Research Methods
Upcoming SlideShare
Loading in...5
×
 

Like this? Share it with your network

Share

Research Methods

on

  • 1,901 views

Basic structure of the frequently used methods in medical researches

Basic structure of the frequently used methods in medical researches

Statistics

Views

Total Views
1,901
Views on SlideShare
1,900
Embed Views
1

Actions

Likes
1
Downloads
136
Comments
0

1 Embed 1

https://ysu.blackboard.com 1

Accessibility

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Research Methods Presentation Transcript

  • 1. Research methods “an overview” Dr. Tarek Tawfik Professor of Public Health Cairo University 12/9/2013 Dr. Tarek Tawfik
  • 2. Research?  More than a set of skills, it is away of thinking: examining critically the various aspects of day to day professional work;  Understanding and formulating guiding principles that govern a particular procedures;  Developing and testing new theories for the enhancement of your practice. It is the habit of questioning with systematic examination of the observed information to find answers which may results in more effective professional services. Kumar R 2005. 12/9/2013 Dr. Tarek Tawfik
  • 3. Definition: Research is a structured inquiry that utilizes acceptable scientific methodology to solve problems and creates new knowledge that is generally applicable. Grinnell 1993 12/9/2013 Dr. Tarek Tawfik
  • 4. Types of research Application Pure research Applied research Objectives Descriptive research Correlational research Inquiry mode Exploratory research Explanatory research Quantitative research Qualitative research
  • 5. Research process “the 8 steps model” FINER Research design: functions Literature review Formulating a research question Methods and tools of data collection Instruments for data collection Research design Methods of data Processing: computing and statistics Sampling theory and designs Selecting a sample Research protocol writing Data collection Editing Study designs Variables and hypotheses: definition and typology What How Data processing Research report Coding Code book Field test of the tools Validity and reliability of the research tool Principles of Scientific writing Contents of research proposal Conducting of the study
  • 6. The structure of a research project is set out in its protocol, the written plan of the study. The functions of the protocol are:  Seeking grant funds.  Helping the investigator to organize his research in a logical, focused, and efficient way. 12/9/2013 Dr. Tarek Tawfik
  • 7. Elements of protocol Research questions Significance (background) Design time frame epidemiologic approach Subjects selection criteria sampling design Variables predictor variables confounding outcome variables Statistical issues hypotheses sample size analytic approach Purpose What questions will the study address? Why are these questions important? How is the study structured? Who are the subjects and how will they be selected? What measurements will be made? How large is the study and how will it be analyzed?
  • 8. I- Conceiving the Research Question. The research question is the uncertainty about something in the population that the investigator wants to resolve by making measurements on his study subjects. No shortage of questions as one leads to another. 12/9/2013 Dr. Tarek Tawfik
  • 9. Tamoxifen and Cancer Breast. Tamoxifen reduces the risk of cancer breast during 4 years of use by women at high risk of breast cancer. Many other questions evolved: o Does tamoxifen reduce the risk of death due to breast cancer? o How long should treatment be continued? o Might other drugs with the same action are beneficial without the risk of tamoxifen-induced thromboembolism? o Does the use of such drug increases the risk for other cancer (ovarian)? The difficulty in question lies in finding one that can be transformed into a feasible and valid study plan. 12/9/2013 Dr. Tarek Tawfik
  • 10. Origins of a research question.  For established investigator: The best research questions usually emerge from findings and problems faced and observed in prior studies, and in those of other workers in the field “Major Players”.  For new and other investigators: ☼ Mastering of the literature. ☼ Being alert to new ideas and techniques. ☼ Keeping the imagination roaming. ☼ Attending seminar, workshops and conferences. 12/9/2013 Dr. Tarek Tawfik
  • 11. Characteristics of a good research question “FINER Criteria”. Feasible Interesting Novel Ethical Relevant Adequate number of subjects. Adequate technical expertise Affordable in time and money Manageable in scope To the investigator Confirms or refuses previous findings Extends previous findings Provides new findings To scientific knowledge To clinical and health policy To future research directions
  • 12. Developing the research question and study plan. ☼ A one or two page outlining the study question and the study plan at an early stage is very helpful. ☼ This will focus the attention to clarify the ideas about the plan and to discover potential specific problems that need correction. 12/9/2013 Dr. Tarek Tawfik
  • 13. The research question should specifies! Predictor Exposure Smoking Confounders Confounders Occupational hazards Outcome Disease Cancer lung
  • 14. The research question and study plan: problems and solutions Potential problem The research question is not FINER 1- Not feasible too broad not enough subjects available methods beyond the skills of the investigator too expensive 2- Not interesting, novel, or relevant 3- Uncertain ethical suitability The study plan is vague Solutions Specify a smaller set of variables Narrow the question. Expand the inclusion criteria Eliminate or modify exclusion criteria Add other sources of subjects Lengthen the time frame for entry into study Use strategies to decrease sample size Collaborate with those who have skills Consult and review the literature for alternative methods Consult and modify the research question
  • 15. Exercise: Consider the following research questions. First, write each question in a single sentence that specifies a predictor, outcome, and population. Then discuss whether it meets the FINER criteria. Rewrite the question in a form that overcomes any problems in meeting their criteria. 12/9/2013 Dr. Tarek Tawfik
  • 16. Exercise: A. B. C. D. E. F. What is the relationship between depression and health? Does eating red meat cause cancer? Does lowering serum cholesterol prevent heart disease? Can a relaxation exercise decrease the anxiety associated with mammography? Do contraceptive vaginal sponges prevent HIV infection? Does dietary pattern among school children affect their health? 12/9/2013 Dr. Tarek Tawfik
  • 17. Assignment: Formulate a research questions regarding health and health-related problems that may be encountered in: A. B. C. Rural community and the available health facilities. Urban primary health care facility. Primary schools. 12/9/2013 Dr. Tarek Tawfik
  • 18. II- Rationale (Significance). This section sets the proposed study in context and gives its rationale:    What is known about the topic at hand? Why is the research question important? What kind of answers will the study provide? 12/9/2013 Dr. Tarek Tawfik
  • 19. Rationale “Background” ۞This section cites previous research that is relevant (including the investigator‟s own work) and indicates the problem with that research and what question remain. ۞It makes clear how the findings of the proposed study will help o In resolving uncertainties, o Leading to new scientific understanding and o Influencing clinical and public health policy. 12/9/2013 Dr. Tarek Tawfik
  • 20. Sequence of the rationale In a concise logical sequence:  Discuss the importance of the topic “significance”  Review the relevant literature and current knowledge (including deficiencies in knowledge that make the study worth doing).  Describe any results you have already obtained in the area of the proposed study. 12/9/2013 Dr. Tarek Tawfik
  • 21. Sequence of the rationale Indicate how research question has emerged and fits logically with the above. Outline in broad terms how you intend to address the research question. Explain how your study will add to knowledge and help to improve health and/or save money. 12/9/2013 Dr. Tarek Tawfik
  • 22. How to determine research priorities? (Importance/Significance) I- How frequent is the condition relative to other conditions? Prevalence As a cause of death II- What is the degree of disability or dysfunction due to the condition? III- Are there cost-effective means to cure, control, or prevent such condition? 12/9/2013 Dr. Tarek Tawfik
  • 23. Assignment: State the rationale (significance) for the proposed study question? 12/9/2013 Dr. Tarek Tawfik
  • 24. III-Setting up research objectives. Purpose broad objectives (aims) ☼ The statement of a research project should describe the main questions to be addressed by the research without going into details. ☼ It should give a reader a clear idea of the nature of the research that will be undertaken. „ The purpose is to measure the effect of a plasmodium falciparum asexual blood-stage vaccine in reducing morbidity and mortality due to malaria‟ „ This study is conducted to assess the nutritional problems among primary school children‟ 12/9/2013 Dr. Tarek Tawfik
  • 25. Specific objectives The specific objective should be S M A R T 12/9/2013 SMART: Specific Measurable (effect size) Applicable, achievable Relevant Timely (a time frame and end point). Dr. Tarek Tawfik
  • 26. Objectives “characteristics” Clear Complete + + Specific + Identify the Main variables to be correlated Descriptive studies Correlation studies (experimental and non experimental) Hypothesis-testing studies + Identify the direction of the relationship
  • 27. Specific objectives in research They should include a concise but detailed description of: o The intervention (study) to be evaluated, o The outcome (s) of interest, o And the population in which the study will be conducted. 12/9/2013 Dr. Tarek Tawfik
  • 28. Why is asthma among children in Istanbul exceptionally frequent? The purpose of the study are to determine if the excess asthma in Istanbul is related to a combination of genetic predisposition (estimated by atopy) and socio-economic and/or indoor air pollution. 12/9/2013 Dr. Tarek Tawfik
  • 29. What are the specific objectives to achieve such type of study? I. Identify a suitable source of childhood asthma cases and select 200 cases, following a specific case definition. II. Identify and select suitable control subjects (individuals without asthma). III. Measure indoor particulate exposure on each of 3 randomly selected days for each participant. IV. Perform allergy skin test on cases and controls (atopy). V. Record personal, demographic, and socio-economic information about cases and control. VI. Compare risk ratio for atopy, low socio-economic status, and increased indoor air pollution between cases and controls.
  • 30. Hypotheses and Underlying Principles Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 31. Hypothesis definition A hypothesis is written in such a way that it can be proven or disproved by valid and reliable data-it is in order to obtain these data that we perform our study. Grinnel 1988:200. Hypothesis has certain characteristics: 1. It is a tentative proposition “hunch” 2. Its validity is unknown. 3. In most cases, it specifies a relationship between two or more variables. 12/9/2013 Dr. Tarek Tawfik
  • 32. Functions of hypothesis  Formulation of a hypothesis provides a study with focus “specific aspects of a research problem to investigate”  What data are necessary to collect to test the hypothesis.  Enables you to specifically conclude what is true or what is false. Process of testing a hypothesis Phase I Formulate your Hunch or assumption 12/9/2013 Phase II Collect the required data Dr. Tarek Tawfik Phase III Analyze data To draw conclusions About the hunch-true/false
  • 33. Hypotheses It is the further formulation of the study question into a final and more specific version, that summarizes  the elements of the study;  the sample, the design,  and the predictor and outcome variables. The primary purpose is to establish the basis for tests of statistical significance. 12/9/2013 Dr. Tarek Tawfik
  • 34. Hypotheses I- Hypotheses are not needed in descriptive studies which describe how characteristics are distributed in a population. The prevalence of particular genotype among patients with hip fracture. II- Hypotheses are needed in most of the observational and experimental studies that address statistical comparison. The study of weather a particular genotype is more common in patients with hip fracture compared to control. 12/9/2013 Dr. Tarek Tawfik
  • 35. Hypotheses If any of the following terms appear in the research question, then the study is not descriptive and a hypothesis should be formulated: Greater than, less than, causes lead to, compared with, more likely than, associated with, related to, similar to, or correlated with. 12/9/2013 Dr. Tarek Tawfik
  • 36. Characteristics of a good hypothesis Simple, Specific, Stated in advance (3Ss) A-Simple versus complex Contains one predictor and one outcome variable; (a sedentary lifestyle is associated with an increased risk of proteinuria in patients with diabetes). A complex hypotheses contains more than one predictor; (a sedentary lifestyle and alcohol consumption are associated with increased risk of proteinuria in patients with diabetes). 12/9/2013 Dr. Tarek Tawfik
  • 37. Simple hypotheses Or more than one outcome variable; (alcohol consumption is associated with an increased risk of proteinuria and neuropathy in patients with diabetes). Complex hypotheses can be readily tested with a single statistical tests and can be easily approached by breaking them into two or more simple hypotheses. 12/9/2013 Dr. Tarek Tawfik
  • 38. Simple hypotheses (smoking cigarettes, cigars, or a pipe is associated with an increased risk of proteinuria in patients with diabetes). What type of hypotheses is this? 12/9/2013 Dr. Tarek Tawfik
  • 39. B-Specific versus Vague   A specific hypothesis leaves no ambiguity about the subjects, the variables, or about how the test of statistical significance will be applied. it uses concise operational definitions that summarize the nature and source of the subjects and how variables will be measured; (a history of using tricyclic antidepressant medications, as measured by review of pharmacy records, is more common in patients hospitalized with an admission diagnosis of myocardial infarction at Longview Hospital in the past year than in control hospitalized for pneumonia). 12/9/2013 Dr. Tarek Tawfik
  • 40. Specific versus Vague  It is often obvious from the research hypothesis whether the predictor variable and the outcome variable are dichotomous, continuous, or categorical. (alcohol consumption (in mg/day) is associated with an increased risk of proteinuria (> 30 mg/dL) in patients with diabetes). 12/9/2013 Dr. Tarek Tawfik
  • 41. C-In Advance versus After-the-Fact    The hypothesis should be stated in writing at the outset of the study. A single pre-tested hypothesis creates a stronger basis for interpreting the study results than several hypotheses that emerge as a result of data inspection. Hypotheses that are formulated after data examination are a form of multiple hypothesis testing that often leads to over-interpreting the importance of the findings. 12/9/2013 Dr. Tarek Tawfik
  • 42. Types of hypothesis Alternate hypothesis Null hypothesis Research hypothesis Hypothesis of difference Hypothesis of no difference “null hypothesis” Hypothesis of pointprevalence Hypothesis of association
  • 43. Types of hypothesis “examples” There is no significant difference in the proportion of male and female smokers in the study population. Hypothesis is ? A greater proportion of females than males are smokers in the study population. Hypothesis is ? A total of 60% of females and 30% of males in the study population are smokers. Hypothesis is ? There are twice as many female smokers as male smokers in the study population. Hypothesis is ? 12/9/2013 Dr. Tarek Tawfik
  • 44. Types of Hypotheses 1- Null and Alternative I- The null hypothesis states that there is no association between the predictor and outcome variables in the population. (there is no difference in the frequency of drinking well water between subjects who develop peptic ulcer disease and those who do not). II- It is the formal basis for testing statistical significance. Statistical tests help to estimate the probability that an association observed in a study is not due to chance. 12/9/2013 Dr. Tarek Tawfik
  • 45. Null and Alternative o The proposition that there is an association is called the alternate hypothesis. o The alternative hypothesis cannot be tested directly; it is accepted by default if the test of statistical significance rejects the null hypothesis. “accepted when null is rejected” 12/9/2013 Dr. Tarek Tawfik
  • 46. 2- One and Two-sided alternative Hypothesis I- A one-sided hypothesis specifies the direction of the association between the predictor and the outcome variables. Drinking well water is more common among subjects who develop peptic ulcer (one-sided). II- A two-sided hypothesis states only that an association exists; does not specify the direction. The prediction that subjects who develop peptic ulcer disease have a different frequency of drinking well water than those who do not (two-sided). 12/9/2013 Dr. Tarek Tawfik
  • 47. Indications For one-sided:  When only one direction for an association is important or biologically meaningful (a new drug for hypertension is more likely to cause rashes than a placebo).  When there is good evidence from prior studies that an association is unlikely to occur in one of the two directions (smoking affects the risk of cancer brain). 12/9/2013 Dr. Tarek Tawfik
  • 48. Underlying Statistical Principles Research Q implement design Target Population Phenomena Of interest Truth in Universe Actual study Study plan Random Systematic error infer Intended Sample Intended variables Truth in the study Random Systematic error infer Actual Subjects Actual Measure. Findings in the study
  • 49. Underlying Statistical Principles Jury decision Statistical tests Innocence: the defendant did not counterfeit money Guilt: the defendant counterfeit Null hypothesis: there is no association between dietary carotene and incidence of colon cancer. Alternative hypothesis: there is an association between money dietary carotene and colon cancer incidence. Standard for rejection null hypothesis: Standard for rejecting innocence: beyond a reasonable doubt. Correct judgment: convict a counterfeiter Correct judgment: acquit an innocent person Incorrect judgment: convict an innocent person Incorrect judgment: Acquit a counterfeiter Level of statistical significance ( ≤ 0.05) Correct inference: conclude an association when one does not exist in the population. Correct inference: no association between carotene and colon cancer when one does not exist Incorrect inference (Type I error): association in the study when actually is none Incorrect inference (Type II error): there no association when actually there is one.
  • 50. Type I and type II error A type I error (false-positive) occurs if the investigator rejects a null hypothesis that is actually true in the population. A type II error (false-negative) occurs if the investigator fails to reject a null hypothesis that is actually not true in the population. 12/9/2013 Dr. Tarek Tawfik
  • 51. Truth in the population Vs. the results in the study sample (the four possibilities). Truth in the population Results in the study sample Reject null hypothesis Fail to reject null 12/9/2013 Association between predictor and outcome No association between predictor and outcome Correct Type I error Type II error Correct Dr. Tarek Tawfik
  • 52. , and Power  The probability of committing a type I error (rejecting the null when it is actually true) is called  (alpha), another name is the level of statistical significance.  An  level of 0.05, setting 5 % as the maximum chance of incorrectly rejecting the null hypothesis. 12/9/2013 Dr. Tarek Tawfik
  • 53.   The probability of making a type II error (failing to reject the null hypothesis when it is actually false) is called  (beta).  The quantity (1-  ) is called power, the probability of rejecting the null hypothesis in the sample if the actual effect in the population equals effect size.  If  is set at 0.10, we are willing to accept a 10 % chance of missing an association of a given effect size. This represents a power of 90 % (there is 90 % chance of finding an association of that size). 12/9/2013 Dr. Tarek Tawfik
  • 54. P Value  A „non significant‟ result (i.e., one with a P value greater than ) does not mean that there is no association in the population, it only means that the result observed in the sample is small compared with that occurred by chance alone.  Those with hypertension were twice as likely to develop cancer prostate compared to normotensive subjects (P of 0.08) 12/9/2013 Dr. Tarek Tawfik
  • 55. Sampling Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 56. In research what we are looking for? The variable: is a condition, quality or trait that varies from one case to another Provokes research In the target population (population of interest) To study these variables. Either include the whole Population OR A Sample
  • 57. Basic Terms and Concepts Target Population and Sample o A population is a complete set units with a specified set of characteristics while a sample is a subset of that population. o The defining characteristics of population include geographic, clinical, demographic and temporal. o Clinical and demographic characteristics define the target population, the large set of people throughout the world to which the results will be generalized. (all teenagers with asthma). o The study sample is the subset of the target population available for study. (teenagers with asthma in the investigator‟s town in 2005).
  • 58. Steps in designing the protocol for choosing the study subjects Research question Study plan Target population Specify clinical, Demographic and then Geographic and temporal characteristics Truth in the Universe Design Intended sample Specify accessible population and approach to selecting the sample Findings in the study
  • 59. Selection Criteria  How would you define the population to be studied?  Through establishing selection criteria that include inclusion and exclusion criteria. Example: Demonstrate the selection criteria for subjects to evaluate the efficacy of calcium supplements for preventing osteoporosis? 12/9/2013 Dr. Tarek Tawfik
  • 60. Designing selection criteria for a clinical trial of calcium supplements to prevent osteoporosis Considerations Inclusion criteria (be specific) Specifying the characteristics that define population that are relevant to the research question and efficient for study: ®Demographic: age, sex, and race. ®Clinical characteristics. ®Geographic (administrative). ®Temporal characteristics Example A 5-year trial of calcium supplementation for preventing osteoporosis might specify the subject be: White females 50 to 60 years old In good general health** Patients attending clinic at X Hospital Between Jan. 1st and December 31st of next year.
  • 61. Designing selection criteria for a clinical trial of calcium supplements to prevent osteoporosis Considerations Exclusion Criteria (be parsimonious) Example Specifying the subsets of the population that will not be studied because of: The calcium supplementation trial might exclude subjects who are: A oAlcoholic high likelihood of being lost to follow-up. An inability to provide good data. Being at high risk of side effects. Characteristics that make it unethical to withhold the study treatment or plan to move of the country or region. oDisoriented or have a language barrier. oSarcoidosis /hypercalcemia. oTaking steroids.
  • 62. Clinical versus Community populations If the research question involves patients with a disease; hospitalized or clinic-based patients are inexpensive and easy to recruit, but selection factors that determine who comes to the hospital or clinic may have an important effect. Tertiary clinics tend to accumulate patients with serious forms of disease. 12/9/2013 In choosing the sample in the community who will represent a non clinical population (populationbased) Samples are difficult and expensive to recruit, but they are particularly useful for guiding public health and clinical practice in the community. Dr. Tarek Tawfik
  • 63. Studying The whole population    Resorted to if we are interested in the characteristics of each individual, particularly with descriptive research questions, and there is a need for generalizing the findings. Probability sampling is the gold standard. It provides a rigorous basis for estimating the fidelity with which phenomena observed in the sample represent those in the population, and for computing statistical significance and confidence intervals. A. B. C. D. It is expensive. It is time consuming. It has higher error chances because of the many persons, equipments and wide geographic area covered. Carried out in censuses.
  • 64. Sampling Resorted to if we are interested in studying the prevalence of a problem, associations or intervention effect,…..etc A. B. C. D. E. It is less expensive. It is less time consuming. It has lower error chances because of less persons, equipments and geographic area covered. Only estimates are concluded, the reality is unknown. It allows for continuous study of the population “longitudinal studies”. Study of a sample is carried out in the majority of biomedical researches. 12/9/2013 Dr. Tarek Tawfik
  • 65. The concept of sampling Study population: Sampling units You select a few sampling units from the study population You make an estimate “prediction” extrapolated to the study population (prevalence, outcomes etc.) 12/9/2013 Dr. Tarek Tawfik Sample You collect information from these people to find answers to your research questions.
  • 66. Principles of sampling In a majority of cases of sampling there will be a difference between the sample statistics and the true population mean, which attributable to the selection of the units in the sample “sampling error”. II. The greater the sample size, the more accurate will be the estimate of the true population mean “reduction in sampling error” III. The greater the difference in the variable “heterogeneous variable” under study in a population for a given sample size, the greater will be the difference between the sample statistics and the true population mean “the larger the sampling error”. I.
  • 67. Types of sampling Non-random/probability Random/probability Simple Stratified Cluster Quota Mixed sampling Systematic sampling Judgmental Proportionate Disproportionate Single Accidental Double stage Multi-stage Snowball
  • 68. Types of Samples  Probability samples: Units are selected according to probability laws i.e. everyone in the underlying population has an equal (a specified) and independent chance of appearing in that sample.  Non-probability (convenience) samples: Units are selected based on known factors. In clinical research the study sample is usually made up of people who meet the inclusion criteria and are easily accessible to the investigator. 12/9/2013 Dr. Tarek Tawfik
  • 69. Probability Samples In order to be able to infer from sample results to the underlying population, that sample should be a representative sample. i.e. it should represent the population from which it is drawn in every respect. Because we can not anticipate all characteristics of the population that the sample should represent, we chose a probability (random) sample. 12/9/2013 Dr. Tarek Tawfik
  • 70. How to draw a probability Sample? Identify the study units (individuals, villages, houses, …etc). II. Make a complete list of the study units in the underlying population. That complete list is known as the sampling frame. III. Each of these units is given a number. IV. Then select the required number of units (sample size) at random from that frame. I. 12/9/2013 Dr. Tarek Tawfik
  • 71. The selection of units can be made either by: 1. 2. 3. The lottery method “fishbowl draw” (the numbers of frame units are written on identical pieces of papers, mixed thoroughly in a bowl and the required number is blindly picked up). Through the use of random numbers tables. Computer generated random numbers. Two systems of drawing a random sample: Sampling without replacement. Sampling with replacement.
  • 72. Random number table
  • 73. Random Sampling Techniques 1-Simple random sample 2-Stratified random sample 3-Systematic random sample 4-Cluster random sample 5-Multistage random sample 12/9/2013 Dr. Tarek Tawfik
  • 74. 1-Simple random sample We prepare a complete and up-to-date list of the underlying population (sample frame). The specified sample size is drawn from that frame at random. Disadvantages:       12/9/2013 Suitable for homogenous population (single sex). Larger sample size is required. More expensive as we have to get the cases from widely scattered areas. Time consuming and more laborious. Some groups might not be represented in the sample. Extreme values can occur by chance. Dr. Tarek Tawfik
  • 75. Example of Simple random sample using random digit table. Draw at random a sample size of 50 from a population of 10,000. A. B. C. D. E. F. The size of the population is 10,000 i.e. it is formed of 5 digits. Select at random a page from the random numbers table Select 5 adjacent columns Proceed from up down, any value falling between 00001 and 10,000 is chosen and so on until you completed your 50 cases. Duplicate numbers are left aside Individuals with those 50 numbers compose our sample.
  • 76. The First 15 columns of the first page of a Random numbers table 26804 00010 93445 90720 12805 58563 85027 32242 86468 09362 16212 00128 64590 75362 32348 29273 34703 23763 96215 01556 63708 59207 22211 48522 49674 01534 98685 04104 00047 14986
  • 77. 2-Stratified random sampling o Based upon the logic of heterogeneity of the included variables. o Ensure homogeneity of sub-population though ranking them into strata. 12/9/2013 Dr. Tarek Tawfik
  • 78. 2-Stratified random sample     Ensures representativeness with regard to important characteristics as age, sex, educational or socioeconomic levels. The population is divided into strata (subgroups) according to the different levels of the important variable. The population in each stratum is homogenous so sampling accuracy is increased. We choose a simple random sample from each stratum, the size of which is proportionate to the size of that stratum. In other words the sampling fraction is the same for each stratum and the total sample. n n1 n2 n3    N N1 N2 N3
  • 79. Example of Stratified random sample A town with a total population of 12,000 was classified into 4 homogenous socioeconomic strata. The population in each stratum was 2,000 (class I), 4,000 (class II), 5,000 (class III) and 1,000 (class IV) respectively. A sample size of 600 is to be drawn from the town. Calculate the number of individuals to be drawn at random from each of the 4 strata? Sampling fraction   1 20 Stratum1 sample  2000 x 1 20  100 Stratum2 sample  4000 x 1 20  200 Statum3 sample  5000 x 1 20  250 Stratum4 sample  1000 x 600 12 , 000 1 20  50
  • 80. 3-Systematic random sample 1. The underlying population is classified into intervals: The size of intervals = the size of the population the required sample size. 2. 3. The first case is selected at random from the first stratum (interval) and the others are selected by adding systematically the size of each interval. Accordingly we are taking each (nth) individual. n is the size of the interval. If the latter is 10 we take every tenth observation 12/9/2013 Dr. Tarek Tawfik
  • 81. Example of systematic random sample 1000 patients visit King Faisal University outpatient clinics every day. We need a systematic random sample of 100 patients. Explain how should we proceed in selecting those 100 patients composing our sample? We classify the patients into 100 intervals and select a patient from each. Size of each interval =1000/100 = 10 Choose at random a number that lies between 1 and 10 say 9. Choose from the second interval patient number 19th. Choose from the third interval observation number 29th. 9  1x10  19 th 9  2 x 10  29 th 12/9/2013 OR OR Dr. Tarek Tawfik 9  10  19 th 19  10  29 th
  • 82. 4-Cluster random sample ۞ In this method, the sampling units are clusters (groups) of individuals – (incomplete sampling frame and/or the total sampling population is large) rather than individuals. ۞ The clusters (schools, houses, villages, …etc.) form the sampling frame, from which the required number of clusters is selected at random. ۞ All individuals in a cluster, a specific group, or a random sample of them are included. ۞ Very useful when the population is widely dispersed, and it is impractical to list and sample from all its elements. 12/9/2013 Dr. Tarek Tawfik
  • 83. Example of random cluster sample In some research, the objective was to study the prevalence of malnutrition among primary school children in Hofuof. There are 200 primary schools in Hofouf. The estimated sample size is 20 clusters. Describe how would you proceed in drawing such sample? A. List all 200 schools B. Give each a number C. Use the random numbers tables in selecting the 20 schools whose numbers will fall between 001 and 200. 12/9/2013 Dr. Tarek Tawfik
  • 84. 5-Multistagerandom sample We use this method if the target population is spread over wide geographic area and there is limited budget or resources (in community-based surveys). In this method, the sample is drawn in many stages. The area is divided into smaller clusters, the clusters are divided into smaller clusters and so on. Random selection is carried out at each level successively. 12/9/2013 Dr. Tarek Tawfik
  • 85. You were asked to head a research team to investigate the problem of handicapping in K.S.A. How would you proceed in drawing your sample? List all governorates       12/9/2013 Select 4 governorates at random List the districts in each of the 4 governorates Select a district from each governorate at random List all village and urban areas in each districts Select a village and an urban centre from each district randomly Study all or sub-sample of individuals in the selected villages and urban centres Dr. Tarek Tawfik
  • 86. II-Non-probability (convenience) samples    A convenience sample can minimize volunteerism and other selection biases by consecutively selecting every accessible person who meets the inclusion criteria. A consecutive sample is specially desirable when it mounts to taking the entire accessible population over a long enough period to include seasonal variation or other changes over time that considered important to research question. Representativness is a matter of judgment. 12/9/2013 Dr. Tarek Tawfik
  • 87. Non-probability samples These designs are used when the number of elements in a population is either unknown or can not be individually identified.  Quota sampling.  Accidental sampling.  Judgmental or purposive sampling.  Snowball sampling. 12/9/2013 Dr. Tarek Tawfik
  • 88. Non-probability (convenience) samples 1-Purposive sample: Chosen according to the investigator‟s judgement in such a way that maximizes the chances of proving the study hypothesis. “selecting patients with ESRD” 2-Quota sample: Involves only few strata e.g. men and women >20 years. The enumerators select any individual belonging to those strata from whom they get the required information in an easy, quick and accessible way. 12/9/2013 Dr. Tarek Tawfik
  • 89. Sample size How many observations should we include? The greater the sample size: I. The more precise are the estimates derived. II. III. 12/9/2013 The more powerful are the tests (probability of rejecting a false null). Larger degrees of freedom and smaller test statistic required. Smaller standard error. Higher costs, more time and efforts needed. Dr. Tarek Tawfik
  • 90. Sample size The size of the sample depends on: 1. 2. 3. 4. 5. 6. 7. 8. Study design, Maximum tolerable sampling error, Homogeneity of the population, Number of variables studied, The extent of breaking down the data in analysis, Cost, Available staff, equipments, time and tools, Statistical tests used. 12/9/2013 Dr. Tarek Tawfik
  • 91. Data Collection Techniques and Tools Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 92. Objective of data collection techniques: Allow the investigator to systematically collect data about the subjects under the study including the setting in which they were occur. 12/9/2013 Dr. Tarek Tawfik
  • 93. Methods of data collection Primary Sources Secondary Sources Documents Observation Participant Interviewing Structured oGovt publications oEarlier research oCensus oPersonal records oClient histories oService records Non-participant Questionnaire Mailed Unstructured Collective
  • 94. Observation  Participant: the researcher participates in the activities of the group being observed “submitted to clinical examination to observe practice of physicians”  Non-participant: involved in the activities and remains a passive observer “functions carried out by nurses in a hospital” 12/9/2013 Dr. Tarek Tawfik
  • 95. Problems with observation: Hawthorne effect: change in behavior as a result of the observation process. Observer bias. Inter-observer variation in interpretation. Incomplete observation and /or recording “keen observation with missing recording or vice versa”. 12/9/2013 Dr. Tarek Tawfik
  • 96. Recording of observation     Narrative: description of the process in the researcher‟s own words “deeper insight in interpretation and conclusions”. Scales: interpreting in a form of rates using scales for measurements. No in-depth interpretation, error of central tendency and Halo effect. Categorical recording: yes/no, always/sometimes/never. Using mechanical devices: videotape “uncomfortable or behave differently before a camera or cassette recorder. 12/9/2013 Dr. Tarek Tawfik
  • 97. Scale “example” Neutral Positive 5 4 3 2 1 0 Aggressive behavior of nurses in hospital Z 12/9/2013 Dr. Tarek Tawfik Negative 1 2 3 4 5
  • 98. Interviewing Different levels of flexibility and specificity. Unstructured Interviews -Flexible interview structure. -Flexible contents -Flexibility in questions In-depth interviews Focus group discussion Narratives Oral histories Structured Interviews -Rigid interview structure. -Rigid contents -Rigidity in questions and their wording. Interview schedule Questionnaire
  • 99. Techniques of data collection  Using the available information (records and registries).  Observing and recording using an observation check list.  Interviewing (face to face)  Self-administered questionnaire  Telephone and net surveys.  Focus group discussion.  Measuring scales.  Others (life histories, essay, case studies, and mapping). 12/9/2013 Dr. Tarek Tawfik
  • 100. Techniques of data collection (advantages and disadvantages) Technique Records and registries Observation Advantages 1. 2. A. B. C. Disadvantages Inexpensive Permit examination of past trends. 1. More detailed information. Facts not mentioned by questioning Test reliability A. 2. 3. B. C. D. Accessible. Non-ethical Incomplete and imprecise. Ethical issues Observer bias Data collector may influence results. Need training.
  • 101. Techniques of data collection (advantages and disadvantages) Technique Personal interviewing Advantages I. II. III. Suitable for illiterates Permits clarification High response rate Disadvantages I. II. III. Self administered questionnaire 1. 2. 3. 4. Less expensive Permit anonymity Less personnel Eliminate bias 1. 2. 3. Interviewer may influence results Less accurate recording than observation Needs trained personnel Not suitable for illiterate Low response rate Problem of misunderstanding
  • 102. Techniques of data collection (advantages and disadvantages) Technique Focus group discussion Advantages Collection of in-depth information and exploration Disadvantages 1. 2. 3. 4. Measuring scale oPrecision oEliminate o bias o Interviewer may influence results Open-ended questions Domination Non response Training Validity and accuracy
  • 103. Differentiation between data collection techniques and tools. Techniques Using available data Observation   Interviewing  Self-administered questionnaire Tools Data compilation sheet Check list, eye, watch, scales, Microscope, pen and paper. Schedule, agenda, questionnaire, recorder.  Questionnaire.
  • 104. Designing Questionnaire and Data Collection Instruments. In many instances the validity of the results depends on the quality of the data collection instruments. 12/9/2013 Dr. Tarek Tawfik
  • 105. Choosing between an interview schedule and a questionnaire.  Nature of the investigation: reluctant to discuss “sexuality, drug use”.  Geographical distribution of the study population.  The type of study population. “illiterate, young, handicapped, very old”. 12/9/2013 Dr. Tarek Tawfik
  • 106. Administration of questionnaire. Mailed or via other electronic media. Collective administration “people attending some function (schooling)”. Administration in a public place “hospital, medical center”. 12/9/2013 Dr. Tarek Tawfik
  • 107. Advantages and disadvantages of questionnaire. Advantages 1. 2. Less expensive Offers greater anonymity Disadvantages 1. 2. 3. 4. 5. 6. 12/9/2013 Dr. Tarek Tawfik Application is limited Response rate is low Self-selecting bias Opportunity to clarify is lacking Spontaneous responses are not allowed. Possible to consult others.
  • 108. Advantages and disadvantages of interview. Advantages 1. 2. 3. 4. 5. More appropriate for complex situations. Collecting in-depth information. Information can be supplemented. Questions can be explained. Has a wider application “any type of population” Disadvantages 1. 2. 3. 4. 5. Time consuming and expensive. Quality of data depends on the quality of interaction. Quality of data depends on the quality of interviewer. Many interviewers Interviewer bias.
  • 109. Designing Good Questions and Instruments Open-ended and Closed-ended Questions Open-ended question: Useful when it is important to hear what respondents have to say in their own words; What habits do you believe increase a person’s chance of having a heart attack? ----------------------------------------------------------------------------------------------------------------------------------------------------It leave the respondent to answer freely without limits that may imposed by the interviewer. 12/9/2013 Dr. Tarek Tawfik
  • 110. Designing Questionnaire and Data Collection Instruments. Open-ended questions: A. B. Often used in exploratory phases of question design because they facilitate understanding a concept as respondent express it. Phrases and words used by respondent can form the basis for more structured items in a later phase. Disadvantage: Usually require qualitative methods of coding and analyze the responses, which take more time and subjective judgment than coding closed-ended questions. 12/9/2013 Dr. Tarek Tawfik
  • 111. Designing Questionnaire and Data Collection Instruments. Closed-ended questions: More commonly used, and form the basis for most standardized measures. Ask the respondent to choose from one or more pre-selected answers; Which one of the following do you think increases a person’s chance of having a heart attack the most ? (Check one) Smoking Being overweight Stress 12/9/2013 Dr. Tarek Tawfik
  • 112. Closed-ended questions: They quicker and easier to answer. The answers are easier to tabulate and analyze. The list of possible answers often help to clarify the meaning of the question. Disadvantages: It may lead the respondent, and do not allow them to express their own, potentially unique answers. ii. The potential responses listed may not include an answer most appropriate for a particular respondent. i. 12/9/2013 Dr. Tarek Tawfik
  • 113. Designing Questionnaire and Data Collection Instruments. Whenever there is a chance that the set of answers is not exhaustive (does not include all the possible options), include the option „Other (please specify)‟ or „None of the above” When a single response is desired, the set of possible responses should be mutually exclusive „ the categories should not overlap‟ to ensure clarity. All that apply is used for multiple answer. 12/9/2013 Dr. Tarek Tawfik
  • 114. The Visual Analog Scale  Used for recording the answers to closed-ended questions using lines or other drawings.  The participant is asked to mark a line at a spot, along the continuum from one extreme to another, that best represents his characteristics.  It is important that the words that anchor each end describe the most extreme value for the item of interest.  The line is 10 cm long and score is the distance, in cm from the lowest extreme.
  • 115. Visual Analog Scale for Rating the Severity of Pain 4- please use an X to mark the place on this line that best describe the severity of your pain in general over the past week None Unbearable A participant might answer as follow None Unbearable There is a 10 cm line, and the mark is 3 cm from the end (30 % of the distance from none to unbearable) so the respondent‟s pain would be recorded as having a severity of 30 %. 12/9/2013 Dr. Tarek Tawfik
  • 116. Formatting of questionnaire  It is customary to describe the purpose of the study and how the data will be used in a brief statement on the cover together with name of the institution, assure anonymity, contact number for any questions, return address, deadline date and thank them for participation. “the covering letter”  To ensure accurate and standardized responses, all instruments must have instructions specifying how they should be filled out. Some time it is helpful to provide an example of how to complete question, using a simple question that is easily answered. 
  • 117. Formatting  To improve the flow of the instrument, questions concerning major subject areas be grouped together an introduced by headings or short descriptive statements. “personal data include: age, sex, educational status, marital status”  To warm up the respondent to the process of answering questions, it is helpful to begin with emotionally neutral questions such as self-rated health of functioning.  More sensitive questions can be placed in the middle.  Questions about personal characteristics such as income or sexual function are often placed at the end of the instrument.
  • 118. Formatting The visual design should be as easy as possible for the respondent to complete all questions in the correct sequence. With too complex format, the respondent or interviewer may skip questions, provide wrong answers, and even refuse to complete the instruments. A plenty of space is more attractive and easier to use than one that is crowded. When open-ended questions are used, the space of responding should be big enough to allow respondent with large handwriting to answer comfortably. 12/9/2013 Dr. Tarek Tawfik
  • 119. Formatting People with visual problems, including elderly will appreciate large type (font size 14), and high contrast (black on white). Possible answers to closed-ended questions should be lined up vertically and preceded by boxes or brackets to check, or by number to circle, rather than open blanks: How many different medicines do you take every day? (Check one) None 1-2 3-4 5-6 7 or more 12/9/2013 Dr. Tarek Tawfik
  • 120. Formatting The Branched Question: Sometimes the investigator may wish to follow up certain answers with more detailed questions: Respondent‟s answer to initial question (screener) determine whether they directed to answer additional question or skip ahead to later questions; 10- Have you ever been told that you have high blood pressure? Yes No If yes, how old were you when you were first told that you had high blood pressure? -------------- years old. If no, go to question 11. 12/9/2013 Dr. Tarek Tawfik
  • 121. Wording Clarity, Simplicity, Neutrality Every word in a question can influence the validity and reproducibility of the responses. • • Constructed question should be simple and free of ambiguity. Encourage accurate and honest responses without embarrassing or offending of the respondent. 12/9/2013 Dr. Tarek Tawfik
  • 122. Clarity o o Question must be as clear as specific as possible. Concrete words are preferred over abstract words: How much exercise do you usually get? Is less clear than “ during a typical week, how many hours do you spend exercising (e. g., vigorous walking or sports)?” 12/9/2013 Dr. Tarek Tawfik
  • 123. Simplicity Simple and common wording should be used to convey the idea, avoid technical terms and jargon. “ drugs you can buy without a doctor‟s prescription”. Clearer than “over-the-counter medications”. The sentences should also be simple, using the fewest words and simplest grammatical structure. 12/9/2013 Dr. Tarek Tawfik
  • 124. Neutrality Avoid Loaded words and stereotypes that suggest that there is a most desirable answer. “During the last month, how often did you drink too much alcohol” “During the last month, how often did you drink more than five drinks in one day” Less Judgmental question. 12/9/2013 Dr. Tarek Tawfik
  • 125. Neutrality It is useful to set a tone that permits the respondent to express behaviors and attitudes that may be considered undesirable. “ People sometimes forget to take medications their doctor prescribed. Do you ever forget to take your medications?” 12/9/2013 Dr. Tarek Tawfik
  • 126. Avoid Pitfalls I. II. III. IV. 12/9/2013 Double-Barreled Questions. Hidden assumptions. The question and answer options do not match. Leading questions. Dr. Tarek Tawfik
  • 127. I- Double-Barreled Questions. Each question should contain only one concept :Or or And will lead to unsatisfactory responses. “How many cups of coffee or tea do you drink during a day?”. In this case you should ask two questions to assess two things. 12/9/2013 Dr. Tarek Tawfik
  • 128. II- Hidden Assumptions. “How many cigarettes do you smoke in a day?” “What contraceptives do you use?” 12/9/2013 Dr. Tarek Tawfik
  • 129. III-The question and answer options do not match. “ Have you had pain in the last week” The options are : (never, seldom, often, very often), grammatically incorrect: “ How often have you had pain in the last week?” or the answer should change to (yes, no). 12/9/2013 Dr. Tarek Tawfik
  • 130. The question and answer options do not match. Question about intensity: “ I am sometimes depressed” (agree) (disagree). For those who are often depressed, it is unclear to respond, disagreeing with this statement could mean that the person is often depressed or never depressed. (never, sometimes, and often) should be the options. 12/9/2013 Dr. Tarek Tawfik
  • 131. IV-Leading questions It is the one in which, contents, wording or structure leads a respondent to answer in a certain direction “judgmental questions”. “Unemployment is increasing, isn‟t it?” “Smoking is bad, isn‟t it?” 12/9/2013 Dr. Tarek Tawfik
  • 132. Collecting data using attitudinal scales Dr Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 133. Function of attitudinal scales Attitudinal scales measure the intensity of respondent‟s attitudes towards the various aspects of a given situation or issue and provide a techniques which combine the attitudes towards different aspects into one overall indicator. To develop an overall picture out of various opinions and perspectives. 12/9/2013 Dr. Tarek Tawfik
  • 134. Developing a scale 1. Which aspects is going to be measured? 2. Procedures adopted to combine these aspects to give an indicator for measurement? 3. The validity of such scale? 12/9/2013 Dr. Tarek Tawfik
  • 135. Types of attitudinal scales Summated rating Scale “Likert scale” Differential scale “Thurstone sclae” The cumulative Scale “Guttman scale”
  • 136. I-Likert Scale 12/9/2013 Dr. Tarek Tawfik
  • 137. Basic Research Designs Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 138. Definition of a research design o o o o A traditional research design is a blueprint or detailed plan for how a research study is to be completedOperationalizing variables so they can be measured, Selecting a sample of interest to study, Collecting data to be used as a basis for testing hypotheses and Analyzing the results. „Thyer 1993‟ 12/9/2013 Dr. Tarek Tawfik
  • 139. Types of study design (I) Reference period One Two Experimental Three or more Prospective Nonexperimental Longitudinal Studies Cross-sectional Studies Before and after studies Retrospective Prospective Semiexperimental Study designs Retrospective Nature of investigation Classification base Number of contacts
  • 140. Research designs (II) Did the investigator assign exposure “intervention”? Yes No Observational study Experimental study Comparison group? Random allocation? Yes No Yes Analytical study Randomized Controlled Trial RCT NonRandomized Controlled trial Cohort study Exposure →outcome No Descriptive study Direction? Exposure and outcome at the same time Case-control study Exposure ←outcome Cross-sectional study
  • 141. Phases and indications of basic study designs Type of study Timing Form Crosssectional Cross-sectional Observational Repeated crosssectional Cross-sectional Cohort Case-control C.T Action in past time Action in present time Action in future time Prevalence estimates Collect All information Reference range Current health status Observational Collect Collect Collect All All All information information information Longitudinal (prospective) Longitudinal (retrospective) Longitudinal (prospective) Typical uses Define cohort and assess risk factors Assess Risk factors trace Observe outcome Apply intervention Prognosis and natural history Etiology Etiology particularly for rare diseases Define cases and controls (outcome) follow Experimental over time follow Observational Observational Changes Clinical Observe outcome trials to assess therapy Trials to assess preventive measures Lab. experiments
  • 142. Descriptive Studies The Descriptive Pentad Descriptive studies are „the first toe in the water‟ They concerned with and designed only to describe the existing distribution of variables without regard to causal or other hypotheses. Good descriptive study should answer five basic „Ws”. 12/9/2013 Dr. Tarek Tawfik
  • 143. The Five Ws Ws Who has the disease? What is the condition or disease being studied? Why did the condition or disease arise? Components Age, sex, and other characteristics. A clear, specific, and measurable case definition is essential. Descriptive studies often provide clues about cause that can be pursued with more sophisticated research designs. When is the condition common Time provides important clues about health events. or rare? Where does or does not the disease or condition arise? Geography has a huge effect on health. So what? The implicit W relates to the public health effect.
  • 144. Descriptive Studies Deal with individual Case report Case-series report Cross-sectional prevalence Surveillance Relate to the population Ecological cor-relational studies
  • 145. I- Case Report The least publishable units in the medical literature. o An observant clinician reports an unusual disease or association which prompts further investigations with more rigorous study design. Example: benign hepatocellular adenoma and higho dose contraceptive pills. o Not all case reports deal with serious health threats, however, some simply enliven the generally drab medical literature. 12/9/2013 Dr. Tarek Tawfik
  • 146. What is the most probable diagnosis?
  • 147. II-Case-series report A case series report aggregates individual cases in one report. Sometimes, the appearance of several similar cases heralds an epidemic. Example: a cluster of homosexual men in Los Angeles with a similar syndrome alerted the medical community of HIV/AIDS epidemic in North America. Case-series report is a major trigger for further investigations compared to case report. Can constitute the case group for a case-control study. 12/9/2013 Dr. Tarek Tawfik
  • 148. III- Cross-sectional (prevalence) Studies. Prevalence studies describe the health of populations. Examples: Health and Nutrition Examination Survey (HNES), and Censuses. These studies provide a snapshot of the population at a particular time. Both exposure and outcome are identified at at one point in time. Particularly useful for estimating the point prevalence of a condition in the population: Point prevalence = Number with the disease at a single time point Total number studied at the same time point
  • 149. Design of a Cross-Sectional Study Defined population Begin with Gather data on exposure and disease Exposed: Have disease Exposed: Do not have Disease Not exposed: Have disease Not exposed: Do not have disease End with four possible groups
  • 150. Cross-sectional (prevalence) Studies. Advantages Low costs. No follow up is required. Quick. 12/9/2013 Disadvantages Only association can be inferred “not causation”. Temporal sequence is difficult to ascertain “exposure-outcome sequence”. Incidence can not be estimated “occurrence of new cases over time”. Trend over time can not be identified “change of magnitude/pattern over time”. Dr. Tarek Tawfik
  • 151. Assignment: o o o The New Valley Governorate is located in the Western desert of Egypt; several reports had described a grade II goiter among primary school children, little is known about the prevalence, socio-demographic characteristics of the condition. Some clinicians have proposed observing a large number of cases of renal failure in the Manzala region at the Northern cost of Nile delta, the prevalence and distribution of which are lacking. Little is known about the magnitude of extra pulmonary tuberculosis in Egypt. According to the previous given data give the most appropriate study design?
  • 152. IV-Repeated cross-sectional studies “Longitudinal study”  Studies that may be carried out at different time points to assess trends over time.  These studies involve different groups of individuals at each time point.  It can be difficult to assess whether apparent changes over time simply reflect differences in the group included in the study rather in the condition itself. 12/9/2013 Dr. Tarek Tawfik
  • 153. Longitudinal study design. Study population Study population Interval Data collection Study population Interval Data collection Data collection Study population Interval Data collection Disadvantages: 1. Maturation effect „maturation of responses in young subjects. 2. Reactive effect „instrument educates the respondents‟ 3. Regression towards the mean „shift of extreme attitudes and behavior towards the average‟. 4. Conditioning effect „repeated contacting with same persons‟ 12/9/2013 Dr. Tarek Tawfik
  • 154. V- Surveillance The ongoing systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practices, closely integrated with timely dissemination of these data to those who need to know. Passive Data gathered through the traditional channels e.g., death certificates Active Searching and reporting cases.
  • 155. VI-Ecological Correlational Studies     Look for associations between exposures and outcomes in the population rather than in individuals. Can be a convenient initial search for hypotheses as the data are already collected. Correlation coefficient r, which indicates how linear is the relation between exposure and outcome. The mortality of coronary heart disease correlates with per capita sales of cigarettes.  Inverse correlation between access to safe abortion and maternal mortality rate.
  • 156. Consumption of dietary fat and fast food in certain community. Ecological study High mortality from coronary heart disease (high incidence of MI)
  • 157. Ecological Correlational Studies   The inability to link exposure to outcome in individuals. Controlling of confounders. are the two major limitations of this type of study. Death rates from coronary heart disease is positively correlated with number of color television sets per capita???? 12/9/2013 Dr. Tarek Tawfik
  • 158. VII- Before-and After study design. “pre-test/post-test design”  The most appropriate design for measuring the impact of effectiveness of a program.  Described as a two sets of cross-sectional data collection on the same population to find out the change in the phenomenon or variables between two points in time.  The change is measured by the difference change before and after the intervention.  It could be experimental or non-experimental.  Commonly used in evaluation studies. 12/9/2013 Dr. Tarek Tawfik
  • 159. Program/intervention Study population Study population Time Before/pre observation Data collection Actual or recall After/post Data collection
  • 160. Disadvantages ® Two sets of data collection, more expensive and more difficult to implement. ® Time lapse may cause attrition of participants. ® It only measures total change without ruling out the role of other variables “confounders” ® Maturation of the response of young participants “maturation effect” ® Reactive effect ® Regression effect. 12/9/2013 Dr. Tarek Tawfik
  • 161. Uses of Descriptive Studies Trend analysis. Planning Clues about cause Monitor health of the population, provided by ongoing surveillance: epidemic syphilis in USSR, international epidemic of multiple births, prematurity, caused by assisted reproductive technologies. Health services: Laparoscopy, introduction of Anti HIV/AIDS therapy. Development of hypotheses: retrolental hyperplasia, and painted radium dial watches.
  • 162. Descriptive Studies. Overstepping of the data: Post hoc inference, a temporal association is incorrectly inferred to be a causal one. Intake of 6 cups of coffee /day is associated with lower risk of colonic cancer!!!!  The role of the media,  The damage in the control efforts,  Damage to the public health.
  • 163. Research design in relation to time Now Exposure Outcome Concurrent Exposure Outcome Retrospective Exposure Time Outcome Prospective
  • 164. Finding Your Way in the Terminology Jungle Case-control study Cohort study Concurrent cohort study Retrospective cohort study Randomized trial Cross-sectional study 12/9/2013 = Longitudinal study Prospective cohort Historical cohort = = Dr. Tarek Tawfik Retrospective study Prospective study Concurrent prospective Non-concurrent prospective Experimental study Prevalence study
  • 165. Experimental or Observational Study     Experimental studies involve the investigator intervening in someway to affect the outcome. Clinical trial is an example of an experimental study in which the investigator introduces some form of „treatment, vaccine, new surgical procedure, change in the health policy or introduction of behavioral interventions‟. Other examples include animal studies or laboratory studies that are carried out under experimental conditions. These studies provide the most convincing evidence for any hypothesis as it can possibly control confounders.
  • 166. Experimental or Observational Study    Observational studies „cohort or case-control‟ studies are those in which the investigator does nothing to affect the outcome, but simply observes what happens. These studies provide poorer information than the experimental studies because it is often impossible to control for all factors that may affect the outcome „confounders‟. Epidemiological studies which assess the relationship between factors of interest and disease in the population, are observational.
  • 167. Observational (Analytical) Studies. 12/9/2013 Dr. Tarek Tawfik
  • 168. Bias and Casual Associations in Observational Research. I-Validity and Reliability 12/9/2013 Dr. Tarek Tawfik
  • 169. Definitions : Validity *Internal validity: the ability of the tool/test to measure what it sets out to measure. The inference from participants in a study should be accurate, avoiding systematic errors and bias. Wrong extrapolation to the general population is potentially dangerous. ** External validity: can results from study participants be extrapolated to the reader‟s patients? Including the results into the clinical practice.
  • 170. II-Bias Bias in research denotes deviation from the truth. (when there is systematic difference between the results from study and the truth). All observational studies and badly done randomized controlled trials have built-in bias. The most often used classification of bias includes: I. Selection bias, II. Information bias, III. Confounding. 12/9/2013 Dr. Tarek Tawfik
  • 171. I- Selection Bias Are the groups similar in all important respects? Selection bias stems from absence of comparability between groups being studied. In a cohort study, are participants in the exposed and unexposed groups similar in all important respects except for exposure? In case-control study, are cases and controls, similar in all respects except for the disease in questions? 12/9/2013 Dr. Tarek Tawfik
  • 172. Selection Bias Bias accompanying case-control study: Berkson bias (admission-rate bias): knowledge of the exposure of interest might lead to an increased rate of admission to hospital. Admission preference of disease of interest. Neyman bias (an incidence-prevalence bias): arises when a gap in time occurs between exposure and selection of study subjects. This bias crops up in studies of diseases that are quickly fatal, transient, or sub-clinical. Myocardial infarction and its relation to snow shoveling. 12/9/2013 Dr. Tarek Tawfik
  • 173. Selection Bias  Unmasking bias: An exposure might lead to provoking of an outcome. Estrogen replacement therapy and symptomless endometrial cancer.  Non-respondent bias: In observational studies, non-respondents are different from respondents. Smokers are less likely to return questionnaires than are nonsmokers or pipe and cigar smokers. 12/9/2013 Dr. Tarek Tawfik
  • 174. II- Information Bias Has the information been gathered in the same way? Also known as observation, classification or measurement bias, results from incorrect determination of exposure or outcome or both. Information should be gathered in the same way in any comparative study.
  • 175. II- Information Bias Has the information been gathered in the same way? Sources:  Differentials in information gathering: (bedside for cases while using telephone for control).  Diagnostic suspicion bias: (intensive search for HIV in drug addicts).  Family history bias: Medical information flows differently to affected and nonaffected family members (rheumatoid arthritis). 12/9/2013 Dr. Tarek Tawfik
  • 176. Information Bias Recall bias: cases are motivated to search their memories in order to identify the cause of their illness than the healthy people. Observer bias: one observer consistently under or over reports a particular variable. Meticulous observation of those who are exposed than the non-exposed. 12/9/2013 Dr. Tarek Tawfik
  • 177. Information Bias control  Observer and data gatherer should be blinded.  Using a standardized instruments for data collection,  Proper selection of the subjects are the possible maneuvers to lower the information bias. 12/9/2013 Dr. Tarek Tawfik
  • 178. III- Confounding. Is an extraneous factor blurring the effect? A confounding variable is associated with the exposure and it affects the outcome, but it is not an intermediate link in the chain of causation between exposure and outcome. Oral contraceptive Myocardial infarction Smoking IUD insertion Salpingitis STDs
  • 179. Confounding „Control‟  Restriction (exclusion or specification): Enrollment with restricted selection criteria, including nonsmokers.  Matching: A pair wise matching (for every case who smokes, a control who smokes is found).  Stratification: Used after completion of the study. Results can be stratified by the levels of the confounding factor.  Multivariate analysis techniques: logistic regression, proportional hazard regression, and others. 12/9/2013 Dr. Tarek Tawfik
  • 180. Judgment of Associations Bogus, indirect, or real? Statistical associations do not imply causal associations. Types of associations:  Bogus or spurious associations: Results of selection, information bias and chance.  Indirect association: Stems from confounding.  Real associations. 12/9/2013 Dr. Tarek Tawfik
  • 181. Hill‟s Criteria for Real Associations Temporal sequence: Did exposure precede outcome? the cause must antedate the outcome. Strength of association: How strong is the effect, measured as relative risk (>3 ) or odds ratio (> 1)? Consistency of association: Has effect been seen by others? In different populations with different study designs. 12/9/2013 Dr. Tarek Tawfik
  • 182. Hill‟s Criteria for Real Associations Biological gradient (dose-response relationship): Does increased exposure result in more of the outcome? Lung cancer and years of cigarette smoking. Specificity of association: Does exposure lead only to outcome? “weak criterion, few exposure will only lead to the outcome”. Biological plausibility: Does the association make sense? “weak criterion, limited by our lack of knowledge”. 12/9/2013 Dr. Tarek Tawfik
  • 183. Hill‟s Criteria for Real Associations Coherence with existing knowledge: Is the association consistent with available evidence? The effect of cigarette smoke on the bronchial epithelium of animals is coherent with an increased risk of caner in human. Experimental evidence: Has a randomized controlled study been done? Analogy: Is the association similar to others? 12/9/2013 Dr. Tarek Tawfik
  • 184. Case-control Design Research in Reverse Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 185. Examples of Topics Investigated with Case-control Studies Exposure Cat ownership in childhood Body mass index Physical disability Hiatus hernia Hair dyes History of shingles Pig farming Ghee applied to umbilical cord Pickled vegetables Digital rectal examination Statins for lipid lowering Paracetamol use Phyto-estrogens Male condom use Physical activity Sigmoidoscopy screening Influenza vaccination Outcome Schizophrenia, schizoaffective disorder, or bipolar disorder Pancreatic cancer Earthquake mortality Reflux oesophagitis Connective tissue disorders Systemic lupus eryhtematosus Nipah virus infection Neonatal tetanus Esophageal cancer Metastatic prostate cancer Dementia Ovarian cancer Breast cancer prevention Genital warts Ovarian cancer Colon cancer Recurrent myocardial infarction prevention
  • 186. Case-Control Studies Structure A case-control study compares the characteristics of a group of patients with a particular disease outcome (the cases) to a group of individuals without a disease outcome (the control), to see whether any factors occurred more or less frequently in cases than the controls.  Such retrospective studies do not provide information on the prevalence or incidence of disease but may give clues as to which factors elevate or reduce the risk of disease. 12/9/2013 Dr. Tarek Tawfik
  • 187. Basic structure of case-control design Population Diseased Unexposed to factor (b) Diseased (cases) Sample The Odds “chance of exposure Is calculated between both groups Exposed to factor (a) Disease-free Exposed to factor (c) Disease-free (controls) Unexposed to factor (d) Trace Past time Present time Starting point
  • 188. Calculate the difference in Odds for the included exposures for comparison. Calculate the difference in Odds for the included exposures for comparison.
  • 189. 12/9/2013 Dr. Tarek Tawfik
  • 190. Selection of Cases Cases Incident cases Patients who are recruited at the time of diagnosis 1. Less recall bias 2. Less altered behavior 3. But, we have to wait to be diagnosed Prevalent cases Patients who were already diagnosed before entering the study 1. Recall bias 2. Altered behavior 3. Risk factors may be related more to survival
  • 191. Selection of Cases Hospital patients Patients in Physician‟s practices Clinic patients Problems: * Single or multiple hospitals; Some hospitals have an aggregation of certain risk factors than others. * Tertiary Health Care Facility; A tendency to select severely ill cases, any risk factors identified may be only found in these severe forms of the disease.
  • 192. Selection of Controls Non-hospitalized persons Community-based Probability sample School rosters Selective service list Insurance company list Neighborhood controls: Door-to-door approach Or random digit dialing (Socio-economic, cultural) Hospitalized persons Best-friend control: Similarity in demographic Characteristics (lifestyle pattern) Spouse or sibling controls: Sibling control may provide Some control over genetic Difference between Cases and controls Captive population: They represent a sample of ill population. Hospital patients are differ from people in the community. A sample of all other patients, admitted or to select a specific other diagnoses?
  • 193. Problems in Controls Selection   When a difference in exposure is observed between cases and controls, We must ask whether the level of exposure observed in the controls is really the level expected in the population in which the study was carried out or whether-perhaps (due to the manner of selection)- The controls may have a particularly high or low level of exposure that might not be representative of the level in the population in which the study was carried out. 12/9/2013 Dr. Tarek Tawfik
  • 194. Distribution of Cases (cancer pancreas) and Controls by Coffeedrinking Habits and Estimates of Risk Ratios Coffee consumption (cups/day) Sex Category Male Females 0 1-2 3-4 >5 Total No. of cases No. of controls Adjusted RR 95 % CI 9 32 1.0 - 94 119 2.6 1.2-5.5 53 74 2.3 1.0-5.3 60 82 2.6 1.2-5.8 216 307 2.6 1.2-5.4 No. of cases No. of controls Adjusted RR 95 % CI 11 56 1.0 - 59 152 1.6 0.8-3.4 53 80 3.3 1.6-7.0 28 48 3.1 1.4-7.0 151 336 2.3 1.2-4.6
  • 195. Estimates of Relative Risk of Cancer of the Pancreas Associated with use of Coffee and Cigarettes Coffee drinking (cups/day) 0 1-2 >5 Total Never smoked Ex-smokers Current smokers 1.0 1.3 1.2 2.1 4.0 2.2 3.1 3.0 4.6 1.0 1.3 1.2 (0.9-1.8) Total “RR/95% CI” 1.0 1.8 (1.0-3.0) 2.7 (1.6-4.7) Cigarette smoking status
  • 196. Matching  The process of selecting controls so that they are similar to the cases in certain characteristics, such as age, race, sex, socioeconomic status, and occupation.  To nullify the difference in characteristics or exposures other than that has been targeted for study. 12/9/2013 Dr. Tarek Tawfik
  • 197. Types of Matching Group Matching (frequency) Selection of controls: Proportion of controls with certain characteristics identical to proportion of cases; 25% of cases are married, then 25 % of controls are married. All cases should be selected first, and calculation of proportions are made. Individual Matching (matched pairs) For every case included an identical matched control should be selected; 45 year old white female case, we seek for 45 year white female control. used in hospital-based case-control studies
  • 198. Problems with Matching Practical problems Matching of too many characteristics is very difficult or impossible to identify an appropriate control. A 48-years old black female, married, has 4 children, lives in zip code 21209, and work in photo-processing plant Find her control? Conceptual problems Once we have matched controls to cases to a given characteristics, we can not study that characteristics. Marital status and cancer breast, if matching occur as regard marriage, we can not be able to study of that factor „marital status‟. Why? Matching ensures the same prevalence of that characteristic in both cases and controls.
  • 199. Uses of Multiple Controls In case-control studies we usually use more than one control per case to increase the power of the study. 12/9/2013 Dr. Tarek Tawfik
  • 200. 1-Multiple controls of the same type. The power of the study is increasing by including more controls for each case up to 4 controls per case. Why not keep the ratio of controls to cases 1:1 and just increase the number of cases? 1. For many rare disease „cancer, connective tissue disorders‟ the number of the cases are limited for study. 2. In addition, with the limited time frame of the study that does not allow more inclusion of cases and 3. In the absence of multi-centric collaboration, the option remained is to increase the number of controls. 12/9/2013 Dr. Tarek Tawfik
  • 201. 2-Multiple Controls of Different Types The use of hospital and neighborhood controls:  To assess the level of exposure among the different controls group in relation to the cases.  Comparing cases with hospital controls, then cases to neighborhood controls to assess discrepancy in the level of exposure, and if present, the reason should be thought. 12/9/2013 Dr. Tarek Tawfik
  • 202. Nested Case-Control Studies Population (Cohort) Time Develop disease Cases Initial data and/or specimen obtained Do not develop Disease Subgroup Selected as controls
  • 203. Advantages of Nested Case-Control Design Interviews are performed at the beginning of the study (baseline), the data are obtained before any disease has develop, the problem of possible recall bias is eliminated. If abnormalities in biologic characteristics are found „specimens obtained years before the development of clinical disease‟ , it is more likely that these findings represent risk factors or other pre-morbid characteristics than a manifestation of early, subclinical disease. Temporal association can not be concluded from the ordinary case-control design. More economical to conduct.
  • 204. Assignments:  The risk factors for end-stage renal disease are largely unknown, describe a study to identify such factors?  The prevalence of iodine deficiency disorders showed a geographic discrepancy between Jeddah and Qaseem, mention a design to explore such discrepancy.  Cross-sectional study reported a difference in the dietary fat intake among obese subject, how to confirm such difference? 12/9/2013 Dr. Tarek Tawfik
  • 205. Cohort Study Design Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 206. Cohort study (marching towards outcomes)  The term cohort has military, not medical roots.  A cohort was a 300-600-man unit in the Roman army, ten cohorts formed a legion.  A cohort study consists of bands or groups of persons marching forward in time from an exposure to one or more outcomes. 12/9/2013 Dr. Tarek Tawfik
  • 207. Basic Structure of cohort study Diseased Disease-free The Relative Risk is calculated for exposure Develop Disease (a) Sample Exposed to factor Develop Disease (c) Diseasefree Unexposed to factor Disease-free (d) Future time Present time Starting point Disease-free (b) Follow Comparing the incidence of disease in each group Population
  • 208. Incidence of cancer lung Cohort Incidence of cancer lung 12/9/2013 Dr. Tarek Tawfik
  • 209. Direction Time Prospective Exposure Exposure Outcome Retrospective Outcome Exposure Exposure Outcome Time Short/long term effects Outcome Ambi-directional
  • 210. Design of Cohort Then follow to see whether Disease develops Exposed Disease does not develop Totals a b a+b First select Not exposed c d c+d Incidence rate of disease a a+b c c+d
  • 211. Data collection in cohort: forwards and backwards A cohort study follow-up two or more groups from exposure to outcome. In the simplest form, it compares the experience of a group exposed to some factor with another group not exposed to that factor. The frequency of the outcome „whether higher or lower‟ in relation to the unexposed, will gives the evidence of association between exposure ad outcome. In general, the cohort should always moves in the same direction, although the data gathering might not.
  • 212. Cohort versus Randomized Trials Both types compare exposed with non-exposed groups (or a group with a certain exposure to a group with other exposure). Because of ethical and other reasons, we can not randomize people to receive a putatively harmful substance (carcinogens), the exposure in RCTs is often a treatment or preventive measure. In cohort studies investigating etiology “exposure” is often to a toxic or carcinogenic agent. The difference between the two design is the presence or absence of randomization which is critical in interpreting the study findings.
  • 213. Selection of Study Population Comparison of outcomes in an exposed group and non-exposed group (or a group with a certain characteristic and a group without) Select a defined population before any of its members become Create a study Population by exposed or before their exposures selecting groups for inclusion are identified selection by on the basis of whether or not factor not related to exposure they were exposed (residence), In both cases we (occupationally exposed took histories wait for the cohorts) or tests and then outcome separate into exposed and non-exposed
  • 214. Types of Cohort Studies (concurrent prospective) Concurrent 2000 Using a defined population (smoking and lung cancer), population of elementary school children. Non randomized 2010 Exposed (smoke) Disease No disease Non-exposed (non-smoker) Disease No disease 2020 Time frame for a hypothetical concurrent cohort study begun in 2000
  • 215. Types of Cohort Studies Retrospective Historical Retrospective 1980 Defined population (old roster of elementary School children found) Non randomized 1990 2000 Exposed (smoke) Disease No disease Surveyed for smoking habit Non-exposed (non-smoker) Disease No disease Time frame for a hypothetical retrospective cohort study begun in 2000
  • 216. Advantages of Cohort Design I. II. III. IV. V. The best way to ascertain both incidence and natural history of a disease (the temporal sequence between the putative cause and outcome is usually clear). Useful in investigation of multiple outcomes that might arise after a single exposure (sometimes misleading). Useful in the study of rare exposures. Reduce the risk of survival bias (diseases that are rapidly fatal are difficult to study because of this factors). Allow calculation of incidence rates, relative risks, and confidence intervals. VI. Other outcome measures include life table rates, survival curves and hazard ratios.
  • 217. Potential Biases in Cohort Studies 1) 2) Bias in assessment of the outcome (blinding or masking is used to avoid). Information bias (particularly in historical or retrospective cohort). 3) Bias from non-response and losses to follow-up (attrition). 4) Analytic bias (blinding is needed). 12/9/2013 Dr. Tarek Tawfik
  • 218. When Is A Cohort study Warranted? A. B. C. When a good evidence suggests an association of a disease with a certain exposure (from clinical observations or case-controls or other types of studies). When are able to minimize attrition of the study population. When the interval between exposure and development of outcome is relatively short. 12/9/2013 Dr. Tarek Tawfik
  • 219. What To Look For In Cohort Studies Who is at risk? All participants in a cohort study must be at risk of developing the outcome. Who is exposed? Clear, unambiguous definition of exposure at the outset is required (sometimes quantifying the exposure by degrees, rather than yes/no). Who is an appropriate Unexposed should be similar to the exposed in all control? aspects except for the exposure. Either internal or external sources. The healthy worker effect. Have outcomes been assessed equally? Outcomes must be defined in advance; should be clear, measurable and specific.
  • 220. Reporting of Cohort Studies      The first table in reports should provides demographic and other prognostic factors for both groups with hypothesis testing (P value), to show the likelihood that observed differences could be due to chance. For dichotomous outcome measures (sick/well), provide raw data sufficient for the reader to confirm the results. For cumulative incidence: calculate the proportion who develop the outcome during the specified study interval. For incidence rates, the value is expressed per unit of time. The relative risks, and confidence intervals should be provided. Use of P values should not replace interval estimation (relative risk with confidence).
  • 221. How to Choose the Study Design? Study Design Cross-sectional Case- Control Selection of subjects by status Information collected on Exposure Information collected on Disease No Current Current Disease Past Current Cohort:  Prospective Exposure Current Future  Retrospective Exposure Past Current
  • 222. How to Choose the Study Design? (cont.) Case-Control Concurrent Cohort Retrospective Cohort Study time Short Long Short Cost Low High Low Rare diseases Yes No No Sample Size Small Large Large Loss to follow up No Yes Yes Incidence No Yes Yes Approx. Yes Yes Options Relative Risk
  • 223. Experimental study design Dr Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 224. Experimental study designs Experimental studies Treatment / Intervention/ Program Exploration Randomization Study population Causes/associations Non Exploration Outcome/ Impact/ Change Effect Non-experimental studies Experimental: starts from the cause to effect. Non-experimental: starting from the effects to trace the cause. Semi (Quasi) experimental: a mix of both.
  • 225. The concept of Randomization Randomization Study population Group A Or Randomization Or Study population Group B Any individual or unit of study population has an equal and independent chance of becoming a part of an experimental or control group, or in the case of multiple treatment modalities, any treatment has an equal and independent chance of being assigned to any of the population groups.
  • 226. The control group design “the control experimental design” Independent variable Experimental group Study population Intervention arm Study population Study population No intervention Control group Study population Baseline Data Measuring dependent variables “outcome” The chief objective of the control group is to quantify the impact of extraneous factors “possible confounders”, which help to ascertain the impact of the intervention only.
  • 227. The placebo design  A patient‟s belief that is receiving treatment can play an important role in recovery from an illness even if treatment is ineffective “psychological effect known as placebo effect”  The placebo design attempts to determine the extent of this effect.
  • 228. The placebo design Experimental Group Treatment/placebo/ confounders Treatment Placebo/ confounders Placebo Group Placebo Placebo Group Treatment+ Placebo (-) Treatment+ Confounders Placebo Confounders Control Group Experimental Group Control Control Group Treatment Outcome Confounders (-)
  • 229. Cross-over comparative design  Denial of treatment to the control group is considered unethical.  Denial of treatment may be unacceptable to some individuals in the control group, which could result in drop out of cases.  The cross-over design experimental design makes it possible to measure the impact of a treatment without denying treatment to any group.  Design is based upon the assumption that participants at different stages are similar in terms of their characteristics and the problem for which they are seeking intervention. 12/9/2013 Dr. Tarek Tawfik
  • 230. Cross-over experimental design Outcome Drug A Outcome Drug A Non Non Outcome Outcome Study population Placebo Placebo Non Washout Period Non
  • 231. Blind Blind Blind Blind
  • 232. Meta-analysis and systematic review. 12/9/2013 Dr. Tarek Tawfik
  • 233. Estimating Risk Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 234. Absolute Risk The incidence of a disease in a population is termed absolute risk.    Can indicate the magnitude of the risk in a group of people with a certain exposure, but: It does not take into consideration the risk of disease in the nonexposed individuals, It does not indicate whether the exposure is associated with an increased risk of disease. Absolute risk doe not stipulate an explicit comparison. Rubella in 1st trimester: what is the risk that my child will be malformed? Abortion will be decided on the basis of this information. 12/9/2013 Dr. Tarek Tawfik
  • 235. Determination that a certain disease is associated with a certain exposure. By using the case-control and cohort studies we can assess whether there is an excess risk of disease in persons who have been exposed. We have to compare the different risks among different groups to assess the presence of excessive risk (by calculating the incidence rate „attack rates‟ and the difference in the risks). So, estimation of relative risks are vital in determining who will be at a higher risk following the exposure. 12/9/2013 Dr. Tarek Tawfik
  • 236. Relative Risk (concept) o Both case-control and cohort studies are designed to determine whether there is an association between exposure to a factor and development of a disease. If an association exists, how strong is it? o If we carry out a cohort study, we can put the question another way: what is the ratio of the risk of disease in exposed individuals to the risk of disease in nonexposed individuals? This ratio is called the relative risk. Relative risk = Risk in exposed Risk in non-exposed
  • 237. Interpreting the Relative Risk (measure the strength of the association) If RR = 1 If RR > 1 If RR < 1 Risk in exposed equal to risk in nonexposed (no association). Risk in exposed greater than risk in nonexposed (positive association; possibly causal). Risk in exposed less than risk in nonexposed (negative association; possibly protective).
  • 238. Calculating the Relative Risk in Cohort Studies Then follow to see whether Disease develops a First select a+b b c d Totals a+b Incidence rate of disease a a+b Exposed No exposed a Disease does not develop = incidence in exposed c c+d c+d c c+d = incidence in non-exposed
  • 239. Hypothetical Cohort 3,000 smokers and 5,000 non-smokers to investigate the relation of smoking to the development of coronary heart disease (CHD) over a 1-year period. Develop CHD Do not develop CHD Totals Incidence per 1,000/year Smoke cigarettes 84 2,916 3,000 28.0 Do not smoke cigarettes 87 4,913 5,000 17.4 Incidence among the exposed= 84/3,000 = 28.0 per 1,000 Relative risk = Incidence in exposed Incidence in non-exposed = Incidence among the non-exposed = 87/5000 =17.4 per 1,000 28.0/17.4 = 1.61
  • 240. Example: the British Heart Study A large cohort study of 7735 men aged 40-59 years randomly selected from general practices in 24 British towns, with the aim of identifying risk factors for ischemic heart disease. At recruitment to the study, the men were asked about a number of demographic and lifestyle, including information on cigarette smoking habits. Of the 7718 men who provided information on smoking status, 5899 (76.4 %) had smoked at some stage during their lives (including those who were current smokers and those who were ex-smokers). Over subsequent 10 years, 650 of these 7718 men (8.4 %) had a myocardial infarction (MI). 12/9/2013 Dr. Tarek Tawfik
  • 241. MI in subsequent 10 years Yes No Total Ever smoked 563 (9.5%) 5336 (90.5%) 5899 Never smoked 87 (4.8%) 1732 (95.2%) 1819 Total 650 (8.4%) 7068(71.6%) 7718 Smoking status at baseline The estimated relative risk= (563/5899) (87/1819) = 2.00 CI = 1.60-2.49 (does not include 1) The middle aged man who has ever smoke is twice as likely to suffer a MI over the next 10 years period as a man who has never smoked.
  • 242. The Odds ratio (relative odds)  In order to calculate a relative risk, we must have values for the incidence in the exposed and non-exposed, as can be obtained in the cohort study.  In a case-control study, however, we do not know the incidence in the exposed population or the incidence in the non-exposed population because we start with diseased people (cases) and non-diseased people (controls).  Hence, we can not estimate the RR in case-control study directly and we implement another measure of association called Odds ratio.
  • 243. Defining the Odds ratio in Cohort and in casecontrol studies. Suppose we betting on a horse named Little Beauty, which has a 60% probability of wining the race (P). Little Beauty, therefore has a 40 % probability of losing (1-P). What are the odds that the horse will win the race? The odds is defined as: the ratio of the number of ways the event can occur to the number of ways the event can not occur. Odds = Probability that Little Beauty will win the race Probability that Little Beauty will lose the race Odds = P/(1-P) or 60 %/40 % = 1.5:1 = 1.5 Probability of wining is 60 %, while the odds of wining is 1.5 times. 12/9/2013 Dr. Tarek Tawfik
  • 244. Odds Ratios in Case-Control and Cohort Studies Cohort Exposed Not exposed Develop disease Do not develop disease a c Odds ratio= Odds that an exposed person Develops disease Odds that a non-exposed Person develops disease = a/b c/d = ad bc b d Case-control Cases Controls History of exposure a b No history of exposure c d Odds ratio = Odds that a case was exposed Odds that a control was exposed = a/c b/d = ad bc
  • 245. Example: HRT    A total of 1327 women aged 50 to 81 years with hip fractures, who lived in a largely urban area in Sweden, were investigated in this un-matched casecontrols study. They were compared with 3262 controls within the same age range selected from the National register. Interest was centered on determining whether postmenopausal hormone replacement therapy (HRT) substantially reduced the risk of hip fracture. The results in the table show the number of women who were current users of HRT and those who had never used or formerly used HRT in cases and controls.
  • 246. Current users of HRT Never used HRT/ former user of HRT Total With hip fracture (cases) 40 (14%) 1287 (30%) 1327 Without hip fracture (controls) 239 3023 3262 Total 279 4310 4589 The observed Odds ratio = (40X3023) (239X1287) =0.39 C.I = 0.28 to 0.56 A postmenopausal woman in this age range in Sweden who was a current user of HRT thus had 39 % of the risk of hip fracture of a woman who had never used or formerly used HRT Being current user of HRT reduced the risk of hip fracture by 61%.
  • 247. When is the Odds Ratio a Good Estimate of the Relative Risk? In case-control, only the odds ratio can be calculated as a measure of association, whereas in a cohort, either the relative risk or the odds ratio is a valid measure of association. Nevertheless, estimate of RR can be used in interpreting casecontrol study in the following occasions: When the cases are representative, with regard to history of exposure, of all people with disease in the population from which the cases are drawn. When the controls are representative with regard to history of exposure, of all people without the disease in the population from which the cases were drawn. When the disease being studied dose not occur frequently.
  • 248. Odds Ratios and Relative risk Disease develops Exposed Not exposed Do not develop disease Total 200 9800 10,000 10,000 100 9900 Relative risk= 200/10,000 100/10,000 =2 Odds Ratio= 200X9900 100X9800= 2.02 Develop disease Do not develop disease Total Exposed 50 50 100 Not exposed 25 75 100 Relative Risk = 50/100 25/100 =2 Odds ratio = 50X75 25X50 =3
  • 249. Remember    The relative odds (odds ratio) is a useful measure of association in and of itself, in both case-control and prospective studies “Cohort”. In a cohort study, the relative risk can be calculated directly. In a case-control study, the relative risk cannot be calculated directly, so that the relative odds or odds ratio (cross-product ratio) is used as an estimate of the relative risk when the risk of the disease is low. 12/9/2013 Dr. Tarek Tawfik
  • 250. Calculating the Odds ratio in a Matched Pairs CaseControl Study. According to the type of exposure, case-control study can be classified into four groups: - pairs in which both cases and controls were exposed. Concordant pairs - pairs in which neither the cases nor the controls were exposed. - pairs in which the case was exposed but the control was not. Discordant pairs - pairs in which the control was exposed and the case was not. 12/9/2013 Dr. Tarek Tawfik
  • 251. 2X2 table Control Cases Exposed Not exposed Exposed a Both the case and control were exposed b The case was exposed and the control was not Not exposed c The case was not exposed and the control was exposed d Neither the case nor the control was exposed Calculation entail the discordant pairs only (b and c), we ignore the concordant pairs, because they do not contribute to our knowledge of how cases and controls differ in regard to past history of exposure. The odds ratio will then equals = b /c
  • 252. Case-control study of brain tumors in children. o o A number of studies have suggested that children with higher birth weights are at increased risk for childhood cancer. In the next analysis, exposure is defined as birth weight greater than 8 lbs. Normal control Cases 8+ lbs < 8lbs 8+ lbs 8 18 26 < 8 lbs 7 38 45 Total 15 56 71 Odds ratio = 18/7 = 2.57 2= 4.00 P = 0.046 12/9/2013 Total Dr. Tarek Tawfik
  • 253. Attributable Risk How much of the disease that occurs can be attributed to a certain exposure? Attributable risk is defined as the amount or proportion of disease incidence (or disease risk) that can be attributed to a specific exposure. How much of lung cancer risk experienced by smokers can be attributed to smoking? More important than RR as it addresses important clinical practice and public health. How much of the risk (incidence) of disease can we hope to prevent if we are able to eliminate exposure to the agent in question? 12/9/2013 Dr. Tarek Tawfik
  • 254. Attributable Risk for the Exposed Group Level of risk 12/9/2013 Exposed Group Background risk In non Exposed group Dr. Tarek Tawfik
  • 255. Incidence due to exposure Incidence not due to exposure In exposed group In the nonexposed group
  • 256. Calculations The incidence of a disease that is attributable to the exposure in the exposed group can be calculated as follow: (incidence in the exposed group) - (incidence in the non-exposed group) Then, what proportion of the risk in exposed persons is due to the exposure? (incidence in the exposed group) - (incidence in the non-exposed group) incidence in the exposed group 12/9/2013 Dr. Tarek Tawfik
  • 257. Attributable Risk for the Total Population What proportion of the disease incidence in a total population (both exposed and non-exposed) can be attributable to a specific exposure? What would be the total impact of a prevention program on the community? Calculations entail: (Incidence in the total population) – (incidence in non-exposed group „background risk‟). In proportion: (Incidence in the total population) – (incidence in non-exposed group „background risk‟). Incidence in total population 12/9/2013 Dr. Tarek Tawfik
  • 258. Example for calculating the attributable risk in the exposed group Smoking status Develop CHD Do not develop CHD Total Incidence per 1,000 per year Smoke cigarettes Do not smoke cigarettes 84 2,916 3,000 28.0 87 4,913 5,000 17.4 Incidence among smokers = 84/3,000 = 28.0 per 1,000 Incidence among non smokers = 87/5,000 = 17.4 per 1,000 The AR = (incidence in exposed group) – (incidence in the non exposed group) = 28.0 – 17.4 /1,000 = 10.6 /1,000???? In proportion = The AR = (incidence in exposed group) – (incidence in the non exposed group) /( incidence in exposed group) = 28.0 – 17.6/ 28.0 = 10.6/28.0 = 0.379 = 37.9 %?????
  • 259. What does this mean?  The attributable risk = 10.6 /1,000, it means that 10.6 of the 28.0/1,000 incident cases in smokers are attributable to the fact that these people smoke.  Thus if we had an effective smoking cessation campaign, we could prevent 10.6 of the 28/1,000 incident cases of CHD that smokers experience.  In proportion, 37.9 % of the morbidity from CHD among smokers may be attributable to smoking and could presumably be prevented by eliminating smoking. 12/9/2013 Dr. Tarek Tawfik
  • 260. Attributable risk in total population The incidence in the total population can be calculated by subtracting the background risk. (incidence in the total population) – (incidence in the non-exposed group),    for calculation we must know the incidence of the disease in the total population (which we often do not know), or all of the following three values, from which we can then calculate the incidence in the total population: The incidence among exposed. The incidence among the non-exposed. The proportion of the total population that exposed (frequently assumed or judged). 12/9/2013 Dr. Tarek Tawfik
  • 261. AR in total population.   Assuming that the incidence in the total population of smoking is 44% (and therefore the proportion of non-smokers is 56%). The incidence in the total population can then be calculated as follows: (incidence in smokers)(% of smokers in the population) + (incidence in non-smokers)(% of non-smokers in population). = (28.0/1,000)(0.44)+(17.4/1,000)(0.56)= 22.1/1,000 Then the AR= 22.1/1,000 – 17.4/1,000 = 4.7/1,000.  It means that, if we an effective prevention program, how much reduction in the incidence of the CHD could be anticipated. 12/9/2013 Dr. Tarek Tawfik
  • 262. AR in total population  Proportion of incidence in the total population = (incidence in the total population) – (incidence in the nonexposed group)/ incidence in the total population = 22.117.4/22.1= 21.3%.  Thus, 21.3 % of the incidence of CHD in this total population can be attributed to smoking, and if an effective prevention program eliminated smoking, the best we could hope to achieve would be a reduction of 21.3 % in the incidence of CHD in the total population which consisting of both smoking and non-smoking. 12/9/2013 Dr. Tarek Tawfik
  • 263. Clinical Trials An introduction Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 264. What is a Clinical Trial? A prospective study comparing the effect and value of intervention (s) against a control in human being. Friedman, 1998 12/9/2013 Dr. Tarek Tawfik
  • 265. Hierarchy of Medical Evidence From weakest to strongest evidence: Case report. Case series. Database studies. Observational studies. Controlled clinical trials. Randomized controlled trial (RCTs). Leon Gordis 2001. 12/9/2013 Dr. Tarek Tawfik
  • 266. Randomized Controlled Clinical Trail The gold standard of research Level of evidence R.C.T s Controlled Clinical trails Observational studies Case reports, case series, and database studies
  • 267. Intervention studies (Clinical Trials)  In an intervention study, the investigator determines which individuals are exposed to the factor of interest (intervention arm) and which are unexposed (control arm). 12/9/2013 Dr. Tarek Tawfik
  • 268. Essential Elements of RCTS Properly designed. Unbiased treatment assignment (randomization). Comparable test groups “similar baseline data”. Intervention and control arms. Follow-up for a specific outcome. 12/9/2013 Dr. Tarek Tawfik
  • 269. Types of RCTS Treatment trials. Preventive trials (vaccine). Diagnostic or screening tests. Trials of health care delivery. Trials of health care policy. 12/9/2013 Dr. Tarek Tawfik
  • 270. Types of Treatment Trials Pharmaceutical (treatment, prevention, biological, synthetic). Device (prosthesis, sensory aids). Procedure (surgery, laser, radiological). Behavior change (smoking cessation, dietary modification, exercise). Other (counseling, information provision). 12/9/2013 Dr. Tarek Tawfik
  • 271. Pharmaceutical Development 12/9/2013 Dr. Tarek Tawfik
  • 272. Clinical Trials Phases – Phase I Purpose: determine basic safety and pharmacological information: I. Route of administration. II. Safe dosage range. III. Toxicity. IV. Pharmacokinetics. oTreat: small numbers of patients over short period of time. oUsually no control group oHealthy adult volunteers or patients who have exhausted all other options (terminal cancer patients) 12/9/2013 Dr. Tarek Tawfik
  • 273. Clinical Trials Phases – Phase II Purpose: evaluate the drug in patients who suffer from the disease or condition that the drug is proposed to treat: Provide preliminary evaluation of efficacy. Identify group of patients most likely to benefit. Collect additional dosage and safety data. Usually comparison group but not always randomized. 12/9/2013 Dr. Tarek Tawfik
  • 274. Clinical Trials Phases – Phase III Purpose: further evaluate the efficacy and safety: Randomized. ⌂ ⌂ ⌂ New agent compared to placebo or current therapy. Usually multi-centeric. Serve as basis for NDA i.e. new drug application for marketing approval. 12/9/2013 Dr. Tarek Tawfik
  • 275. Clinical Trials Phases – Phase IV    Drug is on the market – post surveillance study. Purpose: collect longer term data on safety and efficacy and identify an advantage over other therapies. Conducted for the approved indication, but may evaluate different doses or effects of extended therapy. 12/9/2013 Dr. Tarek Tawfik
  • 276. Outcomes of Trial Phases o Phase I : maximum tolerated dose. o Phase II : biological effect, adverse events. o Phase III : efficacy, adverse events. o Phase IV : long term effectiveness and safety. 12/9/2013 Dr. Tarek Tawfik
  • 277. Measures For Bias Control ☻ Written protocol. ☻ Tested data collection forms, handbooks, manuals of procedures. ☻ Written definitions. ☻ Standard equipment. ☻ Training and certification of personnel. ☻ Independent data entry. 12/9/2013 Dr. Tarek Tawfik
  • 278. Reference population Sampling (Random) Experimental population Sampling procedures Unwilling Willing Screening selection criteria Ineligible Eligible Study population
  • 279. RCTs “Basic Structure” Reference population Random sampling Sample population Randomization Control Outcome No outcome Intervention Outcome No outcome
  • 280. Control arm WHY? effects Spontaneous cure HOW? ⌂ Criteria Historical Ethical 12/9/2013 Dr. Tarek Tawfik Side
  • 281. Examples of control arm Standard care.  Placebo.  Careful follow-up.  Early or late application of same intervention.  Higher or lower dose level.  12/9/2013 Dr. Tarek Tawfik
  • 282. Randomization o Means that subjects recruited from the study population are allocated to either intervention or control arm by chance. o Random 12/9/2013 procedure ≠ haphazard procedure Dr. Tarek Tawfik
  • 283. Why Randomization o Ensures comparability of the two arms regarding known and unknown factors. o Avoid selection bias. o Provides basis for standard statistical analysis. oDifferences in baseline characteristics of the study arms indicate break in randomization. 12/9/2013 Dr. Tarek Tawfik
  • 284. Why Randomization is difficult? Any randomization technique must insure: Every new subject has an equal chance to be allocated to either arms (alternation?!) Nearly equal number of subjects in each arm (coin toss?!). 12/9/2013 Dr. Tarek Tawfik
  • 285. Randomization Techniques I- Fixed allocation randomization: ☺ Simple randomization. ☺ Blocked randomization. ☺ Stratified randomization. II- Outcome adaptive designs: ☻ Play the winner. III- Others. 12/9/2013 Dr. Tarek Tawfik
  • 286. Simple randomization  Sealed envelopes.  Random number tables.  Computer generated. 12/9/2013 Dr. Tarek Tawfik
  • 287. Blocked Randomization I. II. C Blocks containing specific number of participants are generated (5 blocks, each containing 4 participants for a study with total of 20 participants). Within each block, participants are randomly allocated to either arms. T T 12/9/2013 C T T C C T T C C T Dr. Tarek Tawfik C C T C T C T
  • 288. Stratified randomization Control Age<40 Test Enrolled Control Age>40 Test 12/9/2013 Dr. Tarek Tawfik
  • 289. Baseline measurements Useful to check that comparability has been successfully achieved. 12/9/2013 Dr. Tarek Tawfik
  • 290. Design of the trial Methodology section should include the following: I. Patient inclusion criteria. II. Time of patients inclusion in the study. III.Presence of a comparison group. IV. Matching criteria of the two groups. V. Method used for randomization. 12/9/2013 Dr. Tarek Tawfik
  • 291. Blindness Means ensuring that a person “investigator, data collector, or analyst” remains unaware of which arm a subject has been allocated to. 12/9/2013 Dr. Tarek Tawfik
  • 292. Why Blindness? I. II. To reduce selection bias. To avoid bias in outcome measures. Blinding is not possible in all studies so, one needs to consider how important it is, and to what extent it can be achieved. 12/9/2013 Dr. Tarek Tawfik
  • 293. Blindness(continued) Trials are often described as: o Single-blind: the subject participating in the trial. o Double-blind: the subject & investigators (clinician, interviewers, laboratory personnel). o Triple blind: the subject, investigators & the committee (including data entry and analysis) responsible for monitoring outcome. 12/9/2013 Dr. Tarek Tawfik
  • 294. Procedures to be considered Compliance of the subjects can be assessed by: I. Questioning II. Observing III. Check drug Complications. Completeness of follow-up. 12/9/2013 Dr. Tarek Tawfik
  • 295. Complex designs 1- Multiple treatment groups More than 2 different treatments (or doses) may be compared with a control group. Sample population Control 12/9/2013 Drug A Drug B Dr. Tarek Tawfik Drug C
  • 296. Complex designs 2- Cross-over trial o Each subject receives both the active o and control treatments during two periods separated by a wash-out period. 12/9/2013 Dr. Tarek Tawfik
  • 297. Enrolled population Placebo Outcome Drug A No outcome Outcome No outcome Wash-out period Placebo Outcome No outcome Drug A Outcome No outcome
  • 298. Complex designs 3- Factorial design      Used to evaluate the separate and combined effects of two different factors: Group 1: Placebo. Group 2:. Iron Group 3: Folate. Group 4: Iron + Folate Sample population Control Surgery Radiotherapy Surgery+Radio
  • 299. Losses to follow-up (Attrition) 1) One of the most important sources of bias, since those lost may be different from those seen. 2) Compare drop-outs to non-drop-outs. 3) Perform sensitivity analysis. 12/9/2013 Dr. Tarek Tawfik
  • 300. Interpretation of trial 1- Reporting the data. 2- Statistical methods. 3- Statistical analysis. 4- Power. 12/9/2013 Dr. Tarek Tawfik P < 0.05 ??
  • 301. Good RCT should report Clear definition of patients. Comparison group. Randomization and blindness. Outcome criteria and variables. Compliance and completeness. Complications of treatment. Statistical manipulation. 12/9/2013 Dr. Tarek Tawfik
  • 302. Sample Size Calculation  Standard formulae and look-up tables are available to calculate the minimum sample size and ratio of controls to cases.  Some computer packages (Epi-Info, MedCalc) are also available for free (internet). 12/9/2013 Dr. Tarek Tawfik
  • 303. Ethical Issues In RCT The Belmont Report Ethical Principles and Guidelines for the Protection of Human Subjects of Research. It sets the fundamental ethical principles underlying acceptable conduct of research involving human participants: • Respect for persons • Beneficence • Justice 12/9/2013 Dr. Tarek Tawfik
  • 304. Critical Appraisal of Published Medical Research Dr. Tarek Tawfik 12/9/2013 Dr. Tarek Tawfik
  • 305. Consider the study design Consider the outcome variable Consider the predictor variables Consider the methods of analysis Consider the possible source of bias Consider the interpretation of results Consider the utility of the results 12/9/2013 Dr. Tarek Tawfik Steps in evaluation of a published paper Consider the research hypothesis
  • 306. Stepwise Approach for Appraisal. Step 1. Consider the research hypothesis Is there a clear statement of the research hypothesis? Does the study address a question that has clinical relevance? 12/9/2013 Dr. Tarek Tawfik
  • 307. Step 2. Consider the Study Design Is the study design appropriate for the hypothesis? Does the design represent an advance over prior approaches? Does the study use an experimental or an observational design? 12/9/2013 Dr. Tarek Tawfik
  • 308. Step 3. Consider the Outcome Variable Is the outcome being studied relevant to clinical practice? What criteria are used to define the presence of disease? Is the determination of the absence or presence of disease accurate? 12/9/2013 Dr. Tarek Tawfik
  • 309. Step 4. Consider the Predictor Variable How many exposures or risk factors are being studied? How is the presence or absence of exposure determined? Is the assessment of exposure likely t be precise and accurate? Is there an attempt to quantify the amount or duration of exposure? Are biological markers of exposure used in the study? 12/9/2013 Dr. Tarek Tawfik
  • 310. Step 5. statistical methods employed suitable for Are the Consider the Methods of Analysis the types of the variables (nominal versus, ordinal versus continuous) in the study? Have the levels of type I and type II errors has been discussed appropriately? Is the sample size adequate to answer the research question? Have the assumptions underlying the statistical tests been met? Has chance been evaluated as a potential explanation of the results? 12/9/2013 Dr. Tarek Tawfik
  • 311. Step 6. Consider Possible source of Bias (Systematic Error) Is the method of selection of subjects likely to have biased results? Is the measurement of either the exposure or the disease likely to be biased? Have the investigators considered whether confounders could account for the observed results? In what direction would each potential bias influence the results? 12/9/2013 Dr. Tarek Tawfik
  • 312. Step 7. Consider the interpretation of the results. How large is the observed effect? Is there evidence of a dose-response relationship? Are the findings consistent with laboratory models? Are the effect are biologically plausible? If the findings are negative, was there sufficient statistical power to detect an effect? 12/9/2013 Dr. Tarek Tawfik
  • 313. Step 8. Consider how the results of the study can be used in practice. Are the findings consistent with other studies of the same questions? Can the findings be generalized to other human populations? Do the findings warrant a change in current clinical practice? 12/9/2013 Dr. Tarek Tawfik
  • 314. Thank you 12/9/2013 Dr. Tarek Tawfik