CHAPTER - I
RESEARCH: A WAY
Research is
undertaken within most professions. More than a set of skills research is a way
of thinking examining critically the various aspects of your day-to-day
professional work understanding and formulating guiding principles that govern
a particular procedure and developing and testing new theories for the
enhancement of your practice. It is habit of questioning what you do and a
systematic examination of the observed information to find answers with a view
to instructing appropriate changes for a more effective professional service.
Let us take some disciplines as examples.
Suppose you are working in the field
of health. You may be a front-line service provider, supervisor or health
administrator/planner. You may be in a hospital or working as an our reach
community health worker. You may be a
nurse , doctor, occupational therapist, physiotherapist, social worker or other
paramedic. In any of these positions, some of the following questions may come
to your mind:
How
many patients do I see every day?
What
are some of the most common conditions prevalent among my patients?
What are the causes of these conditions?
Why
do some people have a particular condition whereas others do not?
What
are health needs of the community?
Why
do some people use the service while others do not?
What
do people think about the service?
How
satisfied are patients with the service?
How
effective is the service?
How
can the service be improved?
You can add many other questions to
this list. At times it may be possible to ignore these question because of the
level at which you work, at other time
you may make an effort to find answers on your own initiative or sometimes you
may be required to obtain answers for effective
administration and planning.
Let us take another discipline:
business studies Assume you work in the area of marketing. Again you can work
at different levels as a salesperson sales manager or sales promotion executive.
The list of questions the may come to your mind can be endless. The types of
question and the need to find answers to them will vary with the level at which
you work in the organization. You may just want to find out the monthly fluctuation
in the sale of a particular product. Or you may be asked to develop an R &
D strategic plan to compete for a greater share of the market for the products
produced by your company. Besides these, there could be many other questions
for which you require answers. For example:
What
is the best strategy to promote the sale of a particular product?
How many salespersons do I need?
What is the effect of a particular advertising campaign on
the sale of this product?
How satisfied are the consumers with
product?
How much are consumers prepared to spend
on this item?
What do consumers like or dislike
about this product?
What type of packaging do consumers
prefer for this product:?
What
training do the salespersons need to promote the sale of this product?
What are the attributes of a good
salesperson?
To take a
different example, let us assume that you work as a psychologist counselor or
social worker. While engaging in the helping process you may ask yourself (or someone else can ask) the
following questions:
What are my clients’ most common presenting
problems?
What are their most common
underlying problems?
What is the socioeconomic background
of my clients?
Why am I successful in certain cases
and not in other?
What resources are available in the community to help a
client with a particular need?
What intervention strategies are appropriate for this
problem?
How satisfied are my clients with my service?
As
a supervisor, administrator or manager of an agency, again different questions
relating to efficient and effective service may come to your mind For example:
How many people are coming to my agency?
What are the socioeconomic-demographic characteristics of my
clients?
How many cases in day can a worker effectively handle?
Why do some people use the service while other do not?
How effective is the service?
What are the most common needs of clients who come to this
agency?
What are the strengths and weaknesses of the service?
How satisfied are the clients with the service?
How can I improve this service for my clients?
As
a professional you might be interested in finding answers to theoretical
questions, such as:
Which is the most effective
intervention for a particular problem?
What causes X or what are the
effects of Y?
What is relationship between two
phenomena?
How do I measure the self-esteem of
my clients?
How do I ascertain the validity of
my questionnaire?
What is the pattern of program
adoption in the community?
Which
is the best way of finding out community attitudes towards an issue?
Which
is the best way to find out the effectiveness of a particular treatment?
How
can I select an unbiased sample?
What
is the best way to find out about the level of marriage satisfaction among my
clients?
In
this age of consumerism you cannot afford to ignore the consumers of a service.
Consumers have the right to ask questions about the quality and effectiveness
of the service they are receiving and you, as a service provider, have an
obligation to answer their questions. Some of the questions that a consumer may
ask are:
How effective is the service that I am
receiving?
Am I getting value for money?
How well-trained are the service
providers?
Most
professions that are in the human service industry would lend themselves to the
questions raised above and you as a service provider should be well prepared to
answer them. Research is one of the ways to help you to answer such questions
objectively.
Applications of research
Very
little research in the field is pure in nature. That is, very few people do
research in research methodology per se. Most research is applied research,
which has wide application in many disciplines. Every profession uses research
methods in varying amounts in many areas. They use the methods and procedures
developed by research methodologists in order to increase understanding in
their own profession and to advance the professional knowledge base. It is
through the application of research methodology that strengthens and advance
their own profession. Examine your field. You will find that its professional
practice follows procedures and practices tested and developed by others over a
long period of time. It is in this testing process that you need research
skills, the development of which falls in the category of pure research. As a
matter of fact, the validity of your findings entirely depends upon the
soundness of the research methodology adopted.
Research techniques applied entirely
in nature are used primarily for professional consolidation, understanding,
development and advancement.
As just mentioned, the questions
that can be raised about any profession where you directly or indirectly
provide a service-health (nursing occupational therapy , physiotherapy ,
community health, promotion, public health), education, town planning, library
studies, psychology, business studies, social work-can be considered from four
different perspectives:
1.
the service provider;
2.
the service administrator, manager and /or planner;
3.
the service
consumer; and
4.
the professional.
These perspectives are summarized in
Figure 1.1.It is impossible to list all the issues in every discipline but this
framework can be applied to most disciplines and situations in the humanities
and the social sciences to identify, from the viewpoint of the above
perspectives, the possible issues in your own academic field.
Definitions
of research
There
are several ways of obtaining answers to your professional questions.
These
methods range from the fairly informal based upon clinical impressions, to the
strictly scientific, adhering to the conventional expectations of scientific procedures.
Research is one of the ways to find answers to your questions. When you say that you are undertaking a
research study to find out answers to a question, you are implying that the
process:
1.
is being undertaken within a framework of a set of
philosophies;
2.
uses procedures, methods and techniques that have been
tested for their validity and reliability;
3.
Is designed to be unbiased and objective.
Your philosophical orientation may stem
from one of the several paradigms and approaches in research-positivist interpretive,
phenomenolistist, action or participatory, feminist, qualitative,
quantitative-and the academic discipline in which you have been trained. The
concept of validity can be applied to any aspect of the research process. It
ensures that in a research study correct procedures have been applied to find
answers to a question. Reliability refers to the quality of a measurement procedure
that provides repeatability and accuracy. Unbiased and objective means that you
have taken each step in an unbiased manner and drawn each conclusion to the
best of your ability and without introducing your own vested interest. The
author makes a distinction between bias and subjectivity. Subjectivity is an
integral part of your way of thinking that is conditioned by your educational
background, discipline, philosophy, experience and skills. Bias on the other
hand, is a deliberate attempt to either conceal or highlight something. For
example, a psychologist may look at a piece of information differently from the
way in which an anthropologist or a historian looks at it.
Adherence to the three criteria
mentioned above enables the process to be called research. Therefore when you
say you are undertaking a research study to find the answer to a question, this
implies that the method(s). you are adopting fulfils these
expectations(discussed later in the chapter).
However, the degree to which these
criteria are expected to be fulfilled varies from discipline to discipline and
so the meaning of research differs from one academic discipline to another. For
example, the expectations of the research process are markedly different
between the physical and the social sciences. In the physical sciences a
research Endeavour is expected to be strictly controlled at each step, whereas
in the social sciences rigid control control enforced and sometimes is not even
demanded
Within the social sciences the level
of control required also varies markedly from one discipline to another, as
social scientists differ over the need for the research process to meet the
above expectations. Despite these differences among disciplines, their broad
approach to inquiry is similar. The research model in this book is based upon
this broad approach.
As beginners in research you should
understand that research is not all technical, complexes, statistics and
computers. It can be a very simple activity designed to provide answers to very
simple questions relating to day to day activities. On the other hand, research
procedures can also be employed to formulate intricate theories or laws that
govern our lives. The difference between research and non-research activity is,
as mentioned in the way we find answers: the process must meet certain
requirements to called research. To identify these requirements let us examine
some definitions of research.
The word research is composed of two
syllables, re and search. The dictionary defines the former as a prefix meaning
again, anew or over again and the latter as a verb meaning to examine closely
and carefully, to test and try, or to probe Together they form a noun
describing a careful, systematic, patient study and investigation in some field
of knowledge, undertaken to establish facts or principles (Grinnell 1993:4)
Grinnell
further adds: research is a structured inquiry that utilizes acceptable scientific
methodology to solve problems and creates new knowledge that is generally
applicable, (1993:4)
Grinnell further adds: ‘research is a
structured inquiry that utilizes acceptable scientific methodology to solve
problems and creates new knowledge that is generally applicable ‘(1003:4)
Lundberg (1942) draws a parallel
between the social research process which is considered scientific , and the
process that we use in our daily lives According to him:
Scientific
methods consist of systematic observation, classification and inter-predation
of data. Now, obviously, this process is one in which nearly all people engage
in the course of their daily lives. The main difference between our day-to-day
generalizations and the conclusions usually recognized as scientific method
lies in the degree of formality, rigorousness, verifiability and general
validity of the latter (Loudberg 1942:5)
Burns
(1994.2) defines research as a systematic investigation to find answers to a
problem’
According to Kerlinger
(1986:10),’scientific research is a systematic, controlled empirical and
critical investigation of propositions about the presumed relationships about
various phenomena; Bulmer (1977:5) states:’ Nevertheless sociological research,
is primarily committed to establishing systematic, reliable and valid knowledge
about the social world;
Characteristics of research
From
these definitions it is clear that research is a process for collecting analyzing
and interpreting information to answer questions. But to qualify as research,
the process must have certain characteristics: it must, as far possible, be
controlled, rigorous, systematic, valid and verifiable, empirical, and
critical.
Let
us briefly examine these characteristics to understand what they mean.
Controlled- in real life there are many
factors that affect an outcome A particular event is seldom the result of a
one-to-one relationship. Some relationship is more complex than others. Most
outcomes are a sequel to the interplay of a multiplicity of relationship and
interacting factors. In a study of cause
and effect relationships it is important to be able to link the effect (s) with
the cause (s) and vice versa. In the study of causation, the establishment of
this linkage is essential; however,
in practice, particularly in the social
sciences, it is extremely difficult –and often impossible- to make the link.
The concept of control
implies that in exploring causality in relation to two variables, you set up
your study in way that minimizes the effects of other factors affecting the
relationship. This can be achieved to a large extent in the physical sciences,
as most of the research is done in a laboratory, However, in the social sciences
it is extremely difficult as research is carried out on issues relating to
human beings living in society, where such controls are impossible. Therefore,
in the social sciences, as you cannot control external factors, you attempt to
quantify their impact.
Rigorous –You must be scrupulous in
ensuring that the procedures followed to find answers to questions are
relevant, appropriate and justified. Again, the degree of rigor varies markedly between the physical and the social sciences and
within the social sciences.
Systematic-this implies that the
procedures adopted to undertake an investigation follow a certain logical
sequence. The different steps cannot be taken in a haphazard way. Some
procedures must follow others.
Valid and verifiable this concept
implies that whatever you conclude on the basis of your findings is correct and
can be verified by you and others.
Empirical this means that any
conclusions drawn are based upon hard evidence gathered from information
collected from real-life experiences or observations.
Critical critical scrutiny of the
procedures used and the methods employed is crucial to a research inquiry. The
process of investigation must be foolproof and free from any drawbacks. The
process adopted and the procedures used must be able to withstand critical
scrutiny.
For a process to be called research,
it is imperative that it has the above characteristics.
Types of research
Research can be
classified from three perspectives (Figure 1.2):
1.
application of the research study;
2.
objectives in undertaking the research;
3.
Inquiry mode employed.
These three
classifications are not mutually exclusive –that is, research study classified
from the viewpoint of application can also be classified from the perspectives
of objectives and inquiry mode employed. For example a research project may be
classified as pure or applied research (from the perspective of application),
as descriptive, correlation, explanatory or exploratory .(from the perspective
of objectives) and as qualitative or quantitative (from the perspective of the
inquiry mode employed).
Application
If
you examine a research Endeavour from the perspective of its application there
are two broad categories: pure research and applied research. In the social
science, according to Bailey (1978:7):
Pure research involves developing
and testing theories and hypotheses that are intellectually challenging to the
researcher but may not have practical application at the present time or in the
future. Thus such work often involves the testing of hypotheses containing very
abstract and specialized concepts.
Pure research is
also concerned with the development examination verification and refinement of
research methods, procedures, techniques and tools that form the body of
research methodology. Examples of pure research include developing a sampling
technique that can be applied to a particular situation; developing a methodology
to assess the validity of a procedure; developing an instrument, say to measure
the stress level in people; and finding the best way of measuring people’s
attitudes. The knowledge produced through pure is sought in order to add to the
to the existing body of knowledge of
research methods.
Most of the research in the social
sciences is applied. In other words the research techniques, procedures and
methods that form the body of research methodology are applied to the
collection of information about various aspects of a situation, issue, problem
or phenomenon so that information gathered can be used in other ways-such as
for policy formulation, administration and the enhancement of understanding of
a phenomenon.
Objectives
If you examine a
research study from the perspective of its objectives, broadly a research
endeavor can be classified as descriptive, correlation explanatory or
exploratory
A study classified as descriptive
research attempts to describe systematically a situation, problem,
phenomenon, service or program, or provides information about, say the living
conditions of a community, or describes attitudes towards an issue. For
example, it may attempt to describe the types of service provided by an
organization, the administrative structure of an organization, the living
conditions of Aboriginal people in the outback, the needs of a community, what
it means to go through a divorce, how a child feels living in a house with
domestic violence, or the attitudes of employees towards management. The main
purpose of such studies is to describe what is prevalent with respect to the
issue problem under study.
The main emphasis in a correlation
research study is to discover or establish the existence of a
relationship/association/interdependence between two or more aspects of a
situation. What is the impact of an advertising campaign on the sale of a
product? What is the relationship between stressful living and the incidence of
heart attack? What is the relationship between fertility and mortality? What is
the relationship between technology and unemployment? What is the effect of a
health service on the control of a disease, or the home environment or
educational achievement? These studies examine whether is a relationship
between two or more aspects of a situation or phenomenon and therefore, are
called co relational studies.
Explanatory research attempts to
clarify why and how there is a relationship between two aspects of a situation
or phenomenon. This type of research attempts to explain, for example, why
stressful living results in heart attacks; why a decline in mortality is
followed by fertility decline; or how the home environment affects children’s
level of academic achievement.
The fourth type of research, from
the viewpoint of the objectives of a study, is called exploratory research.
This is when a study is undertaken with the objective either to explore an area
where little is known or to investigate the possibilities of undertaking a
particular research study. When a study is carried out to determine its
feasibility it is also called a feasibility study or a pilot study. It is
usually carried out when a researcher wants to explore areas about which s/he
has little or no knowledge. A
small-scale study is undertaken to decide if it is worth carrying out a
detailed investigation. On the basis of the assessment made during the
exploratory study, a full study may eventuate. Exploratory studies are also
conducted to develop, refine and/or test measurement tools and procedures.
Table 1.1 show types of research study from the view point of objectives.
Although, theoretically, a research
study can be classified in one of the above perspectives, in practice most
studies are a combination of the first three categories; that is, they contain
elements of descriptive, co relational and explanatory research. In this book
the guidelines suggested for writing a research report encourage you to
integrate these aspects.
Table1.1 Types of research studies from
the viewpoint of objectives
|
Examples
|
Aim
|
Main theme
|
Type of research
|
·
Problems faced
by new immigrants Extent of occupational mobility among immigrants
·
Consumers’
likes and dislikes with regard to a product.
·
Effects of
living in a house with domestic violence
·
Strategies put
in place by a company to increase productivity of workers
|
To
describe what is prevalent regarding:
·
A group of
people
·
A community
·
A phenomenon
·
A program
·
An outcome
|
To describe what is prevalent
|
Descriptive
research
|
|
To
establish or explore:
|
To
ascertain if there is a relationship
|
Co
relational research
|
|
To explain:
|
To explain
why the relationship is formed
|
Explanatory
research
|
Inquiry mode
The third
perspective in our typology of research concerns the process you adopt to find answers to your research
questions. Broadly, there are two approaches to inquiry:
- the structured approach;
- the unstructured approach;
The structured
approach to inquiry is usually classified as quantitative research and
unstructured as qualitative research. In the structured approach
process-objectives, design, sample, and the questions that you plan to ask of
respondents- is predetermined. The unstructured approach, by contrast, allows
flexibility in all these aspects of the process. The structured approach is
more appropriate to determine the extent of a problem, issue or phenomenon: the
unstructured, to explore its nature. Both approaches have their place in
research. Both have their strengths and weaknesses. Therefore, you should not
lock yourself into solely quantitative or qualitative research. The choice of a
structured or unstructured approach and of quantitative mode of inquiry should
depend upon:
Aim
of your inquiry-exploration, confirmation or quantification.
Use
of the findings-policy formulation or process understanding.
The distinction
between quantitative and qualitative research, in addition to the
structured/unstructured process of inquiry, is also dependent upon some other
considerations which are briefly presented in table 2.1 on page 17,.
The study is classified as
qualitative if the purpose of the study is primarily to describe a situation,
phenomenon, problem or event; the information is gathered through the use of
variables measured on nominal or ordinal scales (qualitative measurement
scales); and if analysis is done to establish the variation in the situation,
phenomenon or problem without quantifying it. The description of an observed
situation, the historical enumeration of events an account of the different
opinions people have about an issue, and a description of the living conditions
a community are examples of qualitative research.
On the other hand, the study is
classified as a quantitative study if you want to quantify the variation in a
phenomenon , situation , problem or issue; if information is gathered using
predominantly quantitative variables; and if the analysis is geared to
ascertain the magnitude of the variation .Examples of quantitative aspects of a
research study are: How many people have a particular problem? How many people
hold a particular attitude?
The use of statistics is not an
integral part of a quantitative study. The main function of statistics is to
act a test to confirm or contradict the conclusions that you have drawn on the
basis of your understanding of analyzed data. Statistics, among other things
help you to quantify the magnitude of an association or relationship, provide
an indication of the confidence you can place in your findings and help you to
isolate the effect of different variables. It is strongly recommended that you
do not lock yourself into becoming either solely a quantitative or solely a
qualitative researcher. It is true that there are disciplines that lend
themselves predominantly either to qualitative or to quantitative research. For
example, such disciplines as anthropology ,history and sociology are more
inclined towards qualitative research,
whereas psychology, epidemiology, education, economics, public health and
marketing are inclined towards quantitative research. However, this does not
mean that an economist or a psychologist never uses the qualitative approach,
or that an anthropologist never uses
quantitative information. There is increasing recognition by most disciplines
in the social sciences that both types of research are important for a good
research study. The research problem itself should determine whether the study
is carried out using qualitative or qualitative methodologies.
Both qualitative and quantitative
approaches have their strengths and weaknesses, and advantages and advantages
and disadvantages. ‘Neither one is markedly superior to the other in all
respects’ (Ackroyd & Hughes 1992:30).
The measurement and analysis of the
variables about which information is obtained in a research study are dependent
upon the purpose of the study .In many studies you need to combine both qualitative
and quantitative approaches. For example, suppose you want to find out the
types of service available to victims of
domestic violence in a city and the
extent of their utilization. Types of service is the qualitative aspect of the
study as finding out about them entails description of the services. The extern
of utilization of the services is the quantitative aspect as involves
estimating the number of people who use the services and calculating other
indicators that reflect the extent of utilization.
Paradigms of research
There are two
main paradigms that form the basis of research in the social sciences, It is
beyond the scope of this book to go into any detail about these. The crucial question that divides the
two is whether the methodology of the
physical sciences can be applied to the study of social phenomena. The paradigm
that is rooted in the physical sciences is called the systematic, scientific or
positivist approach. The opposite paradigm has come to be known as the
qualitative, ethnographic , ecological or naturalistic approach The advocates of the two opposing sides have developed their own values, terminology,
methods and techniques to understand social phenomena . However, since the
mid-1960s there has been a growing recognition that both paradigms have their
place. The research purpose should determine the mode of inquiry, hence the paradigm. To
indiscriminately apply one approach to
all the research problems have their place. The research purpose should
determine the mode of inquiry, hence the paradigm. To indiscriminately apply
one approach to all the research problems can be misleading and inappropriate.
A positivist paradigm lends itself
to both quantitative and qualitative research. You can conduct qualities
research within the positivist paradigm.
However, the author makes a distinction
between qualitative data on the one hand and qualitative research on the other
as the first is confined to the measurement of variables and the second to a
use of methodology.
The author believes that no matter
what paradigm the researcher works within, s/he should adhere to certain values
regarding the control of bias, and the maintenance of objectivity in terms of
both research process itself and the conclusions drawn, It is the application
of these values to the process of information gathering, analysis and
interpretation that enables it to be called a research process.
SUMMARY
There are
several ways of collecting and understanding information and finding answers to
your questions-research is one way. The difference between research and other ways of obtaining
answers to your questions is that in a process that is classified as research,
you work within a framework of a set of philosophies, use methods that have
been tested for validity and reliability, and attempt to be unbiased and
objective.
Research has many applications. You
need to have research skills to be an effective service provider,
administrator/manager or planner. As a professional who has a responsibility to
enhance professional knowledge, research skills are essential.
The typology of research can be
looked at from three perspectives: application, objectives and the inquiry
process. From the point of view of the application of research, three is
applied and pure research. Most of the research undertaken in the social
science is applied, the findings being designed either for use in understanding
a phenomenon/issue or to bring change in a program. Pure research is academic
in nature and is undertaken in order to gain knowledge about phenomena that may
or may not have application in the near future, and to develop new techniques
and procedures that form the body of research methodology. A research study can
be carried out with four objectives: to describe a situation, phenomenon, and
problem or issue (descriptive research); to establish or explore a relationship
between two or more variables (co relational research); to explain why certain
things happen the way they do (explanatory research); and to examine the
feasibility of conducting a study (exploratory research). From the point of
view of the mode of inquiry, there are two types of research: quantitative and
qualitative. The main objective of a qualitative study is to describe the variation
in a phenomenon, situation or attitude, whereas quantitative research, in
addition, helps you to quantify the variation.
There are two main paradigms that
form the basis of social science research: positivist and naturalist. The
crucial question that divides the two is whether the methodology of research in
the physical sciences can be applied to research in the social sciences.
CHAPTER-II
The Research
Process: A Quick Glance
The research process: an eight-step model
Research
methodology is taught as a supporting subject in several ways in many academic
disciplines at various levels by people committed to a variety of research
paradigms. Though paradigms vary in their contents and substance, their broad
approach to inquiry, in the author’s
Opinion , is
similar. Such ideas have also have been expressed by fastener and Katz, who in
the foreword of their book Research
Methods in Behavioral Sciences say that Although the basic logic of scientific
methodology is the same in all fields, its specific techniques and approaches
will vary, depending upon the subject matter (1966:vi). Therefore, the model
developed here is generic in nature and can be applied to a number of disciplines
in the social sciences. It is based upon
a practical and step-by approach to a research inquiry and each step provides a
smorgasbord of methods, models and
procedures.
Suppose you want to go out for a drive.
Before you start, you must decide where
you want to go and then which route to take. If you know the route, you do not
need to consult a street directory but, if you do not, you need to use one.
Your problem is compounded if there is more than one route. You need to decide
which one to take. The research process is very similar to undertaking a
journey. As with your drive, for a research journey there are also two
important decisions to make. The First is to decide what you to find out or in
other words what research questions you want to find answers to . Having
decided upon your research questions or
problems you then need to think how to go about finding their answers. The path
to finding answers to your research questions constitutes research methodology.
Just as there are posts along the way to your travel destination, so there are
practical steps through which you must pass in your research journey in order
to find the answers to your research questions(Figure2.1). The sequence of these
steps is not absolute. With experience you can change it. At each operational
step in the research process you are required to choose from a multiplicity of
methods, procedures and models of research methodology which will help you to
best achieve your objectives. This is
where your knowledge base of research methodology plays a crucial role.
The aim of this book is to provide
you with knowledge that will enable you to select the most appropriate methods
and procedures. The strength of this book lies in anchoring the theoretical
knowledge to the posts of the research journey. A smorgasbord choice at each
operation step aims to provide, at a
beginner’s level, knowledge of methods and procedures used both by qualitative
and quantitative researches, though the book is more inclined towards the
quantitative way of thinking .
Figure 2.1 The research journey- touch each post and select methods and procedures
appropriate for your journey.
Deciding Planning
how Actually
What doing
RESEARCH
JOURNEY
__________________________________________________________________________________________
Stage
I Stage
II Stage III
Quantitative and
qualitative research methodologies differ in the philosophy that underpins
their mode of inquiry as well as, to some extent, in methods, models and
procedures used. Though the research process is broadly the same in both quantitative
and qualitative research are differentiated in terms of the methods of data
collection, the procedures adopted for data processing and analysis, and the
style of communication of the findings. If your research problem lends itself
to a qualitative mode of inquiry, you are more likely to use the unstructured
interview or observation as your method of data collection. When analyzing data
in qualitative research you go through the process of identifying themes and
describing what you have found out during your interviews or observation rather
than subjecting your data to statistical procedures. Table 2.1 summarizes the
difference between qualitative and quantitative research.
Table 2.1 Differences
between qualitative and quantitative research
|
Difference
with respect to:
|
Quantitative
research
|
Qualitative
research
|
|
Underpinning philosophy
|
Rationalism: That human beings achieve knowledge
because of their capacity to reason’ (Bernard 1994:2)
|
Empiricism: The only knowledge that human beings
acquire is from sensory experiences’ (Bernard 1994:2)
|
|
Approach to inquiry
|
Structured/rigid/predetermined methodology
|
Unstructured/flexible/open methodology
|
|
Main purpose of investigation
|
To quantify extent of variation in a phenomenon,
situation, issue etc.
|
To describe variation. In a phenomenon, situation,
issue etc.
|
|
Measurement of variables
|
Emphasis on
some form of either measurement or classification of variables
|
Emphasis on description of variables
|
|
Sample size
|
Emphasis on greater sample size
|
Fewer cases
|
|
Focus of inquiry
|
|
Covers multiple issues but assemble required
information from fewer respondents
|
|
Dominant research value
|
Reliability and objectivity (value-free)
|
Authenticity but does not claim to be value-free
|
|
Dominant research topic
|
Explains prevalence, incidence, extent, nature
of issues, opinions and attitude;
discovers regularities and formulates theories
|
Explores experiences, meanings perceptions and
feelings
|
|
Analysis of data
|
Subjects variables to frequency distributions,
cross-tabulations or other statistical procedures
|
Subjects responses, narratives of observation data
to identification of themes and describes these
|
|
Communication of findings
|
Organization more analytical in nature, drawing
inferences and conclusions, and testing magnitude and strength of
relationship
|
Organization more descriptive and narrative in
mature
|
Since,
at a number of steps of the choice of methods and procedures is influenced by
quantitative/qualitative distinction, the methods and procedures discussed in
some chapters are differentiated; however, I have tried to keep this
distinction to the minimum as the model is applicable to both. Note that this book is
for beginners. There is not enough space to cover extensively the applicability
and use of each method, model and procedure. I have elaborated on those
associated with quantitative research more than on those linked to qualitative
research. For a deeper understanding of a method or procedure relating to either,
you may wish to consult other books identified in the text.
Figure 2.2 shows the proposed model.
The tasks identified in arrows are the
operational steps you need to follow in order to conduct a study quantitative
or qualitative. Topics identified in rectangles are the required theoretical
knowledge needed to carry out these steps. The tasks identified in circles are the intermediary steps that you
need to complete to go from one step to another.
It is important for a beginner to work through these steps in the proposed,
though with experience you do not need to follow the sequence.
The research process
|
The research process
|
This book is written around the theoretical
knowledge required to undertake each operational step and follows the same sequential progression as
is needed to undertake a research
investigation . For each operational step, the required theoretical knowledge
is further organized, in different chapters, around the operational step to
which, in the author’s opinion, it is most logically related (Figure 2.3).
Again, for a beginner, it is important to study this diagram to relate the
theoretical knowledge to the operational steps.
The following section of this chapter provide a quick glance at the
whole process to acquaint you with the
various tasks you need to undertake to
carry out your study, thus giving you some idea of what the research
journey involves.
Steps in planning a research study
Step I: formulating a research problem
Formulating a
research problem is the first and most important step in the research process. A research problem
identifies your destination: it should
tell you, your research supervisor and your readers what you intend
to research. The more specific and clear
you are the better, as everything that follows in the research process- study design,
measurement procedures, sampling
strategy , frame of anayle and the style
of writing of your dissertation or report- is greatly influenced by the way in
which you formulate your research problem. Hence, you should give it
considerable and careful thought at this stage. The main function of
formulating a research problem is to
decide what you want to find out about. Chapter 4 deals in detail with
various aspects of formulating a research problem.
It is extremely important to
evaluate the research problem in the in the light of the financial resources at your disposal, the
time available, and your own and your research supervisor’s expertise and knowledge in the field of study. It is
equally important to identify and any gaps in your knowledge of relevant
disciplines, such as statistics required
for analysis. Also, ask yourself whether you have sufficient knowledge about
computers and software if you plan to
use them.
Step II: conceptualizing a research design
An extremely
important feature of research is the use of appropriate methods. Research involves
systematic, controlled valid and rigorous exploration and description of what is not known and
establishment of associations and
causation that permit the accurate prediction of outcomes under a given
set of conditions. It also involves identifying gaps in knowledge, verification
of what is already known, and
identification of past errors and limitations. The strength of what you find largely rests on how
it was found.
The main function of a research
design is to explain how you will find answers to your research questions. The
research design sets out the logic.
|
Operational steps and research methodology
|
Figure 2.3 The
chapters in the book in relation to the operational steps
Of
your inquiry. A research design should include the following: the study design
per se and the logistical arrangements that you propose to undertake, the
measurement procedures, the sampling strategy, the frame of analysis and the
time –frame. For any investigation, the selection of an appropriate research
design is crucial in enabling you to arrive at valid findings , comparisons and
conclusions. A faulty design results in misleading findings and is therefore
tantamount to wasting human and financial resources. In scientific circles, the
strength of an empirical investigation is primarily evaluated in the light of
the research design adopted. When selecting a research design it is important
to ensure that it is valid, workable and manageable chapter 7 provides details
about research design.
There is an enormous variety of
study designs and you need to be acquainted with some of the most common ones. Chapter 8
explains some of these designs. Select or develop the design that is most
suited to your study. You must have strong reasons for
selecting a particular design you must be able to justify your selection; and
you should be aware of its strengths, weaknesses and limitations. In addition,
you will need to explain the logistical details needed to implement the
suggested design.
Step III: constructing an instrument for
data collection
Anything
that becomes a means of collecting information for your study is called a
research tool or a research instrument’ For example, observation forms,
interview schedules, schedules, questionnaires and interview guides are all
classified as research tools.
The construction of a research tools
is the first practical step in carrying
out a study. You will need to decide how you are going to collect data for the proposed study and then construct a research instrument for
data collection. Chapter 9 details the various methods of data collection and
chapter 10 deals with methods for
collecting data using attitudinal scales.
If you are planning to collect data specifically for
your study (Primary data), you need to either construct a research instrument
or select an already constructed one. The process of developing a research
instrument is also discussed in Chapter
9. The concepts of validity and reliability in relation to a research instrument
are discussed in Chapter 1.1.
If you are using secondary data
(information already collected for other purposes), develop a form to extract
the required data. In order to determine what information is required, the same
process as described for primary data above.
Field testing also know as
pre-testing a research tool is an integral part of instrument construction. As a
rule the field test should not be carried out
on the sample of your study but on a similar population.
If you are planning to use a
computer for data analysis, you may wish to provide space for condign the data
on the research instrument.
Step
IV: selecting a sample
The
accuracy of your findings largely depends upon the way you select your sample.
The basic objective of any sampling design is to minimize, within the
limitation of cost, the gap between the values obtained from your sample and those prevalent in the population.
The underlying premise in sampling
is that, if a relatively small number of units is selected, it can provide with
a sufficiently high degree of probability a fairly true reflection of the
sampling population that is being studied. Sampling theory is guided by two
principles:
1.
the avoidance of bias in the selection of a sample; and
2. the
attainment of maximum precision for a
given outlay of resources.
There
are three categories of sampling design (Chapter 12):
1. Random/probability sampling designs;
2. Non-random probability sampling
designs; and
3. Mixed sampling design.
There are several sampling
strategies within the first two categories. You need to be acquainted with these sampling designs the
strengths and weaknesses of each and the situations in which they can or cannot
be applied in order to select the one most
appropriate for your study. The type of sampling strategy you use will
influence your ability to make gener -alisations from the sample findings about the study population, and the
type of test you can apply to the data.
Step V: writing a research proposal
Having
done all the preparatory work, the next step is to put everything together in a
way that provides adequate information about your research study, for your
research supervisor and others. This overall plan, called a research proposal,
tells a reader about your research problem and how you are planning to
investigate. Broadly, a research proposal’s main function is to detail the
operational plan for obtaining answers to your research questions. In doing so
it ensures- and reassures the readers of – the validity of the methodology to
obtain answers accurately and objectively.
Universities and other institutions
may have differing requirements regarding the style and content of a research
proposal , but the majority of institution would require most of what is set
out here. Requirements may also very within an institution, form discipline to
discipline or from supervisor to supervisor. However, the guidelines set out in
Chapter 13 provide a framework which will be acceptable to most.
A research proposal must tell you,
your research supervisor and a reviewer the following information about your
study:
- what you are proposing to do;
- how you plan to proceed.
- Why you selected the proposed strategy.
Therefore
it should contain the following information about your study (Chapter 13):
- A statement of the objectives of the study;
- A list of hypotheses. If you are testing any;
- The study design you are proposing to use;
- The setting for your study;
- The research instrument(s) you are planning to use;
- Information on sample size and sampling design;
- Information on data processing procedures;
- An outline of the proposed chapters for the report;
- The proposed time frame
Phase III: conducting a research study
Step VI: collecting data
Having
formulated a research problem, developed a study, constructed a research
instrument and selected a sample, you then collect the data from which you will
draw inferences and conclusions for your study.
Many methods could be used to gather
the required information. As a part of the research design, you decided upon
the procedure you wanted to adopt to collect your data. In this phase your
actually collect the data. For example, depending upon your plans, you might
commence interviews, mail out a questionnaire, conduct nominal focus group
discussions or make observations. Collecting data through any one of the
methods may involve some ethical issues, which are discussed in Chapter 14.
Step VII: Processing and displaying data
The
way you analyse the information you collected largely depends upon two things: the type of
information (descriptive, quantitative, qualitative or attitudinal); and the
way want to communicate your findings to your readers.
Chapter 15 describes different ways
of analyzing quantitative and qualitative data and Chapter 16 details various
methods of displaying analyzed data.
In addition to the qualitative
quantitative distinction, it is important for data analysis that you consider
whether the data is to be analyzed manually or by a computer.
If
your study is purely descriptive, you can write your dissertation/report on the
basis of your field notes, manually analyze the contents of your notes (content analysis),
or use a computer program such as NUD*IST N6, NVivio or Ethnography for this purpose.
If you want quantitative analysis,
it is also necessary to decide upon the type of analysis required( i.e
frequency distribution, cross tabulations or other statistical procedures, such
as regression analysis, factor analysis and analysis of variance) and how it should be presented. You
will also will also need to identify the variables to be subjected to these statistical procedures:
Step VIII: writing a research report
There
are two broad categories of reports: quantitative and qualitative. As mentioned
earlier, the distinction is more academic than real as in most studies you need
to combine quantitative and qualitative skills. Nevertheless, there are some solely
qualitative and some solely quantitative studies.
Writing the report is the last and,
for many the most difficult step of the research process this report informs
the world what you have done, what you have discovered and what conclusions you
have drawn from your findings. If you are clear about the whole process, you
will also be clear about the way you want to write to write report. You report
should be written in an academic style and be divided into different chapters
and / or sections based upon the main themes of your study. Chapter 17 suggests
some of the ways of writing a research report.
Summary
This chapter has provided an
overview of the research process, which has been broken down into eight steps,
the details of which are covered in the remainder of this book. At each step the research model provides a
smorgasbord of methods, models, techniques and procedures so you can select the
one most appropriate for your study. It is like a buffet party with eight tables, each with different
dishes made from similar ingredients. You go to all eight tables and select the
dish that you like most form each table. The main difference between the model
and this example is that in the model you select what is most appropriate for
your study and not what you like the most. For a beginner it is important to go
through all the steps, perhaps not in the same sequence. With experience you
can take a number of shortcuts.
The
eight steps cover the total spectrum of a research endeavor, from problem
formulation through to writing a research report. The steps are operational in
nature, following a logical sequence, and detailing the various methods and
procedures in a simple step-by step manner.
For You to Think About
Ø
Re familiarise yourself with the keywords listed
at the beginning of this chapter and if you are uncertain about the meaning or
application of any of them revisit these in the chapter before moving on.
Ø
Reflecting on the differences between
quantitative and qualitative research (as outlined in Table 2.1), determine which approach you
are more inclined to follow. To what extent dose this reflect your own
underpinning philosophy?
Ø
Use the information provided in Table 2.1 map
the main differences between quantitative and qualitative research at each step
in the eight-step model.
STEP
I Formulating a Research Problem
This
Operational step includes four chapters:
· Chapter 3: Reviewing the literature
· Chapter 4: Formulating a research problem
· Chapter 5: Identifying variables
· Chapter 6: Constructing hypotheses
CHAPTER 3
Reviewing the Literature
In this chapter
you will learn about:
·
The
functions of the literature review in research
·
How
to carry out a literature search
·
How
to review the selected literature
·
How
to develop theoretical and conceptual frameworks
·
How
to write a literature review
Keywords:
Catalogue, conceptual
framework, contextualize, internet, knowledge base, literature review, search
engines, summary of literature, thematic writing, theoretical framework.
The
place of the literature review in research
One of the essential preliminary tasks when you undertake a
research study is to go through the existing literature in order to acquaint
yourself with the available body of knowledge in your area of interest.
Reviewing the literature can be time consuming, daunting and frustrating but it
is also rewarding. The Literature review
is an integral part of the research process and makes a valuable
contribution to almost every operational step. It has value even before the first
step; that is when you are merely thinking about a research question that you
may want to find answers to through your research journey. In the initial
stages of research it helps you to
establish the theoretical roots of your
study, clarify your ideas and develop your research methodology. Later in the
process, the literature review serves to enhance and consolidate your own
knowledge base and helps you to integrate your findings with existing body of
knowledge. Since an important responsibility in research is to compare your
findings with those of other, it is here that the literature review plays an
extremely important role. During the write-up of your report it help it helps
you to integrate your findings with existing knowledge-that is, to either
support or contradict earlier research. The higher the academic level of your
research, the more important a thorough integration of your findings with existing
literature becomes.
In
summary, a literature review has the following functions:
·
It provides a
theoretical background to your study.
·
It helps you establish
the links between what you are proposing to examine and what has already been
studied.
·
It enables you to show
how your findings have contributed to the existing body of knowledge in your
profession. It helps you to integrate your research findings into the existing
body of knowledge.
In relation to your own study, the literature review can
help in four ways. It can:
1 bring
clarity and focus to your research problem;
2 improve
your research methodology;
3 broaden
your knowledge bade in your research area: and contextualize your findings.
Bringing clarity
and focus to your research problem
The literature review involves a paradox. On the one hand,
you cannot effectively under effectively undertake a literature search without
some idea of the problem you wish to investigate. On the other hand, the
literature review can play an extremely important role in shaping your research
problem because the process of reviewing the literature helps you to understand
the subject area better and thus helps you to conceptualize your research
problem clearly and precisely and makes it more relevant and pertinent to your
field of enquiry. When reviewing the literature you learn what aspects of your
subject area have been examined by others, what they have found out about these aspects, what gaps they have
identified and what suggestions they have made for further research. All these
will help you gain a greater insight into your own research questions and provide you with clarity and focus which are
central to a relevant and valid study.
In addition, it will help you to focus your study on areas where there are gaps
in the existing body of knowledge, thereby enhancing its relevance.
Improving your
research methodology
Going through the literature acquaints you with the
methodologies that have been used by others to find answers to research
questions similar to the one you are investigating. A literature review tells
you if others have used procedures and methods similar to the ones that you are
proposing, which procedures and methods have worked well for them and what
problems they have faced with them. By becoming aware of any problems and
pitfalls, you will be better positioned to select a methodology that is capable
of providing valid answers to your research question. This will increase your
confidence in the methodology you plan to use and will equip you to defend its
use.
Broadening your
knowledge base in your research area
The most important function of the literature review is to ensure
you read widely around the subject area in which you intend to conduct your
research study. It is important that you know what other researchers have found
in regard to the same or similar questions, what theories have been put forward
and what gaps exist in the relevant body of knowledge. When you undertake a
research project for a higher degree (e.g.an MA or a PhD) you are expected to
be an expert in your area of research. A thorough literature review helps you
to fulfill this expectation. Another important reason for doing a literature
review is that helps you to understand how the findings of your study fit into
the existing body of knowledge (Martin 1985: 30).
Enabling you to
Obtaining answers to your research questions is comparatively
easy: the difficult part is examining how your findings fit into the existing
body of knowledge. How do answers to your research questions compare with what others have found? What contribution
have you been able to make to the existing body of knowledge? How are your
findings different from those of others? Undertaking a literature review will
enable you to compare your findings with those of others and answer these
questions. It is important to place your findings in the context of what is
already known in your field of enquiry.
How to review the
literature
If you do not have a specific research problem, you should
review the literature in your broad area of interest with the aim of gradually
narrowing it down to what you want to find out
about. After that the literature review should be focused around your
research problem. There is a danger in reviewing the literature without having
a reasonably specific idea of what you want to study. It can condition your
thinking about your study and the methodology you might use, resulting in a
less innovative choice of research problem and methodology than otherwise would
have been case. Hence, you should try broadly to conceptualize your research
problem before undertaking your major literature review.
There are four steps involved in conducting a literature
review:
1.
Searching for the
existing literature in your area of
study.
2. Reviewing the selected literature.
3. Developing a
theoretical framework
4. Developing a
conceptual framework.
The skills
required for these tasks are different. Developing theoretical and conceptual
frameworks is more difficult than the other tasks.
Searching for the
existing literature
To search effectively for the literature in your field of
enquiry, it is imperative that you have at least some idea of the broad subject
area and of the problem you wish to investigate , in order to set parameters
for your search. Next, compile a bibliography
for this broad area. There are three sources that you can use to prepare
a bibliography:
(a)
books;
(b)
journals;
(c)
the Internet.
Books
Though books are a central part of any bibliography, they
have their disadvantages as well as advantages. The main advantage is that the
material published in books is usually important and of good quality, and the findings are
‘integrated with other research to form a coherent body of knowledge’ (Martin
1985:33). The main disadvantage is that the material is not completely up to
data as it can take a few years between the completion of a work and its
publication in the form of a book.
The best way
to search for a book is to look at your library catalogues. When librarians
catalogue a book they also assign to it subject headings that are usually based
on library of congress subject Headings. If you are not sure, ask your
librarian to help you find the best subject heading for your area. This can
save you a lot of time. Publications such as Book Review index can help you to
locate books of interest.
Use the
subject catalogue or keywords option to search for books in your area of
interest Narrow the subject area
searched by selecting the appropriate keywords. Look through these titles carefully and identify the books you
think are likely to be of interest to you. If you think the titles seem
appropriate to your topic, print them out (if this facility is available), as
this will save you time, or note them
down on a piece of paper. Be aware that sometimes a title dose not provide enough information to help you
decide if a book is going to be of use so you may have to examine its contents
too.
When you have
selected 10-15 books that you think are appropriate for your topic, examine the
bibliography of each one. It will save time if you photocopy their
bibliographies. Go through these bibliographies carefully to identify the books
common to several of them. If a book has been referenced by a number of
authors, you should include it in your reading list. Prepare a final list
of books that you consider essential
reading.
Having
prepared your reading list locate these books in your library or borrow them
from other sources. Examine their contents to double check that they really are
relevant to your topic. If you find that a book is not relevant to your research,
delete it from your reading list. If you find that something in a book’s contents
is relevant to your topic, make an annotated bibliography. An annotated bibliography
contains a brief abstract of the aspects covered in a book and your own notes
of its relevance. Be careful to keep track of your references. To do this you
can prepare your own card index or use a computer program such as Endnotes or
Pro Cite.
Journals
You need to go through the journals relating to your
research in a similar manner. Journals provide you with the most up-to date
information, even though there is often a gap of two to three years between the completion of a
research project and its publication in a journal. You should select as many
journals as you possibly can, though the number of journals available depends
upon the field of study of study certain fields have more journals than others.
As with books, you need to prepare a list of the journals you want to examine
for identifying the literature relevant to your study. This can be done in a
number of ways. You can:
·
Locate the hard copies
of the journals that are appropriate to your study;
·
Look at citation or
abstract indices to identify and/or read the abstracts of such articles;
·
Search electronic
databases.
If you have been able to identify any useful journals and
articles, prepare a list of those you want to examine, by journal. Select one
of these journals and, starting with the latest issue, examine its contents
page to see if there is an article of relevance to your research topic. If you
feel that a particular article is of interest to you , read its abstract. If
you think you are likely to use it, depending upon your financial resources,
either photocopy it, or prepare a summary and record its reference for later
use.
There are
several sources designed to make your search for journals easier and these can
save you enormous time. They are:
·
Indices of journals
(e.g. Humanities Index);
·
Abstracts of articles
(e.g. ERIC);
· Citation indices (e.g.
Sciences Citation index).
Each of these indexing, abstracting citation services is
available in print , or accessible through the Internet.
In most libraries, information on books, journals and
abstracts is stored on computers. In each case the information is classified by
subject, author and title. You may also have the keywords option
(author/keyword; title/keyword; subject/keyword; expert/keyword; or just
keywords). What system you use depends upon what is available in your library
and what you are familiar with.
There are
specially prepared electronic databases in a number of disciplines. These can
also be helpful in preparing a bibliography. For example, most libraries carry
the electronic data bases shown in Table 3.1.
Select the
database most appropriate to your area of study to see if there are any useful references. Of course, any computer
database search is restricted to those journals and articles that.
TABLE 3.1 Some commonly used electronic databases in public
health, sociology, education and business studies
|
Electronic
database
|
Description
|
Printed equivalent
|
|
ABI/INFORM
ERIC
HEALTHROM
MEDLINE
CINHAL
|
Abstracted Business information contains
reference to business information worldwide. It covers subjects such as
accounting, banking, data processing, economics, finance, health care, insurance,
law, management, marketing, personnel, product development, public
administration, real estate, taxation and telecommunications.
ERIC is database of educational material
collected by the
HEALTHROM provides references and some
full-text publications on the environment, health, HIV/AIDS and communicable
diseases, Aboriginal health, clinical medicine, nutrition, alcohol and drug addiction
MEDLINE contains references to material
in the biomedical sciences, including medicine, pharmacology, nursing
dentistry, allied health professions, public health, behavioral sciences,
physiotherapy, occupational therapy, medical technology, hospital
administration, and basic sciences such as anatomy and physiology
CINAHL(Cumulative Indices to Nursing and
Allied Health Literature) provides access to virtually all English-language
nursing journals and primary journals from 13 allied health disciplines
including health education, medical records,
occupational therapy, physical therapy and radiologic technology
|
None
CIJE: Current Index to Journals in
Education
None
Index Medicos
Cumulative indices to nursing and allied
health literature
|
Are already on the database. You should also talk to your
research supervisor and other available experts to find out about any
additional relevant literature to include in your reading list.
The Internet
In almost every academic discipline and professional field,
the Internet has become an important tool for finding published literature. Through
an Internet search you can identify published material in books , journals and
other sources with immense ease and speed.
An
Internet search is carried out through search engines, of which there are many,
though the most commonly used are Google and Yahoo. Searching through the
Internet is very similar to the search for books and articles in a library
using an electronic catalogue, as it is based on the use of keywords. An
Internet search basically identifies all material in the database of a search engine that
contains the keywords you specify, either individually or in combination. It is
important that you choose words or combinations of words that other people are
likely to use.
According
to Gilbert(2008:73), ‘Most search facilities use Boolean logic, which allows
three types of basic search ‘AND’ OR’ and ‘NOT’ ‘ With practice you will become
more efficient and effective in using keywords in combination with AND, OR and
NOT , and so learn to narrow your search to help you identify the most relevant
references.
Reviewing the
selected literature
Now that you have identified several books and articles as
useful, the next step is to start
reading them critically to pull together themes and issues that are of
relevance to your study.
Unless you have a theoretical framework of themes in mind
to start with, use separate sheets of paper for each theme or issue you
identify as you go through selected books and articles. The following example
details the process.
The author recently examined , as part of an evaluation
study, the extent of practice of the concept of community responsiveness’ in
the delivery of health services in western Australia by health service
providers. Before evaluating the extent of its use, pertinent literature
relating to community responsiveness in health was identified and reviewed.
Through this review, many themes emerged, which became the of developing the theoretical
framework for the study. Out of all of this, the following themes were selected
to construct the theoretical framework for the evaluation study:
- Community responsiveness: what does
it mean?
- Philosophies underpinning community
responsiveness.
- Historical development of the
concept in
- The extent of use in health
planning?
- Strategies developed to achieve community
responsiveness.
- Indicators of success or failure.
- Seeking community participation.
- Difficulties in implementing
community responsiveness.
- Attitude of stakeholders towards the
concept of community responsiveness.
Once you develop a rough framework, slot the findings from
the material so far reviewed into these themes, using a separate sheet of paper
for each them of the framework so far developed. As you read further, go on
slotting the information where it logically belongs under the themes so far developed.
Keep in mind that you may need to add more themes as you go along. While going
through the literature you should carefully and critically examine it with respect
to the following aspects:
- Note whether the knowledge relevant
to your theoretical framework has been confirmed beyond doubt.
- Note the theories put forward, the
criticisms of these and their basis , the methodologies adopted (study design, sample size and
its characteristics, measurement procedures, etc.) and the criticisms of
them.
- Examine to what extent the findings
can be generalized to other situations.
- Notice where there are significant
differences of opinion among researchers and give your opinion about the
validity of these differences.
- Ascertain the areas in which little
or nothing is know- the gaps that exist in the body of knowledge.
Developing a
theoretical framework
Examining the literature can be a never-ending task, but as
you have limited time it is important to set parameters by reviewing the
literature in relation to some main themes pertinent to your research
topic. As you start reading the literature, you will soon discover that the
problem you wish to investigate has its roots in a number of theories that have
been developed from different perspectives. The information obtained from
different books and journals now needs to be sorted under the main themes and
theories, highlighting agreements and disagreements among the authors and
identifying the unanswered questions or gaps. You will also realize that the
literature deals with a number of aspects that have a direct or indirect bearing on your research topic. Use these
aspects as a basis for developing your theoretical framework. Your review of
the literature should sort out the information, as mentioned earlier, within
this framework. Unless you review the literature in relation to this framework,
you will not be able to develop a focus in your literature search: that is,
your theoretical framework provides you
with a guide as you read. This brings us to the paradox mentioned previously:
until you go through the literature you cannot develop a theoretical framework,
and until you have developed a
theoretical framework you cannot effectively review the literature. The
solution is to read some of the literature and then attempt to develop a frame
work, even a loose one, within which you
can organize the rest of the literature you read. As you read more about the area, you are likely
to change the framework. However, without it , you will get bogged down in a
great deal of unnecessary reading and note-taking that may not be relevant to
your study.
Literature pertinent to your study
may deal with two types of information:
1
Universal;
2
More specific (i.e. local trends or a specific
programme).
In
writing about such information you should start with the general information,
gradually
Narrowing
it sown to the specific.
Look at the example in Figure 3.1a and
3.1b
|
If you want to study the relationship between
mortality and fertility, you should review the literature about:
Out of this literature review you need to develop
the theoretical framework for your study. Primarily this should revolve
around theories that have been put forward about the relationship between
mortality and fertility. You will discover that a number of theories have
been proposed to explain this relationship. For example, it has been
explained from economic, religious, medical and psychological perspectives.
Within each perspective several theories have been put forward: “insurance
theory’ fear of non survival’ ‘replacement theory ‘price theory’ utility
theory’ extra’ or hoarding theory and risk theory’
Your literature review should be written under the
following headings, with most of the review involving the examination of the
relationships between fertility and mortality:
|
FIGURE 3.1a Developing a
theoretical framework- the relationship between mortality and fertility.
|
Note: Preliminary discussions with some
stakeholders revealed that not much was known to them about community responsiveness and therefore it was
proposed that study be carried out in two phases: preparatory phase and
actual evaluation phase. The main aim of the preparatory phase was to
ascertain the understanding of the concept, identify the strategies that are
being or can be used, and developing a set of indicators for measuring its
success or failure. This framework become the basis of the first phase of the
study.
The review of literature was written around the following theoretical framework
which, of course emerged from the literature review itself.
Community
responsiveness: What do the stakeholders (service
providers, service managers and the consumers) understand by community
responsiveness, why it is needed , and what purpose does it serve? Historical and philosophical perspectives:
Start of the concept, and historical overview of its emergence,
philosophical perspective that underpins the concept. Implementation strategies: What strategies have been used to
achieve community responsiveness in the service delivery area? Attitude of the stakeholders: What
are attitudes of service providers, service managers and consumers of the
services towards community responsiveness? Evaluation of community responsiveness: What indicators can be
used to determine the impact of these strategies, what should determine the
success or failure of the implementation of the strategies and who and how
should it be determined?
|
FIGURE 3.1b Theoretical framework for the study community
responsiveness in health’
Developing a
conceptual framework
The conceptual framework is the basis of your research
problem. It stems from the theoretical framework and usually focuses on the
section (s) which become the basis of your study . Whereas the theoretical
framework consists of the theories or
issues in which your study is embedded, the conceptual framework
describes the aspects you selected from the theoretical framework to become the
basis of your enquiry. For instance, in the example cited in Figure 3.1a, the
theoretical framework includes all the theories that have been put forward to
explain the relationship between fertility and mortality. However, out of
these, you may be planning to test only one, say the fear of non-survival.
Similarly, in Figure 3. 1b, the conceptual framework is focused on indicators
to measure the success or failure of the strategies to enhance community responsiveness.
Hence the conceptual framework grows out of the theoretical framework and
relates to the specific research problem.
Writing about the
literature reviewed
Now, all that remains to be done is to write about the
literature you have reviewed. As mentioned in the beginning of this chapter,
two of the broad functions of a literature review are (1) to provide a
theoretical background to your study and (2) enable you to contextualize your
findings in relation to the existing body of knowledge in addition to refining
your methodology. The content of your literature review should reflect these
two purposes. In order to fulfill the first purpose, you should identify and
describe various theories relevant to your field; and specify gaps in existing
knowledge in the area, recent advances in the area of study, current trends and
so on. In order to comply with the second function you should integrate the
results from study with specific and relevant findings from the existing
literature by comparing the two for
confirmation or contradiction. Note that at this stage you can only accomplish
the first function of the literature review , to provide a theoretical
background to your study. For the second function, the contextualization of the
findings, you have to wait till you are at the research report writing stage.
While
reading the literature for theoretical background of your study, you will
realize that certain themes have emerged. List the main ones, converting them
into subheadings. Some people write up the entire literature review in one
section, entitled ‘ Review of the literature; Summary of literature or The literature review without
subheadings , but the author strongly suggests that you write your literature
review under subheadings based upon the main themes that you have discovered
and which form the basis of your theoretical framework. These subheadings
should be precise, descriptive of the theme in question and follow a logical
progression. Now, under each subheading record the main findings with respect
to the theme in question (thematic writing), highlighting the reasons for and
against an argument if they exist, and identifying gaps and issues. Figure 3.2
shows the subheadings used to describe the themes in a literature review
conducted by the author for a study entitled ‘Intercountry adoption in Western Australia ’.
|
Intercountry adoption in
|
|
(A profile of adoptive families)
The literature was reviewed under the following themes:
|
FIGURE 3.2 Sample of outline of a literature review
The second
broad function of the literature review-contextualizing the findings of your
study –requires you to compare very systematically your findings with those
made by others.
Quote from these studies to show how your findings
contradict, confirm or add to them. It places your findings in the context of
what others have found out providing complete refer about your findings, that
is after analysis of your data.
Summary
Reviewing the literature is a continuous process. It begins before a research problem is finalized
and continues until the report is finished. There is a paradox in the
literature review: you cannot undertake an effective literature review unless
you have formulated a research problem, yet your literature search plays an
extremely important role in helping you to formulate your research problem. The
literature review brings clarity and focus to your research problem, improves
your research methodology and broadens your knowledge base.
Reviewing
the literature involves a number of steps: searching for existing literature in
your area of study; reviewing the selected literature; using it to develop a
theoretical frame-work from which your study emerges and also using it to
develop a conceptual framework which will become the basis of your
investigation. The main sources for identifying literature are books, journals
and the Internet. There are several sources which can provide information about
locating relevant journals.
The
literature review serves two important function: (1) it provides theoretical
background to your study, and (2) it helps you to contextualize your findings
by comparing them with what other have found out in relation to the area of
enquiry. At this stage of the research process, only the first function can be
fulfilled. You can only take steps to achieve the second function when you have
analyzed your data and are in the process of writing about your findings.
Your
writing about the literature reviewed should be thematic in nature, that is
based on main themes; the sequence of these themes in the write-up should
follow a logical progression; various
arguments should be substantiated with specific quotations and citations from the literature and should adhere to an
acceptable academic referencing style.
|
For you to
think About
Ø
Refamiliarise
yourself with the keywords listed at the beginning of this chapter and if you
are uncertain about the meaning or application of any of them revisit these
in the chapter before moving on.
Ø
Undertake a keyword
search for a theme or issue that interests you using (a) internet search
engine, such a Google Scholar, and (b) a library search facility. Compare the
results.
Ø
Choose two or three
research reports from your search and scan through the summaries noting the theories
put forward, the methodologies adopted and any recommendations for further study. Do these reports point to a
consensus or differences or opinion in the field?
Ø
Develop a
theoretical framework for the theme or issue you selected.
|
CHAPTER
4
Formulating
a Research Problem
|
In this chapter
you will learn about:
·
The
importance of formulating a research problem
·
Sources
of research problems
·
Considerations
in selecting a research problem
·
Specific
issues to consider when formulating a research problem in qualitative
research
·
Steps
in formulating a research problem
·
How
to formulate research objectives
·
The
importance of establishing operational definitions.
|
|
Keywords: Concepts, dissect, operational definition, qualitative
research, quantitative research objectives, research problem, study area,
study population, subject area, validity, variable, working definition.
|
The central aim of this chapter is to detail the process of
formulating a research problem, even though the specific process that you are
likely to adopt depends upon:
- Your expertise in research
methodology ;
- Your knowledge of the subject area;
- Your understanding of the issues to examined;
- The extent to which the focus of
your study is predetermined.
If you are not very familiar with the research process
and/or do not have a very specific idea about what is to be researched, you
need to follow every step detailed in this chapter.
However, more experienced researchers can take a number of
shortcuts. The process outlined here
assumes that you have neither the required knowledge of the process of
formulating a
Research problem nor a specific idea about what is to be researched. If you have a specific
idea for the basis of your enquiry, you do not need to go through this chapter.
However, you should make sure that your idea is researchable as not all
problems lend themselves to research methodologies.
The research
problem
Broadly speaking,
any question that you want answered and any assumption that you want to challenge or investigate can
become a research problem or research topic for your study. However, it is
important to remember that not all questions can be transformed into research
problems and some may prove to be extremely difficult to study. According to Powers,
Meenaghan and Twoomey (1985:38), ‘Potential research questions may occur to us
on a regular basis, but the process of formulating them in a meaningful way is
not at all easy task’. As a newcomer it might seem easy to formulate a problem
but it requires considerable knowledge
of both the Subject area and
research methodology. Once you examine a question more closely you will soon
realize the complexity of formulating an idea into a problem which is
researchable. ‘First identifying and then specifying a research problem might
seem like research tasks that ought to be easy and quickly accomplished.
However, such is often not the case ‘ (
Yegidis & Weinback 1991: 35).
It is
essential for problem you formulate to be able to withstand scrutiny in terms
of the procedures required to be undertaken. Hence you should spend
considerable time in thinking it through.
The importance of
formulating a research problem
The formulation of a research problem is the and most
important step of the research process. It is like the identification of a destination before undertaking a
journey. In the absence of a destination, it is impossible to identify the
shortest- or indeed any-route. Similarly, in the absence of a clear research
problem, a clear and economical plan is impossible. To use another analogy, a
research problem is like the foundation of a building. The type and design of the building are dependent upon the foundation.
If the foundation is well designed and
strong you can expect the building to be also. The research problem
serves as the foundation of a research study : if it is well formulated, you
can expect a good study to follow.
According to Kerlinger:
If one wants to solve a problem, one
must generally know what the problem is. It
can be said that a large part of the problem lies in knowing what one is
trying to do (1986:17)
You must have a
clear idea with regard to what it is that you want to find out about and not what you think you must find.
A research
problem may take a number of forms, from the very simple to the very complex.
The way you formulate a problem determines almost every step that follows: the
type of study design that can be used; the type of sampling strategy that can
be employed; the research instrument that can be used or developed; and the
type of analysis that can be undertaken. Suppose your broad area of interest is
depression. Further suppose you want to conduct a research study regarding
services available to patients with depression living in a community. If your
focus is to find out the types of service available to patients with depression
the study will dominantly be descriptive and qualitative in nature. These type
of studies fall in the category of qualitative research and are carried out
using qualitative research methodologies. On the other hand, if you want to
find out the extent of use of these services, that is the number of people
using them, it will dominantly use
quantitative methodologies even though it is descriptive in nature describing
the number of people using a service. If your focus is to determine the extent
of use in relation to the personal attributes of the patients, the study will
be classified as co relational (and quantitative). The methodology used will be
different than the one used in the case of a descriptive study. Similarly, if
your aim is to find out the effectiveness of these service, the study will
again be classified as correlational and
the study design used, methods of collecting data and its analysis will be a
part of the quantitative methodology. Hence, it is important for you to
understand that the way you formulate a research problem determines all the
subsequent steps that you have to follow during your research journey.
The
formulation of a problem is like the input to a study and the output – the
quality of the contents of the research report and the validity of the
associations or causation established – is entirely dependent upon it. Hence
the famous saying about computer, garbage out is equally applicable to a
research problem.
Initially,
you may become more confused but this is normal and a sign of progression.
Remember: confusion is often but a first step towards
clarity. Take time over formulating your problem, for the clearer you are about
your research problem/question, the easier it will be for you later on.
Remember, this is the most crucial step.
Sources of
research problems
This section is of particular relevance if you have not yet
selected a research topic and do not know where to start. If you have already
selected your topic or question, go to the next section.
Most
research in the humanities revolves around four Ps:
·
People;
·
Problems;
·
Programmes;
·
Phenomena.
In fact, a closer look at any academic or occupational
field will show that most research revolves around these four Ps. The emphasis
on a particular ‘P’ may vary from study to study but generally, in practice, most research
studies are based upon at least a combination of two Ps. You may select a group
of individuals (a group of individuals – or a community as such – “people’), to
examine the existence of certain issues or problems relating to their lives, to
ascertain their attitude towards an issue (‘problem’), to establish the
existence of a regularity (‘phenomenon’) or to evaluate the effectiveness of
intervention (‘programme’). Your focus may be the study an issue, an
association or a phenomenon per se; for example, the relationship between
unemployment and street crime, smoking and cancer, or fertility and mortality,
which is done on the basis of information collected from individuals, groups,
communities or organizations. The emphasis in these studies is on exploring,
discovering or establishing associations or causation. Similarly, you can study
different aspects of a programme: its effectiveness, its structure, the need
for it consumers’ satisfaction with it, and so on. In order to ascertain these
you collect information from people.
Every
research study has two aspects: the people provide you with the study
population’ whereas the other three Ps furnish the subject areas your study
population individuals, groups and communities- is the people from whom the
information is collected. Your subject area is a problem, programme or
phenomenon about which the information is collected. This is outlined further in Table 4.1, which shows
the aspects of a research problem.
TABLE 4.1 Aspects of a research problem
|
Aspects of a
study
|
About
|
Study of
|
|
|
Study population
Subject area
|
People
Problem
Programme
Phenomenon
|
Individuals, organizations, groups, communities
Issues, situations,
associations, needs, population composition, profiles, etc. Contents, structure, outcomes,
attributes, satisfaction, consumers, providers, etc. cause and effect,
relationships, the study of a
phenomenon itself, etc.
|
The provide you with the required
information or you collect information from or about them
Information that you need to collect to
find answers to your service research questions
|
You can study a problem, a programme or a phenomenon in any
academic field or from any professional perspective. For example , you can
measure the effectiveness of a programme in the field of health, education,
social work, industrial management, public health, nursing, health promotion or
welfare, or you can look at a problem from a health, business or welfare
perspective. Similarly you can gauge consumers’ opinions about any aspect of a
programme in the above fields.
Examine
your own academic discipline or professional field in the context of the four
Ps in order to identify anything that looks interesting. For example, if you
are a student in the health field there are an enormous number of issues,
situations and associations within each
subfield of health that you could examine. Issues relating go to the spread of
a disease, drug rehabilitation, an immunization programme, the effectiveness of
a treatment, the extent of consumers satisfaction or issues concerning a particular
health programme can all provide you with a range of research problems. Similarly,
in education there are several issues: students satisfaction with a teacher, attributes
of a good teacher, the impact of the home environment on the educational achievement
of students, and the supervisory needs
of postgraduate students in higher education. Any other academic or
occupational field can similarly be dissected into subfields and examined for a
potential research problem. Most fields lend the above categorization even
though specific problems and programmes vary markedly from field to field.
The
concept of 4Ps is applicable to both quantitative and qualitative research
though the main difference at this stage is the extent of their specificity, dissection,
precision and focus. In qualitative research these attributes are deliberately
kept very loose so that you can explore more as you go along, in case you find
something of relevance. You do not bind yourself with constraints that would
put limits on your ability to explore. There is a separate section on ‘Formulating
a research problem in qualitative research later in the chapter, which provides
further guidance on the process.
Considerations in
selecting a research problem
When selecting a research problem/topic there are a number
of considerations to keep in mind which will help to ensure that your study
will be manageable and that you remain motivated. These consideration are:
·
Interest Interest
should be the most important consideration in selecting a research problem. A
research Endeavour our is usually time consuming, and involves hard work and
possibly unforeseen. If you select a topic which does not greatly interest you,
it could become extremely difficult to sustain the required motivation and put
in enough time and energy to complete it.
·
Magnitude – You should
have sufficient knowledge about the research process to be able to visualize
the work involved in completing the proposed study. Narrow the topic down to
something manageable, specific and clear, It is extremely important to select a
topic that you can manage within the time and with the resources at your
disposal. Even if you are undertaking a descriptive study, you need to consider
its magnitude carefully.
·
Measurement of concepts
– If you are using a concept in your study (In quantitative studies). Make sure
you are clear about its indicators and their measurement. For example, if you
plan to measure the effectiveness of a health promotion programme, you must be
clear as to what determines effectiveness and how it will be measured. Do not use
concepts in your research problem that you are not sure how to measure. This
not mean you connot develop a measurement procedure as the study progresses.
While most of the developmental work will be done during your study, it is
imperative that you are reasonably clear about the measurement of these
concepts at this stage.
·
Level of expertise
–Make sure you have an adequate level of expertise for the task you are proposing
Allow for the fact that you will learn during the study and may receive help
from your research supervisor and others, but remember that you need to do most
of the work yourself.
·
Relevance – Select a
topic that is of relevance to you as a professional. Ensure that your study
adds to the existing body of knowledge, bridges current gaps or is useful in policy
formulation. This will help you to sustain interest in the study.
·
Availability of data-
If your topic entails collection of information from secondary sources (office records, client records, census or
other already-published reports, etc.) make sure that this data is available
and in the format you want before finalizing your topic.
·
Ethical issues –Another
important consideration in formulating a research problem is the ethical issues
involved. In the course of conducting a research study, the study population
may be adversely affected by some of the questions (directly or indirectly); deprived
of an intervention; expected to share sensitive and private information; or
expected to be simply experimental ‘guinea pigs’. How ethical issues can affect
the study population and how ethical problems can be overcome should be
thoroughly examined at the problem-formulation stage.
Steps
in formulating a research problem
The formulation of a research problem is the
most crucial part of the research journey as the quality and relevance of your
research project entirely depends upon it. As mentioned earlier, every step
that constitutes the how part of the research journey (Figure 2.1) depends upon
the way you formulated your research problem. Despite the importance of this
step, there is very little available by way of specific guidance in other
books. This task is largely left either to the teachers of research methodology
or to students to learn for themselves. One of the strengths of this book is
that it offers a beginner a very specific set of step guidelines in one place
despite the fear of being labeled as prescriptive .
The
process of formulating a research problem consists of a number of steps.
Working through these steps presupposes a reasonable level of knowledge in the
broad subject area within which the study is to be undertaken and the research
methodology itself. A brief review of the relevant literature helps enormously
in broadening this knowledge base. Without such knowledge it is difficult to
dissect a subject area clearly and adequately.
If
you do not know what specific research topic, idea, questions or issue you want
to research (Which is not uncommon among students), first go through the
following steps:
Step 1 Identify a broad field or subject area of
interest to you. Ask yourself, ‘What is
That really interests me as a professional? In the author’s
opinion, it is a good idea to think about the field in which you would like to
work after graduation. This will help you find an interesting topic, and one
which may be of use to you in the future. For example, if you are a social work in the youth welfare, refugees
or domestic violence after graduation, you might take to research in one of
these areas. Or if you are studying marketing you might be interested in
researching consumer behavior. Or as a student of public health, intending to
work with patients who have HIV/AIDS,
Subject area Sub
areas
Profile of families in
which DV occurs
Profile of the victims of DV
Profile
of the perpetrators
Reasons
for DV
Domestic violence Extent
and types of DV
(DV) Impact
of DV on the family Impact
of DV on children
Services
available to the victims of DV
Effectiveness of the services
provided to the victims of DV
Extent of DV in a
community
Etc.
FIGURE 4.1 Dissecting the
subject area of domestic violence into sub areas
You might like to conduct research on a subject area relating
to HIV/AIDS. As far as the research journey goes, these are the broad research
areas. It is imperative that you identify one of interest to you before undertaking
your research journey.
Step 2 Dissect the broad area into subareas. At the onset, you will
realize that all the broad areas
mentioned above- youth welfare, refugees, domestic violence, consumer behavior
and HIV/AIDS- have many aspects. For example, there are many aspects and issues
in the area of domestic violence, illustrated in Figure 4.1.
Similarly,
you can select any subject area from other fields such as community health or
consumer research and go through this dissection process. In preparing this
list of subareas you should also consult others who have some knowledge of the
area and the literature in your subject area. One you have developed an
exhaustive list of the sub areas from various sources, you proceed to the next
stage where you select what will become the basis of your enquiry.
Step 3 Select what is of most interest to you. It is neither advisable nor
feasible to study all sub areas. Out of this list select or sub areas about which you are passionate.
This is because your interest should be the most important determinant for
selection, even though there are other considerations which have been discussed
in the previous section, Considerations in selecting a research problem; One
way decide what interests you most is to start with the process of elimination.
Go through your list and delete all those sub areas in which you are not very interested. You
will find that towards the end of this process, it will become very difficult
for you to delete anything further. You need to continue until you are left
with something that is manageable considering the time available to you, your
level of expertise and other resources needed to undertake the study, Once you
are confident that you have selected an issue you are passionate about and can
manage, you are ready to go to the next step.
Step 4 Raise research questions. At this step ask yourself, what is it
that I want to find out about in this
sub area? Make a list of whatever questions come to your mind relating to your chosen sub area and if you think there are too many to be
manageable , go through the process of elimination, as you did in Step 3.
Step 5 Formulate objectives. Both your main objectives and your sub
objectives now need to be formulated, which grow out of your research questions.
The main difference between objectives and research questions is the way in
which they are written. Research questions are obviously that-questions.
Objectives transform these questions into behavioral aims by using action
–oriented words such as to find out, to determine, to ascertain and to examine.
Some researchers prefer to reverse the process; that is they start from
objectives and formulate research questions from them. Some researchers are
satisfied only with research questions, and do not formulate objectives at all.
If you prefer to have only research questions or only objectives, this is fine,
but keep in mind the requirements of your institution for research proposals.
For guidance on formulating objectives, see the later section.
Step 6 Assess your objectives. Now examine your objectives to ascertain
the feasibility of achieving them through your research endeavor. Consider them
in the light of the time, resources
(financial and human ) and technical expertise at your disposal.
Step 7 Double – check. Go back and give final consideration to whether or
not you are sufficiently interested in the study, and have adequate resources
to undertake it. Ask yourself, Am I really enthusiastic about this study? And
Do I really have enough resources to undertake it? Answer these questions
thoughtfully and realistically. If your answer to one of them is ‘on’, reassess
your objectives.
Figures 4.2 to
4.44 operationalise Step 1-7 with examples
from different academic disciplines (health, social work/social sciences
and community development).
The formulation of research objectives
Objectives
are the goals you set to attain in your study. Since these objectives inform a
reader of what you want to achieve through the study, it is extremely important
to word them clearly and specifically.
Objectives
should be listed under two headings:
·
Main objectives;
·
Sub objectives.
The main
objective is an overall statement of the thrust of your study. It is also a
statement of the main associations and relationships that you seek to discover
or establish. The sub objectives are the specific aspects of the topic you want
to investigate within the main framework of your study.
Example 1 : Suppose you want to conduct a study in the area of
alcoholism. In formulating your research problem take the following steps.
|
Step 1
|
|
Identify
|
|
Alcoholism
|
|
Step 2
|
|
Dissect
|
|
1 Profile of alcoholics
2 the causes of alcoholism
3 the process of becoming an alcoholic
4 the effects of alcoholism on the
family
5 community attitudes towards alcoholism
6 the effectiveness of a treatment
model, etc
|
|
Step 3
|
|
Select
|
|
Effects of alcoholism
On the family
|
|
Step 4
|
|
Identify
|
|
1 What impact has alcoholism on marital relations?
2 How does it affect the
various aspects of children’s
3 What are the effects on the family’s finances?
|
|
Step 7
|
|
Double
-check
|
|
1 that you are really interested in the
study
2 that you agree with the objectives
3
that
you have adequate resources
4
that
you have the technical expertise to undertake the study
|
|
Step 6
|
|
Make sure
|
|
Assess these objectives in the light of:
1 the work involved
2 the time available t you
3 the financial resources at your disposal
4 your (and your
5 research’s technical expertise in the
area
|
|
Step 5
|
|
Formulate objectives
|
|
Main objective:
To find out the
effects of alcoholism on the family
Specific objectives:
1
to
ascertain the impact of alcoholism on marital relations
2
to
determine the ways in which alcoholism affects the different aspects of
children’s lives
3
to
find out the effects of alcoholism on the financial situation of the family
etc.
|
Example 2: Suppose you want to study the relationship between
fertility and mortality. Follow these steps.
|
Step 1
|
Step 2
|
Step 3
|
Step 4
|
|
Identify
|
Dissect
|
Select
|
Raise questions
|
|
Fertility
|
1
trends in fertility and mortality
2
determinants of fertility behavior
3
relationship between fertility and mortality
4
impact of health services on mortality
5
impact of contraceptives on fertility behavior, etc
|
Relationship between
fertility
|
1
What happens to fertility when mortality declines?
2
What is the time lag between the start of decline in mortality and
start of decline in fertility?
3
What are the factors that contribute to the decline in fertility? Etc
|
|
Step 7
|
Step 6
|
Step 5
|
|
Double -check
|
Make sure
|
Formulate objectives
|
|
1 that you are really
interested in the study
2 that you agree
with the objectives
3 that you have
adequate resources
4 that you have
the technical expertise to undertake the study
|
Assess these objectives in the light of:
1
the work involved
2
the time available to you
3
the financial resources at your disposal
4 your (and your research supervisor’s)
technical expertise in the area
|
Main objective: to explore the
relationship between fertility and mortality specific objectives:
1
to find out the extent of the decline in fertility in relation to the decline
in mortality
2
to ascertain the time lag between the decline in mortality and the
decline in fertility
3
to identify the factors that affect the changes in fertility
4
to expire the relationship between socioeconomic-demographic
characteristics of the population and the extent of changes in fertility and
mortality
|
FIGURE 4.3
Formulating a research problem- the relationship between fertility and
mortality
Example 3: Suppose you want to conduct a study in the area of health,
Follow these steps.
|
Step 1
|
Step 2
|
Step 3
|
Step 4
|
|
Identify
|
Dissect
|
Select
|
Raise questions
|
|
Health
|
1
health services provided to the community
2
effectiveness of the services
3
cost of the services
4
health insurance schemes available to people
5
training of health professionals
6
adherence to ethics in health practices
7
attitude of the consumers towards health services
8
community responsiveness in the delivery of health services, etc.
|
Community responsiveness
in the delivery of health services
|
1
How do the health administrators, planners, service providers and
consumers define community responsiveness?
2
How can community responsiveness be achieved?
3
What indicators can be used to evaluate the effectiveness of community
responsiveness strategies?
|
|
Step 7
|
Step 6
|
Step 5
|
|
Double – check
|
Make sure
|
Formulate objectives
|
|
1 that you are
really interested in the study
2 that you agree
with the objectives
3 that you have
adequate resources
|
Assess these objectives in the light of:
1
the work involved
2
the time available to you
3
the financial resources at your disposal
4 your (and your research supervisor’s)
technical expertise in the area
|
Main objective: to evaluate the
effectiveness of community of community responsiveness strategies in the
delivery of health services
Specific objectives:
1
to find out the understanding of the concept ’community responsiveness’
among health administrators, planners, service providers and service
consumers
2
to identify the strategies to implement the concept of community responsiveness
in health services
3
to develop a set of indicators to evaluate the effectiveness of the
strategies used in implementation of community responsiveness
|
FIGURE 4.4 Narrowing a research problem – health
RESEARCH
METHODOLOGY
Sub
objectives should be numerically listed. They should be worded clearly and
unambiguously. Make sure that each sub objective contains only one aspect of
the study. Use action-oriented words or verbs when writing your objectives. The
objectives should start with words such as ‘to determine’ to find out to
ascertain to measure and to explore.
The way
the main objectives and sub objectives are worded determines how your research
is classified (e.g. descriptive, co
relational or experimental). In other words, the wording of your objectives
determines the type of research design you need to adopt to achieve them.
Hence, be careful about the way you word you objectives.
Irrespective
of the type of research, the objectives should be expressed in such a way
that the wording clearly, completely and
specifically communicates to your readers your intention. There is no place for
ambiguity, non – specificity or incompleteness, either in the wording of your
objectives or in the ideas they communicate. Figure 4.5 displays the
characteristics of the wording of objectives in relation to the type of
research study.
|
Clear
|
Complete
|
Specific
|
Identify the main variables to be correlated
|
Identify the direction of the relationship
|
Descriptive
studies
Co
relational studies (experimental and non-experimental)
FIGURE 4.5 Characteristics
of objectives
If your
study is primarily descriptive, your main objective should clearly describe the
major focus of your study, even mentioning the organization and its location unless these are to be kept
confidential (e.g. to describe the types of treatment programme provided by
[name of the organization] to alcoholics in [name of the place] or to find out
the opinion of the community about the health services provided by [name of the
health centre/department] in [name of
the place]. Identification of the organization and its location is important as
the services may be peculiar to the place and the organization and may not
represent the services provided by others to similar populations.
If your
study is co relational in nature, in addition to the first three
characteristics shown in figure 4.5, the wording of the main objective should
also include the main variables being correlated 9e.g.to ascertain the impact
of migration on family roles or to compare the effectiveness of different
teaching methods on the comprehension of students).
If the overall
thrust of your study is to test a hypothesis, the wording of the main
objectives should also indicate the direction of the relationship being tested
(e.g to ascertain if an increase in you unemployment will increase the
incidence of street crime, or to demonstrate that the provision of maternal and
child health services to Aboriginal people in rural Australia will reduce
infant mortality).
The study
population
So far we have focused on only one aspect of a study, the
research problem. Nut every study in social sciences has a second aspect, the Study population, from whom the
required information to find answers to your research questions is obtained. As
you narrow the research problem, similarly you need to decide very specifically
and clearly who constitutes your study
population, in order to select the appropriate respondents.
Suppose you have designed a study to ascertain the needs of
young, people living in a community. In terms of the study population, one of
the first questions you need to answer is: Who do I consider to be a young
person? You need to decide, in measurable terms, which age group your
respondents should come from. Is it those between 15 and 18 and20 or 15 and 25
years of age? Or you may be interested in some other age group. You need to
decide this before undertaking your research journey. Having decided the age
group that constitutes your ‘young
person’ the next question you need to consider is whether you want to select young
people of either gender or confine the study to one only. In addition, there is
another dimension to consider: that is , what constitutes the community ? Which
geographical area (s) or ethnic background should I select my respondents from?
Let us
take another example. Suppose you want to find out the settlement process of immigrants.
As a part of identifying your study population, you need to decide who would you
consider an immigrant. Is it a person who immigrated 5,10, 15 or 20 years ago?
You also need to consider the countries from where the immigrants come. Will
you select your respondents irrespective of the country of origin or select
only those who have come from a specific country (ies)? In a way you need to
narrow your definition of the study population as you have done with your
research problem. These issues are
discussed in greater depth under ‘Establishing operational definitions’
following this section.
In
quantitative research, you need to narrow both the research problem and the
study population and make them as specific as possible so that you and your
readers are clear about them. In qualitative research, reflecting the ‘exploratory’ philosophical base of the
approach, both the study population and the research problem should remain
loose and flexible to endure the freedom necessary to obtain varied and rich
data if a situation emerges.
Establishing
operational definitions
In defining the problem you may use certain words or items
that difficult to measure and/or the understanding of which may very from
respondent to respondent. In a research study it is important to develop,
define or establish a set of rules, indicators or yardsticks in order to
establish clearly the meaning of such words/items. It is sometimes also important
to define clearly study population from which you need to obtain the required
information. When you define concept that you plan to use either in your
research problem and /or in identifying the study population in a measurable
form, they are called working definitions or operational definitions. You must understand
that these working definitions that you develop are only for the purpose of
your study and could be quite different to legal definitions, or those used by
others. As the understanding of concepts
can very markedly from person to person, your working definitions will inform
your readers what exactly you mean by the concepts that you have used in your
study. The following example studies help to explain this. The main objectives
are:
1. To find out
number of children living below the poverty line in Australia .
2. To
ascertain the impact of immigration on family roles among immigrants.
3. To measure
the effectiveness of a retraining programme designed to help young people.
Although these objectives clearly state the main thrust of
the studies, they are not specific in terms of the main variables to be studied
and the study populations. You cannot count the number of children living below
the poverty line until you decide what constitutes the poverty line and line
and how to determine it; it you cannot find out the impact of immigration on
family roles unless you identify which roles constitute family roles; and you
cannot measure effectiveness until you define what effectiveness until you
define what effectiveness is . On the other hand, it is equally important to
decide exactly what you mean by ‘children’ immigrants’ or ‘young’ Up to what
age will you consider a person to be a child (I.e.5,1015 or 18)? Who would you
consider young? A person 15 years of age, 20,25 or 30? Who would you consider
to be an immigrant? A person who immigrated 40, 20 or 5 years ago? In addition,
are you going to consider immigrants from every country or only a few? In many
case you need to develop operational definitions for the variables and concepts
you are studying and for the population that becomes the source of the
information for your study. Table 4.2 lists the concepts and the population
groups to be operationalised for the above examples.
TABLE 4.2 Operationalisation of concepts and the study
populations
|
Study
|
Concept to be
studied
|
Population to
be studied
|
||
|
Concepts
|
Issues
|
Study
populations
|
Issues
|
|
|
1
2
3
|
Poverty
Family
Effectiveness
|
What constitutes
‘poverty line’?
What constitutes
‘family roles’?
What constitutes
‘effectiveness’?
|
Children
Immigrants
The young
|
Who would you consider a child? Who would you consider an
immigrant? Who would you consider a
young person?
|
|
You must:
Operationalise the concepts : define in practical, observable and measurable terms poverty line’, ‘family roles’
and effectiveness’ Operationalise the
study population: define in identifiable terms ‘children’ immigrants and
‘young’
|
||||
In a
research study you need to define these clearly in order to avoid ambiguity and
confusion. This is achieved through the
process of developing operational/working definitions. You need to develop
operational definitions for the major concepts you are using in your study and
develop a framework for the study population enabling you to select appropriate
respondents.
Operational
definitions may differ from day-to-day
meanings as well as dictionary or legal definitions. These meanings may
not be helpful in identifying either your study population or the concepts you
are studying. Though in daily in daily life you often use words such as
‘children’ youth’ and ‘immigrant’ loosely, you need to be more specific when
using them in a research study. You should work through you own definitions.
Operational
definitions give an operational meaning to the study population and the concepts
used. It is only through making your procedures explicit that you can validly
describe, describe, explain, verify and test. It is important to remember that
there are no rules for deciding if an operational
definition is valid. Your arguments must
convince others about the appropriateness of your definitions.
Formulating a
research problem in qualitative research
The difference in qualitative and quantitative studies
starts with the way you formulate your research problem. In quantitative research
you strive to be as specific as possible, attempt to narrow the magnitude of
your study and develop a framework within which you confine your search. On the
other hand, in qualitative research, this specificity in scope, methods and
framework is almost completely ignored. You strive to maintain flexibility,
openness and freedom to include any new
ideas or exclude any aspect that you initially included but later consider not
to be relevant . At the initial stage you only identify the main thrust of your
study and some specific aspects aspects which you want to find out about .
Qualitative research primarily employs inductive reasoning. In contrast to
quantitative research, where a research problem is stated before data
collection, in qualitative research the problem is reformulated several times
after you have begun the data collection. The research problem as well as data
collection strategies are reformulated as necessary throughout data collection
either to acquire the ‘totality’ of a phenomenon or to select certain aspects
for greater in- depth study.
This
problems in terms of comparability of the information gathered. It is possible
that your areas of search may become markedly different during the preliminary
and final stages of data gathering. During the initial developmental
phase, many researchers produce a
framework of ‘reminders’ (a conceptual framework of enquiry) to ensure that key
issues/aspects are covered during discussions with the respondents . As the
study progress, if needs be, issues or themes are added to this framework. This
is not a list of questions but reminders that are only used if for some reason
the interaction with respondents lacks discussion. Let us take an example to
detail the process of formulation of a research of formulation of a research
problem in qualitative research: Once I supervised a student who was interested
in attention deficit hyperactivity disorder (ADHD). She wanted to find out, as
she put it, ‘What does it means to have a child with ADHD in the family? Of course
my first question to her was, ‘What do you mean by ‘what does it mean to have a child with ADHD? To
which my answer was, ‘I do not understand your question. Could you please
explain to me the meaning of “what does it mean”? She found it difficult to
explain and immediately realized the problem with the question. What she had in mind. During the discussion that followed,
though she could explain some of the things she had in mind, she realized that
she could not go to a respondent with her initial question.
The
student knew a family who had a child with ADHD from which her interest in the
topic had probably stemmed. I suggested that she have a talk with the mother.
She did, and to her surprise, the mother asked her the same question that I
had.
I advised
her to read some literature on ADHD and also have informal talks with two
families who a child with ADHD. We decided to select on single mother family
and the other where the father and the mother both take responsibility for the
child. She was advised to record all the issues aspects that reflected her
understanding of ‘what does it mean’, relating to bringing up a child with ADHD
in the family. After going through the
above, she developed a list three and a half pages long of the aspects and issues that, according to her reflected her
understanding of what it mean’ she did not construct any specific questions
around these aspects or issues. They served as background for her to raise with
potential respondents in case respondents did not come up with issues or
aspects for discussion in terms of what does it mean to have a child with ADHD
in the family?
This list
brought immense clarification to her thinking about what does it mean’ and
served as the basis of her interviews with the families. A number of times
during the supervisory sessions she had mentioned that she would not have been
able to do much without the conceptual framework. You should not confuse it with the interview guide. The
list is a conceptual construction of the thoughts that serve as background and
become the basis of discussions in case there is insufficient dialogue with
your potential respondents.
Summary
The
formulation of a research problem is the most important step in the research
process. It is the foundation. In terms of design, on which you build the whole
study. Any defects in it will adversely affect the validity and reliability of
your study.
There are
no specific guidelines but the model suggested in this chapter could serve as a
useful framework for the beginner. The seven model helps you narrow your broad
area of interest to enable you to decide what specifically you want study. It
is operational in nature and follows a logical sequence that takes beginner
through the complexities of formulating a research problem in a simple and easy
to understand manner.
It is important to articulate the objectives of your study clearly. Objectives
should be specific and free from ambiguity, and each one should relate to only
aspect of the study. They should be under two headings : main objective and sub
objectives. Use action oriented words when
writing your objectives.
Formulation
of a research problem in qualitative research follows a different path you
do not predetermine the exact nature and
extent of the research problem you propose to find answers to. You continue to modify it as you
start finding out more about it. However, it will help you if you develop a
conceptual framework of the different aspects of a problem to serve as a
backdrop for issues to be discussed with potential respondents.
Developing
operational definitions for the concepts that you propose to study is extremely
important. This enhances clarity about the issues you are trying to find out
about and about the study population you plan to gather information from. It is
important that you operational ise both the main variables you are proposing and the study population.
For you to Think About
Ø
Refamiliarise
yourself with the keywords listed at the beginning of this chapter and if you
are uncertain about the meaning or application of any of them revisit these in
the chapter before moving on.
Ø
Identity
two or three potential research questions, related to your own academic field
or professional area, that would fall under each of the four Ps (as outlined in
Table 4.1):
Ø
People;
Ø
Problems
Ø
Phenomena.
Ø
For
each of these hypothetical research questions, identify which concepts and
study populations would need to be operationally defined. Consider what
problems might occur if this was not done.
Ø
Select
a broad subject area of interest to you and ‘dissect’ it into sub areas.
CHAPTER
5
Identifying Variables
In this chapter
you will learn about:
- What variables and concepts are how
they are different
- How to turn concepts into operational
variables
- Types of variables from the
viewpoint of:
-
Causation
-
The study design
-
The unit of
measurement
- Types of measurement scales:
-
The nominal or
classificatory scale
-
The ordinal or ranking
scale
-
The interval scale
-
The ratio scale
Keywords: active
variables, attribue variables, categorical variables, causation, constant
variables causation, constant variables, continuos variables, dépendent variables,
dichotomises, extraneous variables, indépendant variables, interval scale, intervening
variables, measurement scales, nominal scale, ordinal scale, polytomous, ratio
scale, unit of measurement.
If it exists, it can be measured (Babbie 1989: 105)
In the process of formulating a research problem, in the
case of quantitative research, there are two important considerations: the use
of concepts and the construction of hypotheses. In the previous chapter, we
established that concepts are highly
subjective as an understanding of them
varies from person to person. It follows, therefore, that as such they may not
be measurable. In a research study it is important that the concepts used
should be operationalised in measurable terms so that the extent of variation
in respondents understanding is reduced if not eliminated. Using techniques to
operationalise concepts, and knowledge about variables, plays an important role
in reducing this variability and fine tuning your research problem.
What is a
variable?
Whether we accept it or not, we all make value judgments
constantly on our daily lives: This food is excellent’ I could not sleep well
last night; I do not like this and I
think this is wonderful. These are all judgments
based upon our own preferences, or assessment, Because these explain feelings
or preferences , the basis on which they are made markedly from person to
person. There is no uniform yardstick with which to measure them. A particular
food may be judged’ excellent by one person but awful by another, and something
else could be wonderful to one but ugly to another. When people express these
feelings or preferences, they do so on the basis of certain in their minds, or
in relation to their expectations. If you were to question them you will
discover that their judgment is based is based upon indicators and/or
expectations that lead them to conclude and express a particular opinion.
Let us
consider this in a professional context:
- This programme is effective.
- This programme is not effective.
- We are providing a quality service
to our clients.
- This is a waste of time.
- In this institution women are discriminated
against.
- There is no accountability in this
office.
- This product is not doing well.
These are not preferences per se; these are judgments that require
a sound basis on which to proclaim. For example, if you want find out if a
programme is effective, if a service is of quality or if there is
discrimination, you need to be careful that such judgments have rational and
sound basis. This warrants the use of a measuring mechanism and it is in the process
of measurement that knowledge about variables plays an important role.
An image,
perception or concept that is capable of measurement hence capable of taking on
different values is called a variable. In other words a concept that can be
measured is called a variable. According to Kerlinger, A variable is a property that takes on different
values putting it redundantly, a variable is something that varies…. A variable
is symbol to which numerals or values are attached’ (1986 : 27). Black and Champion
define a variable as ‘rational units of analysis that can assume any one of a
number of designated sets of values’ (1976:34). A concept that can be measured
on any one of the four types of measurement scale, which have varying degrees
of precision in measurement, is called a
variable (measurement scales are discussed later in this chapter).
However, there
are some who believe that scientific methods are incapable of measuring feelings, preferences, values
and sentiments. In the author’s opinion most of these things can be measured,
though there are situations where such feelings or judgements cannot be
directly measured but can be measured indirectly through appropriate indicators. These feelings and judgements are
based upon observable behaviors in real life, though the extent to which the
behaviors reflect their judgements may vary form person to person. Cohen and
Nagel express their opinion in the following words:
There are,
indeed , a great many writers who believe that scientific method is inherently inapplicable
to such judgements as estimation or value, as This is beautiful , this is good
or this ought to be done…. All judgements of the latter type express nothing but
feelings tastes or individual preferences, such judgements cannot be said to
be true or false (except as descriptions of the personal feelings of the one
who utters them)…. Almost all human discourse would become meaningless if we
took the view that every moral or aesthetic judgment is no more true or false
than any other.(1966:352).
The difference
between a concept and variable
Measurability is the main difference between a concept and
a variable. Concepts are mental images or perceptions and therefore their
meanings vary markedly from individual to individual, whereas variables are
measurable, though, of course, with varying degrees of accuracy. A concept
cannot be measured whereas a variable can be subjected to measurement by crude
refined or subjective/objective units of measurement. Concepts are subjective
impressions which, if measured as such would cause problems in comparing responses
obtained from different respondents.
According to Young:
Each
collaborator must have the same understanding of the concepts if the
collaborative data are to be similarly classified and the findings pooled and
tested, or reproduced. Classification and comparison demand uniform and precise
definitions of categories expressed in concepts. (1966:18)
It is therefore
important for the concepts to be converted into variables (either directly or
through a set of indicators) as they can be subjected to measurement, even though
the degree of precision with which they
be measured markedly varies from one measurement scale to another (nominal, ordinal, interval
and ratio). Table 5.1 gives examples of concepts and variables to illustrate
the differences between them.
TABLE 5.1 Examples
of concepts and variables
|
Concepts
|
Variables
|
|
|
|
-
Subjective
impression
-
No
uniformity as to its understanding among different people
-
As
such cannot be measured
|
-
Measurable though the degree of precision varies from scale to scale
and from variable to variable (e.g. attitude- subjective, income- objective)
|
Converting
concepts into variables
If you are using a concept in your study, you need to
consider its operationalisation that is , how it will be measured. In most
cases, to operationalise a concept you
first need to go through the process of identifying indicators- a set of
criteria reflective of the concept- which can then be converted into variables.
The choice of indicators for a concept might vary the researcher but those
selected must have a logical link with the concept. Some concepts, such as rich
(in terms of wealth), can easily be converted into indicators and then
variables. For example, to decide objectively if a person is rich, one first
needs to decide upon the indicators of wealth. Assume that we decide upon
income and assets as the indicators. Income is also a variable since it can be
measured in dollars; therefore, you do not need to convert this into a variable.
Although the assets owned by an individual are indicators of his/her richness
they still belong to the category of concepts. You need to look further at the
indicators of assets. For example house, boat, car and investments are
indicators of assets. Converting the value of each one into dollars will give
the total value of the assets owned by a person. Next, fix a level, based upon available information on
income distribution and an average level of assets owned by members by of a
community, which acts as the basis for classification. Then analyze the
information on income and the total value of the assets to make a decision
about whether the person should be classified as rich. The operationalisation
of other concepts, such as the
effectiveness or impact of a programme, may prove more difficult. Table 5.2 shows some example
that will help you to understand the process of converting concepts into variables.
One of the main
differences between quantitative and qualitative research studies is in the area
of variables. In qualitative research, as it usually involves studying perceptions,
beliefs, or feelings, you do not make any attempt to establish uniformity in
them across respondents
TABLE 5.2
Converting concepts into variables
Concepts Indicators Variables
|
Concepts
|
Indicators
|
Variables
Decision
level (working definitions
|
|
|
Rich
|
1 Income
2 Assets
|
1 Income per year
2 Total value of :
Home(s); boat; car (S) Investments
|
1 if > $100 000
2 if > $250 000
|
|
High academic achievement
|
1 Average marks obtained in examinations
2 Average marks obtained in practical
work
3
Aggregate marks
4 etc.
|
1 Percentage of marks
2 Percentage of marks
3 Percentage of marks
|
1 if>75%
2 if>75%
3 if>80%
|
|
Effectiveness of a health
|
1 Number of patients
2 Changes in morbidity (a) Changes in
the extent of morbidity
(b) Changes in the pattern of morbidity
3
Changes in mortality (a) Changes in the crude Death Rate (CDR)
(b) Changes in the Age-Specific Death Rate (ASDR)
4 Changes in nutritional status
(a) changes in weight
(b) changes in illness episodes
© Changes in morbidity
|
1 number of patients serviced in a
month/year
2 (a) Changes in morbidity rate (number
of illness or episodes per 1000 pop.)
(b) changes in morbidity typology
31 Changes in CDR
2 Changes in ASDR
41 Changes in weight
21 illness episodes in a year
3 Changes in morbidity type
|
Whether the difference in before and after jevels is statistically significant
Point-prevalence increase or decrease in each variable as
decided by the researcher or other experts
|
And hence measurements and variables do not carry much
significance. On the other hand , in quantitative studies, as the emphasis is
on exploring commonalities in the study population, measurements and variables
play an important role.
Types of variable
A variable can be classified in a number of ways. The classification developed here result
from looking at variables in three different ways (see Figure 5.1 ):
- The causal relationship;
- The study design;
- The unit of measurement.
From the viewpoint
of causal relationship
In studies that attempt to investigate a causal
relationship or association, four sets of variables may operate (see Figure
5.2):
1
Change variables,
which are responsible for bringing about change in a phenomenon situation or
circumstance;
2
Outcome variables,
which are the effects, impacts or consequences of a change variable;
3
Variables which affect
or influence the link between cause and effect variables;
4
Connecting or linking
variables, which in certain situations are necessary to complete the
relationship between cause and variables.
In research terminology change variables are called
independent variable, outcome/effect variables are called dependent variables,
the unmeasured variables affecting the cause and effect relationship are called extraneous variables
and the variables that link a cause and effect relationship are called intervening variables. Hence:
1.
Independent variable The
cause supposed to be responsible for bringing about change(s) a phenomenon or
situation.
2.
Dependent variable-
the outcome or change (s) brought about by introduction of an independent variable.
3.
Extraneous variable
several other factors operating in a real life situation may affect changes in
the dependent variable. These factors,
not measured in the study, may increase or decrease the magnitude or strength
of the relationship between independent and dependent variables
4.
Intervening variable
sometimes called the confounding variable (Grinnell 1988: 203), it links the independent
and dependent variables. In certain situations the relationship between an
independent and a dependent variable cannot be established without the
intervention of another variable. The
cause, or independent, variable will have assumed effect only in the presence
of an intervening variable.
|
Type of variable
|
|
Causal model
|
|
Study design
|
|
Unit of measurement
|
|
|
|
Attribute
variables
|
|
Active
variables
|
|
Dependent
variables
|
|
Extraneous
variables
|
|
Intervening
variables
|
|
Independent
Variables
|
|
Categorical or discrete variables
|
|
Continuous variables
|
|
Qualitative
variables
|
|
Quantitative
variables
|
|
Polytomies
|
|
Dichotomies
|
|
Constants
|
FIGURE
5.1 Types of variable
Note:
Classification across a classification base is not mutually exclusive but
classification within a classification base is. Within a study an independent variable
can be an active variable, or a quantitative or a qualitative variable and it
can also be a continuous or a categorical variable but it cannot be a
dependent, an extraneous or an intervening variable.
|
Cause
|
|
Effect
|
Change variable 1 Outcome
variables 2
Variables that affect the
Relationship (3)
FIGURE 5.2 Types
of variable in a causal relationship
To explain these variables let us
consider some examples. Suppose you want to study the relationship between
smoking and cancer. You assume that smoking is a cause of cancer. Studies have
shown that are there are many factors affecting this relationship, such as the number
of cigarettes or the amount of tobacco smoked every day; the duration of
smoking; the age of the smoker; dietary habits; and the amount of exercise
undertaken by the individual. All of these factors may affect the extent to
which smoking might cause cancer. These variables may either increase or
decrease the magnitude of the relationship.
In the above example the extent of
smoking is the independent variable, cancer is the dependent variable and all
the variables that might affect this relationship, either positively or negatively,
are extraneous variables. See Figure 5.3.
|
Smoking
|
|
(Assumed
cause)
|
|
Independent
variable
|
|
Cancer
|
|
(Assumed effect)
|
|
Dependent variable
|
|
Affect the relationship
|
|
·
The age of the person
·
The extent of his/her smoking
·
The duration of smoking
·
The extent of daily exercise, etc.
|
|
Extraneous variable
|
FIGURE 5.3
Independent, dependent and extraneous variables in a causal relationship
Let
us take another example. Suppose you want to study the effects of a marriage
counseling service on problems among clients of an agency providing such a
service. Figure 5.4 shows the sets of variables that may operate in studying
the relationship between counseling and marriage problems.
|
Counseling service
|
|
(Assumed
cause)
|
|
Independent
variable
|
|
Marriage problems
|
|
(Assumed effect)
|
|
Dependent variable
|
|
Affect the relationship
|
|
|
Extraneous variables
|
FIGURE 5.4 Set
of variables in counseling and marriage problems
In studying the relationship between
a counseling service and marriage problems, it is assumed that the counseling
service will influence the extent of marital problems. Hence, in the study of
the above relationship, the type of counseling service is the independent
variable and the extent of marriage problems
is the dependent variable. The magnitude or strength of this
relationship can be affected, positively or negatively, by a number of other
factors that are not the focus of the study. These extraneous variables might
be the birth of a child; improvement in a couple’s economic situation; the
couple’s motivation to change the situation ; the involvement of another
person; self-realisation; and pressure from relatives and friends. Extraneous
variables that work both ways can increase or decrease the strength of the
relationship.
The example in Figure 5.5 should
help you to understand intervening variable. Suppose you want to study the relationship
between fertility and mortality. Your aim is to explore what happens to
fertility when mortality declines. The history of demographic transition has
shown that a reduction in the fertility level follows a decline in the
mortality level, though the time taken to attain the same level of reduction in
fertility varied markedly from
|
(Mortality)
|
The extent of
the use of contraceptives
|
Fertility
|
|
Independent variable
|
Intervening variables
|
Dependent variable
|
|
|
Extraneous
variables
|
FIGURE
5.5 Independent, dependent, extraneous and intervening variables
Country
to country. As such, there is no direct relationship between fertility and
mortality. With the reduction in mortality, fertility will decline only if
people attempt to limit their family
size. History has shown that for a multiplicity of reasons (the discussion of
which is beyond the scope of this book) people have one method or another to or
another to control their fertility, resulting in lower fertility levels. It is thus
the intervention of contraceptive methods that completes the relationship: the
greater the use of contraceptives, the greater the decline in the fertility
level and the sooner the adoption of contraceptive methods by people, the sooner
the decline. The extent of the use of contraceptives is also affected by a
number of other factors, for example attitudes towards contraception , level of
education, socioeconomic status and age, religion, and provision and quality of
health services. These are classified as extraneous variables.
In the above example, decline in
mortality is assumed to be the cause of a reduction in fertility, hence the
mortality level is the independent variable and fertility is the dependent
variable. But this relationship will be completed only if another variable
intervenes – that is, the use of contraceptives. A reduction in mortality
(especially child mortality) increases family size, and an increase in family
size creates a number of social, economic and psychological pressures on
families, which in turn create attitudes favorable to a smaller family size.
This
change in attitudes is eventually operationalised in behavior through the
adoption of contraceptives. If people do
not adopt methods of contraception, a change in mortality levels.
|
FIGURE
5.5 Active and attribute variables
Will
not be reflected in fertility levels. The population explosion in developing
countries is primarily due to lack of acceptance of contraceptives. The extent of the use of contraceptives
determines the level of the decline in fertility. The extent of contraceptive
adoption by a population is dependent
upon a number of factors. As mentioned earlier, in this causal model, the
fertility level is the dependent variable, the extent of contraceptive use is
the intervening variable, the mortality level is the independent variable, and
the unmeasured variables such as attitudes, education, age, religion, the
quality of services, and so on, are all
extraneous variables. Without the intervening variable the relationship between
the independent and dependent variables will not be complete.
From the viewpoint of study design
A
study that examines association or causation may be a controlled/contrived
experiment, a quasi-experiment or an ex post facto or non-experimental study.
In controlled experiments the independent (cause) variable may be introduced or
manipulated either by the researcher or by someone else who is providing the
service. In these situations else who is providing the service. In these
situations there are two sets of variables (see Figure 5.6);
- Active variables those variables that can be manipulated, changed or controlled.
- Attribute variables those variables that cannot be manipulated, changed or controlled, and that reflect the characteristics of the study population, for example age, gender, education and income.
Suppose a study is designed to measure the relative
effectiveness of three teaching models
(Model A, Model B and Model C). The structure and contents of these
models could vary and any model might be tested on any population group. The
contents, structure and testability of a model on a population group may also
vary researcher to researcher. On the
other hand, a researcher does not have any control over characteristics of the
student population such as their age gender or motivation to study. These
characteristics of the study population are called attribute variables.
However, a researcher does have the
ability to control and/or change the teaching models. S/he can decide what constitutes
a teaching model and on which group of
the student population it should be tested (if randomization is not used).
From the viewpoint of
the unit of measurement
From the viewpoint of the unit of measurement, there are two
ways of categorizing variables:
·
Whether the unit of measurement is categorical
(as in nominal and ordinal scales) or continuous in nature (as in interval and
ratio scales);
·
Whether it is qualitative (as in nominal and
ordinal scales ) or quantitative in nature (as in interval and ratio scales).
On the whole there is very little difference
between categorical and qualitative, and between continuous and quantitative,
variables. The slight difference between them is explained below.
Categorical
variables are measured on nominal or ordinal measurement scales, whereas
for Continuous variables the
measurements are made on either an interval or a ration scale. There are three
types of categorical variables:
- Constant variable has only one category or value, for example taxi, tree and water;
- Dichotomous variable –has only two categories, as in male/female, yes/no, good/bad, head/tail, up/down and rich/poor;
- Polytomous variable – can be divided into more than two categories, for example religion (Christian, Muslim, Hiddu); political parties (Liberal, Democrat); and attitudes (strongly favorable, favorable, uncertain, unfavorable, strongly unfavorable).
Continuous variables, on the other hand, have continuity in
their measurement , for example age, income and attitude score. They can take
any value on the scale on which they are
measured. Age can be measured in years, months and days. Similarly, income can
be measured in dollars and cents.
In many ways
qualitative variables are similar to categorical variables as both use either nominal
or ordinal measurement scales. However, there are some differences. For
example, it is possible to develop categories on the basis of measurements made
on a continuous scale, such as measuring the income of a population in dollars
and cents and then developing categories such as low middle and high income.
The measurement of income in dollars and cents is classified as the measurement
of a continuous variable, whereas its subjective measurement in categories such
as low middle and high group is a qualitative variable.
Although
this distinction exists, for most practical purposes there is no real
difference between categorical and
qualitative variables or between continuous and quantitative variables. Table
5.3 shows similarities and differences among the various type of variable.
TABLE 5.3 Categorical/continuous and quantitative/qualitative
variables
|
Categorical
|
Continuous
|
Qualitative
|
Quantitative
|
||
|
Constant
|
Dichotomous
|
Polytomous
|
|||
|
|
Attitudes
Age*
|
Income
($)
Age
(years)
Weight
(kg)
|
Gender
Temperature+
|
Education
level
__
no.of
Years
complete
Age*
_
Years/months
Income^
___$
per
Temperature+
___
C or F
|
- Can be classified in qualitative categories, e.g. old, young, child; or quantitatively on a continuous scale, e.g. in years, months and days.
^ Can be measured quantitatively in dollars and cents as well
as qualitatively in categories such as high, middle and lo.
+ Similarly, temperature can be measured quantitatively in
degrees on different scales (Celsius, Fahrenheit) or in qualitative categories
such as hot and cold.
For a beginner it
is important to understand that the wa a variable is measured determines the type of analysis that can be performed ,
the statistical procedures that can be applied to the data, the way the data
can be interpreted and the findings that can be communicated. You may not
realize in the beginning that the style of your report is entirely dependent
upon the way the different variables have been measured – that is, the way a
question has been asked and its response recorded. The way you measure the variables
in your study determines whether a study is qualitative or quantitative in
nature. It is therefore important to know about the measurement scales for
variables.
Types of measurement
scale
The frame into
which we wish to make everything fit is one of our own construction; but we do
not construct it at random, we construct it by measurement so to speak; and that
is why we can fit the facts into it without altering their essential qualities.(Poincare
1952: xxv)
Measurement is central to any enquiry. In addition to the
ideology and philosophy that underpin each mode of enquiry, the most
significant difference between qualitative and quantitative research studies is
in the types of measurement used in collecting information from the respondents.
Qualitative research mostly uses descriptive statements to see answers to the
research questions, whereas in quantitative
research these answers are usually sought on one of the measurement scales
(nominal, ordinal, interval or ratio). If a piece of information is not
collected using one of the scales at the time of data collection, it is
transformed into variables by using these measurement scales at the time of
analysis. Measurement on these scales could be either in the form of qualitative
categories or through a precise unit of
measurement. Those scales which have a unit of measurement (interval and ratio)
are considered to be more refined, objective and accurate. On the other hand,
nominal and ordinal scales are considered subjective and hence not as accurate
as they do not have a unit of measurement per se. The greater the refinement in
the unit of measurement of a variable,
the greater the confidence placed in the findings by others, other
things being equal. One of the main differences between the physical and the
social sciences is the units of measurement used and the degree of importance
attached to them. In the physical sciences measurements have to be absolutely
accurate and precise, whereas in the social sciences they may vary from the
very subjective to the very quantifiable. Within the social science the
emphasis on precision in measurement varies markedly from one discipline to
another. An anthropologist normally uses very subjective units of measurement,
whereas an economist or an epidemiologist emphasizes objective measurement.
There are two main
classification systems in the social sciences for measuring different type of variable. One was developed by
S.S.Stevens (in 1946) and the other by Duncan
(in1984). According to Smith (1991; 72) Duncan
(1984) has enumerated in increasing order of interest to scientists, five types
of measurement: nominal classification, ordinal scaling, cardinal scaling,
ratio scaling, and probability scaling; Duncan
writes about Steven’s classification as follows:
The theory of
scale types proposed in 1946 by S S Stevens focused on nominal, ordinal,
interval, and ratio scales of measurements. Some of his examples of these types
notably those concerning psychological test scores – are misleading .(1984 :
viii)
However, Bailey
considers that S S Stevens constructed a widely adopted classification of levels
of levels of measurement’ (1978:52). As this book is written for the beginner
and as Stevens’s classification is simpler, it is this used for discussion in
this chapter. Stevens has classified the different types of measurement scale
into four categories:
- Nominal or classificatory scale;
- Ordinal or ranking scale;
- Interval scale;
- Ratio scale.
Table
5.4 summarizes the characteristics of the four scales.
TABLE 5.4
Characteristics and examples of the four measurement scales.
|
Measurement scale
|
Examples
|
Characteristics of the scale
|
|
Nominal or classificatory
|
A Tree, house, taxi, etc. B Gender: male/female
Attitude:
Favourable/unfavourable C political parties
|
Each subgroup has a characteristic/property which is
common to all classified within that subgroup
|
|
Ordinal or ranking
|
Income
|
It has the characteristics of nominal scale, e.g,
individuals, groups, characteristics classified under a subgroup have a common
characteristic
PLUS
Subgroups have a relationship to one another. They
are arranged in ascending or descending order
|
|
Interval
|
Temperature:
Attitudinal scale (Turnstone
scale):
·
10 – 20
·
21 – 30
·
31- 40
·
41 – 50, etc.
|
It has all the characteristics of an ordinal scale
(which also includes a nominal scale)
PLUS
It has a unit of measurement with an arbitrary
starting a terminating point
|
|
|
Height: cm
Income : $
Age: Years/moths
Weight: kg
Attitudinal score:
Guttman scale
|
It has all the properties of an interval scale
PLUS
It has a fixed starting point, e.g. a zero point
|
The nominal or classificatory scale
A nominal scale enables the classification of individuals,
objects or responses based on a common/shared property or characteristic. These
people, objects or responses are divide into a number of subgroups in such a
way that each member of the subgroup has a common characteristic A variable
measured on a nominal scale may have one , two or more subcategories depending upon
the extent of variation. For example, water and taxi have only one subgroup
whereas the variable gender can be classified into two subcategories: male and female. Political
parties in Australia can
similarly be classified into four main subcategories: Lahore , Liberal, Democrat’s and Greens. Those who identify themselves, either
by membership or belief, as belonging to the Lahore Party are classified as
Labor those identifying with the liberals are classified as liberal and so on.
The name chosen for a subcategory is notional but for effective communication
it is best to choose something that describes the characteristic of the
subcategory .
Classification by
means of a nominal scale ensures that individuals objects or responses within
the same subgroup have a common
characteristic or property as the basis of classification. The sequence in
which subgroups are listed makes no difference as there is no relationship
among subgroups.
The ordinal or ranking
scale
An ordinal scale has all the properties of a nominal scale –
categorizing individuals, objects, responses or a property into subgroups on
the basis of a common characteristic- but also ranks the subgroups in a certain
order. They are arranged in either ascending or descending order according to
the extent that a subcategory reflects the magnitude of variation in the
variable. For example, income can be measured either quantitatively (in dollars
and cents) or
Qualitatively, using subcategories: above average. Average
and below average (These categories can also be developed on the basis of
quantitative measures, for example below $ 10 000= below average, $ 10 000 -$
25 000 = average and above $ 25 000 =
above average.) The subcategory’ above average indicates that people so grouped
have more income than people in the average category and people in the average
category have more income than those in the below average category. These
subcategories of income are related to one another in terms of the magnitude of people’s income, but the
magnitude itself is not quantifiable and hence the difference between above
average and average or between average and below average subcategories cannot
be ascertained. The same is true for other variables such as socioeconomic
status and attitudes measured on an ordinal scale.
Therefore, an
ordinal scale has all the properties/characteristics of a nominal scale, in
addition to its own. Subcategories are arranged in order of the magnitude of
the property. characteristic. Also, the distance between the subcategories is
not equal as there is no quantitative unit of measurement.
An
interval scale has all the characteristics of an ordinal scale; that is
individuals or responses belonging to a subcategory have a common characteristic
and the subcategories are arranged in ascending or descending order. In addition,
an interval scale uses a unit of measurement that enables the individuals or
responses to be placed at equally spaced
intervals in relation to the spread of the variable. This scale has a starting
and a terminating point and is divided into equally spaced units/intervals. The
starting and terminating points and the number of units/intervals between them
are arbitrary and vary from scale to scale.
Celsius and Fahrenheit scales are
examples of an interval scale. In the Celsius system the starting point
(considered as the freezing point ) is 0 c and the terminating point
(considered as the boiling point) is 100 c. The gap between the freezing and
boiling points is divided into 100 equally spaced intervals, known as degrees.
In the Fahrenheit system the freezing point is 32 F and the boiling point is
212 F and the gap between the points is divided into 180 equally spaced
intervals. Each degree or interval is a measurement of temperature the higher the degree, the higher the temperature. As the starting and
terminating points are arbitrary, they are not absolute ; that is you cannot say 60 C is twice as hot as 30
C or 30 F is three times hotter than 10 F This means that while no mathematical
operation can be performed on the readings, it can be performed on the differences
between readings. For example if the difference in temperature between two
objects , A and B is 15 C and the
difference in temperature between two other objects, C and D is 45 C you can
say that the difference in temperature between C and D is three times greater
than that between A and B. An attitude towards an issue measured on the
Thurston scale is similar. However, the Likert scale does not measure the
absolute intensity of the attitude but simply measures it in relation to
another person.
The interval scale is relative; that
is it plots the position of individuals or responses in relation to one another
with respect to the magnitude of the measurement variable. Hence, an interval
scale has all the properties of an ordinal scale, and it has a unit of
measurement with an arbitrary starting and terminating point.
The ratio scale
A
ratio scale has all the properties of nominal, ordinal and interval scales and
it also has a starting point fixed at zero.
Therefore, it is an absolute scale – the difference between the intervals is
always measured from a zero point. This means the ratio scale can be used for
mathematical operations. The measurement
of income, age height and weight are examples of this scale. A person who is 40
years age is twice as old as a 20 – Year old. A
person earning $60 000 per year earns three time the salary of a person
earning $20 000.
Summary
The
understanding and interpretation of concept or a perception may vary from
respondent to
Respondent,
hence its measurement may not be consistent. A variable has some basis of classification
and hence there is far less inconsistency in its meaning and understanding. Concepts
are mental perceptions whereas variables are measurable either subjectively or objectively
on one of the measurement scales. When you convert a concept into a variable
you classify it on the basis of measurement into categories, thereby minimizing
the inherent variability in understanding. When you are unable to measure a
concept directly, you need first to convert it into indicators and then into
variables.
The way the required information is
collected in quantitative and qualitative research is the most significant
difference between them. Qualitative research mostly uses descriptive or
narrative statements as the units of measurement’ whereas quantitative research
places greater emphasis of measuring responses on one of the four measurement
scales. Though qualitative research places emphasis on descriptive statements
in data collection. At the time of analysis,
these statements are classified into categories on the basis of the main themes
they communicate.
Knowledge
of the different types of variables and way they are measured plays a crucial
role in quantitative research. Variables
are important in bringing clarity and specificity to the conceptualization of a
research problem, to the formulation of
hypotheses and to the development of a
research instrument. They affect how the data can be analyzed , what
statistical tests can be applied to the data, what interpretations can be made,
how the data can be presented and what conclusions can be drawn. The way you
ask a question determines its categorization on a measurement scale, which in turn affects how the data can
be analyzed, what statistical tests can be applied to the data, what
interpretations can be made, how the data can be presented and what conclusions
can be drawn. Also, the way a variable is measured at the data collection stage
to a great extent determines whether a
study is considered to be predominantly’ qualitative or quantitative in nature.
It is important for a beginner to
understand the different ways in which a variable can be measured and the
implications of this for the study. A variable can be classified from three
perspectives that are not mutually exclusive: causal relationship, design of the study and unit of measurement. From the perspective of causality a variable can be classified into one of four
categories: independent, dependent, extraneous and intervening. From the viewpoint
of study design, three are two categories of variable: active and attribute. If
we examine a variable from the perspective of the unit of measurement, it can
be classified into categorical can continuous or qualitative and quantitative.
There are four measurement scales
used in the social sciences: nominal, ordinal, interval and ration. Any concept
that can be measured on these scales is called a variable. Measurement scales
enable highly subjective responses, as well as responses that can be measured
with extreme precision, to be categorized. The choice of measuring a variable
on a measurement scale is dependent upon the purpose of your study and the way
you want to communicate the findings to readers.
CHAPTER 5
IDENTIFYING VARIABLES
For You
to Think About
Ø
Refamiliarise yourself with the keywords listed at the beginning of
this chapter if you are uncertain about the meaning or application of any them revisit
these in the chapter before moving on.
Ø
Imagine
that you have been asked to evaluate your lecturer. Determine which aspects of
teaching you would consider important
and develop a set indicators that might reflect these.
Ø
Self-esteem
is a difficult concept to operationalise. Think about how you might go about
developing a set indicators to determine variance in the level of self esteem
in a group of individuals.
Ø
Critically
examine the typology of variables developed in this chapter. What changes would
you like to propose?
CHAPTER 6
Constructing Hypotheses
In this chapter you will learn about:
- The definition of a hypothesis
- The functions of a hypothesis in your research
- How hypotheses are tested
- How to formulate a hypothesis
- Different types of hypotheses and their applications
- How errors in the testing of a hypothesis can occur
- The use of hypotheses in qualitative research
Keywords:
alternate hypotheses, hunch, hypothesis, hypothesis of point-prevalence, null hypothesis,
operationlisable, research hypothesis, Type I error, Type II error, one-dimensional,
valid.
Almost every
great step [in the history of science] has been made by the anticipation of
nature that is by the invention of
hypotheses which, though verifiable, often had very little foundation to start
with. (T.H.Huxley cited in Cohen & Nagel 1966: 197)
The definition of a hypothesis
The
second important consideration in the formulation of a research problem in
quantitative research is the construction of a hypothesis. Hypotheses bring
clarity, specificity and focus to a research problem, but are not essential for
a study. You can conduct a valid investigation without constructing a single
formal hypothesis. On the other hand within the context of a research study, you can construct as many
hypotheses as you consider to be appropriate. Some believe that one must
formulate a hypothesis to undertake an investigation; however, the author does
not hold this opinion. Hypotheses
primarily arise from a set of hunches
that are tested through a study and one can conduct a perfectly valid study
without having these hunches or speculations. However, in epidemiological
studies, to narrow the field of investigation, it is important to formulate
hypotheses.
The
importance of hypotheses lies in their ability to bring direction, specificity
and focus to a research study. They tell a researcher what specific information
to collect, and thereby provide greater
focus.
Let
us imagine you are at the races and you place a bet. You bet on a hunch that a
particular horse will wing. You will only know if your hunch was right after
the race. Take another example . Suppose you have a hunch that there are more
smokers than non-smokers in your class. To test your hunch, you ask either all
or just some of the class if they are smokers. You can then conclude whether
your hunch was right or wrong.
Now let us take
a slightly different example. Suppose you work in the area of public health.
Your clinical
impression is that higher rate of a particular condition prevails among people coming
from a specific population subgroup. You want to find out the probable cause of
this condition. There could be many causes. To explore every conceivable
possibility would require an enormous amount of time and resources. Hence, to
narrow the choice, based on your knowledge of the field, you could identify
what you assume to be the most probable cause. You could then design a study to
collect the information needed to verify your hunch. If on verification you
were able to conclude that the assumed cause was the real cause of the
condition, your assumption would have been right.
In these examples, you started with
a superficial hunch or assumption. In one case (horse racing) you waited for
the even to take place and in the other two instances you designed study to
assess the validity of your assumption,
and only after careful investigation did you arrive at a conclusion about the
validity of your assumptions.
Hypotheses are based upon similar
logic. As a researcher you do not know about a phenomenon, a situation, the
prevalence of a condition in a population or about the outcome of a programme, but you do have a hunch a hunch
to form the basis of certain assumptions or guesses. You test these, mostly one
by one , by collecting information that will enable you to conclude of your
hunch was right. The verification process can have one of three outcomes. Your
hunch may prove to be: right partially right or wrong. Without this process of verification,
you cannot conclude anything about the validity of your assumption.
Hence, a hypothesis is a hunch,
assumption, suspicion, assertion or an idea about a phenomenon, relationship or
situation, the reality or truth of which you do not know. A researcher calls
these assumptions, assertions, statements or hunches hypotheses and they become
the basis of an enquiry. In most studies the hypothesis will be based upon
either previous studies or your own or someone else’s observations.
There are many definition of a
hypothesis. According to Kerlinger, A hypothesis is a conjectural statement of
the relationship between two or more variables’ (1986:17). Webster’s Third New International
Dictionary (1976) defines a hypothesis as: a proposition, condition, or
principle which is assumed without belief, in order to draw out its logical
consequences and by this method to test its accord with facts which are know or
may be determine.
Black and
Champion define a hypothesis as ‘a tentative statement about something, the validity
of which is usually unknown’ (1976:126).
In another definition, Bailey defines a hypothesis as:
A proposition that is stated in a
testable form and that predicts a particular relationship between two (or more)
variables. In other words, if we think that a relationship exists, we first
state it state it as a hypothesis and then test the hypothesis in the field. (1978:35)
According to
Grinnell:
A hypothesis is
written in such a way that it can be proven or disproven by valid and reliable
data – it is in order to obtain these data we perform out study. (1988:200)
From the above
definitions it is apparent that a hypothesis has certain characteristics:
1 It is a tentative proposition.
2 Its validity is unknown.
3 In most cases, it specifies a relationship
between two or more variables.
The functions of hypothesis
While
some researchers believe that to conduct a study requires a hypothesis, having
a hypothesis is not essential as already mentioned. However, a hypothesis is important
in terms of bringing clarity to the research problem. Specifically, a
hypothesis serves the following functions:
- The formulation of a hypothesis provides a study with focus. It tells you what specific aspects of a research problem to investigate.
- A hypothesis tells you what data to collect and what not to collect, thereby providing focus to the study.
- As it provides a focus, the construction of a hypothesis enhances objectify in a study.
- A hypothesis may enable you to add to the formulation of theory. It enables you to conclude specifically what is true or what is false.
The testing of a
hypothesis
To test a hypothesis you need to go through a process that
comprises three phases: (1) constructing
a hypothesis; (2) gathering appropriate evidence; and (3) analyzing evidence to
draw
|
Phase I
|
Phase II
|
Phase III
|
|
Formulate
your hunch or assumption
|
Collect
the required data
|
Analyze
data to draw conclusions about that hunch true or false
|
FIGURE 6.1 The process of testing a hypothesis
Conclusions as to its validity. Figure 6.1 shows this process
diagrammatically. It is only after analyzing the evidence that you can conclude
whether your hunch or hypothesis was true or false. When concluding about a
hypothesis, conventionally, you specifically make a statement about the
correctness or otherwise of a hypothesis
in the form of the hypothesis is true or
the hypothesis is false. It is therefore imperative that you formulate your hypotheses clearly,
precisely and in a form that is testable. In arriving at a conclusion about the validity of your hypothesis,
the way you collect your evidence is of central importance and it is therefore
essential that your study design, sample, data collection method (s) , data
analysis and conclusions, and communication of the conclusions be valid,
appropriate and free from any bias.
The
characteristics of a hypothesis
There are a number of considerations to keep in mind when
constructing a hypothesis, as they are important for valid verification. The wording
of a hypothesis therefore must have certain attributes that make it easier for
you to ascertain its validity. These attributes are:
·
A
hypothesis should be simple, specific and conceptually clear. There is no
place for ambiguity in the construction of a hypothesis, as ambiguity will make
the verification of your hypothesis
almost impossible. It should be ‘one-dimensional’ – that is it should test
only one relationship or hunch at a time
. To be able to develop a good hypothesis you must be familiar with the subject
area (the literature review is of immense help). The more insight you have into
a problem, the easier it is to construct a hypothesis. For example:
The average age of the male students in this class is higher
than of the female students.
The above hypothesis is clear, specific and easy to test. It
tells you what you are attempting to compare (average age of this class), which
population groups are being compared (female and male students), and what you
want to establish (higher average of the male students).
Let us take
another example:
Suicide rates vary inversely with social cohesion. (Black
& Champion 1976: 126)
This hypothesis is clear and specific, but a lot more
difficult to test. There are three aspects of this hypothesis: suicide rates;
vary inversely which stipulates the direction of the relationship; and social
cohesion To find out the suicide rates and to establish whether the relationship
is inverse or otherwise are comparatively easy, but to ascertain social
cohesion is a lot more difficult. What determines social cohesion? How can it
be measured? This problem makes it more difficult to test this hypothesis.
·
A
hypothesis should be capable of verification. Methods and techniques must
be available for data collection and analysis. There is point in formulating a
hypothesis if it cannot be subjected to verification because there are no
techniques to verify it. However, this does not necessarily mean that you
should not formulate a hypothesis for which there are no methods of
verification. You might, in the process of doing your research, develop new
techniques to verify it
·
A
hypothesis should be related to the existing body of knowledge. It is
important that your hypothesis emerges from the existing body of knowledge, and
that it adds to it, this is an important function of research. This can only be
achieved if the hypothesis has its roots in the existing body of knowledge.
·
A
hypothesis should be operational sable. This means that it can be expressed
in terms that can be measured. If it
cannot be measured, it cannot be tested and, hence, no conclusions can be
drawn.
Types of hypothesis
Theoretically
there should be only one type of hypothesis, that is the research hypothesis
the basis of your investigation. However, because of the conventions in
scientific enquiries and because of the wording used in the construction of a
hypothesis, hypotheses can be classified into several types. Broadly , there
are two categories of hypothesis:
1
research hypotheses:
2
alternate hypotheses.
The formulation of an alternate
hypothesis is a convention in scientific circles. Its main function is to
explicitly specify the relationship that will be considered as true in case the
research hypothesis proves to be wrong. In a way, an alternate hypothesis is
the opposite of the research hypothesis. Conventionally, a null hypothesis, or
hypothesis of no difference, is formulated as an alternate hypothesis.
Let us take an example. Suppose you
want to test the effect that different combinations of maternal and child
health services (MCH) and nutritional supplements (NS) have on the infant
mortality rate. To test this, a two by factorial experimental design is adopted
(see Figure 6.2). There are several ways of formulating a hypothesis. For
example:
1 There will be no difference in the
level of infant mortality among the different treatment modalities.
2 The MCH and NS treatment groups will
register a greater decline in infant mortality than the only MCH treatment
group, the only NS treatment group or the control group.
|
Maternal and child health services (MCH)
|
|
|
Yes
|
No
|
|
MCH
+ NS
|
NS
|
|
MCH
|
Control
|
FIGURE
6.2 Two by two factorial experiment to
study the relationship between MCH ,
NS
3 Infant mortality in the MCH treatment
group will reach a level of 30/1000 over five years.
4 Decline in the infant mortality rate
will be three times greater in the MCH treatment group than in the NS group only over five
years.
Let us take another example. Suppose
you want to study the smoking pattern in a community in relation to gender
differentials. The following hypotheses could be constructed :
1 There is no significant difference in
the proportion of male and female smokers in the study population.
2 A greater proportion of females than
males are smokers in the study population.
3 A total of 60 per cent of females and
30 per cent of males in the study population are smokers.
4 There are twice as many female smokers
as male smokers in the study population.
In both sets of examples, the way
the first hypothesis has been formulated indicates that there is no difference
either in the extent of the impact of different treatment modalities on the
infant mortality rate or in the proportion of male an female smokers. When you construct a hypothesis stipulating that
there is no difference between two situations, groups, outcomes, or the
prevalence of a condition or phenomenon, this is called a null hypothesis and is usually written as Ho.
The second hypothesis in each
example implies that there is a difference either in the extent of the impact of different treatment
modalities on mortality or in the proportion of male and female smokers among
the population, though the extent of the difference is not specified. A
hypothesis in which a researcher stipulates that there will be a difference but
does not specify its magnitude is called a hypothesis of difference.
|
Types of hypothesis
|
|
Altemate hypothesis
|
Research hypothesis
|
|
Null
hypothesis
|
Hypothesis
of no difference (null hypothesis
|
Hypothesis
of difference
|
Hypothesis
of point prevalence
|
Hypothesis
of association
|
FIGURE
6.3 Types of hypothesis
A research may have enough knowledge
about the smoking behavior of the community or the treatment programme and its likely outcomes to speculate
almost the exact prevalence of the situation or the outcome of a treatment
programme in quantitative units. Examine the third hypothesis in both sets of examples:
the level of infant mortality is 30/1000 and the proportion of female and male
smokers is 60 and 30 per cent respectively. This type of hypothesis is know as
a hypothesis of point prevalence.
The
fourth hypothesis in both sets of examples speculates a relationship between
the impact of different combinations of MCH and NS programmes on the dependent
variable (infant mortality) or the relationship between the prevalence of a
phenomenon (smoking among different populations (male and female). This type of
hypothesis stipulates the extent of the relationship in terms of the effect of
different treatment groups on the
dependent variable (‘three times greater in the
MCH treatment group than in the NS group only over five years’) or the
prevalence of a phenomenon in different population groups (‘twice as many
female as male smokers’). This type of hypothesis is called a hypothesis of
association.
Note that in Figure 6.3 the null
hypothesis is also classified as a hypothesis of no difference under ‘Research
hypothesis’ Any type of hypothesis, including a null hypothesis, can become the
basis of an enquiry. When a null hypothesis becomes the basis of an investigation,
it becomes a research hypothesis.
Errors in testing a hypothesis
As
already mentioned, a hypothesis is an assumption that may prove to be either
correct or incorrect. It is possible to arrive at an incorrect conclusion about
a hypothesis of a variety of reasons. Incorrect conclusions about the validity
of a hypothesis may be drawn if:
When
all null hypotheses is actually:
|
Accept
|
Correct
decision
|
Type
I error
|
|
Reject
|
Type
II error
|
Correct
decision
|
FIGURE
6.4 Type I and II errors in testing a hypothesis
- the study design selected is faulty;
- the sampling procedure adopted is faulty;
- the method of data collection is inaccurate;
- the analysis is wrong;
- the statistical procedures applied are inappropriate; or
- the conclusions drawn are incorrect.
Any, some or all of these aspects of the research process
could be responsible for the inadvertent introduction of error in your stud,
making conclusions misleading. Hence, in the testing of a hypothesis there is
always the possibility of errors attributable to the reasons identified above.
Figure 6.4 shows the types of error that
can result in the testing of a hypothesis.
Hence, in
drawing conclusions about a hypothesis, two types of error can occur:
- Rejection of a null hypothesis when it is true. This is known as a Type I error.
- Acceptance of a null hypothesis when it is false. This is known as a Type II error.
Hypotheses in qualitative research
One
of the differences in qualitative and quantitative research is around the
importance attached to and the extent of use of hypotheses when undertaking a
study. As qualitative studies are
characterized by an emphasis on describing, understanding and exploring
phenomena using categorical and subjective measurement procedures, construction
of hypotheses is neither advocated nor practiced. In addition, as the degree of
specificity needed to test a hypothesis is deliberately not adhered to in
qualitative research, the testing of hypothesis becomes difficult and
meaningless. This does not mean that you cannot construct hypotheses in
qualitative research; the non-specificity of problem as well as methods and
procedures make the convention of hypotheses formulation far less practicable
and advisable. Even within quantitative studies the importance attached to and
the practice of formulating hypotheses vary markedly from one academic
discipline to another. Fro example, hypotheses are most prevalent in epidemiological research and
research relating to the establishment of causality of a phenomenon, where it
becomes important to narrow the list of probable causes so that a specific
cause and effect relationship can be
studied. In the social sciences formulation of hypotheses is mostly dependent
on the researcher and academic discipline, whereas within an academic
discipline it varies markedly between the quantitative and qualitative research
paradigms
Summary
Hypotheses,
though important, are not essential for a study. A perfectly valid study can be
conducted without constructing a single hypothesis. Hypotheses are important
for bringing clarity specificity and
focus to research study.
A hypothesis is a speculative
statement that is subjected to verification through a research study in formulating a hypothesis
it is important to ensure that it is simple, specific and conceptually clear;
able to be verified; rooted in an existing body of knowledge; and able to be operationalised.
There are two broad types of
hypothesis: a research hypothesis and an alternate hypothesis. A research
hypothesis can be further classified, based upon the way it is formulated, as a
null hypothesis, a hypothesis of difference, a hypothesis of point-prevalence
and a hypothesis of association.
One of the main differences in
qualitative and quantitative research is the extent to which hypotheses are
used and the importance attached to them. In qualitative research, because of the
purpose of an investigation and methods used to obtain information, hypotheses
are not used and almost no importance is given to them. However, in
quantitative research, their use is far more prevalent though it varies
markedly from one academic discipline to another and from researcher to
researcher. On the whole it can be said that if the aim of a study is to
explore where very little is know, hypotheses are usually not formulated; however,
if a study aims to test an assertion by way of causality of association,
validate the prevalence of something or establish its existence, hypotheses can
be constructed.
The testing of a hypothesis becomes
meaningless if any one of the aspects of your study design, sampling procedure,
method of data collection, analysis of statistical procedures applied or
conclusions drawn is faulty or inappropriate. This can result in erroneous
verification of a hypothesis: Type I error occurs where you reject a null
hypothesis when it is true should not have been rejected; and Type II error is introduced where you accept a null hypothesis when it is false and should
and not have been accepted.
For You to Think About
Ø
Refamiliarise yourself with the keywords listed
at the beginning of this chapter and if you are uncertain about the meaning or
application of any them revisit these in the chapter before moving on.
Ø
To what extent do you think that the use of
hypotheses is relevant to social research?
Ø
Formulate two or three hypotheses that relate to
your own areas of interest and consider
the factors that might affect their validity.
STEP II Conceptualizing
a Research Design
This operational step includes two
chapters:
- Chapter 7: The research design
- Chapter 8: Selecting a study design
CHAPTER 7
The Research
Design
In this chapter you will learn about
- What research design means
- The important functions of research
design
- Issues to consider when designing
your own research
- The theory of causality and the
research design
Keywords: Chance
variables, control group, experimental group, extraneous variables, independent
variable, matching maxmincon principle principle random error, randomization,
research design study design treatment group.
If you are clear
about your research problem, your achievement is worth praising. You have
crossed one of the most important and difficult sections of your research
journey. Having decided what you want study, you now need to determine how you
are going to conduct your study. There are a number of questions that need to
be answered before you can proceed with your journey. What procedures will you
adopt to obtain answers to research questions? How will you carry out the tasks
needed to complete the different components of the research process? What should you do and what should you not do
in the process of undertaking the study? Basically, answers to these questions
constitute the core of a research design.
What is a research design?
A research
design is a plan, structure and strategy of investigation so conceived as to obtain answers to research questions or problems.
The plan is the complete scheme or programme of the research. It includes an outline of what
the investigator will do from writing the hypotheses and their operational
implications to the final analysis of data. (Kerlinger 1986: 279).
A traditional
research design is a blueprint or detailed plan for how a research study is to
be completed operationalizing variables so they can be measured, selecting a
sample of interest to study, collecting data to be used as a basis for testing
hypotheses, and analyzing the results. (Thyer 1993:94)
A research
design is a procedural plan that is adopted by the researcher to answer
questions validly, objectively, accurately and economically. According to
selltiz , Deutsch and Cook, A research design is the arrangement of conditions
for collection and analysis of data in manner that aims to combine relevance to
the research purpose with economy in procedure’ (1962:50).
Through a
research design you decide for yourself and communicate to others your
decisions regarding what study design you propose to use, how you are going to
collect information from your respondents, how you are going to select your
respondents, how the information you are
going to collect is to be analysed and how
you are going to communicate your findings. In addition, you will need to
detail in your research design the rationale and justification for each
decision that shapes your answers to the how of the research journey. In presenting
your rationale and justification you need to support them critically form the
literature reviewed. You also need to assure yourself and others that the path
you have proposed will yield valid and reliable results.
The functions of a research design
The above
definitions suggest that a research design has two main functions. The first
relates to the identification and/ or development of procedures and logistical
arrangements required to undertake a study, and the second emphasizes the
importance of quality in these procedures to ensure their validity, objectivity
and accuracy accuracy. Hence, through a research design you:
- Conceptualize and operational plan to undertake the various procedures and tasks required complete your study;
- Ensure that procedures are adequate to obtain valid, objective and accurate answers to the research questions. Kerlinger calls this function the control of variance (1986: 280).
Let us take
first of these functions. The research design should detail for you, your
supervisor and other readers all the procedures you plan to use and the tasks
you are going perform to obtain answers to your research questions. One of the
most important requirements of a research design is to specify everything
clearly so a reader will understand what procedures to follow and how them. A
research design, therefore, should do the following:
·
Name the study design per se that is , cross
sectional before and after comparative control experiment or random control’.
·
Provide detailed information about the
following aspects of the study:
-
Who will constitute the study population?
-
How will the study population be identified?
-
Will a sample or the whole population be
selected?
-
If a sample is selected, how will it be
contacted?
-
How will consent be sought?
-
What method of data collection will be used and
why?
-
In the case of a questionnaire, where will the
responses be returned?
-
How should respondents contact you if they have
queries?
-
In the case of interviews, where will they be
conducted?
-
How will ethical issues be taken care of?
Chapter
8 describes some of the commonly used study designs. The rest of the topics
that constitute a research design are covered in the subsequent chapters.
The theory of causality and the research
design
Now let’s turn to the second function of the
research design ensuring that the procedures undertaken are adequate to obtain
valid, objective and accurate answers to the research questions. To ensure this
it is important that you select a study design that helps you to isolate,
eliminate or quantify the effects of different sets of variable influencing the
independent variable. To help explain this, we look at a few examples.
Suppose you want to find out to
which the service has been able to resolve the marital problems of its clients.
In studying such relationships you must understand that in real life there are
many outside factors that can influence the outcome of your intervention. For
example, during visits to your agency for counseling, your client may get a
better job. If some of the marital problems came about because of economic
hardship, and if the problem of money is now solved, it may be a factor in
reducing the marital problems. On the other hand, if a client loses his/her job,
the increase in the economic problems may either intensify or lessen the
marital problems; that is for some couples a perceived financial threat may
increase marital problems, whereas, for others, it may create more closeness
between partners. In some situations, an improvement in a marriage may have
very little to do with the counseling received, coming about almost entirely
because of a change in economic circumstances. Other events such as the birth
of a child to a couple or a couple’s independent self realization independently
arrived at may also affect the extent
and nature of marital problems. Figure 7.1 lists other possible factors under
the category of extraneous variables. This does not exhaust the list by any
means.
|
Type of
counseling service
|
Study
population
|
Extent of
marital problems
|
(Independent variable) (Dependent variable)
|
Extraneous variables
|
|
FIGURE 7.1
Factors affecting the relationship between a counseling service and the extent
of marital problems
Continuing the example of marriage
and counseling there are sets of factors that can affect the relationship
between counseling and marriage problems, and each is a defined category of
variables:
1
Counselling per se.
2
All the factors other than counseling that affect the
marital problems.
3
The outcome that is the change or otherwise in the
extent of the marital problems.
4
Sometimes, the variation in response to questions about
marital problems can be accounted for by the mood of respondents or ambiguity
in the questions. Some respondents may
either overestimate or underestimate their marital problems because of
their state of mind at the time. Or some respondents, in spite of being in
exactly the same situation, may respond to non specific or ambiguous questions
differently according to how they interpret the question.
As
already explained in Chapter 5, any variable that is responsible for bringing
about a change is called an independent variable. In this example, the
counseling is an independent variable. When you study a cause and effect
relationship, usually you study the impact of only one independent variable.
Occasionally you may study the impact of two independent variables, or (very
rarely) more than two, but these study designs are more complex.
For this example counseling was the
assumed cause of change in the extent of marital problems; hence, the extent of
marital problems is the dependent variable, as the change in the degree of marital problems was dependent upon
counseling.
All other factors that affect the
relationship between marital problems and counseling are called extraneous
variables. In the social sciences, extraneous variables operate in very
study and cannot be eliminated. However,
the can be controlled to some extent. (Some of the methods for controlling them
are described later in this chapter.) Nevertheless, it is possible to find out
the impact attributable to extraneous variables. This is done with the
introduction of a control group in
the study design. The sole function of a control group is to quantify the
impact of extraneous variables on the dependent variable (s)
Changes
in the dependent variable, because of the respondent’s state of mood or
ambiguity in the research instrument, are called random variables or chance
variables. The error thus introduced is called the chance or random error, In
most cases the net effect of chance variables is considered to be negligible as
respondents who over report tend to cancel out those who underreport. The same applies
to responses to ambiguous questions in a research instrument.
Hence in any causal relationship, changes
in the dependent variable may be attributed to three types of variable:
|
Change in the
dependent variable
|
Change because
of the independent variable
|
Change because
of extraneous variables
|
Change because
of chance
|
Let us take another example,
Suppose you want to study the impact of want to study the impact of different teaching
models on the level of comprehension of students for which you adopt a
comparative study design. In this study, the change in the level of
comprehension, in addition to the teaching models, can be attributed to a
number of other factors, some of which are shown in figure 7.2:
[change in level of comprehension] =
[change attributable to the
teaching model]+
[change attributable to extraneous variables]+
[change attriabuble to chance
variables]
In
fact, in any study that attempts to establish a causal relationship, you will
discover that there are three sets of variables operating to bring about a
change in the dependent variable. This can be expressed as an equation:
[change in the outcome variable]=
[change because of the chance
variable]+
[change because of extraneous
variables]+
[change because of chance or random variables]
Or
in other words:
[change
in the dependent variable]=
[change attributable to the independent
variable]+
[change attributable to extraneous
variables]+
[change attributable to chance
variables]
|
Study population
|
Teaching model
|
Study population
|
|
Group A
|
Model I
|
Group B
Model I
|
|
Group B
|
Model II
|
Group C
Model II
|
|
Group C
|
Model III
|
Group A
Model III
|
|
Level of Comprehension
|
|
Level of
comprehension
|
|
·
Motivation of the students
·
Competence of the teacher
·
Aspirations of the students
·
Reasons for studying
·
Attitude towards the subject
·
Peer group influence
·
Parental influence, etc.
|
FIGURE 7.2 The relationship between teaching models and
comprehension
Or in technical
terms:
[total variance] =
[variance attributable to the
independent variable ]+
[variance attributable to extraneous
variables]+
[random or chance variance ]
It can also be expressed
graphically (Figure 7. 3).
As the total change measures the
combined effect of all three components it is difficult to isolate the
individual impact of each of them (see Figure 7.3). Since your aim as a
researcher is to determine the change that can be attributed to the independent
variable, you need to design your to ensure that the independent variable has
the maximum opportunity to have its full effect on the dependent variable,
while the effects that are attributed to extraneous and chance variables are
minimized (if possible) or quantified or eliminated. This is what kerlinger (1986:286)
calls the maxmincon principle of
variance.
One of the most important questions
is : how do we minimize the effect attributable to extraneous and chance
variables? The answer is that in most situations we cannot;
|
Change
attributable to independent variables
|
Change
attributable to extraneous variables
|
Chance var.
|
_____________________________Total change_____________________________________
OR
|
Change
attributable to independent variables
|
Change
attributable
to extraneous variables
|
Chance var.
|
______________________________Total
change____________________________________
FIGURE 7.3 The proportion attributable to the three
components may vary markedly
However, it can
be quantified. The sole purpose of having a control group, as mentioned
earlier, is to measure the change that is a result of extraneous variables. The
effect of chance variables is often
assumed to be none or negligible. As discussed, chance variation comes primarily
from two sources: respondents and the
research instrument. It is assumed that if some respondents affect the
dependent variable positively, others will affect it negatively. For example,
if some respondents are extremely positive in their attitude towards an issue,
being very liberal or liberal or
positively biased, are bound to be others who are extremely negative (being
very conservative or negatively biased). Hence, they tend to cancel each other
out so the net effect is assumed to be zero. However, if in a study population
most individuals are either negatively or positively biased, a systematic error
in the findings will be introduced. Similarly, if a research instrument is not
reliable (i.e.it is not measuring correctly what it is supposed to measure), a systematic
bias may be introduced into the study.
In the physical sciences a
researcher can control extraneous variables as experiments are usually done in
a laboratory. By contrast, in the social sciences, the laboratory is society,
over which the researcher lacks control. Since no researcher has control over
extraneous variables, their effect, as mentioned, in most situations cannot be
minimized. The best option is to quantify their impact through the use of a
control group, though the introduction of a control group creates the problem
of ensuring that the extraneous variables have a similar effect on both control
and experimental groups. In some situations their impact can be eliminated
(this is possible only where one or two variables have a marked impact on the
dependent variable). There are two methods used to ensure that extraneous
variables have a similar effect on control and experimental groups and two
methods for eliminating extraneous variables:
|
Maternal health
Yes
No
|
Figure 7.4
Building into the design
1. Ensure
that extraneous variables have a similar impact on control and experimental
groups. It is assumed that if two groups are comparable, the extent to
which the extraneous variables will affect the dependent variable will be
similar in both groups. The following two methods ensure that the control and
experimental groups are comparable with one another:
(a) Randomisation
– Ensures that the two groups are comparable with respect to the variable
(s) It is assumed that if the groups are comparable, the extent to which
extraneous variables are going to affect the dependent variable is the same in
each group.
(b) Matching
– Another way of ensuring that the two groups are comparable so that the
effect of extraneous variables will be the same in both groups (discussed in
Chapter 8).
2 Eliminate extraneous variable (s)
Sometimes it is possible to eliminate the extraneous variable or to build it
into the study design. This is usually done when there is strong evidence that
the extraneous variable has a high correlation with the dependent variable, or
when you want to isolate the impact of the extraneous variable. There are two
methods used to achieve this:
(a) Build
the affecting variable into the design of the study To explain this concept
let us take an example. Suppose you want to study the impact of maternal health
services on the infant mortality of a population. It can be assumed that the
nutritional status of children also has a marked effect on infant mortality. To
study the impact of maternal health services per se, you adopt a two by two
factorial design as explained in Figure 7.4 In this way you can study the
impact of the extraneous variables separately and interactively with the independent
variable.
(b)
Eliminate the
variable To understand this, let us take another example. Suppose you want to
study the impact of a health education programme on the attitudes towards, and
beliefs about, the causation and treatment of a certain illness among
non-indigenous Australians and indigenous Australians living in a particular
community. As attitudes and beliefs vary markedly form culture to culture,
studying non-indigenous Australians and indigenous Australians as one group
will not provide an accurate picture. In such studies it is appropriate to
eliminate the cultural variation in the study population by selecting and
studying the populations separately or by constructing culture specific cohorts
at the time of analysis.
Summary
In this chapter
you have learnt about the functions of a research design. A research design serves
two important functions: to detail the procedures for undertaking a study; and
(2) to ensure that, in the case of causality, the independent variable has the
maximum opportunity to have its effect on the dependent variable while the
effect of extraneous and chance variables is minimized. In terms of the first
function, a research design should outline the logistical details of the whole
process of the research journey. You need to spell out in detail what type of
study design per se you are proposing to use and why, who are going to be your
respondents and how they will be selected, from how many you are proposing to
get the needed information how the information will be collected by you and how
are going to analyse the information. For each aspect you need to provide your
rationale and justification and as far as possible support them from the
literature reviewed.
Through the second function control
of variance when establishing association or causality, it ensures your supe,
visor and readers that you have set up your study in such a way that your
independent variable has the maximum chance of affecting the dependent variable
and that the effects of extraneous and
chance variables are minimized, quantified and/or controlled (the maxmincon
principle of variance).
A study without a control group
measures the total change (change attributable to independent variable +
extraneous variables + chance variables) in a phenomenon or situation. The
purpose of introducing a control group is to quantify the impact of extraneous
and chance variables.
The study design is a part of the
research design. It is the design of the study per se, whereas the research
design also includes other details related to the carrying out of the study.
For You to Think About
Ø
Refamiliarise yourself with the keywords listed
at the beginning of this chapter and if you are uncertain about the meaning or
application of any of them revisit these in the chapter before moving on.
Ø
What are the main functions of a research
design? Why is it important to have a research design before undertaking a
study?
Ø
Provide examples from your own area of study to
illustrate the main variables in terms of causality (you may find it useful to
refer back to Chapter 5).
Ø
Identify one or two examples from an area that
interests you to demonstrate how the maxmincon principle of variance can be
applied.
CHAPTER 8
Selecting a Study Design
In this chapter you will learn about:
·
The differences between quantitative and qualitative study designs
·
Common study designs in quantitative research
and when to use them
·
Common study design in qualitative research and
when to use them
·
The strengths and weaknesses of different study
designs
Keywords: action research, after only
design before and after study design blind studies case studies cohort studies
control studies cross sectional study design, double blind studies experimental
study design feminist research focus
studies, longitudinal studies, non experimental studies, panel studies
prospective study design, quasi experimental studies reflective journal,
retrospective studies, semi experimental studies, trend studies.
Differences between quantitative and
qualitative study designs
In
this chapter we will discuss some of the most commonly used study designs in
both quantitative and qualitative research. Overall, there are many more study
designs in quantitative research than in qualitative research. Quantitative
study are designs are specific, well structure, have been tested for their
validity and reliability, and can explicitly defined and recognized. Study
designs in qualitative research either do not have these attributes or have
them to a lesser degree. They are less specific and precise and do not have the
same structural depth.
Difference
in philosophical perspectives in each paradigm combined with the aims of a study,
to a large extent, determine the focus, approach and mode of enquiry which, in
turn, determine the structural aspects of a study design. The main focus in qualitative research is to
understand, explain explore, discover and clarify situations, feelings
perceptions, attitudes. Values, beliefs and experiences of a group of people .
The study designs are therefore often based on deductive rather than inductive
logic, are flexible and emergent in nature, and are often non linear and non
sequential in their operationalisation. The study designs mainly entail the selection of people from whom the
information through an open frame of enquiry is explored and gathered. The
parameters of the scope of a study, and information gathering methods and processes, are often flexible and
evolving; hence most qualitative designs are not as structured and sequential
as quantitative ones. On the other hand in quantitative research the
measurement and classification requirements of the information that is gathered demand that study designs are more
structured, rigid fixed and predetermined in their use to ensure accuracy in
measurement and classification.
In qualitative studies the distinction
between study designs and methods of data collection is far less clear.
Quantitative study designs have more clarity and distinction between designs
and methods of data collection. In qualitative research there is an overlap
between the two. Some designs are basically methods of data collection. For
example, in depth interviewing is a design as well as a method of data
collection and so are oral history and participant observation.
One of the most distinguishing features of
qualitative research is the adherence to the concept of respondent concordance whereby
you as a researcher make every effort to seek agreement of your respondents
with your interpretation, presentation of the situations, experiences, perceptions
and conclusions. In quantitative research respondent concordance does not
occupy an important place. Sometimes it is assumed to be achieved by
circulating or sharing the findings with those who participated in the study.
The power gap between the researcher and
the study population in qualitative research is far smaller than in
quantitative research because of the informality in structure and situation in
which data is collected.
In quantitative research enough detail about a study is provide for it to be
replicated for verification and reassurance. In qualitative research little
attention is paid to study designs or the other structural aspects of a study,
hence the replication of a study design becomes almost impossible. This leads
to the inability of the designs to produce findings that can be replicated. Findings through
quantitative study designs can be replicated and retested whereas this cannot
be easily done by using qualitative study designs.
Another difference in the designs in
qualitative and quantitative studies is the possibility of introducing researcher bias. Because of
flexibility and lack of control it is more difficult to check researcher bias
in qualitative studies.
Study designs in each paradigm are
appropriate for finding different things. Study designs in qualitative research
are more appropriate for exploring the variation and diversity in any aspect of
social life, whereas in quantitative research they are more suited to finding
out the extent of this variation and diversity. If your interest is in studying
values, beliefs understandings, perceptions, meanings etc qualitative study
designs are more appropriate as they provide immense flexibility. On the other
hand if your focus is to measure the magnitude of that variation, how many
people have a particular value belief etc? the quantitative designs are more
appropriate. For good quantitative research it is important that you combine
quantitative skills with qualitative ones when ascertaining the nature and
extent of diversity and variation in a phenomenon. In the author’s opinion ,
the qualitative quantitative qualitative approach to research is comprehensive
and worth consideration. This involves starting with qualitative methods to
determine the spread of diversity, using quantitative methods to quantify the spread
and then going back to qualitative to
explain the observed patterns. As already stated the author does not
recommended your locking yourself into either the qualitative or quantitative
paradigm and though you may have your preference it is the purpose that should
determine the choice between quantitative and qualitative study designs. If you
already know (from previous studies or
practice knowledge ) the nature of diversity in any area of
interest to you, knowledge about its
extent can be determined only by using
quantitative methods. In most case where you want to explore both you need to
use methods that fall in the domain of both paradigms.
Study designs in quantitative research
Some
of the commonly used designs in quantitative studies can be classified by
examining them from three different perspectives:
1
the number of contacts with the study population;
2
the reference period of the study;
3
the nature of the investigation.
Every
study design can be classified from each one of these perspectives. These
perspectives are arbitrary bases of classification; hence, the terminology used
to describe them is not universal. However, the names of the designs within
each classification base are universally used. Note that the designs within
each category are mutually excusive; that is, if a particular study is cross sectional in nature it cannot be at
the same time a before and after or a longitudinal
study, but it can be a
non-experimental or experimental study, as well as a retrospective study or a prospective study. See Figure 8.1.
Another section has been added to
the three sections listed above titled Others some commonly used study designs.
This section includes some commonly used designs which are based on a certain
philosophy or methodology, and which have acquired their own names.
Study designs based on the number of
contacts
Based
on the number of contacts with the study population, designs can be classified
into three groups:
1.
cross sectional studies:
2.
before and after studies;
3.
longitudinal studies.
|
Types of study design
|
|
Number of
contacts
|
Reference
period
|
Nature of the
investigation
|
|
One
|
Two
|
Three or more
|
Retrospective
|
Experimental
|
|
Cross sectional studies
|
Longitudinal studies
|
Prospective
|
Non-experimental
|
|
Before and after studies
|
Retrospective prospective
|
Semi experimental
|
FIGURE 8.1 Types
of study design
The cross sectional study design
Cross sectional
studies, also known as one shot or
status studies are the most commonly used design in the social sciences. This
design is best suited to studies aimed at finding out the prevalence of a
phenomenon, situation problem attitude or issue, by taking a cross section of
the population. They are useful in obtaining an overall picture as it stands at
the time of the study. They are designed
to study some phenomenon by taking a cross section it at one time (Babbie 1989:89). Such studies
are cross sectional with regard to both the study population and the time of
investigation.
A cross sectional study is extremely
simple in design. You decide what you want to find out about identify the study
population, select a sample (if you need to ) and contact your respondents to
find out the required information. For example, a cross sectional design would be
the most appropriate for a study of the following topics:
- The attitude of the study population
towards uranium mining in
- The socioeconomic demographic characteristics
of immigrants in
- The incidence of HIV positive cases in
- The reasons for homelessness among young people.
- The quality assurance of a service provide by an organization.
- The impact of unemployment on street crime ( this could also be a before and after study).
- The relationship between the home environment and the academic performance of a child at school.
- The attitude of the community towards equity issues.
- The extent of unemployment in a city.
- Consumer satisfaction with a product.
- The effectiveness of random breath testing in preventing road accidents (this could also be a before and after study).
- The health needs of a community.
- The attitudes of students towards the facilities available in their library.
As
these studies involve only one contact with the study population, they are
comparatively cheap to undertake and easy to analyse. However, their biggest
disadvantage is that they cannot measure change. To measure change it is necessary
to have at least two data collection points that is at least two cross
sectional studies. At two points in time on the same population.
The before and after study design
The
main advantage of the before and after design (also know as the pre test
design) is that it can measure change in a situation phenomenon issue problem
or attitude. It is the most appropriate design for measuring the impact or
effectiveness of a programme. A before and after design can be described as two
sets of cross sectional data collection points on the same population to find
out the change in the phenomenon or variable (s) between two points in time.
The change is measured by comparing the difference in the phenomenon or
variable (s) before and after the intervention (see Figure 8.2).
|
Study
population
|
Study
population
|
________Time____________
|
Before/pre-observation
(data
collection)
Actual or
recall
|
After/post-observation
(data
collection)
|
FIGURE
8.2 Before and after (pre-test/post test ) study design.
A before and after study is carried out by
adopting the same process as a cross sectional study except that it two cross
sectional data sets, the second being undertaken after a certain period. Depending
upon how it is set up, a before and after study may be either an experiment or
a non experiment. It is one the most commonly used designs in evaluation
studies. The difference between the two sets collection points with respect to
the dependent variable is considered to be the impact of the programme. The
following are examples of topics that can be studied using this design:
·
The impact of administrative restructuring on
the quality of services provided by an organization.
·
The effectiveness of a marriage counseling
service.
·
The impact of sex education on sexual behavior among schoolchildren.
·
The effect of a drug awareness programme on the
knowledge about, and of drugs among young people.
·
The impact of incentives on the productivity of
employees in an organization.
·
The impact of increased funding on the quality
of teaching in universities.
·
The impact of maternal and child health services
on the infant mortality rate.
·
The effect of random breath testing on road
accidents.
·
The effect of an advertisement on the sale of a
product.
The main advantage of before and after
design is its ability to measure change in a phenomenon or to assess the impact
of an intervention. However, there can be disadvantages which may not occur, individually
or collectively, in every study. The prevalence of a particular disadvantage (s)
is dependent upon the nature of the investigation, the study population and the
method of data collection. These disadvantages include the following:
- As two sets of data must be collected, involving two contacts with the study population, the study is more expensive and more difficult to implement. It also requires a longer time to complete particularly if you are using an experimental design, as you will need to wait until your intervention is completed before you collect the second set of data.
- In some cases the time lapse between the two contacts may result in attrition in the study population. It is possible that some of those who participated in the pre-test may move out of the area or withdraw from the experiment for the reasons.
- One of the main limitations of this design, in its simplest form is that as its measures total change, you cannot assertion whether independent or extraneous variables are responsible for producing change in the independent variable. Also, it is not possible to quantify the contribution of independent and extraneous variables separately.
- If the study of population is very young and if there is a significant time lapse between the before and after sets of data collection, changes in the study population may be because it is maturing. This is particularly true when you are studying young children. The effects of this maturation, if it is significantly correlated with the dependent variable, is reflected at the ‘after’ observation and is known as the maturation effect.
- Sometimes the instrument educates the respondents. This is known as the reactive effect of the instrument. For example, suppose you want ascertain the impact of a programme designed to create awareness of the drugs in a population. To do this, you design a questionnaire listing various drugs and asking respondents to indicate whether they have heard of them. At the pre-test stage a respondent, while answering questions that include the names of the various drugs, is being made aware of them, and this will be reflected in his/her responses at the post-test stage. Thus, the research instrument itself has educated the study population and, hence, has affected the dependent variable. Another example of this effect is a study designed to measure the impact of a family planning education programme on respondents’ awareness of contraceptive methods. Most studies designed to measure the impact of programme on participants’ awareness face the difficulty that a change in the level of awareness to some extent, may be because of this reactive effect.
- Another disadvantage that may occur when you use a research instrument twice to gauge the attitude of a population toward an issue is a possible shift in attitude between the two points of data collection. Sometimes people who place themselves at the extreme positions of a measurement scale at the pre-test stage (see Fig 8.3) they might feel that they have been too negative or too positive at the pre-test stage. Therefore, the mere expression of an attitude in response to a questionnaire or interview has caused them to think about and alter-their attitude at the time of the post test. This type of effect is known as the regression effect.
The Longitudinal Study design
The
before and after study design is appropriate for measuring the extent of change
in a phenomenon, situation, problem, attitude and so on, but is less helpful
for the studying the pattern of change. To determine the pattern of change in
relation to the time, a longitudinal design is used; for example, when you wish
to study the proportion of people adopting a program over a period, longitudinal
studies are also useful when you need to collect factual information on a
continuing basis. You may want to ascertain the trends in the demand for
labour, immigration, changes in the incidence of a disease or in the morality,
morbidity and fertility patterns of a population.
In longitudinal studies the study population
is visited a number of times at regular intervals, usually over a long period,
to collect the required information (see Fig 8.4). These intervals are not
fixed so their length may vary from study to study. Intervals might be as short
as a week or longer than a year. Irrespective
of the size of the interval, the type of information gathered each time is
identical. Although the data collected
is from the same study population, it may or may not be from the same
respondents. A longitudinal study can
be seen as a series of respective cross sectional studies.
Longitudinal
studies have many of the same disadvantages as before-and-after studies, in
some instances to an even greater degree.
In addition, longitudinal studies can suffer from the conditioning effect. This describes a situation where, if the
same respondents are contacted frequently, they begin to know what is expected
of them and may respond to questions with-out thought, or they may lose interest
in the enquiry, with the same result.
The main
advantage of a longitudinal study is that it allows the researcher to measure
the pattern of change and obtain factual information, requiring collection on a
regular or continuing basis thus enhancing its accuracy.
Study designs based on the reference period
The reference
period refers to the time-frame, in which a study is exploring a phenomenon,
situation, event or problem. Studies
are categorized from this perspective as:
·
Retrospective;
·
Prospective;
·
Retrospective – prospective.
The retrospective study design
Retrospective
studies investigate a phenomenon, situation, problem or issue that has happened
in the past. They are usually conducted
wither on the basis of the data available for that period or on the basis of
respondents’ recall of the situation (Figure 8.5a). for example, studies conducted on the
following topics are classified as retrospective studies:
·
The living conditions of Aboriginal and Torres
Strait Islander peoples in Australia
in the early twentieth century.
·
The utilization of land before the Second World
War in Western Australia
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