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2/18/2014

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2
CLASSIFICATION OF RESEARCH DESIGN (POLIT & HUNGLER, 1999)

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ESSENTIAL CHARACTERISTICS OF EXPERIMENTAL
DESIGNS
Randomization

Experimental
Design

Control

Manipulation
RANDOMIZATION
Participants being assigned to either
receive (experimental group) or not
receive
(control
group),
the
treatment condition or intervention
(IV).
METHOD OF RANDOMIZATION
•Lottery method
•Tossing a coin
•Random number table
•Computer
MANIPULATION
Manipulation is the process of
maneuvering the IV, so that its effect
on the dependent variable (D.V) can
be observed/measured.
METHOD OF MANIPULATION
Researcher gives intervention to
experimental group and withholds it to the
control group or administers some other
treatment. E.g. Gentle message is effective
as a pain relief measures for elderly.
CONTROL
Control is for elimination of bias.
Control group refers to a group of
subjects, whose performance is
used to evaluate the performance
of experimental group on same
D.V.
CONTROL
Eg. Effect of nutrient diet on the
weight of premature infant in two
weeks.
Comparison of post intervention
weight with pre-intervention
weight determines the
effectiveness of nutrient diet.
CONTROL
The type of experimental design is
determined by the amount of
control the researcher is able to
exercise over the research condition.
1. TRUE EXPERIMENTAL DESIGN
1.1 Classic experimental design/pretest-post
test control group design

R O1 x O2 (Experimental group)

R O1 O2 (Control group)
Example of Pre test – Post test Design.

Experimental
Group- E

Pre test

Control groupC

Treatment (X)

Pre test

Post test (x)

Post test (y)

Example
•Tepid sponge (IDV) --> reduction of temperature (DV)
•Paracetomol (IDV) --> reduction of temperature (DV)
COLLECT PRETEST DATA BEFORE RANDOMIZATION TWO GROUPS

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Example of True Experimental Study
Sneha, “Effectiveness of massage on the
selected physiological variables of low
birth weight infants”. In NICU of Bharati
Hospital, Pune, 2010.

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1.2 Post test only
control group design
R X O1 (Experimental group)
R O1 (Control group)
Example of Post-Test only Control Group Design

Experimental group E

Intervention
introduced
X

Control group C

Level of phenomenon
after intervention (Y)

Level of phenomenon
without intervention (Z)

Intervention Effect =(Y)-(Z)

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Example of Post Test only Control
Group Design
Vijayakumari G: A study to assess the
effectiveness of structured teaching
program regarding nature and prevention of
accidents among mothers of toddlers in
selected areas of Raichur (2004).

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2. QUASI-EXPERIMENTAL DESIGNS

A quasi experimental design is one in
which experimental and control
(comparison) are present &
randomization is not there.
Ex. Effect of primary Nursing education
on staff morale.

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2.1 Non equivalent control
group design
R

O1

R

O3

X

O2
O4

Effect = (O2 – O1) – (O4 – O3)
R = Randomization.
O = Observation or measurement
X = Treatment or intervention
A researcher might choose a group of patients
with diabetes on one hospital floor for the
experimental group and a group of patients
with diabetes on another floor for the
comparison group. The experimental
treatment would be administered to the
experimental group; the comparison group
would receive no treatment or some alternative
treatment.
E.g. A non-equivalent control group design
was used by Valliammal Sudhakar (2008) to
study the knowledge, attitude and practice
towards physical well being of a group of
IV, V, VIth grade students in two different
schools.
2.2 THE TIME SERIES DESIGN
• The time series design, a single group
experiment comprises of series of
observation in the before-time period to
establish a baseline.
• The experimental independent variable is
then introduced,
• Followed by another series of observation to
examine the effect of the independent
variable.
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2.2.1 Time series Design (single group)
Before

x

After

………...……………………………………...
E O1 O2 O3 O4 O5

x

O6 O7 O8 O9 10

………………………………………………
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2.2.2 The Multiple Time Series Design
Time series non equivalent control group design
(QED)

Before

x

After

………………………………………………………..
E O1 O2 O3 O4 O5

x

O6 O7 O8 O9 10

………………………………………………………………………………………
C O1 O2 O3 O4 O5

-

O6 O7 O8 O9 10

……………………………………………………………………………

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A researcher might assess the pain levels
of a group of patients with low back pain.

After 3 weeks of pain assessment, intervention
will be introduced
(O1 O2 O3 x O4 O5 O6).
The results of this study would help the
researcher to determine if a specific exercise
is effective in reducing low back pain.
3. PRE EXPERIMENTAL DESIGN
Pre experimental design: are
discussed to provide examples
of how not to do research.
PRE-EXPERIMENTAL DESIGNS:
3.1 The one-shot case study or single case study
In single case study, that studies at once, following a
treatment or an agent presumed to cause change.
Because the study design has a total absence of
control; it is considered to be little value as an
experiment

X----------------O
X= independent variables or stimulus

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ONE-SHOT CASE STUDY
Lalitha, Premila & Balu (2006) conducted a
study on nursing personnel registered for a
day workshop on life skill education at
MTIHS, Pondicherry.
3.2 ONE GROUP PRE-TEST AND
POST-TEST DESIGN
• Here only one group is observed before and
after the independent variable is
introduced.
• Loss of the control group decreases the
usefulness of the study but may be
necessary in cases where it is not possible
or feasible to have control groups
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29
E.g. Sailaxmi Gandhi(2006) conducted
a pre-experimental study to assess
the effectiveness of stress
management programme on the
selected variables of nurses working
in psychiatric wards at NIMHANS,
Bangalore.
II- NON EXPERIMENTAL
DESIGN
Non-experimental

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CONCLUSION
• Quantitative research approach is the
commonest
• Replication is possible
• Data analysis is easy
• Researcher’s subjectivity is minimal

2/18/2014

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48
2/18/2014

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Ppt. types of quantitative research

  • 1.
  • 3. CLASSIFICATION OF RESEARCH DESIGN (POLIT & HUNGLER, 1999) 2/18/2014 www.drjayeshpatidar.blogspot.com 3
  • 4. ESSENTIAL CHARACTERISTICS OF EXPERIMENTAL DESIGNS Randomization Experimental Design Control Manipulation
  • 5. RANDOMIZATION Participants being assigned to either receive (experimental group) or not receive (control group), the treatment condition or intervention (IV).
  • 6. METHOD OF RANDOMIZATION •Lottery method •Tossing a coin •Random number table •Computer
  • 7. MANIPULATION Manipulation is the process of maneuvering the IV, so that its effect on the dependent variable (D.V) can be observed/measured.
  • 8. METHOD OF MANIPULATION Researcher gives intervention to experimental group and withholds it to the control group or administers some other treatment. E.g. Gentle message is effective as a pain relief measures for elderly.
  • 9. CONTROL Control is for elimination of bias. Control group refers to a group of subjects, whose performance is used to evaluate the performance of experimental group on same D.V.
  • 10. CONTROL Eg. Effect of nutrient diet on the weight of premature infant in two weeks. Comparison of post intervention weight with pre-intervention weight determines the effectiveness of nutrient diet.
  • 11. CONTROL The type of experimental design is determined by the amount of control the researcher is able to exercise over the research condition.
  • 12. 1. TRUE EXPERIMENTAL DESIGN 1.1 Classic experimental design/pretest-post test control group design R O1 x O2 (Experimental group) R O1 O2 (Control group)
  • 13. Example of Pre test – Post test Design. Experimental Group- E Pre test Control groupC Treatment (X) Pre test Post test (x) Post test (y) Example •Tepid sponge (IDV) --> reduction of temperature (DV) •Paracetomol (IDV) --> reduction of temperature (DV) COLLECT PRETEST DATA BEFORE RANDOMIZATION TWO GROUPS 2/18/2014 www.drjayeshpatidar.blogspot.com 13
  • 14. Example of True Experimental Study Sneha, “Effectiveness of massage on the selected physiological variables of low birth weight infants”. In NICU of Bharati Hospital, Pune, 2010. 2/18/2014 www.drjayeshpatidar.blogspot.com 14
  • 15. 1.2 Post test only control group design R X O1 (Experimental group) R O1 (Control group)
  • 16. Example of Post-Test only Control Group Design Experimental group E Intervention introduced X Control group C Level of phenomenon after intervention (Y) Level of phenomenon without intervention (Z) Intervention Effect =(Y)-(Z) 2/18/2014 www.drjayeshpatidar.blogspot.com 16
  • 17. Example of Post Test only Control Group Design Vijayakumari G: A study to assess the effectiveness of structured teaching program regarding nature and prevention of accidents among mothers of toddlers in selected areas of Raichur (2004). 2/18/2014 www.drjayeshpatidar.blogspot.com 17
  • 18. 2. QUASI-EXPERIMENTAL DESIGNS A quasi experimental design is one in which experimental and control (comparison) are present & randomization is not there. Ex. Effect of primary Nursing education on staff morale. 2/18/2014 www.drjayeshpatidar.blogspot.com 18
  • 19. 2.1 Non equivalent control group design R O1 R O3 X O2 O4 Effect = (O2 – O1) – (O4 – O3) R = Randomization. O = Observation or measurement X = Treatment or intervention
  • 20. A researcher might choose a group of patients with diabetes on one hospital floor for the experimental group and a group of patients with diabetes on another floor for the comparison group. The experimental treatment would be administered to the experimental group; the comparison group would receive no treatment or some alternative treatment.
  • 21. E.g. A non-equivalent control group design was used by Valliammal Sudhakar (2008) to study the knowledge, attitude and practice towards physical well being of a group of IV, V, VIth grade students in two different schools.
  • 22. 2.2 THE TIME SERIES DESIGN • The time series design, a single group experiment comprises of series of observation in the before-time period to establish a baseline. • The experimental independent variable is then introduced, • Followed by another series of observation to examine the effect of the independent variable. 2/18/2014 www.drjayeshpatidar.blogspot.com 22
  • 23. 2.2.1 Time series Design (single group) Before x After ………...……………………………………... E O1 O2 O3 O4 O5 x O6 O7 O8 O9 10 ……………………………………………… 2/18/2014 www.drjayeshpatidar.blogspot.com 23
  • 24. 2.2.2 The Multiple Time Series Design Time series non equivalent control group design (QED) Before x After ……………………………………………………….. E O1 O2 O3 O4 O5 x O6 O7 O8 O9 10 ……………………………………………………………………………………… C O1 O2 O3 O4 O5 - O6 O7 O8 O9 10 …………………………………………………………………………… 2/18/2014 www.drjayeshpatidar.blogspot.com 24
  • 25. A researcher might assess the pain levels of a group of patients with low back pain. After 3 weeks of pain assessment, intervention will be introduced (O1 O2 O3 x O4 O5 O6). The results of this study would help the researcher to determine if a specific exercise is effective in reducing low back pain.
  • 26. 3. PRE EXPERIMENTAL DESIGN Pre experimental design: are discussed to provide examples of how not to do research.
  • 27. PRE-EXPERIMENTAL DESIGNS: 3.1 The one-shot case study or single case study In single case study, that studies at once, following a treatment or an agent presumed to cause change. Because the study design has a total absence of control; it is considered to be little value as an experiment X----------------O X= independent variables or stimulus 2/18/2014 www.drjayeshpatidar.blogspot.com 27
  • 28. ONE-SHOT CASE STUDY Lalitha, Premila & Balu (2006) conducted a study on nursing personnel registered for a day workshop on life skill education at MTIHS, Pondicherry.
  • 29. 3.2 ONE GROUP PRE-TEST AND POST-TEST DESIGN • Here only one group is observed before and after the independent variable is introduced. • Loss of the control group decreases the usefulness of the study but may be necessary in cases where it is not possible or feasible to have control groups 2/18/2014 www.drjayeshpatidar.blogspot.com 29
  • 30. E.g. Sailaxmi Gandhi(2006) conducted a pre-experimental study to assess the effectiveness of stress management programme on the selected variables of nurses working in psychiatric wards at NIMHANS, Bangalore.
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  • 48. CONCLUSION • Quantitative research approach is the commonest • Replication is possible • Data analysis is easy • Researcher’s subjectivity is minimal 2/18/2014 www.drjayeshpatidar.blogspot.com 48