Types of Research Designs RS Mehta

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Types of Research Designs RS Mehta

  1. 1. TYPES OF RESEARCH & RESEARCH DESIGNS 1Dr. R S Mehta, MSND, BPKIHS
  2. 2. Types of Study Design: • There is no best type of study design • The context, assumptions, paradigms and perspectives decide the type of research methodology Dr. R S Mehta, MSND, BPKIHS 2
  3. 3. How to Choose a Research Design 3 • Does it adequately test the hypothesis? • Does it identify & control extraneous factors? • Are results generalizable? • Can the hypothesis be rejected or retained via statistical means? • Is the design efficient in using available resources? Dr. R S Mehta, MSND, BPKIHS
  4. 4. Selecting a Research Design 1. Level of knowledge 2. Nature of the research phenomenon 3. Nature of the research purpose 4. Ethical considerations 5. Feasibility 6. Validity and availability of data 7. Precision 8. Cost 4Dr. R S Mehta, MSND, BPKIHS
  5. 5. 5 1. Define the problem ( Characteristics) 2. Specify the objectives (Hypothesis) 3. Select design or type of study 4. Select study population 5. Collect data 6. Analyze data 7. Determine conclusions Anatomy of Research Dr. R S Mehta, MSND, BPKIHS
  6. 6. Dr. R S Mehta, MSND, BPKIHS 6 Select design or type of study
  7. 7. Types of Research From the view point of Application Pure Research Applied Research Objectives Exploratory Research Descriptive Research Correlation Research Explanatory Research Type of Information Sought Quantitative Research Qualitative Research 7Dr. R S Mehta, MSND, BPKIHS
  8. 8. 8 TYPE OF STUDIES Observational 1. Correlational study 2. Case reports and case series 3. Cross sectional survey 4. Case-control study 5. Cohort study Experimental 1. Community trials 2. Clinical trials – individualsDr. R S Mehta, MSND, BPKIHS
  9. 9. Study Designs 9 1. Descriptive Studies 2. Cross-Sectional Studies 3. Cohort Study 4. Case Control 5. Randomized Controlled Trials 6. Survey Research Dr. R S Mehta, MSND, BPKIHS
  10. 10. Critical Thinking Decision Path: Non-experimental Design Choice 10Dr. R S Mehta, MSND, BPKIHS
  11. 11. Health Sciences and Nursing Research Non-interventional Interventional Explorative Descriptive Analytical Pre-experimental Quasi- experimental True-Experiment - Case study - Cross-sectional - Longitudinal - Etc. - Cross- sectional - Case control - Cohort - Etc - CRD - RBD - FD - etc 11Note: CRD-complete random design, RBD-random block design, FD- factorial designDr. R S Mehta, MSND, BPKIHS
  12. 12. 4 Types of Research • Basic research • Applied research • Action research • Evaluation research 12Dr. R S Mehta, MSND, BPKIHS
  13. 13. Basic Research • Also known as fundamental research (sometimes pure research) is research carried out to increase understanding of fundamental principles. • Many times the end results have no direct or immediate commercial benefits • Basic research can be thought of as arising out of curiosity. • However, in the long term it is the basis for many commercial products and applied research. • Basic research is mainly carried out by universities 13Dr. R S Mehta, MSND, BPKIHS
  14. 14. Applied Research • Concern with addressing problem of the world as they are perceived by participants, organization or group of people • Action oriented and aims to assess, describe, document or inform people concerned about the phenomenon under investigation • Findings are intended to have immediate and practical value • In the field of education, policy, evaluation and contract are all examples of applied research 14Dr. R S Mehta, MSND, BPKIHS
  15. 15. Action Research Action Research is simply a form of self-reflective enquiry undertaken by participants in social situations in order to improve the rationality and justice of their own practices, their understanding of these practices, and the situations in which these practices are carried out. Wilf Carr and Stephen Kemmis (1986) 15Dr. R S Mehta, MSND, BPKIHS
  16. 16. Evaluation research • Major concern is practical application • Tends to be viewed as an isolated case study though the methodologies may be transferable • Rooted in values and politics • Is immediately prescriptive based upon logic and experience • Reports are written for implementers, users and other interested people • The extent of dissemination is controlled by sponsor 16Dr. R S Mehta, MSND, BPKIHS
  17. 17. RESEARCH DESIGNS QUANTITATIVE QUALITATIVE • Experimental study • Quasi-experimental • Survey study • Correlational study • Ethnography • Case study • Historical study 17Dr. R S Mehta, MSND, BPKIHS
  18. 18. Types of Study Design: Details Dr. R S Mehta, MSND, BPKIHS 18
  19. 19. 1. Descriptive Studies: Person, Place and Time 19Dr. R S Mehta, MSND, BPKIHS
  20. 20. Descriptive Epidemiology • Includes activities related to characterizing the distribution of diseases within a population 20 • Concerns activities related to identifying possible causes for the occurrence of diseases Dr. R S Mehta, MSND, BPKIHS
  21. 21. Descriptive Epidemiology 21 PERSON PLACE TIME Think of this as the standard dimensions used to track the occurrence of a disease. Dr. R S Mehta, MSND, BPKIHS
  22. 22. Descriptive Research Design: –Describe facts –Discover new facts –Not invent new theory and methods –Largest effort given on data collection –It answers questions: satisfy curiosity –Solve problems 22Dr. R S Mehta, MSND, BPKIHS
  23. 23. 2. Cross-Sectional Studies 23Dr. R S Mehta, MSND, BPKIHS
  24. 24. Features of C-S Studies 24 • Snapshot in time –e.g. - cholesterol measurement and ECG measured at same time • Determines prevalence at a point in time • Therefore, C-S is a prevalence study Dr. R S Mehta, MSND, BPKIHS
  25. 25. Advantages of C-S Studies 25 • Short term • Fewer resources required • Less statistical analysis • More easily controlled • Design less complex Dr. R S Mehta, MSND, BPKIHS
  26. 26. Advantages of C-S Studies (Cont.) 26 • Provide relationship between attributes of disease and characteristics of various groups, e.g. elderly group • Data is useful for planning of health services and medical programs Dr. R S Mehta, MSND, BPKIHS
  27. 27. Disadvantages of C-S Studies 27 • Represent only those who are surveyed • Identify prevalence, not incidence necessarily –excludes cases that died before study was done • Show association with survival - not risk of development Dr. R S Mehta, MSND, BPKIHS
  28. 28. Disadvantages of C-S Studies (cont.) 28 • People who are ill may not show up for survey -*Healthy Person Effect • Often, not possible to establish temporal relationship between exposure and onset –e.g. does high cholesterol precede CHD? • Not too effective if disease levels are low, as difficult to establish a causal relationship Dr. R S Mehta, MSND, BPKIHS
  29. 29. Design of a C-S Study 29Dr. R S Mehta, MSND, BPKIHS
  30. 30. Design of a C-S study (Cont.) 30Dr. R S Mehta, MSND, BPKIHS
  31. 31. Cross-Sectional Study 31 ineligible physically active & CHD physically active & no CHD physically inactive & CHD physically inactive & no CHD participation no participation eligible Farmers Dr. R S Mehta, MSND, BPKIHS
  32. 32. Cross-Sectional Study 32 Disease Exposure yes no total yes a b a + b no c d c + d Dr. R S Mehta, MSND, BPKIHS
  33. 33. 3. Cohort Study 33Dr. R S Mehta, MSND, BPKIHS
  34. 34. 34 Group by common characteristics Start with a group of subjects who lack a positive history of the outcome of interest yet are at risk for it (cohort).  Think of going from cause to effect. The exposure of interest is determined for each member of the cohort and the group is followed to document incidence in the exposed and non-exposed members. Cohort Studies Dr. R S Mehta, MSND, BPKIHS
  35. 35. When is a cohort study warranted? 35 • When good evidence suggests an association of a disease with a certain exposure or exposures. Dr. R S Mehta, MSND, BPKIHS
  36. 36. 36 Changes and variation in the disease or health status of a study population as the study group moves through time. “Generation effect” Cohort Effect Dr. R S Mehta, MSND, BPKIHS
  37. 37. 37 • Prospective (concurrent) • Retrospective (historical) • Restricted (restricted exposures) Types of Cohort Studies Dr. R S Mehta, MSND, BPKIHS
  38. 38. 38 Types of Cohort Studies Prospective – cohort characterized by determination of exposure levels (exposed vs. not exposed) at baseline (present) and followed for occurrence of disease in future  Groups move through time as they age Retrospective - makes use of historical data to determine exposure level at some baseline in the past and then determine subsequent disease status in the present. Restricted - limited exposure, narrow behavior (e.g. military) Dr. R S Mehta, MSND, BPKIHS
  39. 39. Prospective Studies 39 • Also called – longitudinal – concurrent – incidence studies • Looking into the future • Example: Study of coronary heart disease (CHD) Dr. R S Mehta, MSND, BPKIHS
  40. 40. 40 The essential characteristic in the design of cohort studies is the comparison of outcome in an exposed group and a nonexposed group (or a group with a certain characteristic and a group w/o that characteristic).  A study population can be chosen by selecting groups for inclusion in the study on the basis of whether or not they were exposed Design of a Cohort Experiment Dr. R S Mehta, MSND, BPKIHS
  41. 41. 41 There are two basic ways to generate cohort groups.  Select a cohort (defined population) BEFORE any of its members become exposed or before the exposures are identified.  Select a cohort on the basis of some factor (e.g., where they live) and take histories (e.g., blood tests) on the entire population to separate into exposed and non- exposed groups. Regardless of which selection approach is used, we are comparing exposed and non-exposed persons. Selection of Cohort Groups Dr. R S Mehta, MSND, BPKIHS
  42. 42. 42 Design of a Cohort Experiment Dr. R S Mehta, MSND, BPKIHS
  43. 43. 43 Design of a Prospective Cohort Experiment Major problem with a prospective cohort design is that the cohort must be followed up for a long period of time. Dr. R S Mehta, MSND, BPKIHS
  44. 44. Data Gathering 44 • Person - to - person • Drop off questionnaire • Mailed to people • Telephone interview • Newsletter or magazine Dr. R S Mehta, MSND, BPKIHS
  45. 45. Potential Biases in Cohort Studies 45 • Information bias • Bias in estimation of the outcome • Bias from non-response • Bias from losses to follow-up • Analytic bias Dr. R S Mehta, MSND, BPKIHS
  46. 46. Advantages of Prospective Cohort Studies 46 • Large sample sizes • Certain diseases or risk factors targeted • Can be used to prove cause-effect • Assess magnitude of risk • Baseline of rates • Number and proportion of cases that can be prevented Dr. R S Mehta, MSND, BPKIHS
  47. 47. Advantages of Prospective Studies (cont’d) 47 • Completeness and accuracy • Opportunity to avoid condition being studied • Quality of data is high • Considers seasonal and other variations over a long period • Tracks effects of aging process Dr. R S Mehta, MSND, BPKIHS
  48. 48. Disadvantages of Prospective Cohort Studies 48 • Large study populations required – not easy to find subjects • Expensive • Unpredictable variables • Results not extrapolated to general population • Study results are limited • Time consuming/results are delayed • Requires rigid design and conditions Dr. R S Mehta, MSND, BPKIHS
  49. 49. Disadvantages of Prospective Studies (cont’d) 49 • Subjects lost over time (dropouts) • Costs are high • Logistically demanding • Maintaining quality, validity, accuracy and reliability can be a problem Dr. R S Mehta, MSND, BPKIHS
  50. 50. Cohort/ Longitudinal Studies 50 Design Sample Of Population High Exposure Medium Exposure Low Exposure No Exposure Outcome Outcome Outcome Outcome Dr. R S Mehta, MSND, BPKIHS
  51. 51. 51 Prospective Cohort Design Dr. R S Mehta, MSND, BPKIHS
  52. 52. 52 Retrospective Cohort Design Dr. R S Mehta, MSND, BPKIHS
  53. 53. COHORT STUDY 53 Source Population Cases (= Exposed, =Unexposed) (□= Exposed, ■=Unexposed)    ■ □  □ ■   ■ ■ □   ■ □ ■ □  □ ■ □  ■ □   Dr. R S Mehta, MSND, BPKIHS
  54. 54. 4. Case Control Study 54Dr. R S Mehta, MSND, BPKIHS
  55. 55. CASE-CONTROL STUDIES SOME KEY POINTS 55 • Frequently used study design • Participants selected on the basis of whether or not they are DISEASED (remember in a cohort study participants are selected based on exposure status) • Those who are diseased are called CASES. • Those who are not diseased are called CONTROLS. Dr. R S Mehta, MSND, BPKIHS
  56. 56. Case-Control Study 56 ineligible exposed unexposed bad outcom e (cases) exposed unexposed good outcom e (controls) participation no participation eligible Source Population Dr. R S Mehta, MSND, BPKIHS
  57. 57. 57 Case-Control Design Dr. R S Mehta, MSND, BPKIHS
  58. 58. Case-Control Design 58 Subjects With Outcome of Interest Design Appropriate Control Group Without Outcome Of Interest Measure factors Compare factors Dr. R S Mehta, MSND, BPKIHS
  59. 59. Case-Control Studies 59 dcNo baYes Present Outcome Absent Exposure to intervention or causal factor Direction Of Sampling Results Dr. R S Mehta, MSND, BPKIHS
  60. 60. Case- Control Design: Advantages 60 1. Valuable for studying rare conditions. 2. Short duration 3. Relatively inexpensive 4. Relatively smaller sample needed 5. Yields odd ratio (usually a good approximation of relative risk) Dr. R S Mehta, MSND, BPKIHS
  61. 61. Case- Control Studies: Disadvantages 61 1. Limited to one outcome variable 2. Potential bias from selection of cases and controls 3. Does not establish sequence of events 4. Potential bias in measuring exposure 5. Potential survivor bias 6. Does not yield absolute risk estimates. Dr. R S Mehta, MSND, BPKIHS
  62. 62. PAST PRESENT Exposure recall Cases & Controls Selected Example: lung cancer cases and non-cancerous controls recall past exposure to cigarette smoke Because participants are selected on the basis of disease, exposures for ALL PARTICIPANTS are obtained RETROSPECTIVELY………….. 62Dr. R S Mehta, MSND, BPKIHS
  63. 63. SELECTION OF CASES 63 • Decide on a specific case definition based on a medically diagnosed condition. When diagnosis relies on subjective assessment case definition will be less precise. • Must consider what criteria will confirm the case definition: Lung cancer confirmed by biopsy Osteoporosis confirmed by bone density measurements Studying mild forms of a disease results in largest possible case group but may include non-cases (misclassification) Studying severe forms of a disease decrease the probability of misclassification Dr. R S Mehta, MSND, BPKIHS
  64. 64. SELECTION OF CONTROLS 64 • Controls should be representative of the referent population from which cases are selected (i.e. comparable) – Controls should have the potential to become cases; Controls should also be candidates for having the disease of interest Dr. R S Mehta, MSND, BPKIHS
  65. 65. SELECTION OF CONTROLS (2) 65 • Different Types of Controls……… –Population controls • Randomly selected individuals from the population like RDD (random digit dialing) –Neighborhood controls • Individuals that live in the same neighborhoods as casesDr. R S Mehta, MSND, BPKIHS
  66. 66. SELECTION OF CONTROLS (3) 66 –Friends controls • best friends of cases • spouses or siblings of cases –Hospital controls • Individuals at the same hospital with cases Dr. R S Mehta, MSND, BPKIHS
  67. 67. SELECTION OF CONTROLS (4) 67 • The investigator can elect to use more than one TYPE of control for each case……. When there is no ONE group similar enough to cases. EXAMPLE: A particular leukemia case may have both a neighborhood control (similar to case in terms of environment) and a sibling control (similar to case in terms of genetic background). Dr. R S Mehta, MSND, BPKIHS
  68. 68. Cases & Controls 68 • For each CASE in the study, a control is selected • How many controls should be selected per case? – 1:1 is usual – Increasing the ratio of controls to cases increases the precision and efficiency of the analysis – It also increases the cost to undertake the study Dr. R S Mehta, MSND, BPKIHS
  69. 69. MATCHING 69 • CHARACTERISTICS OFTEN USED –age –gender –body mass index (weight / height2) –smoking status –marital status Dr. R S Mehta, MSND, BPKIHS
  70. 70. MATCHING (2) 70 • GROUP MATCHING • Based on proportions • Idea is to select a control group with a certain characteristic identical to cases in the same proportion as it appeared in cases. Example: If 25% of cases in your study smoke you would select a control population that included 25% smokers. Dr. R S Mehta, MSND, BPKIHS
  71. 71. GROUP MATCHING EXAMPLE CASE POPULATION CONTROL POPULATION Smokers Non-Smokers Smokers Non-Smokers 71Dr. R S Mehta, MSND, BPKIHS
  72. 72. MATCHING (3) 72 2) INDIVIDUAL MATCHING (matched pairs) • For every individual case a control is selected who is identical to the case on certain characteristics. Example: If your first case is a 25 year-old women who smokes then you would find a control who is 25, female and a smoker. So you are matching on age, gender, and smoking status. Dr. R S Mehta, MSND, BPKIHS
  73. 73. MATCHED PAIRS EXAMPLE 73 CASE CONTROL CASE CONTROL Dr. R S Mehta, MSND, BPKIHS
  74. 74. POTENTIAL PROBLEMS WITH MATCHING 74 • It will be difficult to find controls if too many variables are selected for matching. • Variables used for matching can not be studied as exposures or confounders. • OVERMATCHING – when variables related to disease are inadvertently matched upon. Dr. R S Mehta, MSND, BPKIHS
  75. 75. Classic 2 x 2 Table for a Case-Control Study if in the POPULATION 75 Disease No Disease Exposure A B No Exposure C D Odds Ratio = A/C = AD B/D BC Dr. R S Mehta, MSND, BPKIHS
  76. 76. Example: Hypothetical data 76 Cases Controls Exposed 141 133 Unexposed 1250 4867 Total 1391 5000 ODDS RATIO = 141 * 4867 = 4.13 133 * 1250Dr. R S Mehta, MSND, BPKIHS
  77. 77. Interpretation of the Odds Ratio… 77 If: OR = 1 then exposure is NOT related to disease OR>1 then exposure is POSITIVELY related to disease OR<1 then exposure NEGATIVELY related to disease Dr. R S Mehta, MSND, BPKIHS
  78. 78. Interpretation: 78 The odds that those with the outcome had the exposure is 4.13 times greater than those who do not have the outcome Dr. R S Mehta, MSND, BPKIHS
  79. 79. Strengths: 79 1. Quick and inexpensive 2. Well-suited to the evaluation of outcomes with long latent periods 3. Optimal for the evaluation of rare diseases 4. Can examine multiple etiologic factors for a single disease Dr. R S Mehta, MSND, BPKIHS
  80. 80. Limitations: 80 1. Cannot directly compute incidence rates of disease 2. Temporal relationship between exposure and disease may be difficult to establish 3. Prone to bias 4. Insufficient to evaluate rate exposure Dr. R S Mehta, MSND, BPKIHS
  81. 81. TYPES OF RESEARCH & RESEARCH DESIGNS 81Dr. R S Mehta, MSND, BPKIHS
  82. 82. Types of Study Design: • There is no best type of study design • The context, assumptions, paradigms and perspectives decide the type of research methodology Dr. R S Mehta, MSND, BPKIHS 82
  83. 83. Health Sciences and Nursing Research Non-interventional Interventional Explorative Descriptive Analytical Pre-experimental Quasi- experimental True-Experiment - Case study - Cross-sectional - Longitudinal - Etc. - Cross- sectional - Case control - Cohort - Etc - CRD - RBD - FD - etc 83Note: CRD-complete random design, RBD-random block design, FD- factorial designDr. R S Mehta, MSND, BPKIHS
  84. 84. 5. Randomized Controlled Trials 84Dr. R S Mehta, MSND, BPKIHS
  85. 85. Randomized Controlled Trials 85 • Similar groups of individuals from same source population are allocated at random to receive or not to receive an intervention, then observed for occurrence of outcome(s). DESIGN Subjects with condition of Interest Experimental Group Control Outcome Outcome Dr. R S Mehta, MSND, BPKIHS
  86. 86. 86 A Factorial RCT for Two Studies for the Price of One Dr. R S Mehta, MSND, BPKIHS
  87. 87. RCT – the “gold standard” of research designs. They thus provide the most convincing evidence of relationship between exposure and effect. Example: • trials of hormone replacement therapy in menopausal women 87Dr. R S Mehta, MSND, BPKIHS
  88. 88. Randomized Controlled Trial : Advantages 88 1. Comparability due to randomization and same effect of known and unknown confounders gets eliminated 2. Experiments provide strong evidence of cause and effect. 3. Allows standardization of eligibility criteria, maneuver and outcome assessment. 4. Allows use of statistical methods with few inbuilt assumptions. Dr. R S Mehta, MSND, BPKIHS
  89. 89. Randomized Controlled Trial : Disadvantages 89 1. May be expensive in terms of time, money and people. 2. Many research questions are not suitable due to ethics, likely co-operation or rarity of outcome. 3. To a greater or lesser extent RCT tends to be an artificial situation. Dr. R S Mehta, MSND, BPKIHS
  90. 90. Suitable Study Design 90 Issues Study Design Diagnosis Cross sectional Therapy RCT (Non-RCT) Prognosis Prospective cohort Cause Cohort Case control Description Case Series Cross Sectional However, more than one study design can be used to answer any given question of causal association Dr. R S Mehta, MSND, BPKIHS
  91. 91. 6. Survey Research 91Dr. R S Mehta, MSND, BPKIHS
  92. 92. Survey research • Survey research is often used to assess thoughts, opinions, and feelings • Psychologists and sociologists often use survey research to analyze behavior, while it is also used to meet the more pragmatic needs of the media, such as, in evaluating political candidates, public health officials, professional organizations, and advertising and marketing directors. • A survey consists of a predetermined set of questions that is given to a sample. • Every day you find in TV and Radio? Dr. R S Mehta, MSND, BPKIHS 92
  93. 93. Survey design: • Evaluative • Comparative • Short-term • Long-term • Longitudinal • Cross-sectional • Cross-cultural Dr. R S Mehta, MSND, BPKIHS 93
  94. 94. Questions to Ask Before Doing Survey Research 94 • Do you have a clear hypothesis? • Do your questions focus on that hypothesis? • Will participants answers provide accurate answers to your questions? • To whom will your results apply? Dr. R S Mehta, MSND, BPKIHS
  95. 95. Planning a Survey 96 • Deciding on a research question • Choosing the format of your questions • Choosing the format of your interview--if you use an interview • Editing your questions • Sequencing your questions • Refining your survey instrument • Choosing a sampling strategy Dr. R S Mehta, MSND, BPKIHS
  96. 96. Editing Questions: Nine Mistakes to Avoid 97 1. Avoid leading questions 2. Avoid questions that invite the social desirability bias 3. Avoid double- barreled questions 4. Avoid long questions 5. Avoid negations 6. Avoid irrelevant questions 7. Avoid poorly worded response options 8. Avoid big words 9. Avoid ambiguous words & phrases Dr. R S Mehta, MSND, BPKIHS
  97. 97. Survey researchers should carefully construct the order of questions in a questionnaire Dr. R S Mehta, MSND, BPKIHS 98
  98. 98. 7. Case Study • Explores in depth a program, event, activity, process, or one or more individuals • Bounded (separated out for research) by time, place and activity • Researcher collects detailed information using a variety of data collection procedures over a sustained period of time (Stake & Creswell) • A method of learning about a complex instance based on a comprehensive understanding of that instance obtained by extensive description and analysis of that instance taken as a whole 99Dr. R S Mehta, MSND, BPKIHS
  99. 99. Case Study/Reports • Detailed presentation of a single case or handful of cases • Generally report a new or unique finding • e.g. previous undescribed disease • e.g. unexpected link between diseases • e.g. unexpected new therapeutic effect • e.g. adverse events 100Dr. R S Mehta, MSND, BPKIHS
  100. 100. Case Series • Experience of a group of patients with a similar diagnosis • Assesses prevalent disease • Cases may be identified from a single or multiple sources • Generally report on new/unique condition • May be only realistic design for rare disorders 101Dr. R S Mehta, MSND, BPKIHS
  101. 101. Case Series • Advantages • Useful for hypothesis generation • Informative for very rare disease with few established risk factors • Characterizes averages for disorder • Disadvantages • Cannot study cause and effect relationships • Cannot assess disease frequency 102Dr. R S Mehta, MSND, BPKIHS
  102. 102. 8. Historical Study • Focuses primarily on the past • Persuing documents of the period • Examining relics (left over) • Interviewing individuals who lived during that time • Reconstruct what happened during that time as completely as possible • Systematic collection and evaluation of data to describe, explain, and thereby understand actions or events that occurred in the past • No manipulation or control of variables 103Dr. R S Mehta, MSND, BPKIHS
  103. 103. 104 9. Experimental Research Designs Dr. R S Mehta, MSND, BPKIHS
  104. 104. Aim: • The aim of experimental research is to investigate the possible cause and effect relationship by manipulating one independent variable to influence the other variable in the experimental group and by controlling the other relevant variables and measuring the effects of the manipulation by some statistical means. Dr. R S Mehta, MSND, BPKIHS 105
  105. 105. 106 Experimental Research Tries to Establish Cause and Effect • Selection of a good theoretical framework • Application of appropriate experimental design • Use of correct statistical model and analysis • Proper selection and control of independent variables • Appropriate selection and measurement of dependent variables • Correct interpretation of results 106 Dr. R S Mehta, MSND, BPKIHS
  106. 106. Characteristics or Features of Experimental Design 1. Manipulation 2. Control 3. Randomization Dr. R S Mehta, MSND, BPKIHS 107
  107. 107. Experimental Design • Advantages – Best establishes cause-and-effect relationships • Disadvantages – Artificiality of experiments – Feasibility – Unethical 108Dr. R S Mehta, MSND, BPKIHS
  108. 108. Types of Experimental Designs • True-Experimental (Simple) • Quasi-Experimental • Pre-Experimental 109Dr. R S Mehta, MSND, BPKIHS
  109. 109. True, Qusi, & Pre- Experimental Study Randomization, Control and Manipulation • True exp.: All 3: R C M • Quasi exp.: M + R or C • Pre exp.: M, no R & no C 110Dr. R S Mehta, MSND, BPKIHS
  110. 110. Steps in Experimental Research • State the research problem • Determine if experimental methods apply • Specify the independent variable(s) • Specify the dependent variable(s) • State the tentative hypotheses • Determine measures to be used • Pause to consider potential success • Identify intervening (extraneous) variables • Formal statement of research hypotheses • Design the experiment • Final estimate of potential success • Conduct the study as planned • Analyze the collected data • Prepare a research report 111Dr. R S Mehta, MSND, BPKIHS
  111. 111. 10. Ex Post Facto Study • Variable of interest is not subject to direct manipulation but must be chosen after the fact. E.g., Define two groups of people according to a certain characteristic (e.g., history of trauma) and measure how they respond in terms of anxiety to a certain stimulus (e.g., watching violent film). • Limitation – self-selection bias, cohort effects. 112Dr. R S Mehta, MSND, BPKIHS
  112. 112. 11. Meta Analysis 113 • Combining the results from many studies dealing with the same topic. • Statistically combines results of existing research to estimate overall size of relation between variables • Helps in • Developing theory • Identifying research needs, • Establishing validity • Can replace large-scale research studies • Better than literature reviews Dr. R S Mehta, MSND, BPKIHS
  113. 113. • It is similar to a simple cross-sectional study, in which the subjects are individual studies rather than individual people. • A review of literature is a meta-analytic review only if it includes quantitative estimation of the magnitude of the effect and its uncertainty (confidence limits). Dr. R S Mehta, MSND, BPKIHS 114
  114. 114. Meta analysis Quantitativeapproach for systematically combiningresults of previous research to arrive at conclusionsabout the body of research. 115Dr. R S Mehta, MSND, BPKIHS
  115. 115. • Quantitative : numbers • Systematic : methodical • combining: putting together • previous research: what's already done • conclusions: new knowledge 116Dr. R S Mehta, MSND, BPKIHS
  116. 116. Steps for Conducting A Meta-Analysis A. Data Sources B. Study Selection C. Data Abstraction D. Statistical Analysis 117Dr. R S Mehta, MSND, BPKIHS
  117. 117. Dr. R S Mehta, MSND, BPKIHS Statistical concepts The impact of fish oil consumption on Cardio-vascular diseases 118
  118. 118. Dr. R S Mehta, MSND, BPKIHS Forest plot 119
  119. 119. Advantages of Meta-Analysis 1. Study question specific & narrow 2. Data collection comprehensive & specific 3. Study selection based on uniformly applied criteria 4. Data synthesis quantitative 120Dr. R S Mehta, MSND, BPKIHS
  120. 120. 12. Qualitative Research 121Dr. R S Mehta, MSND, BPKIHS
  121. 121. Choice of Colours • 1. What colour would you like the most? 122Dr. R S Mehta, MSND, BPKIHS
  122. 122. 2.What do you associate this colour with? Good luck love Confidence Truthfulness Lively Danger … 123Dr. R S Mehta, MSND, BPKIHS
  123. 123. 3. What is the source of this knowledge? –Own Idea –Own Belief –Own observation –Own experiences –Cultural and Traditional –Books & articles – etc 124Dr. R S Mehta, MSND, BPKIHS
  124. 124. • Not every thing can be quantified. • Some valuable ideas, opinions, perceptions, experiences, behaviours, qualities can be described only in words • These subjective things are shared between people, but the meanings may be distorted in the process of communication and recording. 125Dr. R S Mehta, MSND, BPKIHS
  125. 125. • Although subjective, these aspects often add richness and depth • The art of the doctor and the experience of being human are aspects that need a qualitative approach to investigate/research properly. 126Dr. R S Mehta, MSND, BPKIHS
  126. 126. • Qualitative Research - investigation in which the researcher attempts to understand some larger reality by examining it in a holistic way or by examining components of that reality within their contextual setting. 127Dr. R S Mehta, MSND, BPKIHS
  127. 127. Qualitative Research • „Qualitative Research…involves finding out what people think, and how they feel - or at any rate, what they say they think and how they say they feel. This kind of information is subjective. It involves feelings and impressions, rather than numbers‟ - Bellenger, Bernhardt and Goldstucker, Qualitative Research in Marketing, American Marketing Association 128Dr. R S Mehta, MSND, BPKIHS
  128. 128. Universal Specific Explanatory Descriptive Subjective Objective Universal ------------------------------ Specific Objective ------------------------------ Subjective Explanatory ---------------------------- Descriptive 129Dr. R S Mehta, MSND, BPKIHS
  129. 129. Characteristics of Qualitative Research • Purpose is understanding • Oriented toward discovery • Uses subjective data • Extracts meaning from data • Interprets results in context • Focus is holistic 130Dr. R S Mehta, MSND, BPKIHS
  130. 130. Organizational Structures (Types) Historical Analysis Ethnography Phenomenology Life History, Chronology, Historiography Case Study 131Dr. R S Mehta, MSND, BPKIHS
  131. 131. Ethnographic Design • Examining a group of individuals in the setting where they live and work, and in developing a portrait of how they interact • Describing, analyzing and interpreting a group‟s shared patterns of behavior, beliefs and language that develop over time • Provides a detailed picture of the group, drawing on various sources of information • Describes the group within its settings, explores themes or issues that develop over time as the group interacts • Data analysis emphasize on description and explanation rather than quantification and statistical analysis (Atkinson & Hammersley, 1994) 132Dr. R S Mehta, MSND, BPKIHS
  132. 132. Phenomenology • Definition: “Phenomenology is an approach which attempts to understand the hidden meanings and the essence of an experience together with how participants make sense of these.” (Grbich 2007, p. 84). • Strengths: Phenomenology is used to explore, describe, document rich details of people’s experiences, especially changes in feelings and experiences over time. Dr. R S Mehta, MSND, BPKIHS 133
  133. 133. phenomenology I. Objective of the study: To understand personal experience and feelings II. Methodology choice: Phenomenology III. Data Collection Methods: Observation & individual Interview IV. Data Analysis Methods: Phenomenological Analysis 134Dr. R S Mehta, MSND, BPKIHS
  134. 134. Qualitative Data Collection Techniques • In depth Interviewing • Focus Groups • Participant Observations • Ethnographic Studies • Projective Techniques 135Dr. R S Mehta, MSND, BPKIHS
  135. 135. Analysis Qualitative Data: An Approach • Categorisation • Unitising data • Recognising relationships and developing the categories you are using to facilitate this • Developing and testing hypotheses to reach conclusion 136Dr. R S Mehta, MSND, BPKIHS
  136. 136. Tools for helping the Analytical Process Summaries • Should contain the key points that emerge from undertaking the specific activity Self Memos • Allow you to make a record of the ideas which occur to you about any aspect of your research, as you think of them Researcher Diary 137Dr. R S Mehta, MSND, BPKIHS
  137. 137. Advantages of Qualitative Research  In-depth Examination of Phenomena (Phenomenological Study)  Uses subjective information  Not limited to rigidly definable variables  Examine complex questions that can be impossible with quantitative methods  Deal with value-laden questions  Explore new areas of research  Build new theories 138Dr. R S Mehta, MSND, BPKIHS
  138. 138. Disadvantages of Qualitative Research  Subjectivity leads to procedural problems  Replicability is very difficult  Researcher bias is built in and unavoidable  In-depth, comprehensive approach to data gathering limits scope  Labor intensive, expensive  Not understood well by “classical” researchers 139Dr. R S Mehta, MSND, BPKIHS
  139. 139. Review: Health Sciences and Nursing Research Non-interventional Interventional Explorative Descriptive Analytical Pre-experimental Quasi- experimental True-Experiment - Case study - Cross-sectional - Longitudinal - Etc. - Cross- sectional - Case control - Cohort - Etc - CRD - RBD - FD - etc 140Note: CRD-complete random design, RBD-random block design, FD- factorial designDr. R S Mehta, MSND, BPKIHS
  140. 140. Cont‟d 141Dr. R S Mehta, MSND, BPKIHS
  141. 141. Relative strength of various study designs (based on level of evidence for a cause & effect relationship) 142 Strength Design Strong Clinical trial Cohort study Case control study Cross sectional Case series Weak Case report Dr. R S Mehta, MSND, BPKIHS
  142. 142. Websites, Search Engine, and address of Journals • www.pubmed.com • www.google.com • www.yahoo.com • www.msn.com • www.rn.com • www.who.int (WHO website) • www.randamization.com • www.tnaionline.org (TNAI Journal) • www.hellis.org (NHRC library site) • www.kumj.com.np • www.nhrc.org.np • www.uicc.org (cancer website) • www.unaids.org (HIV/AIDS website) • www.ncasc.org.np (HIV/AIDS website) • www.healthinternetwork.org (HINARI: needs password) • www.blackwell-synergy.com (need passwords) • www.doaj.org (free online journal) Dr. R S Mehta, MSND, BPKIHS 143
  143. 143. Some Popular Resource Sites for Nurses • www.delicious.com • www.connotea.org • www.scribd.ocm • www.authorstream • www.zotero.org • www.scratch.mit.edu • www.myebook.com • www.forvo.com 144Dr. R S Mehta, MSND, BPKIHS
  144. 144. “The beautiful thing about learning is that nobody can take it away from you.” --BB King Thank-You 145 Dr. R S Mehta, MSND, BPKIHS
  145. 145. Review: Health Sciences and Nursing Research Non-interventional Interventional Explorative Descriptive Analytical Pre-experimental Quasi- experimental True-Experiment - Case study - Cross-sectional - Longitudinal - Etc. - Cross- sectional - Case control - Cohort - Etc - CRD - RBD - FD - etc 146Note: CRD-complete random design, RBD-random block design, FD- factorial designDr. R S Mehta, MSND, BPKIHS
  146. 146. Cont‟d 147Dr. R S Mehta, MSND, BPKIHS
  147. 147. Relative strength of various study designs (based on level of evidence for a cause & effect relationship) 148 Strength Design Strong Clinical trial Cohort study Case control study Cross sectional Case series Weak Case report Dr. R S Mehta, MSND, BPKIHS
  148. 148. Websites, Search Engine, and address of Journals • www.pubmed.com • www.google.com • www.yahoo.com • www.msn.com • www.rn.com • www.who.int (WHO website) • www.randamization.com • www.tnaionline.org (TNAI Journal) • www.hellis.org (NHRC library site) • www.kumj.com.np • www.nhrc.org.np • www.uicc.org (cancer website) • www.unaids.org (HIV/AIDS website) • www.ncasc.org.np (HIV/AIDS website) • www.healthinternetwork.org (HINARI: needs password) • www.blackwell-synergy.com (need passwords) • www.doaj.org (free online journal) Dr. R S Mehta, MSND, BPKIHS 149
  149. 149. Some Popular Resource Sites for Nurses • www.delicious.com • www.connotea.org • www.scribd.ocm • www.authorstream • www.zotero.org • www.scratch.mit.edu • www.myebook.com • www.forvo.com 150Dr. R S Mehta, MSND, BPKIHS
  150. 150. “The beautiful thing about learning is that nobody can take it away from you.” --BB King Thank-You 151 Dr. R S Mehta, MSND, BPKIHS
  151. 151. Developmental Research Designs Longitudinal • Powerful (within subject) • Time consuming • Attrition • Testing effect Cross Sectional • Less time consuming • Cohorts problem 152Dr. R S Mehta, MSND, BPKIHS
  152. 152. Research Designs/Approaches Type Purpose Time frame Degree of control Examples Experi- mental Test for cause/ effect relationships current High Comparing two types of treatments for anxiety. Quasi- experi- mental Test for cause/ effect relationships without full control Current Moderate to high 153Dr. R S Mehta, MSND, BPKIHS
  153. 153. Research Designs/Approaches Type Purpose Time frame Degree of control Examples Non- experime ntal - corre- lational Examine relationship between two variables Current (cross- sectional) or past Low to medium Relationship between studying style and grade point average. Ex post facto Examine the effect of past event on current functioning. Past & current Low to medium Relationship between history of child abuse & depression. 154Dr. R S Mehta, MSND, BPKIHS
  154. 154. Research Designs/Approaches Type Purpose Time frame Degree of control Examples Non- experime ntal - corre- lational Examine relat. betw. 2 var. where 1 is measured later. Future - predictive Low to moderate Relat. betw. history of depression & development of cancer. Cohort- sequen- tial Examine change in a var. over time in overlapping groups. Future Low to moderate How mother- child negativity changed over adolescence. 155Dr. R S Mehta, MSND, BPKIHS
  155. 155. Research Designs/Approaches Type Purpose Time frame Degree of control Examples Survey Assess opinions or characteristics that exist at a given time. Current None or low Voting preferences before an election. Quali- tative Discover potential relationships; descriptive. Past or current None or Low People’s experiences of quitting smoking. 156Dr. R S Mehta, MSND, BPKIHS
  156. 156. Dr. R S Mehta, MSND, BPKIHS 157
  157. 157. Experimental Designs Details 158Dr. R S Mehta, MSND, BPKIHS
  158. 158. Symbolism for Diagramming Experimental Designs X = exposure of a group to an experimental treatment O = observation or measurement of the dependent varia If multiple observations or measurements are taken, subscripts indicate temporal order – I.e., O1, O2, etc. = random assignment of test units; individuals selected as subjects for the experiment are randomly assigned to the experimental groups R 159Dr. R S Mehta, MSND, BPKIHS
  159. 159. Pre-Experimental Designs • Do not adequately control for the problems associated with loss of external or internal validity • Cannot be classified as true experiments • Often used in exploratory research • Three Examples of Pre-Experimental Designs – One-Shot Design – One-Group Pretest-Posttest Design – Static Group Design 160Dr. R S Mehta, MSND, BPKIHS
  160. 160. One-Shot Design • A.K.A. – after-only design • A single measure is recorded after the treatment is administered • Study lacks any comparison or control of extraneous influences • No measure of test units not exposed to the experimental treatment • May be the only viable choice in taste tests • Diagrammed as: X O1 161Dr. R S Mehta, MSND, BPKIHS
  161. 161. One-Group Pretest-Posttest Design • Subjects in the experimental group are measured before and after the treatment is administered. • No control group • Offers comparison of the same individuals before and after the treatment (e.g., training) • If time between 1st & 2nd measurements is extended, may suffer maturation • Can also suffer from history, mortality, and testing effects • Diagrammed as O1 X O2 162Dr. R S Mehta, MSND, BPKIHS
  162. 162. Static Group Design • A.K.A., after-only design with control group • Experimental group is measured after being exposed to the experimental treatment • Control group is measured without having been exposed to the experimental treatment • No pre-measure is taken • Major weakness is lack of assurance that the groups were equal on variables of interest prior to the treatment • Diagrammed as: Experimental Group X O1 Control Group O2 163Dr. R S Mehta, MSND, BPKIHS
  163. 163. Pretest-Posttest Control Group Design • A.K.A., Before-After with Control • True experimental design • Experimental group tested before and after treatment exposure • Control group tested at same two times without exposure to experimental treatment • Includes random assignment to groups • Effect of all extraneous variables assumed to be the same on both groups • Do run the risk of a testing effect 164Dr. R S Mehta, MSND, BPKIHS
  164. 164. Pretest-Posttest Control Group Design • Diagrammed as – Experimental Group: O1 X O2 – Control Group: O3 O4 • Effect of the experimental treatment equals (O2 – O1) -- (O4 – O3) • Example – 20% brand awareness among subjects before an advertising treatment – 35% in experimental group & 22% in control group after the treatment – Treatment effect equals (0.35 – 0.20) – (0.22 – 0.20) = 13% R R 165Dr. R S Mehta, MSND, BPKIHS
  165. 165. Posttest-Only Control Group Design • A.K.A., After-Only with Control • True experimental design • Experimental group tested after treatment exposure • Control group tested at same time without exposure to experimental treatment • Includes random assignment to groups • Effect of all extraneous variables assumed to be the same on both groups • Do not run the risk of a testing effect • Use in situations when cannot pretest 166Dr. R S Mehta, MSND, BPKIHS
  166. 166. Posttest-Only Control Group Design • Diagrammed as – Experimental Group: X O1 – Control Group: O2 • Effect of the experimental treatment equals (O2 – O1) • Example – Assume you manufacture an athlete‟s foot remedy – Want to demonstrate your product is better than the competition – Can‟t really pretest the effectiveness of the remedy R R 167Dr. R S Mehta, MSND, BPKIHS
  167. 167. Solomon Four-Group Design • True experimental design • Combines pretest-posttest with control group design and the posttest-only with control group design • Provides means for controlling the interactive testing effect and other sources of extraneous variation • Does include random assignment 168Dr. R S Mehta, MSND, BPKIHS
  168. 168. Solomon Four-Group Design • Diagrammed as – Experimental Group 1: O1 X O2 – Control Group 1: O3 O4 – Experimental Group 2: X O5 – Control Group 2: O6 • Effect of independent variable (O2 – O4) & (O5 – O6) • Effect of pretesting (O4 – O6) • Effect of pretesting & measuring (O2 – O5) • Effect of random assignment (O1 – O3) R R R R 169Dr. R S Mehta, MSND, BPKIHS
  169. 169. Quasi-Experimental Designs • More realistic than true experiments • Researchers lacks full control over the scheduling of experimental treatments or • They are unable to randomize • Includes – Time Series Design – Multiple Time Series Design • Same as Time Series Design except that a control group is added 170Dr. R S Mehta, MSND, BPKIHS
  170. 170. Time Series Design • Involves periodic measurements on the dependent variable for a group of test units • After multiple measurements, experimental treatment is administered (or occurs naturally) • After the treatment, periodic measurements are continued in order to determine the treatment effect • Diagrammed as: O1 O2 O3 O4 X O5 O6 O7 O8 171Dr. R S Mehta, MSND, BPKIHS
  171. 171. Statistical Designs • Multiple experiments are conducted simultaneously to permit extraneous variables to be statistically controlled and • Effects of multiple independent variables to be measured • Advantages – Can measure the effects of more than one independent variable – Can statistically control specific extraneous variables – Economical designs can be formulated when each subject is measured more than once. 172Dr. R S Mehta, MSND, BPKIHS
  172. 172. Completely Randomized Design • Involves randomly assigning treatments to group members – Allows control over all extraneous treatments while manipulating the treatment variable – Simple to administer, but should NOT be used unless test members are similar, and they are also alike regarding a particular extraneous variable – Different forms of the independent variable are called “levels.” 173Dr. R S Mehta, MSND, BPKIHS
  173. 173. Completely Randomized Design Example • Grocery store chain trying to motivate consumers to shop in their stores • 3 possible sales promotional efforts X1 = offer discount of 5% off total shopping bill X2 = offer taste sample of selected foods X3 = control group, no sales promotional effort applied 174Dr. R S Mehta, MSND, BPKIHS
  174. 174. Completely Randomized Design Example SALES PROMOTION TECHNIQUE LEVELS 5% discount Taste samples No sales promotion Sales, store 3 Sales, store 5 Sales, store 9 STORES Sales, store 1 Sales, store 8 Sales, store 7 Sales, store 6 Sales, store 4 Sales, store 2 Average sales Average sales Average sales 175Dr. R S Mehta, MSND, BPKIHS
  175. 175. Randomized Block Design • Randomly assigns treatments to experimental & control groups • Test units broken into similar blocks (or groups) according to an extraneous variable – I.e., location, age, gender, income, education, et c. • Particularly useful when small sample sizes are necessary 176Dr. R S Mehta, MSND, BPKIHS
  176. 176. Randomized Design Example • Grocery store chain trying to motivate consumers to shop in their stores • 3 possible sales promotional efforts X1 = offer discount of 5% off total shopping bill X2 = offer taste sample of selected foods X3 = control group, no sales promotional effort applied Blocks = time stores have been in operation 177Dr. R S Mehta, MSND, BPKIHS
  177. 177. Latin Square Design • Allows control or elimination of the effect of two extraneous variables • Systematically blocks in 2 directions by grouping test units according to 2 extraneous variables • Includes random assignment of treatments to each cell in the design • Used for comparing t treatment levels in t rows and t columns – I.e., if we have 3 treatment levels, we must have 3 rows and 3 columns 178Dr. R S Mehta, MSND, BPKIHS
  178. 178. Latin Square Design Extraneous Variable 2 A B C Extraneous Variable 1 B C A C A B where A, B, & C are all treatments 179Dr. R S Mehta, MSND, BPKIHS
  179. 179. Latin Square Design Example PER CAPITA INCOME TIME IN OPERATION High Medium Low < 5 years X1 X2 X3 5 – 10 years X2 X3 X1 > 10 years X3 X1 X2 180Dr. R S Mehta, MSND, BPKIHS
  180. 180. Factorial Design • Used to examine the effects that the manipulation of at least 2 independent variables (simultaneously at different levels) has upon the dependent variable • The impact that each independent variable has on the dependent variable is referred to as the main effect • Dependent variable may also be impacted by the interaction of the independent variables. This is called the interaction effect 181Dr. R S Mehta, MSND, BPKIHS
  181. 181. Factorial Design Example • Grocery store chain wants to use 12 of its stores to examine whether sales would change at 3 different hours of operation and 2 different types of sales promotions • Dependent variable is change in sales • Independent variables – Store open 6 am to 6 pm – Store open 6 am to midnight – Store open 24 hours/day – Sales promotion: samples for a free gift – Sales promotion: food samples • Called a 3 x 2 factorial design • Need 6 experimental groups (3 x 2 = 6) 182Dr. R S Mehta, MSND, BPKIHS
  182. 182. Factorial Design Example HOURS OF OPERATION SALES PROMOTION 6 am – 6 pm 5 am – midnight 24 hours Gift stamps Food samples 183Dr. R S Mehta, MSND, BPKIHS
  183. 183. Test Marketing • Controlled experiment conducted on a small segment of the target market • Major objectives – Determine how well products will be accepted in the marketplace – Determine how changes in marketing mix will likely affect product success • Major reason for test marketing is risk reduction – Lose $ 1 million in test market or $ 50 million on product failure? • Problems – Expense – Time – Competitors can disrupt 184Dr. R S Mehta, MSND, BPKIHS
  184. 184. Factors to Consider • Population size • Demographic composition • Lifestyle considerations • Competitive situation • Media coverage & efficiency • Media isolation • Self-contained trading area • Overused test markets • Loss of secrecy 185Dr. R S Mehta, MSND, BPKIHS

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