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Epidemiological approach
- 1. Mrs.Madhurima.D Community Health NursingDepartment Hindu Mission College of Nursing
- 2. Epidemiology isdefined as the study of the distribution and determinants of health related states or events in specified populations and the application of this study to control the health problems. John M.Last 1988.
- 3. 1. A diagnosticphase 2. A descriptive phase 3. An investigative phase 4. An experimental phase 5. An analytical phase 6. An intervention phase 7. A decision-making phase 8. A monitoring phase
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- 5. What isthe event? What is the magnitude? Where did it happen? When did it happen? Who are affected? Why did it happen?
- 6. What canbe done to reduce the problem and its consequences? How can it be prevented? What action to be taken by the community?
- 8. OBSERVATIONAL STUDIES EXPERIMENTAL STUDIES
- 9. Descriptive Studies Analytical Studies ◦ Ecological or co-relational- with Populations as unit of study ◦ Cross-sectional or prevalence -with Individuals as unit of study ◦ Case control or case reference - with Individuals as unit of study ◦ Cohort or follow-up - with individuals as unit of study
- 10. Randomized ControlTrials Field Trials Community Trials
- 11. Descriptive studiesare usually the first phase of an epidemiological investigation. These studies are concerned with observing the distribution of disease or health-related characteristics in human populations and identifying the characteristics with which the disease in question seems to be associated.
- 12. Define the population Define the Disease Describe theDisease Measure and compare Formulate Hypothesis
- 13. CASE CONTROL STUDY Case control studies often called “retrospective studies”. The case control method has three distinct features: Both exposure and outcome (disease) have occurred before the start of the study. The study proceeds backwards from effect to cause; and It uses a control or comparison group to support or refute and inference
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- 15. The features ofcohort studies are: The cohorts are identified prior to the appearance of the disease under investigation The study groups, defined, are observed over a period of time to determine the frequency of disease among them. The study proceeds forwards from cause to effect.
- 16. (a) when thereis good evidence of an association between exposure and disease (b) when exposure is rare, but the incidence of disease high among exposed (c) when attrition of study population can be minimized (d) when ample funds are available.
- 17. Prospective cohortstudies Retrospective cohort studies A combination of retrospective and prospective cohort studies
- 18. The Steps ofa cohort study are: Selection of study objects Obtaining data on exposure Selection of comparison groups Follow-up Analysis
- 19. Types 1. Randomized ControlTrials 2. Non-Randomized Trials
- 20. 1. Uncontrolledtrials 2. Natural Experiments 3. Before & after Comparison studies
- 21. Target Population Targetpopulation refers to all the members who meet the particular criterion specified for a research investigation.
- 22. A singleentity of any given population which is not decomposable further is called as an element. An element may be an individual, a household, a factory, a market place, a school, etc. Element depends on nature of population Population depends on nature of investigation
- 24. A populationis said to be homogenous when its every element is similar to each other in all aspects. Example if the goal of a research is to investigate average IQ of the employs of XYZ Company. The population is homogenous which is composed of people who work at the company.
- 25. Elements arenot similar to each other in all aspects. Common variables that may differ are gender, age, ethnicity, socioeconomic status etc. Example To find if the environment of the Company is satisfactory for its employs. In this case, men and women are likely to keep different opinions
- 27. The processthrough which a sample is extracted from a population is called as sampling. The more the sample is representative of the population, the higher is the accuracy of the inferences and better are the results generalisable.
- 29. The characteristicsof elements selected are similar to that of entire target population. The findings obtained from sample are equally true for the entire target population.
- 30. An incorrector false representation of the sample. The selected sample does not truly reflect the characteristics of population
- 31. Economical Improvedquality of data Quick study results Precision and accuracy of data
- 32. Representative Freefrom bias and errors No substitution and incompleteness Appropriate sample size
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- 35. Every memberof the population has a probability of being included in the sample. Also called as random sampling or representative sampling.
- 36. Example: The targetpopulation is defined as students of 2015-16 batch of MMC It means only those students constitute our population who study at the college during the mentioned period.
- 37. Every unitof population does not get an equal chance of participation in the investigation. It is also called as judgment or non- random sampling The selection of the sample is made on the basis of subjective judgment of the investigator
- 38. EXAMPLE :Iftarget population is defined as college students. It means person studying at any college of the world is an element of our population.
- 39. PROBABILITY SAMPLING Reduces the chanceof systematic errors Minimize the chance of sampling biases. Inferences are generalisable NON PROBABILITY SAMPLING Need less effort. Need less time to finish up Not much costly
- 40. Probability sampling Needa lot of efforts A lot of time is consumed They are expensive. Non probability sampling Encounter with systematic errors and sampling biases. Cannot be claimed to be a good representative Inferences are not generalisable
- 41. Simple random sampling Systematic random sampling Stratifiedrandom sampling Cluster sampling Multistage smapling
- 42. Every elementof the population has an equal chance of being selected in the sample. Every element must be able to distinguish from one another and does not have any overlapping characteristics. The population must be homogenous
- 43. Population hasto be defined Preparation of list of all the elements Selection is done through Lottery method Or random table
- 45. The owner ofCompany X wants to know if his employs are satisfied with the quality of food provided in the company. Target population – every person works in the company (1000) Samples needed (100) Make a list of employees Give numbers to each member Select 100 numbers randomly People corresponding to the numbers are samples
- 46. BENEFITS No possiblesampling bias Good representatives of population DRAWBACKS Very costly and time consuming Needs a lot of efforts It is not possible to get or prepare an exhaustive list of elements
- 47. The elementsare selected at a regular interval. The interval may be in terms of time, space or order. Regularity and uniformity in selection makes the sampling systematic The list of elements may or may not be required
- 48. Population neededto be defined If exhaustive list is available, It is arranged/ numbered in an order 1 to N. Population contains N number of elements and we need a sample of n size. Divide N by n. the answer is K and gives the appropriate interval size For eg if population is 300 elements and we need 30 participants, 300/30=10 Interval size will be 10 so we need to select every tenth element
- 50. A super markethas been advertised through bill board a few meters away from its existence. The owner wants to know how much this advertisement has contributed to bring the costumer to the market. Population – every person who visits the super market Exhaustive list – not possible Include any no of population –eg 3rd or 5th Every 10th person from the 3rd is taken as the samples – eg 13th, 23rd, 33rd
- 51. Benefits: Extension ofsample to the whole population way to get a random and representative sample in the situation where prior listing up of elements is not possible. Draw Backs: It may be very costly and time consuming It needs a lot of efforts especially for a large population. If the order of the list is biased in some way, systematic error may occur.
- 52. This isused when population is heterogeneous. Sub groups are formed that are homogenous The sub groups are called as strata (single stratum) The topic and nature of the investigation tells on what criterion the strata are to be made.
- 53. gender,age, ethnicity,socioeconomicstatus. For eg., if an investigation is taking young adults into account, This population need to be divided into sub groups like male and female educated and uneducated high income and low income etc. Each stratum is a different population
- 54. Define thepopulation Describe the criterions to select the sub- strata Make a list of population Select the samples using lottery or stratified random sampling
- 56. The owner ofa chain of schools wants to know what percentages on an average have been obtained by his grade 10 students in the Board examination. He has six branches of his schools.
- 57. The targetpopulation - every student who studies in grade 10 of any branch of the school. population is heterogeneous The 6 schools are divided into 6 sub groups or strata. Students are now randomly selected from each stratum using systematic random or simple random sampling.
- 58. Benefits: For aheterogeneous population it produces a representative sample Draw Backs It needs a lot of efforts. It is costly and time consuming If the criterion characteristic/ variable used for classification is not selected correctly, the whole research may go in vain.
- 59. The groupof elements residing in one geographical region is called as cluster. Sampling of clusters is called as cluster sampling. It is used when the elements of population are spread over a wide geographical area. The population is divided into sub-groups called as clusters on the basis of their geographical allocation.
- 60. First dividethe population into clusters. Random selection of clusters. The selected clusters are visited. All the elements (may be individuals, households, schools, markets etc. depending on the nature of investigation) within the selected clusters are investigated.
- 62. Education department wantsto inspect quality of education in schools of ABC City. There are twenty five thousand schools in the city; the researcher wants to take a sample of 1000 schools. The city’s population is divided into 21 towns; thus into 21 clusters. A number is allotted to each cluster. Then 7 clusters are selected using simple random sampling.
- 63. Advantage: Reduce costas compare to simple random or systematic random sampling. It consumes less time and efforts than we get a group of elements in one geographical region. Crucial Issues/ Draw Backs: lead to sampling biases and systematic errors. If clusters are not homogeneous among them, the final sample may not be representative of the population.
- 64. Two ormore probability techniques are combined. Used when elements of population are spread over a wide geographical region sampling within the sample. Several stages of sampling is done The final unit or element of population is used in investigation
- 65. Target populationis divided into clusters. The clusters are selected randomly. These clusters are called as first stage units or primary units These clusters are homogenous among them but may be heterogeneous inside To overcome this heterogeneity, homogenous sub groups called as strata are formed. So the strata are called the second stage units or sub-units.
- 66. The formationof these strata can be done using cluster sampling technique or stratified random sampling technique depending on the nature of investigation. In each stratum the units may need to be further divided, for instance market places into shops, buildings into houses etc. The final units obtained are investigated.
- 67. Example: The purposeof a research is to find out the best seller food products brands of the year in the country. In this case the target population is constituted by every market where the food products are sold. So the population is not only spread over a wide geographical region of the country but is also dispersed.
- 68. Divides thecountry into cities; there is a formation of 150 clusters Selects 30 clusters randomly; these form the first stage units The sale of a food product is likely to be impacted by its price; so there is a possibility that people belonging to lower and higher income groups are different in their preference of food products. Thus the researcher divides each city into 3 strata: residence of lower class, middle class and upper class; these strata form the second stage units.
- 69. it isnot possible to take a random sample of elements from each stratum So, the researcher makes clusters within each stratum and then randomly selects clusters from each of the 3 strata. These clusters form the final units of the sample. Each element (i.e. food products selling shops and markets) within the selected clusters are now approached and investigated.
- 71. Advantages: It increasescost and time efficacy. The technique is also useful in overcoming the heterogeneity problem within the clusters. Draw Backs: The sample would not be representative of the population. The whole research may go in vain if strata is not selected appropriately
- 72. Sample sizeis not fixed Investigator usually selects small sample and tries out to make inferences If not drawn the results, adds more subjects untill clear cut inferences can be drawn.
- 73. Association betweensmoking and cancer Smallest sample is taken to draw inferences, if unable to draw any inferences, researcher continues to draw the sample until meaningful inferences are drawn.
- 74. MERITS Used tostudy on smallest representative sample Helps to find out the inferences of the study DEMERITS Not possible to study a phenomenon which needs to be study at one point of time Requires repeated entries into the field to collect the sample
- 75. If populationis finite --- probability sampling If population is infinite ….. Non probability sampling
- 76. If populationis homogenous, & list of elements is available……. Simple random sampling If population is homogenous, list of elements cannot be produced…….. Systematic random sampling If population is heterogeneous, not widely spread ….. Stratified random sampling If target population is homogenous, spread in a wide geographical area…… cluster sampling If population is spread over wide geographical area…… multistage sampling