d...
Figure 31.3 Relative risks (risk ratios) for causes of poor outcome in patie...
Figure 31.4 Odds ratios and adjusted (for social class) odds ratios (and 95%...
Figure 31.5 Results of two‐sample
t
‐test to compare outcomes from two treatm...
Chapter 32
Figure 32.1 Scatterplot of hypothetical Glasgow Coma Scale scores given to 1...
Figure 32.2 Scatterplot of percentage mortality from aortic aneurysm in 16 h...
Figure 32.3 Scatterplot of the Patient‐Reported Outcomes Measurement Informa...
Figure 32.4 Pearson correlation coefficients (and
p
‐values) between adult mo...
Figure 32.5 Spearman correlation coefficients between breast size and a numb...
Chapter 33
Figure 33.1 Assessing agreement with Cohen's or Fleiss'
κ
.
Figure 33.2 Agreement about types of intercranial haemorrhage between three ...
Figure 33.3 Injury Severity Scores (ISS) given by two observers to 16 trauma...
Figure 33.4 Bland–Altman plots of Patient‐Reported Outcomes Measurement Info...
Chapter 34
Figure 34.1 The main components of a linear regression model.
Figure 34.2 Scatter plot of birthweight against cord serum EPA acid concentr...
Figure 34.3 Results of multiple linear regression from a prospective study t...
Figure 34.4 A simple coding design for the nominal variable
Ethnic group of
...
Chapter 35
Figure 35.1 Multivariable logistic regression model for the association betw...
Figure 35.2 Multivariate logistic regression analysis of effects of method o...
Chapter 36
Figure 36.1 Incident rate ratios (
IRR
s) and their 95% confidence intervals, ...
Figure 36.2 Risk ratios and 95% confidence intervals, for effect of adherenc...
Figure 36.3 Distribution of days of sickness absence among pregnant women in...
Figure 36.4 Results (simplified) from a zero‐inflated Poisson regression mod...
Figure 36.5 Incidence rate ratios (
IRR
s), from a cross‐sectional study into ...
Figure 36.6 Goodness‐of‐fit (as measured by log‐likelihood) of four regressi...
Chapter 37
Figure 37.1 Kaplan–Meier survival curves from a randomized trial of the effe...
Figure 37.2 Kaplan–Meier analysis of post‐progression survival (PPS) in the ...
Figure 37.3 Hazard ratios showing the association between several individual...
Chapter 38
Figure 38.1 Based on Facchin and Margola (2016).
Figure 38.2 Sample of three themes and corresponding meaning units. From a s...
Figure 38.3 Illness narratives among drug users living with HIV/AIDS.
Figure 38.4 A theory of reconciling incompatibilities.
Chapter 39
Figure 39.1 Extract from a results section to illustrate the interplay of te...
Figure 39.2 Extract from a results section to illustrate more complex interp...
Figure 39.3 Abstract from a clinical trial to illustrate the setting out of ...
Figure 39.4 Abstract from a case–control study to illustrate the setting out...
Figure 39.5 How the clarity of a table depends on its layout and the legend....
Figure 39.6 How the clarity of a table depends on its layout and the legend....
Figure 39.7 A table that successfully uses brackets, dashes and the word ‘to...
Chapter 40
Figure 40.1 Trial profile, showing who was potentially eligible and what hap...
Figure 40.2 Pie chart, showing categories of otology cases discussed at mult...
Figure 40.3 Bar chart comparing disease prevalence before and after fly cont...
Figure 40.4 Bar chart with error bars.
Figure 40.5 Line graph with error bars, showing mean sleep durations for var...
Figure 40.6 Stacked bar charts displaying a pattern over time.
Figure 40.7 Chart using horizontal marks (with error bars) to indicate relat...
Figure 40.8 Histograms shown in a hybrid figure (also showing a scatterplot)...
Figure 40.9 A comparison of two box plots (or box‐and‐whisker charts) accomp...
Figure 40.10 An
infographic
– carefully selected material from a clinical gu...
Chapter 41
Figure 41.1 A Discussion that starts with a résumé of the study findings bef...
Figure 41.2 Critical appraisal of a study's results.
Figure 41.3 A summary box which outlines a study's importance and main findi...
Guide
Cover
Table of Contents
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Understanding Clinical Papers
Fourth Edition
David Bowers
Leeds Institute of Health Sciences, School of Medicine, University of Leeds, UK
Allan House
Leeds Institute of Health Sciences, School of Medicine, University of Leeds, UK
David Owens
Leeds Institute of Health Sciences, School of Medicine, University of Leeds, UK
Bridgette Bewick
Leeds Institute of Health Sciences, School of Medicine, University of Leeds, UK
This edition first published 2021© 2021 John Wiley & Sons Ltd
Edition HistoryJohn Wiley & Sons (3e,2013)
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Library of Congress Cataloging‐in‐Publication Data
Names: Bowers, David, 1938– author. | House, Allan, author. | Owens, David, 1954– author. | Bewick, Bridgette, author.Title: Understanding clinical papers / David Bowers, Allan House, David Owens, Bridgette Bewick.Description: Fourth edition. | Hoboken, NJ : John Wiley & Sons, Inc., [2021] | Includes bibliographical references and index.Identifiers: LCCN 2020024728 (print) | LCCN 2020024729 (ebook) | ISBN 9781119573166 (paperback) | ISBN 9781119572855 (adobe pdf) | ISBN 9781119573142 (epub)Subjects: MESH: Medical Writing–standards | Journalism, Medical | ReadingClassification: LCC R119 (print) | LCC R119 (ebook) | NLM WZ 345 | DDC 808.06/661–dc23LC record available at https://lccn.loc.gov/2020024728LC ebook record available at https://lccn.loc.gov/2020024729
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Preface to the First Edition
Buy this book if you are a health‐care professional and you want some guidance in understanding the clinical research literature. It is designed to help you with reading research papers, by explaining their structure and the vocabulary they use. These essential first steps will make interpretation of clinical research that much easier for you. For example, the book will help with questions like:
Who were the authors, what is their standing, and can they be trusted?
What question or questions did they want to answer, and what was the clinical importance of doing so?
Who were the subjects in the study, how were they chosen, and were the methods used the most suitable?
How were the data collected? Was this the best approach?
What methods did the authors use to analyse the data, and were the methods employed appropriate?
What did they find? Were their conclusions consistent with their results?
Were there any shortcomings in the study? Do the authors acknowledge them?
What are the clinical implications of their results?
Does it all make sense?
This book is not an introduction to medical statistics, study design, epidemiology, systematic reviews, evidence‐based medicine, or critical appraisal, although we inevitably touch on all of these things (and more). Even so, if you are not already well versed in some of these fields, you should know a lot more by the time you get to the end.
We have concentrated on improving our readers’ understanding of quantitative research papers, and while qualitative papers contain several important elements which we have not been able to cover here, there are many other areas, particularly at the beginning and ends of papers, which readers of qualitative papers will find relevant to their needs.
Primarily, this book should be of interest to the following individuals:
Clinicians currently practising. This would include GPs, doctors in hospitals, in the community and in public health, nurses, midwives, health visitors, health educators and promoters, physiotherapists, dietitians, chiropodists, speech therapists, radiographers, pharmacists, and other clinically‐related specialists;
Clinicians of all types engaged in research activities: as part of their training; as a condition of their clinical duties; for postgraduate studies and courses; or for professional qualifications.
Those involved with the education and training of health professionals in colleges of health, in universities, and in in‐house training and research departments.
College, undergraduate, and postgraduate students in all medical and clinical disciplines which involve any element of research methods, medical statistics, epidemiology, critical appraisal, clinical effectiveness, evidence‐based medicine, and the like.
In addition, this book should appeal to individuals who although are not themselves clinicians but nonetheless find themselves in a clinical setting, and need some understanding of what the published clinical research in their area means. These people would include:
Clinical auditors and quality assessors
Clinical managers
Service managers, administrators, and planners
Those working in health authorities and in local government social and health departments
Purchasers of health provision.
People not actually employed in a clinical arena but who nonetheless have a professional or personal interest in the medical literature; for example, members of self‐help and support groups (e.g. migraine, stroke, diabetes, Alzheimer's, etc.); medical journalists; research‐fund‐providers; the educated, interested, lay public.
We have structured the contents of the book into a series of units whose sequence mirrors that of papers in most of the better‐quality journals. Thus we start with the preliminaries (title, authors, institution, journal type and status, and so on) and end with the epilogue (discussion, conclusions, and clinical implications). Throughout the book we have used a wide variety of extracts from recently published papers to illuminate our textual comments. In these we have focussed largely, but not solely, on examples of good practice in the hope that this will provide readers with some ‘how it should be done’ benchmarks. Any errors remain, of course, our own.
David Bowers, Allan House, and David OwensLeeds, 2000
Preface to the Second Edition
We received a great many favourable comments from those who used the first edition of this book – for which many thanks. Why then a second edition? The reason is the usual one in these circumstances – we think we can make the book even better. When we set out to write the first edition we had a good idea of what we wanted to include, but inevitably there was some jostling for the available space. In the end some things that we might have included had to be left on the cutting room floor. With this second edition we have now been able to include most of that excluded material. We have also taken the opportunity to respond to some helpful suggestions from readers. In addition to these changes we have now added a considerable amount of completely new material.
Thus this second edition includes a new chapter on measurement scales, and new or significantly expanded sections on the following: ethical considerations; abstracts; consent to randomization into trials; pragmatic and explanatory trials; intention‐to‐treat analysis; elements of probability; data transformation; non‐parametric tests; and systematic review, among others.
Moreover, there is a lot of new material in the chapters on regression – including more on variable selection and model building, and on Cox regression. A good deal of the material in the middle chapters of the book has been re‐arranged and improved to make for a better and more lucid flow (the treatment of dummy variables has been brought forward a chapter, for example).
We have all taken the opportunity to update many of the extracts from clinical papers which we use to illustrate the various ideas and procedures we describe, and also to revise much of the text in the book to improve clarity and understanding. We remain more than willing to receive any constructive comments and suggestions from readers. Otherwise we are confident that this is now an even better book than the original.
SOME NOTES ON STATISTICAL SOFTWARE
There are several statistical packages, of varying levels of sophistication and complexity, which can be used to analyse clinical data. Among the most widely used are the following:
CIA
(
Confidence Interval Analysis
)
EPI‐Info
Minitab
SPSS
(the
Statistics Package for the Social Sciences
)
STATA
S‐PLUS
In our opinion Minitab is the simplest and friendliest statistics package for the general user. SPSS is not quite as easy to use but handles cross‐tabulation of two variables rather better and has a wider range of the more sophisticated types of analyses. The choice of types of analysis and their outputs are perhaps easier to understand in Minitab than in SPSS. Each application has, of course, its limitations. To the best of our knowledge, Minitab does not do the McNemar test, nor does it have a clinically‐based survival analysis programme, nor allow for a direct calculation of Spearman's correlation coefficient (the data needs first to be ranked). On the other hand, SPSS does not allow a chi‐squared test to be done directly on a contingency table in the columns of the data sheet, nor does it provide confidence intervals for the difference between two proportions, or with the Mann–Whitney or Wilcoxon tests, all of which Minitab does. But as we have said, SPSS has a wider range of applications.
CIA, as its name implies, only does confidence interval calculations (but in this respect is very useful). EPI‐Info is a combination database and epidemiological tool, which originates from the Centre for Disease Control (CDC) in the USA. It has the advantage of being free (it can be downloaded from the internet along with a user's manual).
Most professional clinical statisticians will probably use either STATA or S‐PLUS; both more powerful and versatile than either Minitab or SPSS (but rather less easy to use).
We would not recommend Excel as a statistics programme since it is fundamentally a spreadsheet tool and thus has an extremely limited range of statistical functions – and in any case these are not set out in a way that is well‐suited to clinical research.
WRITING PAPERS FOR CLINICAL JOURNALS
Those of you who envisage writing up your research and submitting a paper to a clinical journal may find the following web site addresses (URLs) useful. They contain detailed advice and instructions to authors on what is required prior to submission: for example, how to contact the journal, what should be in the paper (order and content of sections), information on the required style, editorial policies and guidelines, and so on.
The first URL directs you towards a set of instructions to authors for each of over 3500 health and life‐sciences journals, worldwide. The second and third URLs relate specifically to the British Medical Journal, but contain a huge amount of detailed and splendidly informative material related to the preparation and submission of clinical papers, and collectively provide a set of desirable standards which anyone who is contemplating the submission of such a paper to the BMJ or any other journal should aspire to.
http://mulford.mco.edu/instr
http://bmj.bmjournals.com/advice
http://bmj.bmjjournals.com/advice/article_submissiom.shtml
David Bowers, Allan House, and David Owens School of Medicine, University of Leeds,Autumn, 2005
Preface to the Third Edition
It seems to us quite a long time since the second edition of Understanding Clinical Papers was published (in 2005). In the intervening years we have again (as we did for the previous editions) received from readers many favourable comments, as well as some useful suggestions. One suggestion that struck us as being eminently sensible, coinciding with our own thoughts, was that we should introduce material into the book which would help readers understand clinical papers with a qualitative design. Such papers are increasingly seen in the mainstream clinical journals (in addition of course to the specialist qualitative journals) and we feel that we should be providing readers with some help in making sense of this content.
The inclusion of five new chapters containing this qualitative material is the most important change in our book from the second edition. We are very pleased to have been able to welcome an experienced qualitative researcher as a co‐author, who has contributed this new material.
In addition, we have, not surprisingly, taken the opportunity to update many of the examples of clinical papers with which we illustrate the ideas contained throughout the book. At the same time, we have sharpened and clarified the text were we felt it was needed. We have added small amounts of new material here and there – where we felt that these additions, drawn from our familiarity with the evolving health research literature, would improve the book.
The book should appeal, as before, to doctors, nurses, health visitors, physiotherapists, radiographers, dietitians, speech therapists, health educators and promoters, podiatrists, and all of those other allied professionals (and students in each of these disciplines) – and to all of those involved in health research.
David Bowers, Bridgette Bewick, Allan House, and David OwensLeeds, 2013
Preface to the Fourth Edition
The third edition of this book was published in 2013: that's seven years ago! We are thankful that all of the previous editions were so well liked, and that we received so many favourable comments from readers. But seven years is a long time and we have felt for a while that the book needed refreshing to take into account readers’ suggestions and our own feelings about the potential for improvements. As a consequence, this fourth edition has been extensively revised and extended. The changes include four completely new chapters:
Studies of Complex Interventions.
Systematic Review of Qualitative Studies.
Research Using Already‐Collected Data. This new chapter will include material on missing data, confounding by indication, and other relevant topics.
Poisson Regression.
At the same time every other chapter has been extensively revised, and with much new material added, on, for example, the difference between clinical and statistical significance; reservations about the p‐value; the consequences of multiple testing and methods of correction; nested case–control studies; feasibility and pilot studies; cluster randomized trials; stratified random allocation; adaptive trial designs; sub‐group analysis; standardized guidelines for writing trials and reviews; and much more. In addition, we have improved the text throughout where we thought this would lead to better understanding. Importantly, we have also updated a great many of the examples from the literature.
As before, this edition of our book should appeal to all of those professionals involved in clinical work who wish to improve their understanding of the research literature.
David Bowers, Allan House, David Owens, and Bridgette BewickLeeds 2020
PART ISetting the Scene: Who Did What, and Why
CHAPTER 1Some Preliminaries
Before you start reading a paper, you could usefully ask one or two questions which help set the work in context:
Who wrote the paper?
In what sort of journal does the paper appear?
Who (and what) is acknowledged?
WHO WROTE THE PAPER?
Often, one person writes an article such as a review or an editorial. This is less common for papers describing the results of a research study. Because most research is a joint enterprise, papers describing research studies are usually published under the names of a number of people – the research team. From the list of authors, you can tell:
The range of expertise of the research team
. Professional backgrounds of the authors (and sometimes their level of seniority) are often included, with the address of each.
The research centre or centres involved in the study
. This is useful when you've been reading for a while and you know whose work to look out for – for whatever reason!
The principal researcher
. He or she is often named first, or sometimes identifiable as the only author whose full address and contact details are listed (called the corresponding author).
Figure 1.1 shows a typical example of a research project that required a collaborative effort.
Figure 1.1 Authors and research centres listed at the start of a research paper.
Source: Reprinted from Kuwawenaruwa et al. (2019) https://doi.org/10.1016/j.socscimed.2019.02.005
The list of authors may be quite long. The more people involved with a study, the less likely it is that one of them has a pre‐eminent position, so there may be no principal author. The authors may simply be listed in alphabetical order. They are listed at the top of research papers and (often) in guidance from the journal on how to cite the paper.
When a large study involving many sites is published, it may be that the work is written up by a small team, on behalf of the larger group. You may then find that there are some named authors, or only one or two, or (in very large studies) many authors are listed while the rest of the team is listed elsewhere – as in Figure 1.2. This type of multiple authorship is unavoidable if everybody is to get credit for participating in large studies, such as this project exploring the genetics of stroke.
Figure 1.2 Paper written by multiple authors on behalf of several research groups.
Source: From Pfeiffer et al. (2019).
An undesirable form of multiple authorship arises if members of an academic department attach their names to a paper when they had nothing to do with the study. This is sometimes called ‘gift authorship', although it isn't always given very freely. To try to stop this practice, many journals now expect each author to explain exactly what part he or she has played in the study. For this, and other useful information, you should turn to the Acknowledgements at the end of the paper.
IN WHAT SORT OF JOURNAL DOES THE PAPER APPEAR?
Not all journals are the same. Some are mainly aimed at members of a particular professional group, and therefore include political news, commentaries, and personal opinions. Others publish only research articles which have not appeared elsewhere, while some aim to mix these functions.
In some journals, the letters pages are designed to allow readers to express their opinions about articles which have appeared in previous issues. In others, the letters pages contain only descriptions of original studies.
What appears in a journal is decided by the Editor, nearly always with the help and advice of an Editorial Committee. The best journals also seek opinions from external referees who comment on papers sent to them and advise on suitability for publication. Because these referees are usually experts in the same field as the authors of the paper, this process is called ‘peer reviewing'. It isn't always easy to tell whether papers for a journal are peer‐reviewed, which is unfortunate because the peer‐reviewing process is the best means of establishing the quality of a journal's contents. You shouldn't trust the results of any data‐containing study if it appears in a journal which does not use the peer‐reviewing system.
Some journals produce supplements, which are published in addition to the usual regular issues of the main journal. They may be whole issues given over to a single theme or to describing presentations from a conference or symposium. Often they are produced (unlike the main journals) with the help of sponsorship from pharmaceutical companies. Papers in these supplements may not have been reviewed by the same process as papers in main journals and for that reason they tend not to be of as high quality.
Another way to judge the quality of a journal is to check its impact factor – a measure of the frequency with which papers in the journal are quoted by other researchers.1 The impact factor is only a rough guide because high‐quality journals that cover very specialized topics will inevitably have lower ratings than journals with a wider readership such as those describing cancer research or aimed at a general medical audience.
A frequently cited marker of journal quality is whether it is indexed – that is, whether it is registered on one of the major bibliographic databases such as PubMed. Being indexed isn't much of a marker of quality, but not being indexed should raise questions.
The rapid increase in the number of online journals raises other questions about quality. Many of these are open access – that is, you don't have to subscribe to be able to read them. They cover their costs by charging authors a publication fee – so there may be a financial incentive to publish, and the barrier of limited space is not the issue it is with paper journals.
To summarize – there are several pointers to journal quality: whether it uses peer review; its impact factor; whether it is indexed, and of course its reputation in the scientific community. But these are just that, pointers: there's no way to avoid developing some critical appraisal skills so you can judge for yourself the quality of an article regardless of the journal in which it appears.
WHO (AND WHAT) IS ACKNOWLEDGED?
It is tempting to treat the Acknowledgements at the end of a paper as being a bit like the credits after a film – only of interest to insiders. But they contain interesting information. For example, who is credited with work, but does not feature as an author? This has often been the fate of medical statisticians and others who offer specialist skills for the completion of one task in the study. If the study required special expertise – such as advanced statistics, economic analysis, supervision of therapists – then the necessary ‘expert' should be a member of the research team and acknowledged. If not, then either the expert was not a member of the team or somebody isn't getting credit where it is due. To ensure that co‐authorship is earned, and to guard against research fraud, the Acknowledgements in many journals now also contain a statement from each author about his or her individual contribution.
The Acknowledgements section from a multi‐author paper on HIV showed what additional help the research team received (Figure 1.3). It also contains an indication of the source of funding that supported the research. This is of interest because external funding may bring with it extra safeguards as to the rigour with which work was conducted. On the other hand, it may lead to a conflict of interest (for example if a pharmaceutical or other commercial company has funded research into one of its own products).
Figure 1.3 Acknowledgement of statistical, financial, and other support at the end of a paper.
Source: From Long et al. (2000).
Declaring a conflict of interest is not the same as admitting to a guilty secret. Its aim is to ensure that readers, when they are making their judgements about the study, are informed that there may be non‐scientific influences on the conduct or interpretation of a study.
Although it is usually put at the bottom of the title page rather than in the Acknowledgements, the other piece of information to look out for is advice from the journal on how to cite the paper you are reading. Typically this citation is presented in one of a number of formats that include title, authors, journal name, year, volume, and page numbers. Recently this approach has been supplemented by provision of a DOI (Digital Object Identifier) which is a standardized unique number given to many (but not all) articles, papers, and books, by some publishers, to identify a particular publication.
Note
1
You can check the impact factor of a journal at a number of websites, including, for example, the Thomson Reuters (formerly ISI)
Journal Citation Reports
http://isiknowledge.com/jcr
(accessed 19.02.19).
CHAPTER 2The Abstract and Introduction
At or near the beginning of most papers you will find an Abstract and an Introduction.
THE ABSTRACT
If the title of an article doesn't give you a clear enough idea of what it's about, then most papers reporting primary research data start with an Abstract – a brief summary of the whole paper that appears immediately below the title.
The purpose of this brief summary is to help the reader decide if they want to go on to read the paper in detail, by outlining the content of the research and its main findings. A good Abstract should help the reader decide – if this study has been well conducted, then is it one about which I would be interested enough to read further?
Some journals require authors to provide structured Abstracts – using headings equivalent to those that appear in the main text. A typical example is shown in Figure 2.1, from a study of a day treatment programme for patients with eating disorders. Some Abstracts are unstructured and simply give a brief narrative account of the accompanying paper as in Figure 2.2, from a qualitative study on the attitudes of young male offenders to fatherhood. The decision about which style of Abstract to use is determined not by the author, but by the journal.
Figure 2.1 An example of a structured Abstract – this one from a trial of two treatment programmes for patients with eating disorders.
Source: From Kong (2005) with permission from John Wiley & Sons.
Figure 2.2 An unstructured Abstract accompanied by a list of Keywords indicating the article's content.
Source: From Buston (2010), © 2010, with permission from Elsevier.
A list of Keywords may accompany the Abstract, if the journal requires it. Their purpose is to assist readers who are searching for articles on particular topics. For such a list the words may come from a standard source decided by the journal or they may be chosen by the authors themselves.
THE INTRODUCTION
After the Abstract comes an introductory section. Its aim is to provide some background information that makes it clear why the study described in the paper has been undertaken. The general topic area of the paper may be very familiar, but even so (perhaps especially so) the authors will probably give some summary of its importance, possibly along the lines of:
Is it clinically important?
Is it about a symptom that affects quality of life or causes major treatment difficulties?
Is there a public health importance?
Is it about an illness that represents a big burden for the community – in terms of chronic handicap, or costs to health or social services?
Is the interest theoretical?
Will further study help us to understand the causes of a condition or its consequences?
Figure 2.3 shows the Introduction to a study which examined the effect of two ways of presenting information to women who were making decisions about antenatal testing.
Figure 2.3 Explaining the background to a research study.
Source: From Graham et al. (2000), © 2000, with permission from BMJ Publishing Group Ltd.
These questions will normally be discussed by reference to existing evidence. The Introduction to a paper is not the place to look for a comprehensive literature review, and introductory sections in most papers are brief, but there are one or two pointers to help you decide if the evidence is being presented in a fair and unbiased way:
Is there reference to a systematic review (see
Chapters 10
and
11
)? Or if not, to a search strategy which the authors used to identify relevant evidence? For an example, see
Figure 2.4
, taken from a study of the association between birthweight and adult blood pressure.
Is the evidence mainly from the authors' own group or do the authors quote a range of evidence, even if it is not in support of their own views?
Figure 2.4 Introduction explaining the rationale for the study.
Source: Reproduced from: Shanahan et al. (2019).
Many clinical studies are carried out because the evidence is ambiguous or contradictory. Is there a dilemma which is posed by the evidence and is it clearly spelled out in the Introduction?
Generally speaking, the justification for a new study is that the existing evidence is unsatisfactory and a typical Introduction summarizes why, as in Figure 2.4 from a study on the use of social media to post about self‐harm. The commonest justifications for new research are that:
Different studies have come to different conclusions about the topic and it isn't possible to come to an answer without new work.
The evidence cannot be applied in the setting being considered by the authors. For example, good evidence may cease to be of value simply because it is old – trials showing the benefit of treatment may no longer be useful if a disorder changes so that its sensitivity to treatment changes. Similarly, evidence from one part of the world cannot always be applied freely elsewhere.
The evidence may be incomplete. For example, we may know that rates of smoking are increasing among young women but we don't know why.
The evidence may be of poor quality.
If these elements of the Introduction are well presented, then it should be clear what the paper is about and why the authors have chosen to conduct the work that they have. Armed with this background briefing, you can now move on to check the specific objectives of the authors' work (see Chapter 3).
