Quality of life : the assessment, analysis, and reporting of patient-reported outcomes
The assessment of patient reported outcomes and health-related quality of life continue to be rapidly evolving areas of research and this new edition reflects the development within the field from an emerging subject to one that is an essential part of the assessment of clinical trials and other cli...
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| Hlavní autoři: | , |
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| Médium: | E-kniha Kniha |
| Jazyk: | angličtina |
| Vydáno: |
Chichester, West Sussex
Wiley Blackwell
2016
John Wiley & Sons, Incorporated Wiley-Blackwell |
| Vydání: | 3 |
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| ISBN: | 9781444337952, 1444337955 |
| On-line přístup: | Získat plný text |
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- Intro -- Quality of Life -- Contents -- Preface to the third edition -- Preface to the second edition -- Preface to the first edition -- List of abbreviations -- PART 1 Developing and Validating Instruments for Assessing Quality of Life and Patient‐Reported Outcomes -- 1 Introduction -- 1.1 Patient‐reported outcomes -- 1.2 What is a patient‐reported outcome? -- 1.3 What is quality of life ? -- 1.4 Historical development -- 1.5 Why measure quality of life? -- Clinical trials of treatment with curative intent -- Clinical trials of treatment with palliative intent -- Improving symptom relief, care or rehabilitation -- Facilitating communication with patients -- Patient preferences -- Late problems of psychosocial adaptation -- Medical decision‐making -- 1.6 Which clinical trials should assess QoL? -- 1.7 How to measure quality of life -- Ask the patient -- 1.8 Instruments -- Generic instruments -- Disease‐specific instruments -- Instruments for specific aspects of QoL -- 1.9 Computer‐adaptive instruments -- 1.10 Conclusions -- 2 Principles of measurement scales -- 2.1 Introduction -- 2.2 Scales and items -- 2.3 Constructs and latent variables -- 2.4 Single global questions versus multi‐item scales -- Global questions -- Multi‐item scales -- 2.5 Single‐item versus multi‐item scales -- Reliability -- Precision -- Validity -- Scope -- 2.6 Effect indicators and causal indicators -- Reflective (effect) indicators -- Causal indicators -- Composite indicators -- Formative indicators -- Distinguishing causal from reflective indicators -- Impact of formative models -- Re‐specifying the latent variable -- 2.7 Psychometrics, factor analysis and item response theory -- Parallel items -- Factor models -- Factor analysis seems to work - even with formative indicators! -- Item response theory -- 2.8 Psychometric versus clinimetric scales
- Intraclass correlation coefficient (ICC) -- Test-retest reliability -- Inter-rater reliability -- Equivalent-forms reliability -- 4.7 Sensitivity and responsiveness -- Sensitivity -- Responsiveness -- 4.8 Conclusions -- 4.9 Further reading -- 5 Multi‐item scales -- 5.1 Introduction -- 5.2 Significance tests -- 5.3 Correlations -- Range of variables -- Significance tests -- Confidence intervals -- Significance test to compare two correlations -- Intraclass correlation -- Rank correlation -- Polychoric correlation -- Correction for overlap -- 5.4 Construct validity -- Convergent and discriminant validity -- Multitrait-multimethod analysis -- Multitrait‐scaling analyses -- Factor analysis, dimensionality and multitrait scaling -- 5.5 Cronbach's α and internal consistency -- Alpha revisited -- Modern trends -- 5.6 Validation or alteration? -- 5.7 Implications for formative or causal items -- 5.8 Conclusions -- 6 Factor analysis and structural equation modelling -- 6.1 Introduction -- 6.2 Correlation patterns -- 6.3 Path diagrams -- 6.4 Factor analysis -- 6.5 Factor analysis of the HADS questionnaire -- Eigenvalues and explained variance -- Factor loadings -- Rotation -- 6.6 Uses of factor analysis -- Historical perspective -- Scale validation -- Scale development -- Scale scoring -- 6.7 Applying factor analysis: Choices and decisions -- Sample size -- Number of factors -- Method of estimation -- Orthogonal rotation -- Oblique axes -- 6.8 Assumptions for factor analysis -- Distributional assumptions -- Categorical data -- Normality -- Does the violation of assumptions matter? -- 6.9 Factor analysis in QoL research -- 6.10 Limitations of correlation-based analysis -- 6.11 Formative or causal models -- 6.12 Confirmatory factor analysis and structural equation modelling -- 6.13 Chi-square goodness-of-fit test -- 6.14 Approximate goodness-of-fit indices
- Proportions - paired
- 2.9 Sufficient causes, necessary causes and scoring items -- 2.10 Discriminative, evaluative and predictive instruments -- 2.11 Measuring quality of life: reflective, causal and composite indicators? -- 2.12 Further reading -- 2.13 Conclusions -- 3 Developing a questionnaire -- 3.1 Introduction -- 3.2 General issues -- 3.3 Defining the target population -- 3.4 Phases of development -- Phase 1: Generation of QoL issues -- Phase 2: Construction of the item list -- Phase 3: Pre‐testing -- Phase 4: Field‐testing -- 3.5 Phase 1: Generation of issues -- Literature search -- Specialist interviews -- Patient interviews -- 3.6 Qualitative methods -- Interviews -- Focus groups -- Sample selection -- 3.7 Sample sizes -- Saturation -- 3.8 Phase 2: Developing items -- Ordered categorical or Likert summated scales -- Visual analogue scales -- Guttman scales -- 3.9 Multi‐item scales -- 3.10 Wording of questions -- 3.11 Face and content validity of the proposed questionnaire -- 3.12 Phase 3: Pre‐testing the questionnaire -- Representative sample -- Missing data -- 3.13 Cognitive interviewing -- 3.14 Translation -- 3.15 Phase 4: Field‐testing -- Missing values -- Missing forms -- Distribution of item responses -- Item reduction -- Cultural and subgroup differences -- 3.16 Conclusions -- 3.17 Further reading -- 4 Scores and measurements: validity, reliability, sensitivity -- 4.1 Introduction -- 4.2 Content validity -- Item coverage and relevance -- Face validity -- 4.3 Criterion validity -- Concurrent validity -- Predictive validity -- 4.4 Construct validity -- Known-groups validation -- Convergent validity -- Discriminant validity -- Multitrait-multimethod analysis -- 4.5 Repeated assessments and change over time -- 4.6 Reliability -- Binary data: proportion of agreement -- Binary data: κ -- Ordered categorical data: weighted κ -- Pearson's correlation coefficient
- 6.15 Comparative fit of models -- 6.16 Difficulty-factors -- 6.17 Bifactor analysis -- 6.18 Do formative or causal relationships matter? -- 6.19 Conclusions -- 6.20 Further reading, and software -- 7 Item response theory and differential item functioning -- 7.1 Introduction -- 7.2 Item characteristic curves -- Item difficulty -- Item discrimination -- 7.3 Logistic models -- Logistic regression -- 7.4 Polytomous item response theory models -- 7.5 Applying logistic IRT models -- Choosing IRT models -- Fitting the model -- Graphical methods for goodness of fit -- Goodness-of-fit indices -- Sample size -- 7.6 Assumptions of IRT models -- Monotonicity -- Unidimensionality -- Local independence -- 7.7 Fitting item response theory models: Tips -- 7.8 Test design and validation -- 7.9 IRT versus traditional and Guttman scales -- 7.10 Differential item functioning -- Mantel-Haenszel test -- IRT and logistic regression for DIF analyses -- Logistic regression -- 7.11 Sample size for DIF analyses -- 7.12 Quantifying differential item functioning -- 7.13 Exploring differential item functioning: Tips -- 7.14 Conclusions -- 7.15 Further reading, and software -- 8 Item banks, item linking and computer-adaptive tests -- 8.1 Introduction -- 8.2 Item bank -- 8.3 Item evaluation, reduction and calibration -- 8.4 Item linking and test equating -- Item linking -- Test equating -- 8.5 Test information -- 8.6 Computer-adaptive testing -- 8.7 Stopping rules and simulations -- 8.8 Computer-adaptive testing software -- 8.9 CATs for PROs -- Multidimensional CAT -- DIF and CAT -- 8.10 Computer-assisted tests -- 8.11 Short-form tests -- 8.12 Conclusions -- 8.13 Further reading -- PART 2 Assessing, Analysing and Reporting Patient-Reported Outcomes and the Quality of Life of Patients -- 9 Choosing and scoring questionnaires -- 9.1 Introduction
- Clinical trials or clinical practice? -- 9.2 Finding instruments -- Special populations -- 9.3 Generic versus specific -- 9.4 Content and presentation -- 9.5 Choice of instrument -- Criteria for choosing -- Adding ad hoc items -- 9.6 Scoring multi-item scales -- Summated scales -- Weighted sum-scores -- Norming systems: Z -scores and T -scores -- IRT-based scoring -- Health-economics scores -- 9.7 Conclusions -- 9.8 Further reading -- 10 Clinical trials -- 10.1 Introduction -- 10.2 Basic design issues -- Type of study -- Organisational issues -- Mode of administration -- Protocol -- Sample size -- Defining multiple endpoints -- 10.3 Compliance -- Measuring compliance -- Causes and consequences of poor compliance -- Improving compliance -- Acceptable levels of compliance -- Recording reasons for non‐compliance -- 10.4 Administering a quality‐of‐life assessment -- The patient -- The medical team -- 10.5 Recommendations for writing protocols -- Rationale for including QoL assessment -- Emphasising good compliance -- Identify contact persons -- Written guidelines for administering QoL questionnaires -- Checking forms before the patient leaves -- Baseline assessment -- Assessment during therapy -- Follow‐up (post‐treatment) assessment -- Specifying when to complete questionnaires -- Help and proxy assessment -- Will QoL forms influence therapy? -- Patient information leaflets -- Randomisation checklist -- Clinical follow‐up forms -- 10.6 Standard operating procedures -- 10.7 Summary and checklist -- 10.8 Further reading -- 11 Sample sizes -- 11.1 Introduction -- 11.2 Significance tests, p‐values and power -- 11.3 Estimating sample size -- Choosing the type 1 error -- Choosing the power -- Choosing the target effect size -- Sample size formulae -- 11.4 Comparing two groups -- Means - unpaired -- Means - paired -- Proportions - unpaired