Webiner.pptx

WEBINER
ON
Research Methodology In Quantitative
Research Study- "The planning method in
reckonable research"

PRESENTED BY
MS. ANKITA ROY
M.SC NURSING 1ST YEAR

INTRODUCTION
“ There’s no discovery without a search and there’s no
rediscovery without a research. Every discovery man ever made
has always been concealed. It takes searchers and researchers to
unveil them, that’s what make an insightful leader. ”
- Benjamin Suulola
Research methodology is the systematic way to solve a research
problem. Methodology is the most important part of any research
study which enables the researcher starts from the time of initial
identification of the problem to its final conclusion.

RESEARCH
The word research is derived from the french term ‘recerchier’ , a
compound word composed of a prefix, re, and a verb, search. Re
means ‘once again’, and search means ‘to look for something or
examine closely and carefully’, ‘to look for information’, to test
and try’ or to prove.

WHAT IS NURSING RESEARCH?
“Research is systematic inquiry that uses disciplined methods to
answer questions or solve problem. The ultimate goal of research
is to develop and expand knowledge.”
- polit & beck

THE PURPOSES OF NURSING RESEARCH
The general purpose of nursing research is to answer questions or
solve problems of relevance to nursing. Specific purpose can be
classified in various ways. Classifications are as follows:
 Applied and basic research
 Research to achieve varying levels of explanation
 Identification and description
 Exploration
 Predication and control

BASIC RESEARCH TERMS
 Abstract: a clear, concise summary of a study that communicates the
essential information about the study. In research journals, it is usually
located at the beginning of an article.
 Data: units of information or any statistics, facts, figures, general material,
evidence, or knowledge collected during the study.
 Variables: attributes or characteristics that can have more than one value,
such as height or weight. In other words, variables are qualities, quantities,
properties or characteristics of people, things, or situations that change or
vary.

 Dependent variables: variables that change as the independent variable is
manipulated by the researcher; sometimes called the criterion variables.
 Independent variables: variables that are purposely manipulated or change
by the researcher also called manipulated variables.
 Research variables: these are the qualities, properties or characteristics that
are observed or measured in natural setting without manipulating and
establishing cause and effect relationship
 Demographic variables: the characteristics and attributes of the study
subjects are considered demographic variables; for example age, gender,
educational status, religion, social class.

 Extraneous variables: extraneous variables are the factors that are not the
part of the study but may affect the measurement of the study variables;
they are commonly known as confounders or confounding variables.
• Operational definition: the way by which a researcher clarifies and defines
the variables under investigation.
• Concept: a word picture or mental idea of a phenomenon. Concepts are the
words or terms that symbolize some aspects of reality. For example, stress,
pain or love.
• Construct: a highly abstract, complex phenomenon is denoted by a made-
up or construed term. A construct term is used to indicate a phenomenon
that cannot be directly observed but must be inferred by certain concrete or
less-abstract indicators of the phenomenon.

 Assumption: basic principle that is accepted as being true on the basis of
logic or reason, without proof or verification.
 Hypothesis: a statement of the predicated relationship between two or more
variables in a research study; an educated or calculated guess by the
researcher.
 Literature review: a critical summary or research on a topic of interest,
generally prepared to put a research problem in context or to identify gaps
and weakness in prior studies so as to justify a new findings.
 Limitation: restrictions in a study that may decrease the credibility and
generalizability of the research findings.

 Population: the entire set of individual or objects having some
common characteristic selected for a research study.
 Research study setting: the study setting is the location is conducted
it could be natural, partially controlled, or highly controlled. Natural or
field setting is an uncontrolled real life situation.
 Sample: a part or subset of population selected to participate in
research study.
 Sampling: the process of selecting sample from the target population
to represent the entire population.

 Probability sampling: the selection of subjects or sampling
units from a population using random procedure
 Non-probability sampling: the selection of subjects or
sampling units from a population using nonrandom procedures.
 Reliability: the degree of consistency or accuracy with which
an instrument measures the attribute it is designed to measure.
 Validity: the degree to which an instrument measures what it is
intended to measure.

TYPES OF QUANTITATIVE RESEARCH
DESIGNS
Broad categories Types of research
designs
Main features
1. Experimental research
designs
1. True experimental
design
a) Post-test only control
design
b) Pre-test-post-test
control group design
c) Solomon Four Group
design
d) Factorial design
e) Cross over design
Manipulation of
independent variable, in
the presence of control
group, randomization)
Manipulation of
independent variable, in
the presence of control
group, randomization

Cont..
designs
Main features
2. Quasi-experimental
design
a) Pre test post test with
control group design
b) Time –series design
c) Only control post test
design
d) One-group pretest-post-
test design
Manipulation of
independent variable, but
absence of either
randomization or control
group.
Manipulation of
independent variable , but
limited control over
extraneous variables, no
randomization and control
group.

Cont..
designs
Main features
2. Non experimental
research designs
1. Descriptive design
a) Univarient descriptive
design
b) Comparative descriptive
design
Univariant descriptive:
studies undertaken to
describe the frequency of
occurrence of a
phenomenon rather than to
study relationship .
Comparative: comparing
occurrences of a phenomenon
in two or more groups.

Broad
categories
Types of research
designs
Main features
2. Correlational design
a) Cohort design
b) Case-control design
3. Developmental research
design
a) Cross-sectional design
b) Longitudinal design
4. Survey research design
The investigation of the distribution and
causes of diseases in a population is
known as epidemiology.
Cross-sectional: examining the
phenomenon only at one point in time.
Longitudinal: examining the phenomenon
at more than one point in time.
Survey studies are investigation in which
self-reported data are collected from
sample with the purpose of describing
population on some variables of interest

STEPS OF QUANTITATIVE RESEARCH
 PHASE 1: The Conceptual Phase
1. Formulation and delimiting the problem.
2. Reviewing the related literature
3. Undertaking clinical fieldwork
4. Defining the framework/developing conceptual definitions
5. Formulating hypotheses

Cont..
 Phase 2: The design and planning phase
6. Selecting a research design
7. Developing intervention protocols
8. Identifying the population
9. Designing the sampling plan
10. Specifying methods to measure research variable
11. Developing methods to safeguard subjects
12. Finalizing the research plan

Cont..
 Phase 3: The empirical phase
13. Collecting the data
14. Preparing the data for analysis
 Phase 4: The analytic phase
15. Analyzing the data
16. Interpreting the results

Cont..
 phase 5: The dissemination phase
17. Communicating the findings
18. Utilizing the findings in practice

FACTORS AFFECTING SELECTION
OF RESEARCH DESIGN
 Nature of the research problem
 Purpose of the study
 Researcher’s knowledge and experience
 Researcher’s interest and motivation
 Subjects/participants
 Resources
 Time
 Possible to control extraneous variables
 Users of the study findings a research design

PRESENTED BY
SHUBHRIMA KHAN
1ST YEAR M.SC NURSING

INTRODUCTION
 Experimental is most scientifically sophisticated research
method.
 It is defined as ‘observation under controlled conditions’.
 Experimental research design are concerned with
examination of the effect of independent variable on the
dependent variable, where the independent variable is
manipulated through treatment or intervention & the effect
of those interventions is observed on the dependant variable.

ELEMENTS OF EXPERIMENTAL
RESEARCH
 Random assignment of subjects to groups
 Precisely defined independent variable
 Manipulation of independent variable
 Having a comparison group
 Clearly identified sampling criteria
 Carefully measured dependent variables
 Controlled environment for conducting study

SYMBOLIC PRESENTATION
 R = Random assignment of the subjects to groups
 O = Observation or measurement of dependent variable
 X = Experimental treatment or intervention

TYPES OF EXPERIMENTAL RESEARCH
DESIGN
True experimental research design
Quasi experimental research design

CONCEPT
True experimental research designs are those where researchers
have complete control over the extraneous variables & can
confidently predict that the observed effect on the dependable
variable is only due to the manipulation of the independent
variable.

ESSENTIAL CHARACTERISTICS
 Manipulation
 Control
 Randomization

MANIPULATION
 Manipulation refers to conscious control of the independent
variable by the researcher through treatment or intervention(s) to
observe its effect on the dependent variable.
 Example: ‘A study evaluated the effectiveness of gentle back
massage on improving quality of sleep among depressive
patients.’

CONTROL
 Control means use of control group and controlling the effects of
extraneous variables on the dependent variable.
 The subject in the control & experimental groups are similar in
number & characteristics, but the subject in the control group
receive no experimental treatment or any intervention at all.
 controls ate classed as
 Negative control
 Clear control
 Positive control

RANDOMIZATION
 Randomization means introduction of chance into the selection or
assignment or subjects to treatments.
 Randomization can occur at two levels
 Random selection
 Random assignment:
 Methods
 Flip of coin
 Lottery method
 Random table
 Computer-assisted random

TYPES OF TRUE EXPERIMENTAL DESIGN
True
experimental
design
Basic post
test only
design
Basic pre-
test post-test
design
Solomon
four group
designs
Factorial
design
Crossover
design

BASIC POST TEST ONLY DESIGN
 In this design, dependent variable is measured only once after the
experimental treatment has been administered.
 Schematic diagram: RE X O1
RC O1
 Example: ‘A study to evaluate the effectiveness of antenatal
exercise on labor Outcome among antenatal mothers in selected
hospitals of west Bengal’

BASIC PRE-TEST POST-TEST DESIGN
 This is a classic experimental design wherein the dependent
variable is measured at two points in time, i.e. before and after the
experimental intervention.
 Schematic diagram: RE O1 X O2
RC O1 O2
 Example: ‘An experimental study to assess the effectiveness of
cognitive behavioral therapy in reduction of stress among
patient with breast cancer.’

SOLOMON FOUR GROUP DESIGNS
 This design has four groups two experimental and two controls.
While one experimental and one control group are administered
pretest, the other two groups are not. Post test is conducted for all
the groups.
 Schematic diagram: RE1 O1 X O2
RC1 O1 O2
RE2 X O1
RC2 O1

CONT..
Example: Nursing students completed a questionnaire
measuring their knowledge scores on drug calculation as a
pretest. Later, the students might look up for answers to some
unknown questions. This might result in scoring better on the
posttest compared to scoring without taking the pretest. This
example suggests that pretest sensitization had an influence on
posttest scores. To avoid this sensitization, Solomon four-group
design is used.

FACTORIAL DESIGN
 When the researcher uses multiple independent variables in a
study, it is called factorial design. In this design, two or more
independent variables are manipulated by the researcher
simultaneously to observe their effects on the dependent
variable.
 Schematic diagram: RA O1 X1 O2
RB O1 X2 O2
RC O1 O2

CONT..
 Example: ‘A study to observe the effects of two different
protocols of mouth care (chlorhexidine and normal saline) on
prevention of VAP in a selected hospital in Kolkata.’

CROSSOVER DESIGN
 In this design subjects are exposed to more than one treatment where
subjects are randomly assigned to different orders of treatment. It is
also known as repeat measures design.
 Schematic diagram: RE1 O1 X1 O2 X2 O3
RE2 O1 X2 O2 X1 O3

CONT..
 Example: A study to compare the effectiveness of massage and
music therapy on the development of premature infants. In this
study, some infants are randomly assigned to receive massage
therapy first and music therapy later. However, the other infants
receive music therapy first and massage therapy later.

RANDOMIZED CONTROLLED TRIALS
 Well-designed Randomized controlled trials (RCTs) are considered
the gold standard for measuring the Intervention effect.
 This method is used in various fields such as medicine, psychology,
education, and administration.
 Randomized controlled trials are quantitative, comparative,
controlled experiments wherein the investigator evaluates the effect
of intervention by administering it to subjects who have been
randomly assigned to either of the experimental or control groups.

CONT..
Steps:
 Subjects are randomly assigned to intervention or control groups.
 Subjects in one group receive the treatment being tested; the other
receives an alternate treatment or no treatment.
 Both the groups are followed up and outcomes measured at specific
intervals.
 These outcome measures are statistically compared to assess the
difference in response between the groups so as to study the effect
of experimental treatment.

CONT..
Advantages:
 The most powerful way to find out cause- and-effect
relationship
 Blinding is possible
 Completely removes effect of extraneous variables
 Strict protocols are followed
Disadvantages:
 Recruitment of sample may be difficult
 Costly and time consuming
 Hawthorne effect

ADVANTAGES AND DISADVANTAGES OF
TRUE EXPERIMENTAL DESIGN
Advantages:
 It is most scientific in nature
 It is the most powerful methods for testing hypothesis.
 Most powerful method for evidence-based practice.

CONT..
Disadvantages:
 Sometimes criticized for their artifiality
 Due to ethical reason manipulation can not be done in human
studies.
 Pretest effect

CONCEPT
Quasi experimental designs facilitate the experimentation of
causality in situations in which complete control is not
possible. In these designs, one of the components of true
experiment design i.e. either the random assignment of subjects
to groups or control groups for comparison are typically
lacking.

ESSENTIAL CHARACTERISTICS
 Manipulation of the independent variables.
 Lacks of randomization or control group.

TYPES OF QUASI EXPERIMENTAL DESIGN
Quasi experimental
design
Pre-test post-
test with
control
group design
Only
control post
test design
One group
pre-test
post test
design
One group
post test
only
design
Time
series
design
Single-group
interrupted time
series design
Time series
with control
group design

PRE-TEST POST-TEST WITH CONTROL
GROUP DESIGN
 This design is similar to pre-post control group Design except that
the participants are not randomly assigned to groups.
 Schematic diagram: E O1 X O2
C O1 O2

CONT..
 Example: In a study to evaluate the effectiveness of therapeutic
environment on conflict and containment rates among
schizophrenia patients, the experimental group and comparison
group subjects were admitted to different psychiatric wards. As
the ward environment is manipulated for the study purposes the
researcher preferred different wards for experimental and control
subjects to avoid contamination of treatment conditions.

ONLY CONTROL POST TEST DESIGN
 In this design, the dependent variable is measured only once after
the experimental treatment has been introduced.
 Schematic diagram: E X O1
C O1
 Example: ‘A study to evaluate the efficacy of distraction in
reducing pain perception among children undergoing painful
procedure’.

ONE GROUP PRE-TEST POST -TEST
DESIGN
 This design is used when only one group is available for study.
Dependent variable is assessed (pre-test) before implementation of
the intervention to the subjects followed by post-test observation.
 Schematic diagram: O1 X O2
 Example: ‘A study on the effect of interventions on the stress
coping resources of associate degree nursing students.’

ONE GROUP POST TEST ONLY DESIGN
 In this research design, a single experimental group is exposed
to a treatment & observations are made after that treatment.
 Schematic diagram: X O1
 Example: ‘A study to evaluate the effectiveness of group
therapy on well-being of diabetic patients’. In this study the
researcher chose the patients with diabetes in experimental
group from selected hospitals.

SINGLE-GROUP INTERRUPTED TIME
SERIES DESIGN
 In this design researcher collects data multiple times at pre-test level.
Later, subjects are administered experimental treatment which is
followed by collection of data at multiple time points.
 Schematic diagram: O1 O2 O3 X O4 O5 O6

CONT..
 Examples: A researcher may evaluate pain levels of arthritis
patients. After assessing pain levels for 3 weeks at weekly
intervals, the subjects were provided physiotherapy to reduce pain.
The pain levels are again evaluated for the next 3 weeks.

TIME SERIES WITH CONTROL GROUP
DESIGN
 Here the researcher collects data multiple times at pretest level
after which subjects are administered experimental treatment
followed by collection of data at multiple time points.
 Schematic diagram:
E O1 O2 O3 X O4 O5 O6
C O1 O2 O3 O4 O5 O6

CONT..
 Example: A research may evaluate anxiety levels of school
students studying at class10. After assessing for anxiety levels
for 3 weeks at weekly intervals (both the groups), the Subjects in
experiment group are provided Cognitive behavioral therapy to
reduce anxiety. The anxiety levels are again evaluated for the
next 3 weeks.

ADVANTAGES AND DISADVANTAGES OF
QUASI EXPERIMENTAL DESIGN
Advantages:
 Feasible, practical and generalizable.
 More adaptable to the real world practice setting than true
experimental designs.
 For some hypotheses these designs may be the only way to evaluate
the affect of the Independent variable of interest.
 Introduce some research control when full experimental rigor is not
possible.

CONT..
Disadvantages:
 There is no control over extraneous variables influencing the
dependent variable
 Lack of randomization or absence of control group makes the
results of the study less reliable and weak for establishing the
cause and effect relationship between independent and
dependent variables.

PRESENTED BY
MANUSRI GOSWAMI
1ST YEAR M.SC NURSING STUDENT

DEFINITION
Non Experimental Research is one of the broad categories of
research design in which the researcher observes the
phenomena as they occur naturally.

 It is used to describe the phenomena in real life
situation
 It is used to identify the problem
 It is used to develop theory
 It is used where manipulation of independent variables
are unethical, may cause physical and psychological
harm
NEED OF NON-EXPERIMENTAL RESEARCH

ADVANTAGES OF NON EXPERIMENTAL
RESEARCH
 Closest to real-life situations
 Suitable for the nursing research studies
 Many situation in which it is not practical to conduct
experimental research
 Some human characteristics are not subject to experimental
manipulation

DISADVANTAGES OF NON EXPERIMENTAL
RESEARCH
 The relationship between the dependent and independent
variables can never be absolutely clear and error-free
 Less authentic and generalizable if the sample is not the true
representative of population

1. DESCRIPTIVE RESEARCH DESIGN
DEFINITION:
It is the study which explore and describe the situation or
phenomena under study. It describes what actually exists,
determines the frequency of occurrence
EXAMPLE :
“A study to assess the factors affecting mental illness among
adults, Kolkata”

ADVANTAGES
 More flexible
 Broad in scope
 Great deal of information
 Identify problems
Collected information is superficial
Large scale studies are time consuming and costly
DISADVANTAGES

TYPES OF DESCRIPTIVE STUDY:
UNIVARIATE DESCRIPTIVE DESIGN:
This design is undertaken to describe the frequency of
occurrence of a phenomena
Prevalence study: Estimate prevalence of disease or
behaviour
Incidence study: Estimate the frequency of developing
new cases.

COMPARATIVE DESCRIPTIVE DESIGN
 In this design, two or more groups are compared on the basis of
selected variables.
 Example:
“A comparative study on pain symptoms among male and
female patients suffering with rheumatoid arthritis at selected
hospital, Kolkata”

2. CO – RELATIONAL RESEARCH DESIGN
DEFINITION:
This is a non-experimental design where researcher examines
the relationship between two or more variables in a natural
settings without manipulation of independent variable.
Example: “A co - relational study to assess the effect of
smoking on lung cancer among adults in Kolkata”

CHARACTERISTICS OF CO-RELATIONAL
RESEARCH
 The strength of relationship is determined by this study
 Magnitude and direction of relationship of independent and
dependent variables are measured by using the correlation
coefficient statistical measure
 Cause and effect relationship is investigated in natural settings

TYPES OF CO-RELATIONAL RESEARCH
DESIGN
 COHORT RESEARCH DESIGN
a) Prospective Cohort Design
b) Historical Cohort Design
c) Ambispective Cohort Design
 CASE CONTROL RESEARCH DESIGN

COHORT RESEARCH DESIGN
 Cohort is a group of people who have something's in a
common and who remain a part of a group over an extended
time.
 EXAMPLE:
“A study to assess the effect of smoking on development of
lung cancer among smoker and non smoker adults at Kolkata”

CHARACTERISTICS OF COHORT STUDY
 Cohort studies are design to measure the exposure and
outcome in the context of time
 In this study design, individual subjects are followed over
time to measure the exposure when it happens then they
measure the outcome at a point in time after exposure
 Demonstrate the temporal order of the exposure and out
come, a necessary criterion to determine causality
 Cohort study tend to be very expensive and time consuming

TYPES OF COHORT STUDY
 PROSPECTIVE COHORT STUDY:
This is an observational longitudinal study, where a cohort is
followed over a time period but they differ in certain factors
under study to determine how these factors affect the rate of
certain dependent outcomes.
 Example: “A study to assess the incidence rate of coronary
artery disease among middle aged nurses who vary in terms of
body mass index”

HISTORICAL COHORT STUDY
 This is also known as retrospective cohort design, is one in
which the outcomes have all occurred before the start of the
investigation.
 Example: “A study to assess the roll of arsenic in human
carcinogenesis among the people of West Bengal”

AMBISPECTIVE COHORT STUDY
 The ambispective cohort study design moves both forward and
backward in time.
 Example: “A study on effect of hip replacement surgery
among adults residing in selected areas in West Bengal”

ADVANTAGES OF COHORT STUDY
 Incidence can be calculated
 Several possible outcome related to exposure can be studied
 Estimation of relative risk can be measured
DISADVANTAGES
• It is time taking and expensive
• Difficult to get extensive record
• The study itself alter the people’s behaviour

CASE CONTROL RESEARCH DESIGN
 A design in which the researcher studies the current
phenomena by seeking information from past. It is also known
as a retrospective research design.
 Example: “A case control study to assess the effects of
smoking on lung cancer among adults, kolkata”

CHARACTERISTICS OF CASE CONTROL
DESIGN
 The study begins with the outcome measure and relies on
participants memories or medical records to go back to
measure the potential exposure
 In this design individuals with outcome of interest are
compared to individuals who do not have the outcome
 Cases and controls are identified from either clinical or
community

ADVANTAGES OF CASE CONTROL DESIGN
 Relatively easy to carry out
 Rapid and inexpensive
 Required comparatively few subjects
 Allow the researcher to study different etiological factors
 Rational prevention and control programs can be established
 Ethical problems is minimal

DISADVANTAGES OF CASE CONTROL DESIGN
 Inability to calculate incidence of the outcome
 Uncertainty about the true temporal order of exposure and
outcome due to potential weakness of available historical data
 Data quality may be poor

3. SURVEY RESEARCH DESIGN
A survey is a research design used to collect information from
different subjects within a given population having same
characteristics of interest .

CHARACTERISTICS OF SURVEY RESEARCH
DESIGN
 It is easy method to collect current information from the
population
 Survey research is a mode of enquiry that relies heavily upon
the validity of verbal reports
 The information is obtained directly from the respondents by
self-reporting questionnaires, face-to-face interview

TYPES OF SURVEY RESEARCH DESIGN
Depending on the nature of phenomenon under study
 Descriptive survey
 Exploratory survey
 Comparative survey
 Co-relational survey

BASED ON METHODS OF DATA COLLECTION
 Written survey :
 Oral survey:
 Electronic survey:

ADVANTAGES OF SURVEY RESEARCH
DESIGN
• It is less time taking, convenient and economical
 The survey can be conducted for a longer period of time, which
gives a chance of knowing about the latest changes or
advancement
 Researcher gets a full chance to well organize and to get full and
honest answers from the respondents
DISADVANTAGES:
 Maintaining privacy of responses in case of group interview
 Hide of true responses by the subject

4. DEVELOPMENTAL RESEARCH DESIGN
Developmental research design examines the phenomena with
reference to time. It is systematic study of designing,
developing, and evaluating instructional programmes,
processes, and products
TYPES OF DEVELOPMENTAL DESIGN
1. Cross sectional research design
2. Longitudinal research design

CROSS SECTIONAL RESEARCH DESIGN
 Cross-sectional research designs is the one in which the
researcher collects data at a particular point of time ( One time
data collection )
 Example:
Breastfeeding practices and new born care in rural areas - A
descriptive cross-sectional study.

LONGITUDINAL RESEARCH DESIGN
 It is used to collect data over a period of time. It involves
repeated observations of sample variations over an extended
period of time, which may vary from few months to many
decades
TYPES
1. Trend studies
2. Panel studies
3. Follow-up studies

TREND STUDIES
In trend studies, the phenomenon are observed for a long to
examine pattern and rate of changes to make prediction of future
direction of changes.
PANEL STUDIES
In this study, some people are observed over a long period of
time to observe pattern of changes as well as reason of changes.
It is more informative than trend studies

FOLLOW UP STUDIES
 Follow up studies are undertaken to determine the subsequent
states of subjects with a specified condition or those who have
received a specific intervention

PRESENTED BY:
RIYA SARKAR
M.SC NURSING, 1ST YEAR

Introduction :
Along with research design, sampling design is nothing but the
selection of participants to be observed or studied during the
research. Selection of participants is done with help of different
methods/techniques which are known as sampling methods.
Each and every participant is termed as sample or study
subject.

Terminology used in Sampling:
 Population: Population is the aggregation of all the units in
which a researcher is interested.
 Target Population: A target population consists of the total
number of people or objects which meet the designated set of
criteria.
 Accessible Population: It is the aggregate of cases that confirm
to designated criteria and are also accessible as subjects for a
study.

 Sampling: Sampling is the process of selecting a
representative segment of the population under study.
 Sample: Sample may be defined as representative unit of a
target population, which is to be worked upon by researchers
during their study.
 Element: The individual entities that comprise the samples and
population are known as elements.

 Sampling frame: It is list of all the elements or subjects in the
population from which the sample is drawn. Sampling frame could be
prepared by the
 Sampling error: There may be fluctuations in the values of the
statistics of characteristics from one sample to another, or even those
drawn from the same population.
 Sampling bias: Distortion that arises when a sample is not
representative of the population from which it was drawn.
 Sampling plan: The formal plan specifying a sampling method, a
sample size and the procedure of selecting the subjects.

Purposes of Sampling:
 Economical for large population
 Improved quality of data
 Quick study results
 Precision and accuracy of data

Characteristics of a good Sample:
 Representative of the population
 Free from bias and errors
 No substitution and incompleteness
 Appropriate sample size

Sampling Process :
Identifying and defining the target population
Describing the accessible population and ensuring
sampling frame
Specifying the sample selection methods
Determining the sample size
Specifying Sampling Plan
Selecting a Desired Sample

Factors influencing sampling
process:
Nature of the Researcher:
 Inexperienced investigator
 Lack of interest
 Lack of honesty
 Intensive workload
 Inadequate supervision

Nature of the sample:
 Inappropriate sampling technique
 Sample size
 Defective sampling frame
Circumstances:
 Lack of time
 Large geographic area
 Lack of cooperation
 Natural calamities

Types of Sampling Techniques:
 Probability technique
 Non probability technique

Probability Sampling Technique:
In this, every subject in a population has equal chance to be
selected as study sample. Probability sampling technique is
used to enhance the representativeness of selected sample for a
study. In this technique the chances of systematic bias
relatively less because subjects are randomly selected.

Features of the Probability
Sampling:
 Equal chances all the individuals in the population of getting
selected
 Representative of the whole population
 Randomization
 Quantitative study

Types of the Probability
Sampling:
There are five types of probability sampling techniques.
Simple random sampling
 Stratified random sampling
Systematic random sampling
Cluster/ multistage sampling
Sequential sampling

Simple random sampling
technique :
The list of the subjects in population known as sampling
frame and a sample drawn from sampling frame by using
following methods:
 The lottery method
 The use of table of random
numbers
 The use of computer

Merits:
 Most reliable and unbiased method
 Requires minimum knowledge of study population
 Free from sampling errors/ bias
 Demerits:
 Needs up-to-date complete list of all the members of the
population.
 Expensive and time consuming

Stratified random sampling:
Dividing heterogenous population in strata based on selection
traits, such as age, gender, habituate.
stratified random sampling is further divided into two
categories
i) Proportionate stratified
random sampling
i) Disproportionate
stratified random sampling

 Proportionate stratified random sampling: In this, the
sample chosen from each stratum is in proportion to the size of
total population.
 For eg.:
Stratum A B C
Population size 100 200 300
Sampling fraction 1/2 1/2 1/2
Final sample size 50 100 150

 Disproportionate stratified random sampling: In this
subtype, the sample chosen from each stratum is not in
proportion to size of total population in that stratum.
 For eg.:
Stratum A B C
Population size 100 200 300
Sampling fraction 1/2 1/4 1/6
Final sample size 50 50 50

Merits:
 Ensures representative sample in heterogenous population.
 Comparison is possible in two groups
Demerits:
 Requires complete information of population
 Large population is required
 Chances of faulty classification of strata

Systematic Random sampling:
Selecting of every Kth case from the group such as every
10th person on a patient list or every 100th person.
 For eg. A researcher wants to choose about 100 subjects from a
total target population of 500 people. Therefore, 500/500= 5.
Therefore, every 5th person will be selected.

Merits:
 Convenient and simple
 Distribution of sample is spread evenly over the entire given
population.
 Less cumbersome, time-consuming and is cheaper
 Statistically more efficient
Demerits:
 Less representative sample
 Biased sample

Cluster or multistage sampling:
When simple random sampling is not possible due to the
size of the population, cluster random sampling is carried
out.
For eg. A researcher requiring to survey the academic
performance of Indian high school students.

Merits:
 Cheap, quick and easy
 Large populations can be studied
 Enables investigators to use existing division, such as districts
 Same cluster can be used again for study
Demerits:
 High sampling error.
 Chances of least representative sample

Sequential sampling:
The investigator initially select small sample and tries to
make inferences, if not able to draw results, he/she then
adds subjects until clear cut inferences can be drawn.

Number of
subjects
Smokers Non smokers Having lung
cancer
(A) (B)
20
30
50
7
18
28
12
22
22
2 1
5 3
10 4

Merits:
 Smallest representative sample
 Finding inferences
Demerits:
 Not possible to study a phenomenon which needs to be studied
at one point of time
 Repeated entries

Non probability Sampling:
Non probability sampling is a technique wherein the
samples gathered in a process that does not give all the
individuals in the population equal chances of being
selected in the sample.

Features of the Non probability
Sampling:
 It does not give all the individuals in the population equal
chances of being selected.
 Impossible to randomly sample the entire population.
 Subjects in a non probability sample are usually selected on the
basis of their accessibility or by the purposive personal
judgement of the researcher.
 The sample may or may not represent the entire population
accurately.

Uses of Non probability
Sampling:
 It is utilized when showing that a particular trait is existent in
the population.
 To make qualitative, pilot or exploratory study.
 When the population is almost limitless, it can also be used.
 limited budget, time and workforce, it is also of use.
 This technique can also be used in an initial study (pilot study)
and can be carried again.

Types of the Non probability
Sampling:
Non probability sampling techniques are classified in several
categories, such as
Purposive sampling
Convenient sampling
Quota sampling
Consecutive sampling
 Snowball sampling

Purposive Sampling:
Purposive sampling is more commonly known as ‘judgmental’ or
‘authoritative sampling’. In this sampling, samples are chosen by
choice not by chance, through a judgment made by the researcher
based on his or her knowledge about the population.
For eg. A researcher wants to study the lived experiences of post
disaster depression among people living in earthquake affected areas
of Gujrat.

Merits:
 Simple to draw a sample and useful in explorative studies.
 Saves recourses, requires less fieldwork.
Demerits:
 Requires considerable knowledge about the population under
study.
 It is not always reliable sample, as conscious biases may exist

Convenience sampling:
In Convenience sampling, which is a non probability sampling
technique, subjects are selected due to their convenient
accessibility and proximity to the researcher.

Merits:
 It is easiest, cheapest and least time consuming.
 It helps in saving time, money and resources.
Demerits:
 Chances of sampling bias
 It does not provide the representative sample from the
population of the study.
 It cannot be generalized on the population.

Consecutive Sampling:
In this technique, picks up all the available subjects who are
meeting the preset inclusion and exclusion criteria.

Merits:
 There is very little effort on the part of the researcher
 Not expensive, not time consuming and not workforce
 Ensures more representativeness
Demerits:
 No set plans about the sample size and sampling schedule.
 Always does not guarantee the representative sample.

Quota Sampling:
Quota sampling is a non probability sampling technique
wherein the researcher ensures equal or proportionate
representation of subjects, depending on which trait is
considered as the basis of the quota.

 For eg. If the basis of the quota is college level and the
researcher needs equal; representation, with a sample size of
100, he or she must select 25 first- year students, another 25
second-year students, 25 third-year and 25 fourth-year
students.

Merits:
 Economically cheap
 Suitable where fieldwork like market and public opinion polls
Demerits:
 Does not guarantee representative sample
 Not possible to estimate errors
 Chances of sampling bias

Snowball sampling:
Sampling is a non probability sampling technique that is
used to locate the initial subject and then taking assistance
from the subject to identify people with a similar trait of
interest.
For eg. A researcher wants to conduct a study on the
prevalence of HIV/AIDS among commercial sex workers.

Types of Snowball sampling:
1) Linear snowball sampling

2) Exponential non discriminative snowball sampling

3) Exponential Discriminative snowball sampling

Merits:
 Facilitates sampling for people difficult to locate
 Cheap, simple and cost-efficient
 Needs little planning and lesser workforce
Demerits:
 Little control of researcher over the sampling method
 Sampling representativeness is not guaranteed
 Chances of poor coverage of entire population

Sample size Determination:
 Sample size Determination:
Sample size for descriptive study:
n= t2 (p×q)
d2
t2 = Square value of the standard deviation score that refers to the
area under a normal distribution of values
p = Percentage category for which we are computing the sample
size.
q = 1 - p
d2 = Square value of one-half of the precision internal around the
sample estimate.

TOOLS AND TECHNIQUES
OF
DATA COLLECTION
PRESENTED BY
BAISHAKHI DAS
1ST YEAR M.SC. NURSING STUDENT

INTRODUCTION
“With data collection, ‘the sooner the better’ is always the
best answer.”
– Marissa Mayer
A systematic collection and analysis of data are most vital to any
empirical research. In research studies, two types of data are
collected, those are primary and secondary data. However, nursing
research studies mainly rely on primary data.

CONCEPT OF DATA COLLECTION
Data are the observable and measurable facts that provide
information about the phenomenon under study. Data collection
should aim at identification of observable and measurable facts or
variables that would relate the indicators.

SOURCES OF DATA
Sources of data are generally categorized in two broad categories:
 Primary Sources: Primary sources provide the first-hand
information collected by the researcher directly from the
respondents or the situations.
 Secondary Sources: Secondary data are collected from either
internal or external secondary sources.
 External sources involve existing materials:
 Published records
 Unpublished records
 Internal secondary sources may include the biographies, personal
diaries, letters, memories etc.

COMPONENTS OF DATA COLLECTION
 Technique of data collection: Gathering data with the use of
specific tools used in given methods.
 Instrument for data collection: A device used to measure the
concept of interest in a research project that a researcher uses to
collect data.

SELECTION OF METHODS OF DATA COLLECTION
 The nature of phenomenon under study
 Type of research subjects
 The type of research study
 Size of the study sample
 Time frame of the study
 Literacy level of the subjects
 Availability of resources and manpower

DEVELOPA DATA COLLECTION PLAN
 Identifying data needs
 Selecting types of measures
 Selecting and developing instruments
 Pretesting of the data collection instrument
 Developing data collection forms and procedures

TYPES OF TOOLAND TECHNIQUE
OF DATA COLLECTION
TYPE OF TECHNIQUE TYPE OF TOOL
Self-Reporting Structured self-report instruments
Interviewing Structured interview schedule
Observing Structured Observation
Bio physiologic methods Bio physiologic measurements

STRUCTURED SELF-REPORT INSTRUMENTS
It is called a questionnaire or self-administered questionnaire when
respondents complete the instrument themselves either in a paper
pencil format, or in a computer.
TYPES OF STRUCTURED QUESTIONS:
 Open ended questions
 Closed ended questions
 Composite scales
 Likert type rating scales
 Other type self reported scales

OPEN ENDED QUESTIONS
This allows people to respond in their words, in narrative
fashion. In questionnaires, respondents are asked to give a
written reply to open ended items, and so adequate space must
be provided to permit a full response.
For an Example:
“What was your biggest challenge after your surgery?”

CLOSED ENDED QUESTIONS
This questions offer response options, from which respondents
choose the one that most closely matches the appropriate answer.
 Dichotomous Questions: Choice between two response
alternatives.
Multiple Choice Questions: It offers three or more response
alternatives.
Rank Order Questions: Response with a rank as most to least
important.
Q. Have you ever been hospitalized?
A. Yes B. No
Q. What is the best test to know kidney dysfunction?
A. SGOT B. GFR C.SGPT D. ECG
Q. What is most important in your life? Rank from most to least favourable.
A. Money B. Education C. Family D. Health

CONT….
 Rating questions: Asks respondents to evaluate something
on an ordered dimension.
 Visual analogue scales: Measure subjective experiences.
Q. How do you rank the education quality in India?
A. Good B. Fair C. Poor D. Very Poor
1 2 3 4

 Likert Type Rating Scales: Respondents are asked to
indicate the degree to which they agree or disagree with the
opinion expressed by the statement.
 Semantic Differential Scales: Respondents are asked to
rate concepts (e.g., dieting, exercise) on a series of bipolar
adjectives.
Q. How much are you satisfied with hospital services?
1. Very Unsatisfied 2.Unsatisfied 3.Neutral 4.Satisfied 5.Very Satisfied
Q. How difficult the task was?
Very Easy Difficult

ADVANTAGES OF QUESTIONNAIRE:
 Questionnaires are cost-effective.
 They are easy to analyse.
 They require less time and energy to administer.
 Questionnaires offer the possibility of anonymity.
 They reduce bias as interviewer is not present.
 Questionnaires are used for large sample size.

DISADVANTAGES OF QUESTIONNAIRE:
 Questionnaires are not suitable for all.
 Low response rate.
 Questionnaire sent by mail may be filled by someone other
than the intended person.
 Probing of response is not possible.
 There are chances of misinterpretation.
 People can lie and answer the question vaguely.

STRUCTURED INTERVIEW SCHEDULE
Structured interview is a means of data collection in which the
interviewer has an interview schedule in which the questions are
listed in the order in which they are to be answered.
Characteristics:
 It is formalized and has a limited set of questions.
 The aim is to ensure that each interview is presented with exactly
the same questions in the same order.
 It increases the reliability and credibility of research data.

INTERVIEWING PROCESS
Preparation
of Interview
Pre-interview
Interaction
Carrying the
Interview
Forward
Developin
g Rapport
Recording
and closing
the Interview

ADVANTAGEDS OF INTERVIEW SCHEDULE:
 Data from one interview to the next one are easily
comparable.
 Recording and coding data does not pose any problem.
 Attention is not diverted to irrelevant and time consuming
conversation.
DISADVANTAGES:
 It tends to lose the spontaneity of natural conversation.
 The respondent’s views are minimized and investigator’s
own biases regarding the problems under study are assessed.
 The scope of exploration of information of data is limited.

STRUCTURED OBSERVATION
Structured observation is used to record behaviours,
actions and events. Structured observation involves using
formal instruments and protocols that specify what to
observe, how long to observe it, and how to record
information.
Researchers recording structured observations typically
use either a checklist or a rating scale.

CHECKLISTS
A checklist is a simple instrument consisting prepared list of
expected items of performance or attributes, which are
checked by a researcher for their presence or absence.
Characteristics of Checklists:
 Observe one respondent at one time.
 Clearly specify the characteristics of behaviour to be
observed.
 Use only carefully prepared checklist to avoid more complex
traits.

CHECKLIST FOR EVALUATION OF STUDENT’S
PERFORMANCE DURING SURGICAL DRESSING:
BEHAVIOUR YES NO REMARKS
1. Arrange the articles
2. Preparation of
environment and
patient
3. Explanation of
procedure
4. Wash Hands
5. Maintains Aseptic
techniques
6. Termination of the
article
7. Recording and
reporting of procedure

Advantages of Checklist:
 Checklists allow inter-individual comparisons.
 It is helpful in evaluating procedural work.
 Decreases the chances of error in observation.
 It allows the observer to contain the direct attention.
Disadvantages of Checklist:
 Does not indicate quality of performance, so usefulness of checklist
is limited.
 Only a limited component of overall clinical performance can be
evaluated.
 It has a limited use in qualitative research studies.

RATING SCALES
Rating scale refers to a scale with a set of opinion, which describes
varying degree of the dimensions of an attitude being observed.
Characteristics of Rating Scale:
 Rating scales are value judgements about attributes of one person
by another person.
 Theses scales are most commonly used tools to carry out
structured observations.
 Rating scales provide more flexibility to judge the level of
performance or presence of attributes among subjects.

TYPES OF RATING SCALES:
 Graphic rating scale: It includes the numerical points on
the scale.
 Numerical rating scale: It divides the evaluation criteria
into a fixed number of points, but defines only numbers at
the extremes.
Q. How much are you satisfied with noise control in your ward?
Least Most
Q. Pain Assessment Numerical Scale:
No Pain 2 3 4 5 6 7 8 9 Worst Pain

 Descriptive rating scales: This scales do not use number, but
divide the assessment into series of verbal phrases to indicate the
level of performance.
 Comparative rating scale: The researcher makes a judgement
about an attribute of a person by comparing it with that of a
similar another person.
Q. Judge the level of performance of nursing personnel in medical ICU.
Name of
Nurses
Very Active Active Moderately
Active
Passive
Sr. Kriti R
Sr. Smita C
Sr. Kakoli M

Advantages of Rating Scale:
 Easy to administer and score the measured attributes.
 Graphic rating scale is easier to make and requires less time.
 Rating scales can be easily used for a large group.
 Used to evaluate performance, skills, and product outcomes.
 Rating scales are adaptable and flexible research instruments.
Disadvantages of Rating Scale:
 It is difficult to fix up rating about many aspects of an individual.
 Misuse can result in decrease in objectivity.
 There are chances of subjective evaluation; thus the scales may
become unscientific and unreliable.

BIOPHYSIOLOGIC MEASURES
Setting, in which nurses work are typically filled with a
wide variety of technical instruments for measuring
physiologic function.
Types:
 In vivo measurements are performed directly in or on
living organisms.
 In vitro measurements are performed outside the
organism’s body, as in measuring serum potassium
concentration in blood.

Advantages of bio physiologic measures:
 Accurate and precise compared with psychological measures
(e.g., self-report measures of anxiety).
 Bio physiologic measures are objective.
 Provide valid measures of targeted variables
Disadvantages of bio physiologic measures:
 They may be more expensive than other methods.
 The measuring tool may affect the variables it is attempting to
measure.
 Energy must often be applied to the organism when taking the bio
physiologic measurements.

PERFORMANCE TESTS
Patients' abilities and skills are sometimes measured with
performance tests. Physical performance tests have been
devised to measure such attributes as balance, mobility,
endurance, and flexibility.
For example,
The 6-Minute Walk Test (6MWT) is a widely used measure
of physical functioning for patients with various
cardiovascular, respiratory, or neurologic diseases.

TRAINING OF DATA COLLECTORS
 Depending on prior experience, training will need to cover
both general procedures, and ones specific to the study.
 Training can often be done in a single day, but complex
projects require more time.
 The lead researcher is usually the best person to conduct the
training.
 The manual normally includes background materials (e.g.,
the study aims), general instructions, specific instructions,
and copies of all data forms.

PRESENTED BY
Payel Chatterjee
M.Sc. Nursing, 1st year

INTRODUCTION-
 Reliability and validity are concepts used to evaluate the
quality of research. They indicate how well a method,
technique or test measure something. Reliability is about the
consistency of a measure and validity is about the accuracy of a
measure. Validity is the main extent to which a concept,
conclusion or measurement is well founded and likely
corresponds accurately to the real world.

VALIDITY OF RESEARCH TOOL-
 Validity is as extent to which an instrument measures
what it asserts to measure. Validity of a research
instrument assesses the extent to which the instrument
measures what it is designed to measure. It is the
degree to which the results are truthful.

DEFINITION-
According to Polit and Hungler, ‘Validity refers to the
degree to which an instrument measures what it is
supposed to be measuring’.

TYPES-
Validity
↓
Face Validity Content Validity Criterion Validity Construct Validity
Concurrent Validity Predictive Validity
Test Validity Convergent Validity Discriminant Validity

I. FACE VALIDITY-
 Face validity involves an overall look of an instrument
regarding its appropriateness to measure a particular attribute
or phenomena.
 Face validity is typically not considered a critical measurement
property, but it can be important if patients’ resistance to being
measured reflects the view that the scale is not relevant to their
problems or situations.

II. CONTENT VALIDITY-
 It may be defined as the extent to which an instrument’s
content adequately captures the construct that is whether an
instrument has an appropriate sample of items for the construct
being measured.
 a. Relevance- An assessment for relevance involves feedback
on the relevance of individual items and the overall set of
items.

 b. Comprehensiveness- The flip side of asking experts about
the relevance of items is to ask them. To be content valid a
measure should comprehensively encompass the full
complexity of the construct.
 c. Balance- An instrument that is content valid represents the
domains of the construct in a balanced manner.

CONTENT VALIDITY INDEX. (CVI)-
 CVI (Content validity index) =
(No. of agreement giving a rating of 3 or 4) ⁒ (No. of experts)
There are several variations of labelling the 4 points, but the
scale used most often is as follows: 1= not relevant,2= somewhat
relevant,3= quite relevant,4= highly relevant. Then, for each item,
the item CVI(I-CVI) is computed as the number of experts giving
a rating of 3 or 4, divided by the number of experts, that is the
proportion in agreement about relevance.

 An item rated as quite or highly relevant by 4 out of 5 experts
would have an I-CVI of 0.8, which is considered an acceptable
value.
 Items with an I-CVI below .78 should be carefully.
 Scale CVIs (S CVIs)-
The preferred approach is to compute the S-CVIs by averaging I-
CVIs

CRITERION VALIDITY-
 This type of validity is a relationship between
measurements of the instrument with some other criteria.
 The instrument is valid if its measurements strongly respond to
the score of some other valid criteria.
 The problem with criterion related validity is finding a reliable
and valid external criterion.

EXAMPLE OF CRITERION VALIDITY-
 A tool is developed to measure the professionalism among
nurses and to assess the criterion validity nurses were
separately asked about the number of research papers they
published and number of professional conferences they have
attended. Later a correlation coefficient is calculated to assess
the criterion validity. The tool is considered strong with
criterion validity if a positive correlation exists between score
of the tool measuring professionalism and the number of
research articles published and professional conferences
attended by the nurses.

PREDICTIVE VALIDITY-
 It is the degree of forecasting judgement.
For example- Some personality tests on academic future of
students can be predictive of behavior patterns. It is the
differentiation between performance on some future criterion and
instruments ability. An instrument may have predictive validity
when its score significantly corelates with some future criteria.

CONCURRENT VALIDITY-
 It is the degree of the measures in present. It relates to
the present specific behavior and characteristics, hence the
difference between predictive and concurrent validity
refers to timing pattern of obtaining measurements of a
criterion.

 REASONS FOR CREATING A NEW MEASURE
FALL PRIMARILY IN TO FIVE CATEGORIES-
i. Expense- A new measure that is good reflection of a criterion
may be desired because the gold standard is too expensive to
administer routinely.
ii. Efficiency- A related reason is the desire to create a measure
that is more efficient than the gold standard.

 iii. Risk and discomfort- Sometimes the criterion involves a
measurement that puts people at risk or is invasive and a
substitute is desired to lower risks or pain
 iv. Criterion unavailable- A measure may be needed because
criterion measures are difficult or impossible to obtain
routinely in clinical settings.
 v. Prediction- One other reason for developing an instrument
that can be validated against a criterion is that the criterion can
not be measured until a future point in time.

CONSTRUCT VALIDITY-
 Construct validity gives more importance to test relationship
predicted on theoretical measurements. The researcher can
make a prediction in relation to other such type of construct.
The researcher can make a prediction in relation to other such
type of constructs.
 Example- Nurse may have designed an instrument to measure
the concept of pain in amputated patients. The pain pattern may
be due to anxiety; hence the results may be misleading.

CONVERGENT VALIDITY-
 Convergent validity, a parameter often used in sociology,
psychology and other behavioral sciences refers to the degree
to which two measures of constructs that theoretically should
be related .
DISCRIMINANT VALIDITY- Degree to which the
operationalization is not similar to other operationalizations to
which it theoretically should not be similar.

 The quality and adequacy data can only be assessed by
establishing the reliability of an instrument. Reliability is the
degree of consistency with which the attributes or variables are
measured by instrument. Reliability pertains to the consistency
of a measure.

 RELIABILITY OF RESEARCH TOOL-
The quality and adequacy data can only be assessed by
establishing the reliability of an instrument. Reliability is the
degree of consistency with which the attributes or variables are
measured .A blood pressure measuring instrument gave a reading
of 120 mm Hg systolic blood pressure after some time when
blood pressure is again measured for the same subject, it gave a
reading 160 mm of Hg systolic blood pressure. In this situation
the instrument is not considered reliable. by instrument.

DEFINITION-
 Reliability is the degree of consistency and accuracy with
which an instrument measures the attribute for which it is
designed to measure.

MEASURING OF RELIABILITY-
Reliability
Stability Internal Consistency Equivalence
(Test retest method) (split half method) (Interrater method,
Interobserver validity)
Parallel test reliability

I. STABILITY-
 The stability aspect of reliability means research instrument
provides same results when used consecutively for two or more
times. Stability is estimated to make sure that research
instrument in providing similar results with repeated
administration. It is also known as reliability of test retest
function. To measure test retest reliability the test is given
twice at two different points in time.

 STATISTICAL CALCULATION- (TEST RETEST METHOD)-
Procedure of calculation test retest reliability of research instrument
involves the following steps-
• Administration of a research instrument to a sample of subjects
on two different occasions.
• Scores of the tool administration at two different occasions are
compared and calculated by using following formula of correlation
coefficient.
• The correlation co efficient reveals the magnitude and
directions of relationship between scores generated by a researcher
instrument at two separate occasions.
• Karl Pearson’s correlation coefficient formula for estimation of
reliability.

II. INTERNAL CONSISTENCY-
 It is also called homogeneity. Internal consistency ensures that
all the subparts of a research instrument measure the same
characteristics.
 For example, a patient’s satisfaction measurement scale
developed to measure his or her satisfaction with nursing care
must include all the subparts related to the measurement of
satisfaction withy nursing care only. It should not include
patient’s satisfaction measurement scale with other aspects of
care including a subpart related to patient’s satisfaction with
health care would be inappropriate in this scale.

STATISTICAL CALCULATION (SPLIT
HALF METHOD)-
 Procedure of calculating split half reliability of research
instrument involves following steps-
 Divide items of a research instrument in two equal parts
through grouping either in odd number questions and even
number questions or first half and second half item groups.
 Administer two sub parts of the tool simultaneously score them
independently and compute the correlation coefficient on the
two separate scores by using the Karl Pearson’s correlation
coefficient formula.

III. EQUIVALENCE-
 The aspect of reliability is estimated when a researcher is testing the
reliability of a tool which is used by two different observers to observe a
single phenomenon simultaneously and independently or two presumably
parallel instruments are administered to an individual at about the same
time.
 For example- A rating scale is developed to assess cleanliness of the bone
marrow transplantation unit, the rating scale may be administered to observe
the cleanliness of the bone marrow transplantation unit by two different
observers simultaneously but independently.

 This is also known as interrater or interobserver reliability
which is estimated by the administration of tool to observe a
single event simultaneously and independently by two or more
trained observers, the reliability may be computed by using
following equation-
 r = Number of agreements ⁒ (Number of agreements ₊
Numbers of disagreements)

IV. PARALLEL TEST RELIABILITY-
 Multi system parallel tests or alternative form tests are not
common in health care measurement but there are a few
examples. Similar to test retest reliability parallel test reliability
involves administration of the parallel tests to the same people
on two separate occasions and then estimating a reliability
parameter which would be the interclass correlation coefficient.

CONCLUSION
Quantitative research is all about asking people for their opinions
in a structured way so that you can produce hard facts and
statistics to guide you. To get reliable statistical result, it is
important to survey people in fairly large numbers and to make
sure that they are a representative sample of your target
population.

BIBLIOGRAPHY
1. Kokare C., Kokare S., “Research Methodology”, Nirali Prakashan; 1.1 to
1.13
2. Kothari C.R., “Research Methodology”( Methods and Technique), Second
Revised Edition, New Age International Publishers;1-23
3. Park’s text book of preventive and social medicine. 19th edition. K.Park.
Bhanot publishers. 2007.
4. Text-Book: C.R. Kothari, “Research Methodology Methods and
Techniques”, New Age International Publisher, Second Edition, ISBN-978-
224-1522-3224 1522 3
5. Text-Book: Creswell, J. W. , Research design : Qualitative and Quantitative
Approaches. Thousand Oaks, Calif.; London : Sage Publications, ISBN
0803952546, 19940803952546, 1994
6. Beck T C.,Polit F D.Nursing research generating and assessing evidence
for nursing practice.10th edition. Wolters Kluwer;2017

Webiner.pptx

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Ähnlich wie Webiner.pptx

Ähnlich wie Webiner.pptx (20)

Mehr von ShubhrimaKhan

Mehr von ShubhrimaKhan (20)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

Webiner.pptx