Errors in Medical Science Investigations

Foreword
Preface
Acknowledgments
Contents
Abbreviations
1: Basic Concepts
	1.1	 Introduction
	1.2	 Sources of Error in Biomedical Studies
		1.2.1	 Random or Chance
		1.2.2	 Bias
		1.2.3	 Confounder
	1.3	 The Structure and Nature of Clinical Research
		1.3.1	 Research Structure
			1.3.1.1	 Research Question
			1.3.1.2	 Applicability of the Study
			1.3.1.3	 Importance of the Subject
			1.3.1.4	 Study Design
			1.3.1.5	 Population under Study
			1.3.1.6	 Sampling Methods
		1.3.2	 Variables
			1.3.2.1	 Research Hypothesis
			1.3.2.2	 Characteristics of a Good Hypothesis
				Statistical Hypotheses
		1.3.3	 Calculation of Sample Size
			1.3.3.1	 The Minimal Clinically Significant Difference
			1.3.3.2	 Errors of Type I, Type II, and the Power of a Test
		1.3.4	 Response Variable Changes
			1.3.4.1	 P.Value
		1.3.5	 How to Statistically Analyze the Results
			1.3.5.1	 Nature of Research
	1.4	 Sources of Error in the Design and Execution of the Study
		1.4.1	 Study Design
		1.4.2	 Implementation of Study
	References
2: Research Design Strategies in Medical Sciences and their Potential Specific Errors
	2.1	 Introduction
	2.2	 Basic Issues in Choosing a Research Approach
	2.3	 Types of Biomedical Studies
		2.3.1	 Descriptive Studies
			2.3.1.1	 Correlation Studies
			2.3.1.2	 Normative Studies
			2.3.1.3	 Longitudinal Studies
			2.3.1.4	 Historical Studies
			2.3.1.5	 KAP Studies
			2.3.1.6	 Existing Data Analyses
			2.3.1.7	 Meta-Analysis
		2.3.2	 Analytical Studies
			2.3.2.1	 Observational Studies
			2.3.2.2	 Intervention Studies
	2.4	 Study Design with a Causal Approach
		2.4.1	 Ability to Move
		2.4.2	 Being Positive
		2.4.3	 The Different Levels of the Investigated Variable Are Well Defined
	2.5	 Clinical Investigations
		2.5.1	 Errors in Clinical Medicine
		2.5.2	 Common Mistakes in Clinical Medicine
	2.6	 Common Errors in Nursing
	2.7	 Qualitative Studies and their Potential Specific Errors
		2.7.1	 Phenomenological Studies
		2.7.2	 Ethnographic Studies
		2.7.3	 Grounded Theory Study
		2.7.4	 Historical Case Study
		2.7.5	 Action Research
	References
3: The Method of Designing Studies in Medical Sciences
	3.1	 Introduction
	3.2	 Methods of Descriptive Studies
		3.2.1	 Case Report or Case Study
		3.2.2	 Review of Cases (Case Series)
		3.2.3	 Correlation Studies (Ecological)
		3.2.4	 Ecological Pollution
		3.2.5	 Misclassification Bias
		3.2.6	 Data Quality
	3.3	 Observational Studies
		3.3.1	 Case-Control Studies
		3.3.2	 Selection of Cases in Case-Control Studies
			3.3.2.1	 Hospital Controls
			3.3.2.2	 Matching
			3.3.2.3	 Sampling Based on Healthy People in the Society
			3.3.2.4	 Using Multiple Control Groups
		3.3.3	 Cohort Studies
		3.3.4	 Prospective Cohort Studies
		3.3.5	 Advantages and Disadvantages of Cohort Studies
		3.3.6	 The Retrospective (Historical) Cohort Study
		3.3.7	 Selection of the Exposed Population
		3.3.8	 Selection of the Comparison Group (Nonexposed Population)
		3.3.9	 Data Sources
	3.4	 Types of Interventional Studies
		3.4.1	 Experimental Studies
		3.4.2	 Clinical Trial (Study or Research)
		3.4.3	 Selection of Patients
		3.4.4	 Determining the Entry and Exit Criteria
		3.4.5	 Measurement of Basic Variables
		3.4.6	 Evaluation of the Patient’s Response
		3.4.7	 Main Patient Response Criteria
		3.4.8	 Sub-Criteria and Side Effects
		3.4.9	 Randomization
		3.4.10	 Methods of Randomizing Treatments
			3.4.10.1	 Simple Random Method
			3.4.10.2	 Blinding
		3.4.11	 Standard Report of Clinical Trials
		3.4.12	 Types of Clinical Trial Studies
			3.4.12.1	 Trial with Independent Simultaneous Controls
			3.4.12.2	 Parallel Design
			3.4.12.3	 Factorial Study
			3.4.12.4	 Crossover Design
		3.4.13	 Evaluation of Trial Progress
		3.4.14	 Sample Size in Clinical Trials
		3.4.15	 Design with Consecutive Controls (Semi-Experimental Study)
		3.4.16	 Trial with External Controls
		3.4.17	 Studies without Controls
		3.4.18	 Nonrandomized Trial
		3.4.19	 Field Trials
		3.4.20	 Community Interventions and Cluster Randomized Trials
	3.5	 Studies Based on Existing Data
		3.5.1	 Secondary Data Analysis
		3.5.2	 Auxiliary Studies
		3.5.3	 Systematic Review and Meta-Analysis
	References
4: Precision, Validity, and Repeatability of Measurements and Diagnostic Tests
	4.1	 Types of Measurement Errors
		4.1.1	 Mistake
		4.1.2	 Error
		4.1.3	 Random Errors
		4.1.4	 Sampling Error
		4.1.5	 Bias
	4.2	 Scientific Reports of Measures
		4.2.1	 Validity and Precision in Clinical Studies
		4.2.2	 Precision
		4.2.3	 Evaluation of the Precision of the Results
		4.2.4	 Different Strategies to Increase the Validity
	4.3	 Validity
		4.3.1	 Evaluation of Validity of Results
		4.3.2	 Different Strategies to Increase the Validity of the Results
		4.3.3	 Internal Validity and External Validity
		4.3.4	 Choosing Appropriate Methods for Measuring Research Variables
	4.4	 Designing Studies that Examine the Repeatability of Tests
		4.4.1	 Designing Studies that Examine the Reliability of Tests
			4.4.1.1	 Analysis
			4.4.1.2	 Nominal Variables
			4.4.1.3	 Continuous Variables
	4.5	 Studies that Examine the Accuracy of Tests
		4.5.1	 Design
		4.5.2	 Analysis
	4.6	 Evaluation of the Diagnostic Test
		4.6.1	 ROC Curves
		4.6.2	 4-5-5 Correctness Ratios
		4.6.3	 Evaluation of Diagnostic Methods in Continuous Data
	4.7	 The Effect of Measurement Error in the Analysis of the Results
		4.7.1	 Weakening of the Effects in the Regression Model
		4.7.2	 Regression Around the Mean
	4.8	 Studies that Investigate the Effect of a Test in Diagnosing a Disease
		4.8.1	 Design
		4.8.2	 Analysis
	References
5: Problems Related to Etiology in Medical Sciences
	5.1	 Introduction
	5.2	 Spurious Association
	5.3	 The Difference in Association and Causation
	5.4	 Statistical Significance and Biological Relationship
	5.5	 Controlling the Effect of Chance in Relationships
	5.6	 Controlling the Effect of Bias in Relationships
		5.6.1	 Effect Size
	5.7	 Real Relationships Except for the Causal Relationship
		5.7.1	 Cause-Effect Relationship
		5.7.2	 Types of Relationship
		5.7.3	 One-to-One Causal Relationship
		5.7.4	 Multifactorial Relationship
		5.7.5	 Adjusting the Confounding
	5.8	 Criterion of Causality
		5.8.1	 Henle–Koch Criteria
		5.8.2	 Hill’s Criteria for Causality
			5.8.2.1	 Consistency
			5.8.2.2	 The Power of the Relationship
		5.8.3	 Criteria from MacMahon et al.
		5.8.4	 Criteria of Susser
		5.8.5	 Evans Criteria
		5.8.6	 Individual Casualty in Medical Expertise
		5.8.7	 Inferring the Cause-Effect Relationship Based on Evidence
	References
6: Evaluation of the Role of Intervening Variables in Analytical Studies
	6.1	 Introduction
	6.2	 Variables and Relationship Pattern
	6.3	 Simpson’s Paradox
		6.3.1	 How Is Simpson’s Paradox Controlled: Role of Confounding Factors
	6.4	 Confounding Variables
		6.4.1	 Features of the Confounding Factor
		6.4.2	 Criteria Necessary for a Variable to Be Confounding
		6.4.3	 Confounding Due to the Combination of Exposures
		6.4.4	 Substitute Confounder
		6.4.5	 Interaction
		6.4.6	 Interaction Effect
	References
7: Methods of Controlling Confounding in Medical Sciences Studies
	7.1	 Introduction
	7.2	 Methods of Controlling Confounding When Designing the Study
		7.2.1	 Randomization
		7.2.2	 Restriction
		7.2.3	 Matching
			7.2.3.1	 Advantages and Disadvantages of Matching
	7.3	 Methods of Restraining Confounding During Data Analysis
		7.3.1	 Assumptions
		7.3.2	 Standardization by the Direct Method
		7.3.3	 Indirect Standard Method
		7.3.4	 Mantel-Haenszel Method for Estimating Modified Indices
		7.3.5	 Mantel-Haenszel Method for Analyzing Matched Studies (McNemar Method)
		7.3.6	 Limitations of Adjustment Methods Based on the Stratification
		7.3.7	 Regression Model to Control Confounders at the Same Time
		7.3.8	 Propensity Score Analysis
	References
8: Data Analysis for Controlling Errors in Medical Science Investigations
	8.1	 Introduction
	8.2	 Designing a Written Program for Analysis
	8.3	 Data Quality Review
	8.4	 Descriptive Statistics
		8.4.1	 Mean
		8.4.2	 Variance
		8.4.3	 Standard Deviation
		8.4.4	 Normal Distribution
		8.4.5	 Standard Normal Distribution
		8.4.6	 Confidence Interval
		8.4.7	 Agreement Tables and Measurement of Exposure Effect
		8.4.8	 Comparing Two Ratios with Each Other
	8.5	 Modeling
		8.5.1	 Linear Regression
		8.5.2	 Poisson Regression
		8.5.3	 Logistic Regression
		8.5.4	 Analysis of Survival Data
		8.5.5	 Log-Rank Test
	8.6	 Choosing the Right Method for Data Analysis
	8.7	 Data Analysis Based on the Type of Study Design
		8.7.1	 Randomized Clinical Trials
		8.7.2	 Longitudinal and Crossover Studies
		8.7.3	 Case-Control Studies
	References
9: Identification and Control of Bias in Medical Sciences Investigations
	9.1	 Introduction
	9.2	 Why Is Research Bias a Problem?
		9.2.1	 Generalizability and Comparability
	9.3	 Information Bias
		9.3.1	 Recall Bias
		9.3.2	 Interviewer Bias
		9.3.3	 Hawthorne Effect (or Observer Effect)
		9.3.4	 Performance Bias
		9.3.5	 Regression to the Mean (RTM)
	9.4	 Selection Bias
		9.4.1	 Common Types of Selection Bias
			9.4.1.1	 Sampling or Ascertainment Bias
			9.4.1.2	 Attrition Bias
			9.4.1.3	 Self-Selection (or Volunteer) Bias
			9.4.1.4	 Survivorship Bias
			9.4.1.5	 Non-response Bias
			9.4.1.6	 Undercoverage Bias
			9.4.1.7	 John Henry Effect
	9.5	 Sampling Bias
		9.5.1	 Self-Selection Bias
		9.5.2	 Sampling Bias in Non-probability Samples
		9.5.3	 Pre-screening or Advertising Bias
		9.5.4	 Healthy User Bias
	9.6	 Response Bias
		9.6.1	 Common Types of Response Bias
			9.6.1.1	 Acquiescence Bias
			9.6.1.2	 Demand Characteristics
			9.6.1.3	 Social Desirability Bias
			9.6.1.4	 Courtesy Bias
			9.6.1.5	 Question-Order Bias
			9.6.1.6	 Extreme Responding
	9.7	 Cognitive Bias
		9.7.1	 Anchoring Bias
		9.7.2	 Framing Effect
		9.7.3	 Actor-Observer Bias
		9.7.4	 Availability Heuristic (or Availability Bias)
		9.7.5	 Confirmation Bias
		9.7.6	 Halo Effect
		9.7.7	 The Baader-Meinhof Phenomenon
		9.7.8	 Pygmalion Effect
	9.8	 Misclassification
	9.9	 Other Types of Biases
		9.9.1	 Referral to the Center Bias
		9.9.2	 Conformity Bias
		9.9.3	 Quo Bias
		9.9.4	 Sponsor Bias
		9.9.5	 Affinity Bias
		9.9.6	 Ceiling Effect
		9.9.7	 Recency Bias
		9.9.8	 Primacy Bias
		9.9.9	 Perception Bias
		9.9.10	 Outgroup Bias
		9.9.11	 Optimism Bias
		9.9.12	 Negativity Bias
		9.9.13	 Ingroup Bias
		9.9.14	 Implicit Bias
		9.9.15	 Hindsight Bias
		9.9.16	 Explicit Bias
		9.9.17	 Ideological Bias
		9.9.18	 Partisan Bias
		9.9.19	 Institutional Bias
		9.9.20	 Actor–Observer Bias
		9.9.21	 Perdana (Information)
		9.9.22	 Bias Accountability
		9.9.23	 Monitoring (or Diagnosis) of Patients
		9.9.24	 Researcher Bias
		9.9.25	 Bankbook Bias
		9.9.26	 Omitted Variable Bias
		9.9.27	 “I Am an Expert Bias” (Expertise Bias)
		9.9.28	 Monitoring Bias
		9.9.29	 Berkson Bias
		9.9.30	 Language Bias
		9.9.31	 Bias Caused by Time Delay
		9.9.32	 Lead-Time Bias
		9.9.33	 Time Lag Bias
		9.9.34	 Extraordinary Power Draw
		9.9.35	 The Bias of the Unpopular Journals
		9.9.36	 Famous (Prominent) Author Bias
		9.9.37	 Famous Institute Bias
		9.9.38	 Unknown Institute Bias
		9.9.39	 Small Trial Bias
		9.9.40	 Geographical Bias
		9.9.41	 Unconscious Bias
	9.10	 Common Biases Associated with Case-Control and Cohort Studies
		9.10.1	 Selection Bias
		9.10.2	 Observer Bias
	9.11	 Common Biases Associated with Cross-sectional Studies
		9.11.1	 The Bias of the Disease Period
		9.11.2	 The Bias of the Complementary Ratio of Prevalence
		9.11.3	 Precedence of Consequences Overexposure
	9.12	 Common Biases Associated with Clinical Trials
		9.12.1	 Other Biases in Clinical Trials
			9.12.1.1	 Placebo Effect
			9.12.1.2	 Tarmac bias
			9.12.1.3	 Bias Caused by Insufficient Reviews of Withdrawals and Proposal Rejections
			9.12.1.4	 Publication Bias
	9.13	 Common Biases Associated with Ecological Studies
	9.14	 Bias in Qualitative Investigations
	9.15	 How to Avoid Bias in Research
	References
10: Study Guide: Pilot, Pre-test, Quality Assurance, Quality Control, and Protocol Modifications
	10.1	 Introduction
	10.2	 The Importance of Pilot Studies
		10.2.1	 Problems of Guidance Studies
		10.2.2	 Pilot Study Report
		10.2.3	 Conclusion
		10.2.4	 Finalizing the Protocol
	10.3	 Quality Assurance
	10.4	 Quality Control
		10.4.1	 Missing Data
		10.4.2	 Incorrect Data with Low Accuracy
		10.4.3	 Misleading Data
		10.4.4	 Quality Control of Clinical Stages of Research
		10.4.5	 Special Methods for Drug Interventions
		10.4.6	 Coordination for Quality Control
		10.4.7	 Quality Control of Laboratory Processes
		10.4.8	 Data Quality Control
		10.4.9	 Quality Control in Multicenter Studies
	10.5	 Improvement of the Protocol When Conducting the Study
		10.5.1	 Minor Changes
		10.5.2	 Basic Improvement
	References
11: Errors in Medical Procedures
	11.1	 Introduction
	11.2	 Some Definitions in Errors in Medical Procedures Setting
	11.3	 Magnitude of the Problem of Errors in Medical Procedures
	11.4	 Perceptions of Medical Errors by Physicians
	11.5	 Healthcare Providers Workload and Medical Errors
	11.6	 Common Errors in Clinical Procedures
		11.6.1	 Infection Control Errors and Failure to Follow Proper Hand Hygiene Protocols
	11.7	 Administering the Wrong Medication or Dosage
	11.8	 Miscommunication Between Healthcare Providers
		11.8.1	 Language Barrier Errors in Clinical Practice
	11.9	 Inadequate Patient Identification
	11.10	 Inadequate Monitoring of Patients
	11.11	 Inadequate Informed Consent
	11.12	 Inadequate Training of Healthcare Providers
	11.13	 Equipment Errors and Malfunction
	11.14	 Diagnostic Errors
	11.15	 Common Surgical Errors
	11.16	 Causes of Medical Errors
	11.17	 Strategies for Preventing Medical Errors
	References
Appendix A: Setting Up the Proposal and Providing Research Resources
	Introduction
	Regulation of Proposals
	Elements of a Proposal
		The Starting Stage
		Executive Departments and Institutional Review Board
		Sections of Objectives and Review of Sources
		Scientific Methods Section
	Indicators of a Good Proposal
Appendix B: Questionnaire Design and Interview Guidance
	Introduction
	Designing a Questionnaire and Data Collection Tool
		Designing Open and Closed Questions
		Continuous Scale Spectrum (VAS)
	Elements of a Proposal
		Questionnaire Structure
			Sentences
			Clarity
			Simplicity
			Timing
			Two-Sided Questions
			Contractual Assumptions
			Scoring to Measure Qualitative Variables
		Creating New Scales and Questionnaires
		Stages of Questionnaire Preparation in the Study
			Preparing a List of Variables
			Collection of Existing Questionnaires
			Draft Preparation
			Pre-test
			Sequence of Questions
		Response Rate
		Advantages and Disadvantages of the Questionnaire
			Advantages
			Disadvantages
	Interview
		Regular Interview
		Semi-regular Interview
		Irregular Interview
		Advantages and Disadvantages of Regular Interview
		Advantages and Disadvantages of Semi-regular and Irregular Interviews
			Reliability of Research Tools
			Validity of Research Tools
Appendix C: Control of Random Errors: Issues Related to Sample Size Calculation
	Introduction
	The Basis for Calculating the Sample Size
	Types of Errors in Statistical Tests
	Relationships for Calculating the Sample Size
	Determining the Sample Size for Unbalanced Groups
	Adjusting the Sample Size for Missing Cases from Follow-Ups, Confounders, and Interactions
	Real Examples
		Descriptive Studies
			A Descriptive Study to Determine the Prevalence
			Descriptive Study to Determine the Incidence
		Randomized Clinical Trial
			The Sample Size for Comparing Two Ratios
			The Sample Size for Comparing Two Mean
		Case-Control Studies
		Discussion and Conclusion
References