Types of research studies, advantages and Disadvantages

Prof.Dr.Mulazim Hussain Bukhari
MBBS,DCP,CHPE,MPhil, FCPS, PhD
Director Research, HOD Pathology UCMD, University of Lahore
Types of Research Studies Designs,
Advantages and Disadvantages

In the name of
ALLAH
most gracious, most merciful

Learning Objectives
• What are different types of epidemilogical studies.
• How to conduct these studies
• Practice with the SPSS

• It is the scientific study of factors affecting the health and illness
of populations,
• It serves as the foundation & logic of interventions made in the
interest of public health and preventive medicine.
• It is considered a cornerstone methodology of public health
research, and is highly regarded in evidence based medicine for
identifying risk factors for disease and determining optimal
treatment approaches to clinical practice.
• Occurrence, Transmission, Control of disease
Epidemiology

Components of Epidemiology
• Measure disease frequency
• Quantify disease
• Assess distribution of disease
• Who is getting disease?
• Where is disease occurring?
• When is disease occurring?
Formulation of hypotheses concerning causal and preventive factors
• Identify determinants of disease
• Hypotheses are tested using epidemiologic studies

Three Components of Epidemiology
• Measure disease frequency
• Quantify disease
• Assess distribution of disease
• Who is getting disease?
• Where is disease occurring?
• When is disease occurring?
Formulation of hypotheses concerning causal and preventive factors
• Identify determinants of disease
• Hypotheses are tested using epidemiologic studies

WHAT IS RESEARCH
In the broadest sense of the word, the definition
of research includes a systematical and scientific
attempt for gathering of data, information,
understanding and facts for the advancement of
knowledge.

• To this end, epidemiologists employ a range of study
designs from the observational to experimental,
• with the purpose of revealing unbiased relationships between
exposures such as
• Nutrition,
• Biological agents,
• stress or chemicals to outcomes such as disease, wellness
and health indicators.
Ranging of study design

• the type of problem;
• the knowledge already available about the
problem; and
• the resources available for the study.
The type of study chosen depends on:

The type of study chosen depends on
• Address your research question
• What is Type of problem;
• What is the knowledge already available about the problem; and
• What are the resources available for the study.
• Make sure the study is ethical.
• Work within your budget.
• Make sure the results will be valid

•1) Ensure that it directly addresses your research
question.
•There is no point performing a study which will
not answer the question in hand.
•Many study types can address the same question,
so choose a design carefully.
How do I choose a study type?

(2) Make sure the study is ethical.
• Epidemiology usually involves the active cooperation of
patients.
• They usually participate for the good of research rather
than for any benefit which they stand to gain.
• The ideal study must be ethically sound and ought to
minimize the invasiveness to the participants.

• Epidemiological studies tend to be much larger than other scientific
experiments and resources are always limited.
• Patient recruitment and assessment take time and money.
• You need to consider the cost of collection and testing of biological
samples, telephone calls and postage, and of course salaries--
personnel resources have high costs attached.
• The cost of the research can preclude certain study designs.
(3) Work within your budget.

• The most frequent flaws in epidemiology are bias and
confounding.
• Bias produces incorrect results and can rarely be rectified after
data collection.
• Confounding can be addressed during statistical analysis (number
crunching), provided that sufficient information was gathered
during the study.
• Ways to avoid these two hazards will be discussed in the next
article.
(4) Make sure the results will be valid.

Types of primary studies
• Descriptive studies
• describe occurrence of outcome
• Descriptive studies examine the frequency to which diseases
occur.
• Analytic studies
• Describe association between exposure and outcome
• Analytic studies evaluate the relationship of disease to
different exposures

Basic Question in Analytic Epidemiology
•Are exposure and disease linked?
Exposure Disease

Basic Question in Analytic Epidemiology
•Are exposure and disease linked?
Exposure Disease
Basic designs in epidemiology examine if exposures are
correlated with disease.

Basic Questions in Analytic Epidemiology
•Look to link exposure and disease
• What is the exposure?
• Who are the exposed?
• What are the potential health effects?
• What approach will you take to study the relationship
between exposure and effect?
In order to examine the link of exposure to disease, there needs
to be standardized evaluation of exposure, as well as disease

Research questions may help
•Society will be healthier
•Society can save money on health care
budgets
•It will improve life expectancy
•It will improve the economy

Taxonomy of Epidemiological studies
Analytical
Descriptive
Experimental&
Analytical
Randomization
Randomization
and control trial
Quasi
Experimental
Observational &
Analytical
Incidences an
Surveys
Cross
sectional
Case
control
Cohor
t
Study
Case Report
Case series
Animal
Cross sectional
Prospective Retrospective
Community

Study Design Sequence
Case reports Case series
Descriptive
epidemiology
Analytic
epidemiology
Clinical
trials
Animal
study
Lab
study
Cohort Case-
control
Cross-
sectional
Hypothesis formation
Hypothesis testing

Descriptive Studies
Case-control Studies
Cohort Studies
Develop
hypothesis
Investigate it’s
relationship to
outcomes
Define it’s meaning
with exposures
Clinical trials
Test link
experimentally
IncreasingKnowledgeof
Disease/Exposure

•The descriptive aspect of epidemiological strategies
enable a researcher to describe the pattern of diseases
in terms of person, place and time without using a
control group.
•The causal factors associated with a disease outcome
call for different epidemiological strategies to test the
hypotheses and provide evidence for changing
policies and treatments.
Descriptive type of study design

Non-intervention studies
• in which the researcher just observes and analyses researchable objects or
situations but does not intervene; and
 Descriptive studies
 Analytical studies
Intervention studies
• in which the researcher manipulates objects or situations and measures the
outcome of his manipulations (e.g., by implementing intensive health
education and measuring the improvement in immunization rates.)
Study Designs can be generally divided into

• We will first concentrate on non-intervention studies and their
use in health systems research. We will discuss:
• Exploratory studies
• is a small-scale study of relatively short duration, which is
carried out when little is known about a situation or a
problem. It may include description as well as comparison.
• Descriptive studies
• Comparative (analytical) studies
NON-INTERVENTION STUDIES

• A national AIDS Control Program wishes to establish counseling
services for HIV positive and AIDS patients, but lacks
information on specific needs patients have for support.
• To explore these needs, a number of in-depth interviews are held
with various categories of patients (males, females, married, single)
and with some counselors working on a program that is already
under way.
• Descriptive
• Comparative
Example of exploratory study

•Case Reports
• Case Series
• Cross-sectional
•Incidences
•Surveys etc
Types of Descriptive Study

• Detailed presentation of a single case or handful of cases
• Generally report a new or unique finding
• e.g. previous undescribed disease
• e.g. unexpected link between diseases
• e.g. unexpected new therapeutic effect
• e.g. adverse events 36
Case Report

• Experience of a group of patients with a similar
diagnosis
• Assesses prevalent disease
• Cases may be identified from a single or multiple sources
• Generally report on new/unique condition
• May be only realistic design for rare disorders
37
Case Report

• Advantages
• Useful for hypothesis generation
• Informative for very rare disease with few established risk factors
• Characterizes averages for disorder
• Disadvantages
• Cannot study cause and effect relationships
• Cannot assess disease frequency
Case series

Case Report
Case Series
Descriptive
Epidemiology Study
One case of unusual
findings
Multiple cases of
findings
Population-based
cases with denominator

• The study of the detrimental effects of modern
civilization on the environment, with a view toward their
prevention or reversal through conservation
• Second in our hierarchy comes the ecological study,
• when we compare groups of people not individuals.
• Assuming that associations seen on a group level also hold
on an individual level leads to ecological bias.
Ecological studies
comparative descriptive study

• Consider a study of suicide and religion.
• Higher suicide rates occurred in regions where a higher proportion
of protestants lived.
• To infer that protestants are more likely to commit suicide than
people of other religions may be incorrect.
• Although the rates are higher in the regions with more protestants,
• we do not know the religion of the people committing suicide.
• Suicide could be more common among religious minorities who
live in predominantly protestant regions.
Examples for study

•However, with careful interpretation of results,
ecological studies do have benefits.
•They are generally quick, cheap, and can be
performed from data which are published routinely--
for example, death rates, per caput income, national
food consumption.
Usefulness

• Prevalence measures how much of some disease or
condition there is in a population at a particular point in
time.
• The prevalence is calculated by dividing the number of persons with
the disease or condition at a particular time point by the number of
individuals examined.
• For example, in the study above 6139 individuals completed the
questionnaire were examined).
• Of these 6139 people, 519 currently suffered incontinence and so had
the condition at the particular time point of the study.
• Thus the prevalence of incontinence was 519/6139 = 0.085.
Prevalence and Incidence

• Prevalence quantifies the proportion of individuals
in a population who have the disease at a specific
instant and provides an estimate of the probability
(risk) that an individual will be ill at a point in time
• The formula for calculating the prevalence =
number of existing cases of a disease/ total
population (at a given point in time)
PREVALENCE

• Incidence: The incidence of a disease is another
epidemiological measure.
• Incidence measures the rate of occurrence of new cases
of a disease or condition.
• Incidence is calculated as the number of new cases of a
disease or condition in a specified time period (usually a year)
divided by the size of the population under consideration who
are initially disease free
Incidence

Study Designs -
Analytic Epidemiology
• Experimental Studies
• Randomized controlled clinical trials
• Community trials
• Observational Studies
• Group data
• Ecologic
• Individual data
• Cross-sectional
• Cohort
• Case-control
• Case-crossover

Experimental Studies
• treatment and exposures occur in a “controlled”
environment
• planned research designs
• clinical trials are the most well known experimental
design. Clinical trials use randomly assigned data.
• Community trials use nonrandom data

Observational Studies
• non-experimental
• observational because there is no individual intervention
• treatment and exposures occur in a “non-controlled”
environment
• individuals can be observed prospectively,
retrospectively, or currently

Cross-sectional studies
• An “observational” design that surveys exposures and
disease status at a single point in time (a cross-section of
the population)
time
Study only exists at this point in time

Cross-sectional Design
time
Study only exists at this point in time
Study
population
No Disease
Disease
factor present
factor absent
factor present
factor absent

52
Design of a Cross-Sectional Study
Defined Population
Gather Data on Exposure and Disease simultaneously
Exposed;
Have Disease
Exposed;
Do Not
Have Disease
Not Exposed;
Have Disease
Not Exposed;
Do Not
Have Disease

• Home visits are paid to 400 children between 6-12
months of age.
• Each child is classified on two variables:
– a. whether it is breast-fed today
– b. whether it is sick today with diarrhoeal illness?
1. Cross-sectional study

_____________________________________________
Breastfed Diarrhoeal illness
Yes No Total
_____________________________________________
Yes 16 86 102
No 120 178 298
_____________________________________________
Total 136 264 400
_____________________________________________
We can estimate the Prevalence of breastfeeding as well as the
Prevalence of Diarrhoeal illness:
Prevalence of breastfeeding = 102/400 = 25.5%
Prevalence of diarrhoeal illness = 136/400 = 34%

40
20-
30-
BF Non-BF
Prevalence of diarrhoeal illness in BF and non-BF infants
The statistical significance could preferably be assessed
using a Chi-Square test:
Chi-Square test= (400(16*178-120*86)2/ (102*298*136*264)
= 20.3, p<0.0001

• Physical characteristics of people, materials or the environment, as in
• prevalence surveys (of bilharzia, leprosy, HIV), or Incidences
• evaluation of coverage (of immunization, latrines, etc.),
• Socio-economic characteristics of people such as their age, education, marital
status, number of children and income,
• The behaviour or practices of people and the knowledge, attitudes, beliefs,
opinions which may help to explain that behaviour (KAP studies), or
• Events that occurred in the population.
• Exit polls on voting day are cross sectional studies, where the
population is all voters exiting from a particular polling station.
Examples

• We contact people only once,
• Relatively cheap.
• But that limits their usefulness, since
• we can study only current diseases (prevalence),
• and cannot identify when people first get a disease
(incidence).
• If we are interested in whether a certain behavior may cause a
disease we may infer incorrect results.
• People may change their behavior once they get a disease.
Advantages and disadvantages of this study

• Many cross-sectional surveys focus on describing as well as comparing
groups.
• For example, a survey on malnutrition may wish to establish:
• The percentage of malnourished children in a certain population;
• Socio-economic, physical, political variables that influence the availability of food;
• Feeding practices; and
• The knowledge, beliefs, opinions that influence these practices.
• The researcher will not only describe these variables but, by comparing
malnourished and well-nourished children, he will try to determine which socio-
economic, behavioral and other independent variables may have contributed to
malnutrition.
Cross-sectional comparative studies

Many cross-sectional surveys focus on comparing as well as
describing groups.
For example, a survey on malnutrition may wish to establish:
 the percentage of malnourished children in a certain
population by their:
 Socioeconomic, physical, political differences that may
influence the availability of food
Cross-sectional Comparative studies:

LBW
Yes No
Group A 189 (a) 34 (b) 223
Group A 56 (c) 221 (d) 277
Total 245 255 500
Two groups of pregnant women were enrolled with a BMI <18 in group
A (n=223) and BMI ≥18 (n=277) in group B. Pregnancy outcome was
noted in these groups of women. 189 mothers gave birth to a baby with
low birth weight (LBW) in group A and 56 LBW babies were registered
in Group B.

• A value of Chi square was calculated as 205.89 with one
degrees of freedom giving a highly significant value
(p<0.000001,
• indicating that there is a significant association between
maternal malnutrition and low birth weight babies.
Applying a test of significance, the two proportions were
compared.

• Case control studies select subjects based on their disease
status.
• The study population is comprised of individuals that are
disease positive.
• The control group should come from the same population
that gave rise to the cases.
• The case control study looks back through time at potential
exposures both populations (cases and controls) may have
encountered.
Case control studies

Case control studies
• Case-Control studies represent one form of analytic study that
provides information on the relationship between causal factors and
Disease.
• In a case-control study, subjects who have been suffered are identified
and their past exposure to suspected causal factors is compared with
that of controls (persons who have not been Suffered).
• Many case-control studies ascertain exposure from personal recall,
using either a self administered questionnaire or an interview.
• The validity of such information will depend in part on the subject
matter. People may be able to remember recent events quite well. On
the other hand, long term recall is generally less reliable.

Case-Control Studies
Cases: Disease
Controls No disease

Study
population
Cases
(disease)
Controls
(no disease)
Factor present
Factor absent
Factor present
Factor absent
present
past
time
Study begins here

•Choosing your participants on account of their
disease is the basis of a case-control study.
•On face value, this seems a simple study design,
where cases are people with the condition and
controls are those without.
•Suitable control selection can be tricky, and
unsuitable controls can invalidate your results.
Case-control studies

Case-Control Study
• Strengths of Case-Control Study
• Less expensive and time consuming
• Efficient for studying rare diseases
• Limitations of Case-Control Study
• Inappropriate when disease outcome for a specific exposure is not
known at start of study
• Exposure measurements taken after disease occurrence
• Disease status can influence selection of subjects

• For example, in a study of the causes of neonatal death,
the investigator will first select the ‘cases’ and Controls
(children who died within the first month of life) and
‘controls’ (children who survived their first month of life).
Example

• (S)he then interviews their mothers to compare the
history of these two groups of children, to determine
whether certain risk factors are more prevalent among
the children who died than among those who survived.
Study Design

• Another risk of case-control studies is Recall bias, which occurs if cases and
controls recall past events differently.
• Because we actively choose the cases, a case-control study ensures that we find
enough people when a disease is rare.
• These studies are rarely suitable for investigating causes of death, since dead
people cannot provide vital information.
• Carefully designed case-control studies can provide useful results, and such
studies should not be ignored without a careful evaluation of the methodology
used.
cont

 Suppose that you want to know whether smokers are at an
increased risk of lungs cancer.
 Comparisons are made between the smoking habits (probably
current and past) of cases and controls.
 It is not good choosing controls who have lung cancer or heart
disease, as they will be more likely to be smokers than the
population from which the cases came, and that will distort your
results.
Example 2

• Case control studies are usually faster and more cost effective than
cohort studies, but are sensitive to bias (such as recall bias,
selection bias, confounding variables).
• The main challenge is to identify the appropriate control group; the
distribution of exposure among the control group should be
representative of the distribution in the population that gave rise to
the cases.
• This can be achieved by drawing a random sample from the original
population at risk.
• This has as a consequence that the control group can contain people
with the disease under study, when the disease has a high attack rate
in a population.
Cont

What is ODD Ratio Case exposed to Risk/
control Exposed to Risk
Risk
Disease Outcome Total
Lung cancer
(Cases)
No Lung Cancer
(Control)
Heavy smoker 283(A) 725 (B) 1008
Non Smokers 64 (C ) 1010 (D) 1074
Total 347 1735 2082
Odd Ratio AxD/BxC= 283x1010/725x64=6.16 (Note Less than 2
NS)

A study was carried out to determine whether tonsillectomy was associated
with subsequent development of Hodgkin ’ s disease. 109 cases of
Hodgkin’s disease were identified. 109 controls (without disease) were
identified.
Risk factor
HD No HD
Tonsilectomy + 71(A) 43 (B) 114
No
Tonsilectomy
38 (C ) 66 (D) 104
Total 109 109 218
Odds Ratio = ad/bc = 71 x 66 / 38 x 43 = 2.867

• The odds ratio is one of a range of statistics used to assess
the risk of a particular outcome (or disease) if a certain factor
(or exposure) is present.
• The odds ratio is a relative measure of risk, telling us how
much more likely it is that someone who is exposed to the
factor under study will develop the outcome as compared to
someone who is not exposed.
What is odd ratio

• If the OR is clearly greater than 1, then the conclusion is "those
with the disease are more likely to have been exposed," whereas if
it is close to 1 then the exposure and disease are not likely
associated.
• If the OR is far less than one, then this suggests that the exposure
is a protective factor in the causation of the disease
Interpretation of OR

• A cohort study is an analytical study in which individuals with
differing exposures to a suspected factor are identified and then
observed for the occurrence of certain health effects over some
period, commonly years rather than weeks or months.
• The occurrence rates of the disease of interest are measured and
related to estimated exposure levels.
• Cohort studies can either be performed prospectively or
retrospectively from historical records.
Cohort studies

Timeframe of Studies
• Prospective Study - looks forward, looks to the
future, examines future events, follows a condition,
concern or disease into the future
time
Study begins here

•Prospective - looks forward,
looks to the future, examines future events, follows a
condition, concern or disease into the future
time
Study begins here

Prospective Cohort study
Measure exposure
and confounder
variables
Exposed
Non-exposed
Outcome
OutcomeBaseline
time
Study begins here

• Retrospective Study - “to look back”, looks back in
time to study events that have already occurred
time
Study begins here

•Retrospective Study - “to look back”,
looks back in time to study events that have already
occurred
time
Study begins here

Retrospective Cohort study
Measure exposure
and confounder
variables
Exposed
Non-exposed
Outcome
OutcomeBaseline
time
Study begins here

Cohort Study
• Strengths
• Exposure status determined before disease detection
• Subjects selected before disease detection
• Can study several outcomes for each exposure
• Limitations
• Expensive and time-consuming
• Inefficient for rare diseases or diseases with long
latency

• In a cohort or follow up study, a healthy group of people (cohort) are
identified.
• It is a prospective study
• They are then followed over time to see who develops the disease of
interest and who does not. A group of individuals who are exposed to a
risk factor compared to group who do not have risk
Cohort studies

• The important point to remember about cohort studies is
the time factor that at the beginning of the study neither the
people themselves nor the researchers know who is going
to get what disease.
Cont,

• This effectively avoids recall bias, although other types of bias can
still hinder these studies.
• However, the costs of cohort studies are sometimes prohibitive.
• If you are studying mobile phone use and cancer development you
need to follow up people for a long time before the cancer
becomes evident.
• The resource implications is often why cohort studies are not
chosen in epidemiology.
Cont.

..... Case Non case Total
Exposed A B (A+B)
Unexposed C D (C+D)

Relative Risk factor
Case exposed to Risk/ control Exposed to Risk
Risk in
Healthy peoples
10 years
Lung cancer
(Cases)
No Lung Cancer
(Control)
With exposure
Heavy smoker
60(A) 40(B) 100
Without exposure
Non Smokers
15 (C ) 85 (D) 100
Total 75 125 200
•Exposed group=a/a+b 60%
•Non exposed = c/c+d 15%
Follow up studies, incidence studies, longitudinal study
Induction period can be calculated, incidence rate can be calculated

•Ratio of incidence of the disease (or death) among
exposed and the incidence among non-exposed
(Incidence in exposed / incidence in unexposed).
•It is a direct measure (or index) of the “strength” of
association between suspected cause and effect.
Relative Risk (RR)

• In a simple comparison between an experimental group and a control group:
• A relative risk of 1 means there is no difference in risk between the two
groups.
• An RR of < 1 means the event is less likely to occur in the experimental
group than in the control group.
• An RR of > 1 means the event is more likely to occur in the experimental
group than in the control group.
Interpretation

A cohort of 500 healthy children between the ages of 6 and 12 months
were followed over a period of one year.
312 children were breastfed and during the follow-up they had 89 new
episodes of diarrhoea.
In the rest of the children who were not breastfed, 145 new episodes of
diarrhoea were recorded

Risk in children
Over a period of 1
year
Diarrhea Non Diarrheal Total
No Breast fed 145 (A) 43 (B) 188
(A+B)
Breast fed 89 (C) 223 (D) 312
(C+D)
234 266 500

Incidence of Diarrhoea in non-breastfed gp (Ie)=
145/188 = 0.77
Incidence of diarrhoea in the breastfed gp (Iu) = 89/312
= 0.28
Ratio of two incidences (Ie/Iu) = 0.77 /0.28 = 2.75
= Relative Risk

INTERVENTION STUDIES

• investigator can “control” the exposure
• akin to laboratory experiments except living
populations are the subjects
• generally involves random assignment to groups
• clinical trials are the most well known experimental
design
• the ultimate step in testing causal hypotheses

• In an experiment, we are interested in the
consequences of some treatment on some outcome.
• The subjects in the study who actually receive the
treatment of interest are called the treatment group.
• The subjects in the study who receive no treatment or a
different treatment are called the comparison group.

Epidemiologic Study Designs
• Randomized Controlled Trials (RCTs)
• a design with subjects randomly assigned to “treatment” and
“comparison” groups
• provides most convincing evidence of relationship between
exposure and effect
• not possible to use RCTs to test effects of exposures that are
expected to be harmful, for ethical reasons

Important features of Randmization
The classical experimental study design has
three characteristics:
1.Intervention
2.Control/comparative group
3.Randomization

time
Study begins here (baseline point)
Study
population
Intervention
Control
outcome
no outcome
outcome
no outcome
baseline
future
RANDOMIZATION

Randomized Controlled Trials
•Disadvantages
• Very expensive
• Not appropriate to answer certain types of
questions
• it may be unethical, for example, to assign persons
to certain treatment or comparison groups

• This is a human experiment, where people are randomly assigned to
receive one treatment or the other.
• This treatment is often a drug as clinical trials of drugs are required
before being licensed for prescription.
• The treatment may also be a health intervention, such as a weight
loss or smoking cessation programmed.
• investigate the effect of its use on breast cancer.
Gold standard of epidemiological studiesThe
Randomized controlled trial or clinical trial.

Example
A researcher plans to study the effect of a new drug. (The drug has already been
tested extensively on animals and has been approved for trial use.)
He plans to include 300 patients in the study who are currently receiving the standard
treatment for the same condition for which the new drug has been designed.
He explains the study to the patients asking their consent to be divided into two groups
on a random basis.
One group will receive the experimental drug while the other group will continue to
receive the standard treatment.

• He makes sure that the medications are disguised and labeled in such a manner that neither
the research assistant administering them nor the patient know which drug is used. (This is
called a ‘double blind’ experiment.)
• It is also important that patients, clinicians and others involved in the conduct of
a trial be blinded to (kept unaware of) the group (treatment or control) to which
each patient will be or has been assigned, It is particularly important that
selection bias be avoided by concealing the allocation to treatment or control
group until after the patient has enrolled in the trial; this is called allocation
concealment rather than allocation blinding.
Double Blind

Types and Examples of Clinical Trials
__________________________________________________________
Type Example
__________________________________________________________
Therapeutic/ 1. laser treatment for diabetic retinopathy
drug 2. simple mastectomy for breast cancer
Intervention 1. Antihypertensive drugs to reduce the
risk of developing a stroke.
2. Physical exercise for decreasing the
risk of myocardial infarction.
Preventive 1. BCG vaccination for tuberculosis
2. Isoniazid for prevention of TB

• Preventive trials are essentially conducted
among the healthy population (reducing the
risk of the disease).
• Therapeutic trials are essentially conducted
among the diseased populations (improving
the treatments or survival).

General outline of a protocol for a clinical trial
_________________________________________
• Must start with a clear hypothesis
• Rationale and background
• Specific objectives of study
• Study design (blinding, randomization strategy.
• Types and duration of treatment, number of patients.
• Criteria for including and excluding subjects.

• Outline of treatment procedures.
• Definition of all clinical, laboratory etc methods.
• Methods of ensuring the integrity of data.
• Major and minor endpoints.
• Observing and recording side effects.
• Procedures for handling problem cases.
• Procedures for obtaining informed consent of subjects.
• Procedures for analyzing results.

Reference population
Study or experimental population
Informed consent
Participants Non participants
assigned by randomization
Study Gp A Control Gp B
Receive drug A Receive drug B
Outcome Outcome Outcome?

• Selection Bias
• Sampling bias
• Allocation Bias – Randomization
• Disease ascertainment
• Response Bias
• Avoiding response bias is key to the success of your survey project.
Implementing the above strategies will ensure that your survey delivers valid
data that you will be able to effectively apply to your survey problem.
Main Issues to be controlled

• Compliance
• Follow-up necessary
• Ascertainment of outcome:
• Observation Bias (blinded and Double-blinded) Placebo effect
• Consent (informed and verbal) essential.
• Problems: ethics
• feasibility
Main Issues to be controlled

• The introduction of error due to systematic differences in the
characteristics of those selected to participate in a study, or
receive an intervention.
• Two types of selection bias can be distinguished.
• In sampling bias, error results from failure to ensure that all
members of the reference population have a known chance of
being selected for inclusion in the sample.
Selection bias:

•In allocation bias, error results from systematic
differences in the characteristics of those assigned to
treatment versus control groups in a controlled
study.
• Allowing potential participants to self-select for
participation or for intervention introduces selection bias
Allocation bias

• Write questions that are clear, precise, and relatively short
• Because every question is measuring something, it is important
for each to be clear and precise. Your goal is for each respondent
to interpret the meaning of each survey question in exactly the
same way. If your respondents are not clear on what is being
asked in a question, their responses may result in data that cannot
or should not be applied to your survey goals. Keep questions
short; long questions can be confusing and stressful for
respondents
Techniques for Preventing Response Bias

• A loaded or leading question biases the response
given by the participant. A loaded question is one
that contains loaded words. For example, politicians
often avoid the loaded word “environmentalist”
because it creates a negative reaction in some people
regardless of the content of the statement.
• A leading question is phrased in such a way that
suggests to the respondent that the researcher
expects a certain answer
Do not use “loaded” or “leading” questions

• Don’t you agree that social workers should earn more money than
they currently earn?
Yes, they should earn more
No, they should not earn more
Don’t know/no opinion
• The phrase “Don’t you agree” leads the respondent. A more neutral
wording would be:
Example

• Do you believe social worker salaries are a little lower than
they should be, a little higher than they should be, or about
right?
• Social worker salaries are a little lower than they should be
• Social worker salaries are a little higher than they should be
• Social worker salaries are about right
Don’t know/no opinion
Leading question

• A double-barreled question combines two or more issues or attitudinal
objects in a single question.
• Example
• Do you think professors should have more contact with university staff and
university administrators?
• Clearly, this question asks about two different issues: Do you think professors
should have more contact with university staff? AND Do you think that teachers
should have more contact with university administrators?
• Combining the two questions into one question makes it unclear which attitude is
being measured, as each question may elicit a different attitude. Tip: If the word
“and” appears in a question, check to verify whether it is a double-barreled
question.
Avoid double-barreled questions

• When respondents are asked for their agreement with a statement, double
negatives can occur.
• Example
• Do you agree or disagree with the following statement?
Teachers should not be required to supervise their students during recess.
• If the respondent disagrees, you are saying you do not think teachers should
not supervise students. In other words, you believe that teachers should
supervise students. If you do use a negative word like “not”, consider
highlighting the word by underlining or bolding it to catch the respondent’s
attention.
Avoid double negatives

• Use both mutually exclusive and exhaustive response
categories for closed-ended questions
• Categories are mutually exclusive when there is no overlap:
•
Construction Principles

 What is your current age?
10 or less
10 to 20
20 to 30
30 to 40
40 to 50
50 or greater
 These categories are not mutually exclusive because there is overlap present. For
example, a person who is 20 years old could be placed into two separate categories
(same with those respondents aged 30, 40 and 50).
Example

 Categories are exhaustive when there is a category available to all potential responses.
Below is an example of a question where categories are not exhaustive:
 What is your current age?
1 to 4
5 to 9
10 to 14
The categories are not exhaustive because there is no category available for respondents
more than fourteen years old or respondents less than one year old.
Exhaustive

• Here is an example of response categories that are both
mutually exclusive and exhaustive:
• What is your current age? (Check one box only.)
Less than 18
18 to 29
30 to 39
40 to 49
50 or older
Example

• A response set is the tendency for a respondent to answer a series of
questions on a certain direction regardless of their content.
• One technique used to prevent response sets is to reverse the wording in
some of the survey items. Below is an example of this in a rating scale
question:
Reverse the wording in some of the questions to help prevent
response sets.

Please rate your manager on each of the following descriptive
scales.
Place a checkmark on the space
between each pair of words that best indicates your opinion:
Sociable 1 2 3 4 5 Unsociable
Kind 1 2 3 4 5 Cruel
*Hard 1 2 3 4 5 Soft
Successful 1 2 3 4 5 Unsuccessful
*Wise 1 2 3 4 5 Foolish
Strong 1 2 3 4 5 Weak
You can see that items 3 and 5 (with asterisks) are “reversed”
when compared to the rest of the items, i.e., most of the left-
hand descriptors are associated with positive attributes while the
right-hand descriptors are associated with negative attributes

Patients with haemorrhoids
Random Allocation
High-fibre diet Haemorrhoidectomy
Pain and Pain and
bleeding 50% bleeding 30%
Well 50% Well 70%

• In this study one characteristic of a true experiment is
missing,
• Either randomization or
• the use of a separate control group.
• A quasi-experimental study, however, always includes the
manipulation of an independent variable which is the
intervention.
• Groups are observed before as well as after the intervention,
to test if the intervention has made any difference.
Quasi-experimental studies

• One of the most common quasi-experimental designs uses two
(or more) groups, one of which serves as a control group in
which no intervention takes place.
• Both groups are observed before as well as after the
intervention, to test if the intervention has made any difference
(This quasi-experimental design is called the ‘non-equivalent
control group design’ because the subjects in the two groups
(study and control groups) have not been randomly assigned.)
Example

• A researcher plans to study the effects of health education on the level of
participation of a village population in an immunization campaign.
• She decides to select one village in which health education sessions on
immunization will be given and another village which will not receive
health education and serves as a control.
• The immunization campaign will be carried out in the same manner in both
villages.
• A survey will then be undertaken to determine if the immunization coverage
in the village where health education was introduced before the campaign is
significantly different from the coverage in the ‘control’ village which did
not receive health education.
• (Note: The study is quasi-experimental because the subjects were not
assigned
Example of a quasi-experimental study:

Psychology 242, Dr.
McKirnan
Week 12-13, quasi-experimental designs.
True v. quasi-experimental designs
True experiments: Quasi-experiments:
Emphasize internal validity
 Assess cause & effect (in relatively artificial
environment)
 Test clear, a priori hypotheses
Emphasize external validity
 Describe “real” / naturally occurring events
 Clear to exploratory hypotheses
Participants assigned to experimental v.
control groups
 Random or matching
 Participants & experimenter Blind to
assignment
Existing or non-equivalent groups
 Non-random assignment
 Participants not blind
 Control group not possible?
Control study procedures
 Create / manipulate independent variable
 Control procedures & measures
Control often not possible
 May not be able to manipulate the
independent variable
 Partial control of procedures & measures

• Does this design address my question?
• Is this study design ethical?
• What resources do I have (time, money, personnel)?
• Is there a cheaper or quicker way of answering the
same question?
Considerations when choosing a study type

• As an example of how to choose a study,
• I will return to the study of orgasms and mortality in middle
aged men
• Which of the study types described above would answer the
question of whether sex and death are related?
• A case series of people who have died would not be useful--
given the frequency of the exposure (orgasms) and the outcome
(death), there would be nothing that would stand out in a study
of all people who died. Remember, there is no comparison
Example of study design

• In an ecological study, we would compare rates of
orgasm and death across different geographical areas. But
how would we find out orgasm rates per area? And would
these differ sufficiently across areas to be able to
correlate them with death rates?
Cont.

• A cross sectional study by its nature excludes dead
people. We could do a survey of women, asking them
about the frequency of their partner's orgasms, and
ask if the partner is still alive. But how accurate are
reports from women regarding their partner's
orgasms? (That approach might be more accurate
than asking men directly!) In addition, it may be too
distressing to ask recently widowed women about
their sex life.
Cont.

• Similar problems would be encountered with a case-control
study.
• Such studies of mortality always rely on proxy information--
for example, from a partner rather than the individual.
• The cases would be people who had recently died.
• But who would be the controls? Brothers? Neighbors?
Cont

• The method the authors chose was the
cohort study, when people were asked about
their sex life then followed up for 10 years.
• This is not without its problems, although
these are more issues of interpretation than
design, so will be considered in the next
article.
Cont

• Finally, could they have done a randomized
controlled trial, allocating men to groups
that have frequent, infrequent, or no sex. In
that case recruitment would have been
pretty difficult--would you open yourself to
the option of no sex?
Cont

• As you will have gathered from the series of questions
above, there is no clear cut answer to which study design to
use. Often two or more designs are possible, and then
practical ("how much time and money do I have?") and
qualitative ("which study will give better results?")
considerations help to make the choice. The ability to choose
a useful study design is an art which improves with practice.
And finally...

Types of research studies, advantages and Disadvantages

Types of research studies, advantages and Disadvantages

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