Conducting Research III

Study Design

Hypothesis formation
Hypothesis testing
1. Study Design Descriptive studies Analytical studies Case reportCase serialreportsCross-sectionalstudiesEcological studiesObservational studiesExperimentalstudiesCase-controlstudiesCohort studiesProspectiveRetrospective(historical)RandomizedControlled ClinicaltrialsRandomizedControlled fieldtrialsNon-randomizedexperiments

"There are only a handful of ways to do a study properly but a thousand ways to do it wrong"
Descriptive studies
The investigators merely describe the health status of a population or characteristic of a number of patients.
Description is usually done with respect to time place and person.
Person; who is getting the disease? & who is not? Person characteristics are: Age, sex, race, marital status & socio-economic status (education, occupation & income).
Place; where are the rates of disease highest or lowest?
Time; When does the disease occur commonly or rarely?

Are weak because they make no attempt to link cause and effect and therefore no causal association can be determined.
Are often the first steps to a well designed epidemiological study. They allow the investigator to define a good hypothesis which can then be tested using a better design.
Data provided by descriptive studies are essential for;
Public health administrators {which group(s) or subgroup(s) are more or less affected by the disease}.
Epidemiologists {identification of risk factor(s)}


Descriptive studies are either:
A- Popular studies Ecological studies “Correlational studies”.
B- Individual studies Case report, case series, & cross -sectional.
Ecological studies (Correlational studies)
Here the units of study are populations rather than individuals. For example, when the coronary artery disease (CAD) prevalence rates were compared between different countries, it was found that CAD miss were highest in those countries where mean serum cholesterol values were the highest. CAD rates were very low in countries like Japan (low mean serum cholesterol) while it was very high in countries like Finland (high mean serum cholesterol). This ecological link paved the way for intensive investigation into the association between serum cholesterol and CAD. Another example is the ecological link between malaria incidence and prevalence of sickle cell disease: malaria is rare in areas where sickle cell disease was prevalent.
CAD per 100'000 population in 1 year
Serum cholesterol

The descriptive measure of association in correlational study is ''correlation coefficient'' (r) which ranges from (-1) to(+1).
If r = -ve → inverse association (may be preventive)
If r = +ve → +ve association (may be causal)
If r = 0 → No association.

*Advantages;

a- Quick & inexpensive. b- Use already available data.
c- Usually used as a first step in investigation a possible exposure- out come relation-ship.

*Limitations;

a- In ability to determine the temporal relation-ship between exposure & out come.
b- Lack the ability to control for the effect of confounder.
c- Represent average exposure level rather actual individual level.
d- Formulate the hypothesis but can't test it.

# The presence of correlation doesn't necessarily imply the presence of a valid statistical association.
2- Case report study.
Describe the experience of a single patient. A condition develops in single individual and draws the attention of the clinician or the researcher. It is the first step in disease recognition. Ex; Kaposi sarcoma in healthy homosexual adult.


3- Case series study.
Describe the experience of a group of patients with similar diagnosis.
((Collection of individual case reports))

*Advantages (case report & case series) ;

a- Recognition of new disease e.g. AIDS.
b- Formulation of hypothesis concerning possible risk factor.

*Limitations;

a- Based on experience of one or few patients only.
b- Lack of comparison group.
c- Formulate the hypothesis but can't test it.

4- Cross-Sectional Study (Prevalence Survey);

The exposure & the outcome are assessed simultaneously among individual in well defined population. It is as if we were taking a photo-graph or a slice through the population at a point in time.

Ex; A survey done in a village to identify the number of individuals with hypertension or DM…etc. Here the villagers are screened with blood pressure measurement or blood glucose measurement at one point in time. The frequency of hypertension is then examined in relation to age sex, socioeconomic status, and other risk factors for hypertension.

EX: A researches wished to investigate a possible association between cigarette smoking & CHD in a certain population, 146 young adults were randomly selected, smoking history was taken & an ECG performed for evidence of CHD.

Out-come(CHD)

Total


+ve
-ve

Exposure

(Smoking)
+ve
13
73
86

-ve

2
58
60
Total
15
131
146

*We can calculate the prevalence of disease (CHD) in person with exposure (Smoking) and compare it with the prevalence of disease in person without exposure. Or compare the prevalence of exposure in person with disease to the prevalence of exposure in person without the disease.
*Advantages.
1- Quick, inexpensive and less time consuming.
2- Provide information about the frequency & characteristics of the disease.
3- Provide information about the prevalence of the disease.


*Limitations;
1- Not determine the temporal relation-ship between exposure & out-come.
The main problem with a cross sectional study stems from the fact that both the exposure and the outcome are measured simultaneously. So, even if a strong association is made out between an exposure and the outcome, it is not easy to determine which occurred first, the exposure or the outcome. In other words, causal associations cannot be made based on cross sectional data.
2- Not determine prognostic factor from risk factor.
3- Liable for information bias (recall or interviewer bias).
4- Formulate the hypothesis but can't test it.