What is Research?

What is Research?

Research:Research:A process of Systematic, Scientific A process of Systematic, Scientific

DataData

• Collection• Analysis • InterpretationSo as to find Solutions to a problem

• Qualitative• Quantitative

Steps in Designing and Steps in Designing and ConductingConducting

• Thinking about topic camulating research question/objective

• Matching the research design to research objectives• Defining and clarifying the research variables/analysis plan• Drawing the sample• Developing the tools & defining the methods of data

collection• Monitoring and carrying out the research• Preparing the Data for Analysis• Analyzing data• Writing the research report

Selecting a research topic

Criteria for selecting a research Criteria for selecting a research topictopic

• RelevanceHow big is the problem?How important is it to laak for relevant solutions to it?Are solutions to it available, if so how effective have they been proved?Is the problem of import in our local set up

• InnovationIncase the topic has been researched what new are you looking at

• Feasibility Consider the resources that are required to carry out the project

• AcceptabilityResearch a topic which has the interest and support of the authorities.

• Cost EffectivenessWhether the resources of time, money and manpower being invested in the study are worthwhile

• Ethical- Cultural sensitivity must be given careful consideration- Informed consent ensured- Will treatment be given to individuals identified during study who require treatment?

Priority Ratings for Research Priority Ratings for Research ProposalsProposals

Proposed Topic

Criteria for selectionRelevance Innovation Feasibility Acceptabili

tyCost-effectiveness

Ethical consideration

Total Score


Proposed Topic




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• Literature Search

Literature SearchLiterature SearchWhat?• Allows one to search in a purposeful

and systematic manner, through a range of literature or information relevant to ones particular field, and to hone in on material relevant to ones interest and objectives.

A Literature SearchA Literature SearchWhy?• To keep up with the latest developments

in your field.• To learn more about some topic• To document important facts and ideas

you wish to research in light of previous work done on it.

• To understand your data in the context of what is already known.

• To provide your readers with sources they can consult on their own.

• Research Objective

Research ObjectiveResearch Objective• An objective is an intent of what the

researcher wants to do stated in clear measurable.

Important of Research Important of Research ObjectivesObjectives

• Brings focus to the study.• Avoids collection of unnecessary

data• Determines an appropriate study

desing.• Helps determine analysis plan.

A Good Objective ensures A Good Objective ensures that that

• What is to be measured is clearly stated, be it a measure of frequency, or association in the population of interest.

ExamplesExamplesObjectives:• To determine the frequency of anemia in

pregnant women visiting Tertiary care facilities of Sindh.

• To determine association between maternal smoking and LBW.

• To compare the effectiveness of dressing A vs, dressing B in patients presenting with infected wounds of the foot.

Operational Definition

Operational DefinitionOperational Definition• Is the definition of the exposure and

outcome variables of interest in context to objective in a particular study and their means of measurement / determination.

• Exaples:– Anemia – Effectiveness– PPH– Wound healing

Study Designs

Descriptive StudiesDescriptive StudiesDescriptive studies involve the

systematic collection and presentation of data to give a clear piocture of a particular situation and can be carried out on a small or large scale.

• Case Report• Case series• Cross Sectional Survey

Comparative or Analytical Comparative or Analytical StudiesStudies

• An Analytical Study attempts to establish association or determine risk factors for certain problems. This is done by comparing two or more groups, with or without the outcome of interest/exposure of interest.

• Types:• Observational• Experimental

Case ReportCase Report• A detailed report by a physician of an unusual

disease in a single person.• Classical example is that of a single case reported

in Germany in late 1959 of a congenital malformation affecting the limbs and digits.

• More cases were reported in the following years. In 1961 a hypothesis was put forward that thalidomide, a sleeping pill, was responsible for congenital malformations.

• Subsequent analytic studies confirmed the link between the drug and congential malformation.

Case SeriesCase Series• When several unusual cases all with

similar conditions are described in a published report, this is called a case series.

• A case series does not include a control group.

Cross-Sectional StudiesCross-Sectional Studies• A cross-sectional study is a survey of

a defined population at a single point in time.

• Also called “Prevalence Studies”.• Determines the “Burden of disease”

in a population.• Exposure & outcome are determined

simultaneously.

Design of a Cross-Sectional Design of a Cross-Sectional StudyStudy

Defined Population

Gather Data on Exposure and Disease simultaneously

Exposed: Have

Disease

Not Exposed: Do Not Have

Disease

Not Exposed: Have

Disease

Exposed: Do Not Have

Disease

Cross Sectional Surveys -Cross Sectional Surveys -AdvantagesAdvantages

• Fairly quick and easy to perform.• Inexpensive.• Useful for determining the

prevalence of disease for a defined population and can also measure factors leading to it subsequent to group formations.

Cross-sectional Surveys- Cross-sectional Surveys- DisadvantagesDisadvantages

• Provide only a “snapshot” in time.• The data about both the exposure to

risk factors and the presence or absence of disease are collected simultaneously, hence it is difficult to determine temporal relationship of a presumed cause and effect.

Cohort StudiesCohort Studies• A cohort is a group of people who

have something in common (a characteristics or characteristics suspected of being a precursor to or risk factor for a disease) and who remain part of a group over a period of time.

Types of Cohort StudiesTypes of Cohort Studies• Prospective Cohort Studies• Retrospective Cohort Studies

Prospective Cohort Studies-Prospective Cohort Studies-advantagesadvantages

• Because they are longitudinal, are the study or choice for– Establishing causes of a condition

(temporal relation)– Allows for measurement of incidence

Study of multiple effects of a single exposure.

Prospective Cohort Studies Prospective Cohort Studies DisadvantagesDisadvantages

• With diseaes

Measures of Association

Measures of AssociationMeasures of Association• Relative risk (cohort study)• Odds ratio (case control

Cohort StudiesCohort Studies

A B

C D

Diseased Non Diseased

A+b

C+d

Exposed

Non Exposd

Relative RiskRelative Risk• Incidence in exposed individuals=a/a+b

or proportion of exposed people who developed the disease

• Incidence in non-exposed individuals=c/c+dor proportion of non-express people who develop diseaseRelative Risk= Incidence in exposed

Incidence in non exposed

RR= a/a+b c/c+d

Interpretation or RRInterpretation or RR• Compared to non smokers, the

smokers have a 1.38 times greater risk of developing CHD

Calculating the Relative RiskCalculating the Relative Risk

CHD+CHD- Total

112 176 288

88 224 312

Disease Status

Smoker

Non Smoker

Odds RatioOdds Ratio• Incidence cannot be measured in

case control studies because we start with the diseased people (cases) and non diseased people (controls), hence we calculate OR

Case ControlCase Control

CHD+CHD- Total

112 176 288

88 224 312

Cases

Exposed

Non Exposed

Controls

A+c B+d

A+b

C+d

OR=a/c/b/d or ad/be

• Factors Affecting • Study Outcomes

Passive Smoking & Breast Passive Smoking & Breast CancerCancer

Breast Cancer

No breast cancer

Total

140 (a) 370 (b) 510

40 (c) 234 (d) 274

Exposed (passive Smokers

Non Exposed

Odds=140/40=305 Odds=370/234=1.6

OR=3.5/1.6=2.2

• BIAS

• Bias is:any systematic error that results in an incorrect estimate of the association between the exposure and outcome. Usually introduced by the experimenter or the researcher himself due non-standardized measuring techniques.

• Can Control Bias:• In study design through

Choice of study population data collection:-

Uniform source of information efficient questionnaire development standardization of measurement technique blinding.

Type of BiasType of Bias• Selection Bias observation

(information Misclassification Bias).• Recall Bias• Interviewers Bias• Lost-to-follow up

Confounding Confounding

• The concept of confounding is a central one in the interpretation of any epidemiological study.

• Confounding can be thought of as mixing of the effect of the exposure under study on the disease with that of an extraneous factor.

• This external factor or variable must be associated with the exposure and, independent of the exposure must be a risk factor for the disease.

Example of ConfoundingExample of Confounding

Smoking MI

Age

Table1. Relation of Myocardial Table1. Relation of Myocardial infection (MI) to Recent Oral infection (MI) to Recent Oral

Contraceptive (OC) Use. Contraceptive (OC) Use.

MI+ve MI-veEstimated

relative riskOcYes 29 135 =1.68No 205 1607Total 234 1742

Table2: Age-specific Relation of Myocardial infection Table2: Age-specific Relation of Myocardial infection (MI) to recent Oral Contraceptive (OC) Use.(MI) to recent Oral Contraceptive (OC) Use.

Age (yrs) Recent OC use

MI+ve MI-ve Estimated age-specific relative risk

25-29 YesNo

42

62224

7.2

30-34 YesNo

912

33390

8.9

35-39 YesNo

433

26330

1.5

40-44 YesNo

665

9362

3.7

45-49 YesNo

693

5301

3.9

Total 234 1742

Confounding can be controlled Confounding can be controlled in study design throughin study design through

• RestrictionMatching exposure

• RandomizationConfounding can be controlled in

analysis through• Stratification• Multivariate analysis

Evaluation of the role of Evaluation of the role of chance consists of two chance consists of two

components components

• Hypothesis testing• Estimation of the confidence interval

• The role of confounding, chance and bias have to be evaluated in studies appropriate selection of the population t be studied, with proper study design, so that the results can be applied to other population i.e., they are valid and generalizable.

• Formulation & testing of hypothesis

What is hypothesisWhat is hypothesis• Hypothesis: A testable theory, or

statement of belief used in evaluation of a population parameter of interest e.g. mean or proportion

• There could be only two answers to this question:

• Yes• No

• Suppose a study is being conducted to answer questions about differences between two regimens for the management of diarrhea in children: the sugar based modern ORS and the time-tested indigenous herbal solution made from locally available herbs.

• One question that could be asked is:“ In the population is there a difference in overall improvement (after three days of treatment) between the ORS and the herbal solution?”

Null HypothesisNull Hypothesis• “There is no difference between the

2 regiments in term of improvement” (null hypothesis).

• A null hypothesis is usually a statement that there is no difference between groups or that one factor is not dependent on another and corresponds to the no answer.

Alternative HypothesisAlternative Hypothesis• “There is a difference in terms of

improvement achieved by a three days treatment with the ORS and that of the herbal solution” (alternative hypothesis)

• Associated with the null hypothesis there is always another hypothesis or implied statement concerning the true relationship among the variables or conditions under study if no is an implausible answer. This statement is called the alternative hypothesis and corresponds to the “yes answer”.

Types of alternate Types of alternate hypothesishypothesis

• Directional• Non directional

Why test hypothesisWhy test hypothesis• Hypothesis testing permits generalization

of an association or a difference obtained from a sample to the population from which it came.

• Hypothesis testing involves conducting a test of statistical significance and quantifying the degree to which sampling variability may account for the result observed in a particular study. it entails the following steps.

Types of alternate Types of alternate hypothesishypothesis

• Directional • Non-directional

Steps in Hypothesis TestingSteps in Hypothesis Testing1. Statement of research question in terms

of statistical hypothesis (null and alternate hypothesis)

2. Selection of an appropriate level of significance. The significance level is the risk we are willing to take that a smaple which showed a difference was misleading. 5% significance level means that we are ready to take a 5% significance level means that we are ready to take a 5% chance of wrong results.

Steps in HypothesisSteps in Hypothesis• 3. Choosing an appropriate statistics t

test, z test for continuous data, chi square for proportions etc.

• Test statistics is computed from the sample data and is used to determine whether the null hypothesis should be rejected or retained.

• Test statistics generates p value

P value: indicates the probability or likelihood of obtaining a result at least as extreme as that observed in a study by chance alone, assuming that there is truly no association between exposure and outcome under consideration.

By convention the p value is set at 0.05 level. Thus any value of p less than or equal to 0.05 indicates that there is at most a 5% probability of observing an association as large or larger than that found in the study due to chance alone given that there is no association between exposure and outcome. It p value>0.05 do no reject the null hypothesis.

• Performing calculations and obtaining p value

• Drawing conclusions,, rejecting null hypothesis if the p value is less than set significance level.

αα and and ββTests of Significance

True Ho Hypothesis

FalseHo Hypothesis

Accept Ho Hypothesis

Correct Decision

Wrong Decision β Error

Reject Ho Hypothesis

Wrong Decision α error

Correct Decision

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What is Research?