Epi studies and Research Methods.pdf medical

For medical use

1. Epidemiological studies and
Research
BOYD
[email protected]
0978160357 & 0955975792

2. Course Aims
•Equip students with:
1. Understanding of research
2.Understanding the need for research
3.Understanding of the stages involved in
research
4.Skills and steps for proposal development

3. Course Aims
5. Understanding of Research ethics
6. Acquire skills for literature review

4. Course content
•Classification of Research
•Approaches to Research
- Quantitative
- Qualitative
•Study Designs, Sampling and Sample Sizes
•Steps in Research Design
•Data collection and analysis
•Research Ethics
•Scientific paper writing/Critique of scientific
papers
•Introduction to Grant writing

5. Research Definition
•“Research means a systematic investigation,
including research development, testing and
evaluation, designed to develop or contribute
to generalizable knowledge."

•Some surveillance projects, emergency
responses, and program evaluations are
research, others are not

6. Which projects are research?

Research:
•Purpose of project is to
generate generalizable
knowledge

•Intended benefits may or
may not include study
participants

•Data collected exceed
requirements for: care of
study participants,
surveillance or evaluation
purposes

Nonresearch:
•Purpose of project is to
prevent/control disease,
injury or health problem

•Benefits the participants
or community program

•Improve a public health
program or service

7. Quick Example: Research vs. Non-Research
Surveillance—Research
Sentinel surveillance in four study sites to identify and describe
cases of Lassa fever; purpose is to generate baseline information
in the Republic of Guinea; no public health interventions
planned; no direct benefit for study participants
Surveillance—Non-Research
Evaluation of surveillance system for the prevention and control
of disease; essential for practice of public health; purpose is to
provide information to prevent, detect and control outbreaks of
disease; intended benefits for the residents/population

8. •Principles of Basic and
Applied Research

9. Basic Research
•Also called pure or fundamental research
•Includes all branches of science and even
engineering
•Often arises out of curiosity
•inquisitive thinking such as exploration,
investigation, and learning
•Often a product of observation

10. Definition
•It is a systematic study directed toward
greater Knowledge or understanding of the
fundamental aspects of phenomena
•It is executed without thought of a practical
end goal
•Its often without specific application or
products in mind

11. Overview of Basic Research
•Basic research lays the foundation for
advancements in Knowledge that lead to
applied gains later on
•Occasionally results in unexpected discoveries
•It also focus on refuting or supporting theories
that explain observed phenomena
•It can be exploratory, explanatory or
descriptive

12. Example-computers
•Resulted from basic research into pure
mathematics conducted over a centaury ago
•There were no known practical applications
then
•It stimulated new thinking that have
revolutionaries and dramatically improved our
problem solving capacity and our lives
•So basic science, innovation and development are
intertwined

13. Applied Research
•It’s a systematic inquiry involving practical
application of science
•Accesses and uses research communities
-academia, known methods, techniques
•Deals with solving practical problems
•Employs empirical methodologies

14. Applied research
•Exists in the real world
•May require relaxing of strict research
protocols…example?? In cases wea random
sample is impossible
•Require transparency in methodology
•Interpretation of results should be in context
of the methods
•Conceptual frameworks or working hypotheis
or pillar questions vital

15. •Approaches to Research

16. Understanding Methodologies: Quantitative,
Qualitative and ‘Mixed’ Approaches

17. Understanding The Quantitative/
Qualitative Divide

•Quantitative and qualitative
research traditions represent a
fundamental debate in the
production of knowledge.

•The terms ‘quantitative’ and
‘qualitative’, particularly in
relation to methodology,
however, can be confusing,
divisive and limiting.
Zina O’Leary (2009) The Essential Guide to Doing Your Research Project. London: Sage

18. Zina O’Leary (2009) The Essential Guide to Doing Your Research Project. London: Sage

19. The Quantitative Tradition
•The quantitative tradition is
based on a belief that the study
of society is no different than
the scientific study of any other
element of our world.

•It premises scientific method,
hypothesis testing, deductive
logic, objectivity and
quantification.

Zina O’Leary (2009) The Essential Guide to Doing Your Research Project. London: Sage

20. Hypothetico-deductive Method
•Involves hypothesis testing through collection
and analysis of quantitative data gathered
through experimental design or survey
research.
Zina O’Leary (2009) The Essential Guide to Doing Your Research Project. London: Sage

21. Experimentation
•Experiments explore cause and
effect by manipulating
independent variables to see if
there is a corresponding effect on
a dependent variable.

•Pure experimentation requires
controlled environments and
randomly assigned control groups
(not always possible in social
science experiments often
conducted in the field rather than
a lab).

Zina O’Leary (2009) The Essential Guide to Doing Your Research Project. London: Sage

22. Studying A Population
• Exploring a population involves
building an understanding of
knowledge, attitudes, and
practices (KAP) related to a
particular topic or issue.

• Two broad methodological
strategies are to:

1.explore existing data
2.generate primary data – primarily
through survey research.

23. The Qualitative Tradition
• The qualitative tradition critiques
quantitative assumptions and premises
inductive logic, subjectivity, multiple
truths, the political nature of research, and
the value of depth over quantity.

• Qualitative research strategies for
achieving credibility include thoroughness,
i.e. saturation, crystallization, prolonged
engagement, persistent observation, broad
representation and peer review, and
confirmation, i.e. triangulation, member
checking, and full explication of method.

24. Ethnography
• Exploring a cultural group by:
•discovering
•understanding
•describing
•and interpreting a way of life from the point
of view of its participants.
• Ethnography is reliant on
prolonged engagement,
persistent observation and
analysis that demands a high
level of reflexivity.

25. Ethnography
• Because ethnographic
studies involve ‘immersion’
ethnographers need to
carefully manage their own
subjectivities and thoughtfully
negotiate their relationship
with the ‘researched’.

26. Phenomenology
• Exploring phenomena involves
generating descriptions of lived
phenomena as they present
themselves in direct experience.

• Descriptions emerge through
a dialogic process, and are
synthesized to offer a range of
distinct possibilities for the
experience of a particular
phenomenon.

27. Phenomenology
• While phenomenology
offers a way to study
phenomena, something often
neglected in the social
science literature on
phenomenology is that it can
be thick, divergent, and not
‘methods’-oriented.

28. Ethnomethodology
• Ethnomethodology explores the
methods individuals use to make
sense of their social world and
accomplish their daily actions.

• Ethnomethodologists search for
the collaborative and constantly
emerging nature of interaction
through exploration of breaching
experiments, building of shared
interpretations and interpretative
miscues.

29. Ethnomethodology
•Ethnomethodology:
• recognizes the interpretative work of the
individual
•offers a method for exploring ‘how’ questions
•allows comparisons of divergent cultural norms
•and allows exploration of specific forms of
interaction.
• However, it can be critiqued
for not addressing ‘significant’
questions, and being too
focused on verbal aspects of
communication.

30. Feminist Approaches
• While not a distinct methodology,
feminist research is premised on the belief
that traditional ‘rules’ of research are
imbued with unacknowledged and
unaddressed male bias.

• Feminist researchers argue that research
should be committed to:
•the empowerment of women
•overcoming inequity
•diverse representation of humanity
•empowerment of marginalized voices
•lessening the distinction between researcher
and researched
•searching for multiple, subjective and partial
truths.

31. Mixed Methodology
• “Mixed” studies traverse
traditional divides and can help
you capitalize on the best of both
traditions while overcoming their
shortcomings.

• “Mixed”approaches can be
premised in the quantitative
tradition with acceptance of
qualitative data; the qualitative
tradition with acceptance of
quantitative data; or be driven by
the questions themselves.

32. Mixed Methodology
•Definition

•Mixed methods research – an approach to
inquiry that combines or associates both
qualitative and quantitative forms.

33. Mixed Methodology
• Challenges associated with
mixed approaches include:

•needing to be familiar with and
skilled in two traditions
•being mindful of overambitious
design
•and not having the necessary
time, resources, or supervisory
support for a multi-mixed
method approach.

34. Reasons for “mixing”
•The insufficient argument – either quantitative or qualitative
may be insufficient by itself
•Multiple angles argument – quantitative and qualitative
approaches provide different “pictures”
•The more-evidence-the-better argument – combined
quantitative and qualitative provides more evidence
•Community of practice argument – mixed methods may be
the preferred approach within a scholarly community
•Eager-to-learn argument – it is the latest methodology
•“Its intuitive” argument – it mirrors “real life”
34

35. How methods can be mixed
Types of mixing Comments
Two types of research question. One fitting a quantitative approach and the
other qualitative.
The manner in which the research
questions are developed.
Preplanned (quantitative) versus
participatory/emergent (qualitative).
Two types of sampling procedure. Probability versus purposive.
Two types of data collection
procedures.
Surveys (quantitative) versus focus groups
(qualitative).
Two types of data analysis. Numerical versus textual (or visual).
Two types of data analysis. Statistical versus thematic.
Two types of conclusions. Objective versus subjective interpretations.
35

36. Planning mixed methods procedures
Timing Weighting Mixing Theorizing
No
Sequence
Concurrent
Equal Integrating Explicit
Sequential -
Qualitative
first
Qualitative Connecting Implicit
Sequential -
Quantitative
first
Quantitative Embedding
36

37. 37
Sequential explanatory design:
Characteristics
•Viewing the study as a two-phase project
•Collecting quantitative data first followed by
collecting qualitative data second
•Typically, a greater emphasis is placed on the
quantitative data in the study
•Example: You first conduct a survey and then follow
up with a few individuals who answered positively to
the questions through interviews

38. 38
Sequential explanatory design: When
do you use it?
•When you want to explain the quantitative
results in more depth with qualitative data
(e.g., statistical differences among groups,
individuals who scored at extreme levels)
•When you want to identify appropriate
participants to study in more depth
qualitatively

39. 39
Sequential exploratory design:
Characteristics
•Viewing the study as a two-phase project
•Qualitative data collection precedes quantitative
data collection
•Typically, greater emphasis is placed on the
qualitative data in the study
•Example: You collect qualitative diary entries,
analyze the data for themes, and then develop an
instrument based on the themes to measure
attitudes on a quantitative survey administered to a
large sample.

40. 40
Sequential exploratory design: When
do you use it?
•To develop an instrument when one is not
available (first explore, then develop
instrument)
•To develop a classification or typology for
testing
•To identify the most important variables to
study quantitatively when these variable are
not known

41. 41
The purpose of this two-phase, exploratory mixed methods study will be to explore
participant views with the intent of using this information to develop and test an
instrument with a sample from a population. The first phase will be a qualitative
exploration of a _______(central phenomenon) by collecting ___________(data) from
____________ (participants) at _______ (research site). Themes from this qualitative
data will then be developed into an instrument (or survey) so that the __________
(theory and research questions/hypotheses) can be tested that ________ (relate,
compare) ____________ (independent variable) with __________ (dependent variable)
for _________(sample of a population) at _________ (research site).
Sequential exploratory design:
Sample script

42. Concurrent triangulation design
42
QUAN
Data and Results
+
QUAL
Data and Results
Interpretation

43. 43
Concurrent triangulation design:
Characteristics
•Collecting both quantitative and qualitative data
•Collecting these data at the same time in the research
procedure
•Analyzing the quantitative and qualitative data separately
•Comparing or combining the results of the quantitative
and qualitative analysis
•Example: collect survey data (quantitative) and collect
individual interviews (qualitative) and then compare the
results

44. 44
Concurrent triangulation design: When is it
used?
•When you want to combine the advantages of
quantitative (trends, large numbers, generalization)
with qualitative (detail, small numbers, in-depth)
•When you want to validate your quantitative findings
with qualitative data
•When you want to expand your quantitative findings
with some open-ended qualitative data (e.g., survey
with closed- and open-ended data)

45. Concurrent embedded design
45


QUAN
qual


QUAL
quan
QUAN
Pre-test
Data &
Results
QUAN
Post-test
Data &
Results
Intervention
qual
Process

Interpretation

46. Concurrent embedded design:
Characteristics
•One data collection phase during which both
quantitative and qualitative data are collected (one is
determined to be the primary method).
•The primary method guides the project and the
secondary provides a supporting role in the
procedures.
•The secondary method is “embedded” or “nested”
within the predominant method and addresses a
different question.

46

47. Concurrent transformative design
47

QUAN + QUAL

Social science theory, qualitative theory,
advocacy worldview



QUAL

Social science theory, qualitative theory,
advocacy worldview
quan

48. Concurrent transformative design:
Characteristics
•Guided by a theoretical perspective.
•Concurrent collection of both quantitative and
qualitative data.
•The design may have one method embedded in the
other so that diverse participants are given a choice
in the change process of an organization.
48

49. Qualitative vs. quantitative research
Criteria Qualitative Research Quantitative Research
Purpose To understand & interpret social
interactions.
To test hypotheses, look at
cause & effect, & make
predictions.
Group Studied Smaller & not randomly
selected.
Larger & randomly selected.
Variables Study of the whole, not
variables.
Specific variables studied
Type of Data
Collected
Words, images, or objects. Numbers and statistics.
Form of Data
Collected
Qualitative data such as open-
ended responses, interviews,
participant observations, field
notes, & reflections.
Quantitative data based on
precise measurements using
structured & validated data-
collection instruments.
49

50. 50
Criteria Qualitative Research Quantitative Research
Type of Data
Analysis
Identify patterns, features, themes. Identify statistical relationships.
Objectivity and
Subjectivity
Subjectivity is expected. Objectivity is critical.
Role of
Researcher
Researcher & their biases may be
known to participants in the study, &
participant characteristics may be
known to the researcher.
Researcher & their biases are not
known to participants in the study, &
participant characteristics are
deliberately hidden from the researcher
(double blind studies).
Results Particular or specialized findings that
is less generalizable.
Generalizable findings that can be
applied to other populations.
Scientific
Method
Exploratory or bottom–up: the
researcher generates a new
hypothesis and theory from the data
collected.
Confirmatory or top-down: the
researcher tests the hypothesis and
theory with the data.
Qualitative vs. quantitative research

51. 51
Criteria Qualitative Research Quantitative Research
View of Human
Behavior
Dynamic, situational, social, &
personal.
Regular & predictable.
Most Common
Research Objectives
Explore, discover, & construct. Describe, explain, & predict.
Focus Wide-angle lens; examines the
breadth & depth of phenomena.
Narrow-angle lens; tests a specific
hypotheses.
Nature of
Observation
Study behavior in a natural
environment.
Study behavior under controlled
conditions; isolate causal effects.
Nature of Reality Multiple realities; subjective. Single reality; objective.
Final Report Narrative report with contextual
description & direct quotations from
research participants.
Statistical report with correlations,
comparisons of means, & statistical
significance of findings.
Qualitative vs. quantitative research

52. Study Designs in Epidemiologic
Research


Basic Epidemiology

53. Fundamental Assumption in
Epidemiology
•Disease doesn’t occur in a vacuum

Disease is not randomly distributed
throughout a population
–Epidemiology uses systematic approach to
study the differences in disease distribution
in subgroups
–Allows for study of causal and preventive
factors

54. 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

55. Types of primary studies
•Descriptive studies
–describe occurrence of outcome

•Analytic studies
–describe association between
exposure and outcome

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

57. 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?
Wijngaarden

58. Basic Research Study
Designs and their
Application to Epidemiology

59. Big Picture
•To prevent and control disease
•In a coordinated plan, look to
–identify hypotheses on what is related to
disease and may be causing it
–formally test these hypotheses
•Study designs direct how the
investigation is conducted

60. What designs exist to
identify and investigate
factors in disease?

61. Case report
Case series
Descriptive
Epidemiology
Descriptive
RCT
Before-After
study
Cross-sectional
study
Case-Crossover
study
Case-Control
study
Cohort study
Analytic
Ecologic study

62. 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

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

64. 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

65. 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
Increasing Knowledge of

Disease/Exposure

66. Descriptive Studies

67. Case Reports
•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

68. Case Series
•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

69. Case Series
•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

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

71. Analytical Studies

72. 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

73. 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

74. 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

75. 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

76. 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

77. Cross-sectional Studies
•Often used to study conditions that are relatively
frequent with long duration of expression (nonfatal,
chronic conditions)
•It measures prevalence, not incidence of disease
•Example: community surveys
•Not suitable for studying rare or highly fatal diseases
or a disease with short duration of expression

78. Cross-sectional studies
•Disadvantages
•Weakest observational design,
(it measures prevalence, not incidence of
disease). Prevalent cases are survivors
•The temporal sequence of exposure and effect
may be difficult or impossible to determine
•Usually don’t know when disease occurred
•Rare events a problem. Quickly emerging
diseases a problem

79. Epidemiologic Study Designs
•Case-Control Studies
–an “observational” design comparing
exposures in disease cases vs. healthy
controls from same population
–exposure data collected retrospectively
–most feasible design where disease
outcomes are rare

80. Case-Control Studies
Cases: Disease
Controls: No disease

81. Study
population
Cases
(disease)
Controls
(no disease)
factor present
factor absent
factor present
factor absent
present
past
time
Study begins here

82. Case-Control Study
•Strengths
–Less expensive and time consuming
–Efficient for studying rare diseases
•Limitations
–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

83. Hypothesis Testing: Case-Crossover Studies
•Study of “triggers” within an individual
•”Case" and "control" component, but information
of both components will come from the same
individual
•”Case component" = hazard period which is the
time period right before the disease or event
onset
•”Control component" = control period which is a
specified time interval other than the hazard
period

84. Epidemiologic Study Designs
•Cohort Studies
–an “observational” design comparing
individuals with a known risk factor or
exposure with others without the risk factor or
exposure
–looking for a difference in the risk (incidence)
of a disease over time
–best observational design
–data usually collected prospectively (some
retrospective)

85. time
Study begins here
Study
population
free of
disease
Factor
present
Factor
absent
disease
no disease
disease
no disease
present
future

86. 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

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

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

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

90. 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
–Loss to follow-up

91. Experimental 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

92. Experimental Studies
•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.

93. 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

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

95. Epidemiologic Study Designs
•Randomized Controlled Trials (RCTs)
–the “gold standard” of research designs
–provides most convincing evidence of
relationship between exposure and effect

•trials of hormone replacement therapy in
menopausal women found no protection
for heart disease, contradicting findings of
prior observational studies

96. 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

97. Review Questions
•Describe the link between exposure and
disease
•Describe study design sequence
•Describe strengths and weaknesses of
each design

98. •Steps in Research Design

99. At the start of your research project….
•After you have decided upon your research question, you
need to decide what approach you are going to take:
–Quantitative?
–Qualitative?

Ask yourself are you seeking to prove or disprove a theory?
Or are you trying to generalise your findings to a
population?
If so this will be a deductive approach, a quantitative
approach
Or are you hoping to elicit some understandings on what people
think or feel about an issue? Is the topic an area that there is little
information and so you must undertake an initial, exploratory
study?
If so, this will be induction, a qualitative approach

100. Deductive Theory
Theory

Hypotheses

Data Collection

Findings

Hypotheses Confirmed or Rejected

Revision of Theory

101. Induction
[General research question]

Observation




Theory Formulation

102. Quantitative and Qualitative Methods
Quantitative:
•Deductive
•Tests hypotheses
•Positivism
•Objectivism
•Employs measurement
•Macro
•Detached researcher
Qualitative:
•Inductive
•Produces theories
•Phenomenology
•Constructionism
•Does not employ measurement
•Micro
•Involved researcher

103. Quantitative and Qualitative Methods
•Quantitative:
Measures objective facts
Focuses on variables
Value free
Reliability is key
Independent of context
Many cases
Statistical analysis
•Qualitative:
Constructs social meaning
Focus on interactive processes
Values are present
Authenticity is key
Context constrained
Few cases
Thematic analysis

104. Common errors:
Open ended questions in surveys
•Sometimes people say that they use thematic analysis to
analyze open ended questions on a questionnaire/survey.
This is incorrect! Thematic analysis is a very specific form
of analysis where the data is searched for recurring
themes and theory then built from it.
•For open ended questions, you post-hoc code.
Quantitative by its nature, ‘quantifies’, so after you have
collected your answers, you attach codes to responses.
And so you can count the types of responses you
received.

105. Common errors:
‘Generalising’ in qualitative
research
•Sometimes you’ll come across people saying that the
qualitative study was small scale and so the findings
cannot be generalised to a population. This shows lack of
understanding!
•Qualitative research never seeks to generalise. It is
important that when reporting findings that you use the
terminology and methods appropriate to the approach -
e.g. don’t use ‘hypothesis’ pertaining to qualitative and if
using statistical analysis in quantitative, ALWAYS make
sure your sampling is random! [Sampling is the most
important step in quantitative work, yet so many get it
wrong]

106. Main Steps in Quantitative Research:
1.Identification of the problem
•Defining Research Problem
•Formulation of Problem Statement/Research Questions
2.Problem Analysis Framework
•Literature Review
•Hypothesis
•Objectives
•Methodological Consideration (Study Designs)
3.Collection of relevant data
•Study site and Population
•Sampling and Sample sizes
•Questionnaire Design
•Planning for data analysis- entry, cleaning and data interrogation
4.Interpretation of data
5.Ethical Consideration
6.Write up findings
•Techniques of scientific paper writing/Critique of scientific papers
•Introduction to grant writing

107. Main Steps in Qualitative Research:
1.General research question
2.Select relevant site(s) and subjects
3.Collection of relevant data
4.Interpretation of data
5.Conceptual and theoretical work
6.Tighter specification of the research question
7.Collection of further data
8.Conceptual and theoretical work
9.Write up findings

108. Examples of Quantitative
Research Methods:
•Experiments
•Social surveys
–Cross-sectional
–Comparative (cross-national)
–Longitudinal
•Content Analysis
•Secondary Statistical Analysis
•Official Statistics
–Demography
–Epidemiology
•Field stimulations
– Structured Interviews and Observation.

109. Examples of Qualitative Research:
•In-depth Interviews
•Focus Groups
•Ethnography/Field Research
•Historical-Comparative Research
•Discourse Analysis
•Narrative Analysis
•Media Analysis