Surgical Nursing lecture notes

Research methods
Lecturer: Isaac Amankwaa
Course Objectives
 By the end of the course the student
will:
 Define research
 Describe various types of research
 Describe the research process
 Carry out a simple research

Course outline
 Definition
 Types of research
 Identifying research problem
 Objectives of the research
 Statement of hypothesis
 Operational definition
 Literature review
 Methodology
 Research setting and population
 Sampling method
 Data collection, tools/methods, limitations
 Dissemination of research report

What is Research?
Research means
“ to search again or
carefully examine”
(Langford 2001)


Research defined
 Research is systematic inquiry that uses
disciplined methods to answer questions or
solve problems.
(Polit and Beck, 2010).
Characteristics of nursing research
 It demands a clear statement of the problem
 It requires a plan, order and control
 It builds on existing data
 Based on theory of empiricism
 Generalisation


Purpose of conducting research
 Description
 Exploration
 Explanation
 Prediction
Types of research
1. Basic
2. Applied research.
Basic research
 Also called Fundamental or pure research
 Studies are designed to seek knowledge
without specifying application of the
knowledge
 Ex: examining x‟tics of a cell.
Applied research
 Concerned with using knowledge to solve
immediate problems facing an organization.
 Ex. Using ® to solve patient care difficulties,
educational concerns and administrative issues.
 The nurse investigator contribute to some
modification of the present practices

Quantitative Research
 Originated in the natural sciences such as
biology, chemistry, physics, geology
 This is ® that is concerned with investigating
things which we could observe and measure in
some way.

Qualitative research
 Origin: social sciences like psychology &
nursing.
 Involves study of human behaviour & the
social world inhabited by human beings;
 Answers the “why” and “how” questions.
Definition of nursing research
 Nursing research is the systematic inquiry
designed to develop knowledge about issues of
importance to the nursing profession, including
nursing practice, education, administration, and
informatics.

(Polit and Beck, 2010)
Importance of Nursing Research
1. To promote evidence-based nursing practice:
nursing care must be based on accurate
knowledge.
2. To ensure credibility of the nursing
profession
3. Provide accountability for nursing practice
4. Document the Cost Effectiveness of Nursing
Care:
Sources of nursing knowledge
 Tradition
 Authority
 Trial and error
 Logical reasoning: comprises inductive
and deductive reasoning
 Scientific research
The research process
1. Review of existing literature
2. Research questions
3. Method
4. Analysis
5. Presenting our findings


Chapter Two
Selecting a Research Topic
Chapter objectives
• Enumerate the sources of nursing
research problems
• List the various steps required to
select a research topic
• Describe the criteria for prioritising a
research problem
• Select their own research topic that
is relevant to nursing

Introduction
What is a problem?
A situation that lends itself to
be addressed through
application of the research
process
Sources of research problem
 Experience from clinical practice
 Nursing literature
 Ideas from external sources
 colleagues
Procedure for identifying research
problem
 Select a broad topic of interest
 Refine/narrow down
 Evaluate significance of topic

Identifying research problem
 Select broad topic area
 Write down general area of interest
 E.g. cancer patients in pain
Selecting Research Problem
 Refine/narrow down the topic
 Ask questions
 Review literature
 Talk to people
Is your topic significant?
 A research topic must meet the following
conditions
1. The should be perceived difference betweenwhat
exist and the ideal or planned situation
2. The reason(s) for the difference shd be unclear
3. There should be more than one possible answer
to the question or solution to the problem.

Prioritising Research: Criteria
1. Significance of the problem:
 Is the problem an important one?
 Will patients, nurses etc. benefit from the
evidence that will be produced?
 Will the results lead to practical
applications?
 Will the study help to alter nursing
practices or policies?

Prioritising Research: Criteria
2. Researchability of the problem
 Not all problems are amenable to a
research through a scientific study
 Example include problems that relate to
moral or ethical nature
 Ex. Observing how often couples use
condoms during sexual intercourse

Prioritising Research: Criteria
3. Feasibility
 Time and Timing
 Availability of study participants
 Cooperation of others (e.g. seeking the consent
of parents if children)
 Interest to the researcher
 Avoidance of duplication
 Applicability of possible research findings
 Ethical acceptability


Characteristics of a good
research topic
1. Interesting
2. Researchable
3. Significant
4. Manageable
5. Ethical
Chapter Three
Analysing & Stating Research
Problem
Learning objectives
 Use the problem analysis diagram to analysis a
research problem
 Describe the importance of a clear statement of a
problem
 Enumerate the points that should be included in
the statement of a problem
 Analyse and state their own research problem

Introduction



Adequately analysing the
problem will help you include
all possible contributory factors
from different sectors
Analysing the problem
 Analysis focus on:
 Factors that may have contributed to the
problem
 The relationship between the problem and
the contributing factors
Analysing the problem
 Contributing factors grouped into:
 Service- related factors: e.g. distance to
clinic
 Disease related factors e.g. seriousness of
patient‟s condition
 Socio- cultural factors e.g. occupation &
marital status
Analysing the problem
 STEPS IN PROBLEM ANALYSIS
 Identify and write down the core problem
 Identify possible contributing factors
 Determine relationship between the problem
and the contributing factors
 Regroup the contributing factors into broad
categories where appropriate
 Decide on the focus and scope of the research




Stating the Research Problem
Problem statement is an expression of
the dilemma or disturbing situation that
needs investigation.
Stating the Research Problem
 It has six components:
1. Problem identification: what is wrong with the current
situation?
2. Background: what is the nature of the problem, the
context of the situation that readers need to understand?
3. Scope of the problem: how big a problem is it; how
many people are affected?
4. Consequences of the problem: what is the cost of not
fixing of not fixing the problem?
5. Knowledge gaps: what information about the problem is
lacking?
6. Proposed solution: what is the basis that the proposed
study would contribute to the solution of the problem?

CHAPTER FOUR
Study Purpose, Aim or Objectives
 At the end of the lesson, students
should be able to
 Explain the relationship between the
terms: purpose, aims and objective
 Differentiate between general and specific
objectives
 Formulate specific objectives


Study purpose, aims and objectives are
synonymous terms and are therefore
used interchangeably
Study purpose, aims &
Objective
 Assumed to mean the same thing
 It answers the question „ what does the
researcher wish to achieve?‟
 It is the overall impact of the study
Statement of objectives
 Research objectives are the steps you are going
to take to answer your research questions or
 a specific list of tasks needed to accomplish the
goals of the project.
 While aims are broad in nature, objectives
are focused and practical.
Statement of objectives
 Define the focus of your study
 Clearly identify variables to be measured
 Indicate the various steps to be involved
 Establish the limits of the study
 Avoid collection of any data that is not strictly
necessary
General Objectives
 These are normally the aims/goals of
the study,
 Are broad statements of what is to be
achieved by the study.
 That is, what is the purpose of
research?

Specific Objectives
 These are measurable statements on the
specific questions to be answered.
 They are more specific and are related to the
problem situation
 Refer to example 4.1 in lecture notes
How to state the objectives
 Research objectives should:
 cover different aspects of the problem and its
contributing factors
 be clearly expressed in measurable terms
 be realistic considering local conditions
 meet the purpose of the study
 use action verbs that are specific enough to be
measured

Characteristics of Objectives
(SMART)

Specific

be precise about what you are going to do

Measurable

you will know when you have reached your goal


Achievable

don‟t attempt too much.
Realistic

do you have the necessary resources to achieve
the objective?

Time
Constraint

determine when each stage needs to be
completed.
Examples of strong verbs for
objectives
 To determine
 To compare
 To verify
 To describe
 To establish
 To produce
 To revise



 To find out
 To collect
 To construct
 To classify
 To develop
 To devise
 To measure
 To select
 To synthesise

Avoid the use of weak, vague non-
action verbs such as:
 To appreciate,
 To consider,
 To enquire,
 To learn,
 To know,
 To understand,
 be aware of
 to listen,
 to perceive

Chapter Five
Research Questions, Hypothesis &
Variables
 At the end of this lesson, the student
should be able to:
 Explain the need for developing a research
question and hypothesis
 Formulate research questions and hypothesis.
 Differentiate between dependent & independent
variables
 Explain the need for operationalizing variables
 State operational definition of variables

Introduction
 After deciding on your research topic,
the next thing to do is to state a
research question that will help focus
your research study.
 This will be followed by the making a
scientific guess as to the possible
outcome of the research study.
What is Research Question?
 This is a clear, focused, concise, complex
and arguable question around which you
centre your research.
 The question provides a path through the
research and writing process.
Characteristics of research questions
 Clear
 Focused
 Complex i.e., should not be answerable
with a simple “yes” or “no” or by easily-
found facts.
 Refer to examples 5.1 & 5.2
Research questions, rather than
hypothesis, are normally used in
qualitative research and in descriptive-
survey studies.
Variables-what you‟re measuring
 A variable is a characteristic that varies between
individuals and can be measured, such as weight,
age and gender.

 Refers to “Qualities, properties, or characteristics
of persons, things, or situations that change or
vary”

(Burns & Grove, 2007, p.125).

Examples of variables
 A person's age.
 This variable can take on different values,
such as, 20 years old, 30 years old, and so
on.
 Marital status
 single, married, divorced & widowed

 Other examples: height, weight, job
satisfaction
Types of variables
 Five main types
1. Dependent variable
2. Independent variable
3. Demographic variable
4. Descriptive variable
5. Extraneous variables

Dependent vs. Independent variables
 Nursing researchers may be interested in
answering the following questions
 Does a nursing intervention cause
improvements in patient outcome?
 Does smoking cause lung cancer?
 The presumed cause is the independent
variable, and the presumed effect is the
dependent variable
Dependent vs. Independent variables

Independent variable Dependent variable


intervention, influence or
exposure
outcome

Activity-determine the variables
1. A researcher wants to know whether a
hospitalised child‟s anxiety level during painful
procedure would lessened if a parent were
present during the procedure.
2. You are interested in the effect of daily exercise
on glucose levels in adolescents with type I
diabetes
Activity-determine the variables
2. A researcher asked: What is the effect of heart
failure self-management education on a
patient‟s knowledge level and readmission rate
to the hospital?
3. For term, stable infants, is there a relationship*
between immediate skin-to-skin contact after
birth and exclusive breastfeeding at 2 months of
age?

Demographic variables
 These are attributes or characteristics of
the subjects in a study. Examples:
 Age
 Gender
 Diagnosis
 Socioeconomic information

Extraneous Variables
 Also called nuisance variables.
 Not usually of primary interest but are believed to be
related to the independent and/or dependent
variables.
 Their effects need to be controlled in order to obtain
meaningful results.
 Examples include:
 Transportation
 Literacy
 In doing a research, you need to identify and control
them if possible.

Hypothesis
 A hypothesis attempts to answer a
question which has emerged from a
research problem.
 They are scientifically reasonable
predictions that go further than a
research question and predict an
outcome.
Hypothesis
 A hypothesis states the relationship
between two or more variables that
suggest an answer to the research
question.
Simple VS. complex hypothesis
 Simple hypothesis
 expresses an expected relationship btn one
independent and one dependent variable.
 Complex hypothesis
 Expresses a relationship btn two (or more)
independent variables and/or two (or
more) dependent variables.

Directional vs. Non-directional Hypothesis
 Directional hypothesis: specifies not only
the existence but the expected direction of the
relationship between variables.
 Example
 The risk of falling increases with the age of
the patient.
 In the above example, there is an explicit
prediction that older patients are at
greater risk of falling than younger ones.

Directional vs. Non-directional Hypothesis
 Non-directional hypothesis: does not
stipulate the direction of the relationship.
 Example:
 There is a relationship between the age of a
patient and the risk of falling.
 This hypothesis do not stipulate whether the
researcher thinks that older patients or younger
ones are at greater risk.

Alternate VS. Null Hypothesis
 Alternative hypotheses (H
I
)
 This hypothesis normally suggests a relationship
and a potential outcome in a research study.
 can be directional or non-directional
 Example:
 Children with high IQ will exhibit more anxiety
than children with low IQ”-directional
 There is a difference in the anxiety level of the
children of high IQ and those of low IQ- non-
directional

Alternate VS. Null Hypothesis
 A null hypothesis (H
O
)
 is a statement that there is no actual relationship
between variables.
 predicts no difference between the groups of
events or observations under study.
 Example:
 There is no significant difference in the anxiety
level of children of High IQ and those of low IQ.
 There is no relationship between age of
adolescents and occurrence of unwanted
pregnancy.

 Refer to examples in the handout
Chapter 5
Literature Review
Learning objective
 After reading this chapter, student should be
able to:
 Describe the reasons for reviewing available
literature
 Describe the literature resources that are available
for carrying out review
 Systematically review a literature on a given topic

Introduction
 A literature review
 summarises, interprets, and critically
evaluates existing "literature"
 establish current knowledge of a subject
 establish what knowledge and ideas have
been established on a specific topic
Purpose of literature review
 Refer to lecture notes

Types of literature
 Primary literature e.g. articles published in
reputable journals.
 Secondary literature e.g. textbooks and
review articles.
 Grey literature e.g. government reports,
conference proceedings and theses.
 Web sites : sites other than those associated
with mainstream academic literature.
Steps in the review of literature
 Initial search
 a cursory examination of available publication
 Secondary search
 in-depth & critical evaluation of publications
 Involves:
 Electronic searching
 Manual searching
Steps in the review of literature
 Electronic searching
 Databases contain large quantities of information
 Examples of databases:
 Cochrane library
 Web of science
 Google scholar
 CINAHL
 PubMed/Medline
Steps in the review of literature
 Manual Searching
 not all journals are available on databases;
important information may be missed.
 Ideal to combine manual and computerised
search. This include:
 Hand searching journals
 Searching reference list
 Author searching
Keeping Record
 A systematic method for recording important
information and the search strategy:
 prevent duplicating effort by doing the same
search twice
 missing out a significant and relevant sector of
literature
 Information such as author‟s name, date of
publication, title of article and name of journal or
book can be entered on a separate card
Writing the review
 Final task: organise and report the
material covered
 Outline
 an introduction,
 a body,
 a conclusion

Writing the review
 Your review should:
 well-organized and critical summary of current state
of knowledge
 Studies with comparable findings often can be
summarised together.
 in your own words.
 point out both consistencies and contradictions in
the literature as well as offer possible explanations
for the inconsistencies.
CHAPTER SEVEN
Research Methods
 Learning objective
 After completing this chapter, the student
should be able to:
 Differentiate between quantitative and qualitative
research methods
 Describe and understand the various components
of the methods section in a research proposal
 Explain the cyclical nature of the different steps in
designing the methodology

Introduction
 Not all research methods can be used to answer
every research questions
 E.g.
 a nurse interested in the accuracy of
thermometers in assessing fever will use a
quantitative
 a nurse interested in the experience of fever from
the patient’s perspective will use a qualitative
approach
Definitions
 Research Methodology is the science of studying
how research is done scientifically.
 Research methods are generalized and established
ways of approaching research questions (e.g.,
qualitative vs. quantitative methods).
 Research Design involves determining how a chosen
method (qualitative or quantitative) will be applied to
answer your research question.
 Includes methodology, sample selection, data collection
process, instruments

Quantitative Research Design
 Based on the measurement of
quantity or amount.
 Results can be:
 a number or a set of numbers
 presented in tables and graphs.

Types of quantitative research
 Two main types
 Interventional (experimental) research
 Non-interventional (non-experimental)
research
Types of quantitative research
1. Interventional (experimental) research
 The researcher manipulates objects
 He then measures the outcome of his
manipulation.
 Two main types:
 experimental and quasi-experimental studies.
Types of quantitative research
 Non-interventional (non-experimental)
research:
 the researcher just describes or
analyses variables without intervening
in anyway.
 The main types are
 correlational studies and descriptive
studies.

Interventional Research: Experimental
 The researcher provides a specific
treatment to one group and withholds it
from the other.
 He then determines how both groups
scored on an outcome.
Interventional Research: Experimental
 Characteristics of experimental design
 Manipulation: involves doing something to study
participants.
 Control: the experimenter introduces controls
over the experimental situation, including the use
of a control group
 Randomization: the experimenter assigns
subjects to a control or experimental group on a
random basis.

Interventional Research
Quasi-experimental
 Undertaken when randomization not possible.
 The design introduces some form of treatment or
manipulation but does not utilize
randomization or control group.
 Quasi-experimental therefore lack either
randomisation or a control group

Non-interventional research
 Non-interventional research
 Generally present-oriented.
 describe what exist.
 variables are not deliberately
manipulated,
 the setting controlled
Non-interventional research
 Examples
1. Explorative studies:
 explores new phenomena to enhance the
researcher‟s understanding.
 normally of short duration and carried out on
small scale.

Non-interventional research
 Examples
2. Descriptive studies
 description of phenomena in real life situation.
 It is designed to provide an accurate account of
characteristics of particular individuals,
situations or groups.
 It answers the question: „what is?‟ e.g. „what
factors influence mother-infant bonding?‟
Non-interventional research
 Examples
4. Correlational studies
 investigates relationship btnx or among
variables.
5. Surveys
 provides a quantitative description of
trends, attitudes, or opinions of a population
by studying a sample of that population.
 It can either be cross-sectional or
longitudinal.

Qualitative research design
 Quali ® is a way of looking at the world from
the point of view of people.
 It enquires about what people feel, think,
understand and believe.
 It is more concern with describing and
understanding human experiences from the
point of view of the people who have had, or
are having, the experience.
Qualitative research
 E.g. a patients who are experiencing chronic
pain.
 Quantitative research would be concerned
with the level of pain patient experience
that these people were experiencing, and
 Qualitative research would be concerned
with what it means to be living with
chronic pain.
Examples of qualitative ®
 Grounded theory,
 action research,
 historical,
 ethnographic,
 philosophical and
 phenomenological

Selecting a research method
Refer to section 7.6
CHAPTER EIGHT
Data Collection
 Learning objective
 After completing this chapter, the student
should be able to:
 Define key terms used in data collection
 Mention the data collection techniques and tools
 Differentiate between data collection techniques
and tools
 Mention the characteristics of a good interview
 Design and administer a questionnaire for a simple
study

Definition and types of data
 Data
 pieces of information obtained in a
study
 It can exist as:
 Numeric values Quantitative
 Narrative descriptions Qualitative

Types of data
 Primary data
 collected afresh & for the first time
 original in character.
 Secondary data
 data collected by someone else & already
been passed through the statistical
process.

Data Collection Techniques
 Data are collected using the ff means:
 Interviewing
 Administering questionnaire
 Observing participants
 using existing data
 using focus group discussions
 Historical data and records

Data collection tools
 These are the recording forms. consists
of :
 observation schedule
 interview guide,
 interview schedule,
 questionnaire,
 rating scale,
 check list etc.,

Data collection technique Data collection tool
Using existing data Checklist, data collection
forms
Observing Eyes and other senses, pen
and paper, watch, scales etc
Interviewing Interview schedule,
questionnaire, tape reorder
Administering written
questionnaire
questionnaire
Interview
 Definition
 it is a data-collection technique that
involves oral questioning
 it is a two way systematic conversation
between an investigator and an informant
Interview: characteristics
1. Interviewer and respondent are strangers; proper
introduction needed.
2. The relationship btnx participants and interviewer
must have a fixed beginning and termination points.
3. Interview is conversation with a specific purpose
4. Interview needs not to be face-to-face only
5. Although interview is usually a conversation
between two persons, it need not be limited to a
single respondent.
Advantages of interviews
 improves the percentage of responses & quality of
information received than other method
 supplemental information like economic level, living
conditions etc. can be gathered
 The accuracy and dependability of the answers given
by the respondent can be checked by observation
and probing.
 Interview is flexible and adaptable to individual
situations.
Disadvantages of interviews
1. Results are often adversely affected by interviewer's
mode of asking questions & interactions
2. Certain types of personal and financial information
may be refused in face-to-face interview
3. Interview poses the problem of recording
information obtained from the respondents
4. Lack of training for the person who conduct
interview.
5. Interview is costly both in terms of money and
time.

Types of interview
1. Structured or directive interview
 same questions put to all the respondents and in
the same order.
 Each question is asked in the same way in each
interview.
2. Unstructured or non-directive interview
 Respondent encouraged to talk freely about a
given topic with a minimum of prompting or
guidance.

Interview process
1. Preparation e.g.Prepare interview schedule
2. Researcher properly introduces self
3. Establish rapport with respondent
4. Carrying the interview forward by asking
questions
5. Recording the interview
6. Closing the interview
Questionnaire
 Definition
 Consist of a number of questions printed or
typed in a definite order on a form or set
of forms.
Advantages of questionnaire
 Questionnaires:
 are relatively simple to administer
 not to be a time-consuming
 are inexpensive.
 facilitate the collection of large amount of
data in a short period of time.
 can be relatively anonymous,
Disadvantages
 Questionnaire
 prevents personal contact with
respondents.
 does not allow respondents to qualify
ambiguous questions
 Poorly worded or direct questions might
arouse antagonism or inhibitions on the
part of respondents

Types of questionnaires
 Three basic types of questionnaire:
 closed-ended;
 open-ended;
 combination of both
Types of questionnaires
 Closed-ended questionnaires
 used to generate statistics in quantitative research.
 Questionnaires follow a set format
 Open-ended questionnaires
 Contain blank section for the respondent to write in
an answer.
 E.g. closed-ended questionnaires might be used to find
out how many people use a service, open-ended
questionnaires might be used to find out what people
think about a service.

Types of questionnaires
 Combination of both
 Combination of open-ended and close-ended
questions
 Many questionnaires begin with a series of
closed questions, with boxes to tick or scales to
rank, and then finish with a section of open-
questions for more detailed response.

 Refer to example of questionnaire
Designing effective questionnaire
 Questionnaire design go through:
 Planning
 Composing a draft questionnaire
 Sequencing questionnaire
 Formatting the questionnaire
 Piloting and revising the questionnaire
Designing effective questionnaire
 Planning
 make a list of research objectives/variables
 determine information required to achieve
objectives
 Make a list of all the questions that could go into
the questionnaire.
 The best way to do this is to turn the objectives to
questions.
 Review literature to identify tested questionnaires.
Designing effective questionnaire
 Composing a draft question; POINTS TO NOTE!.
 Avoid leading questions: questions should not be
worded in such a way that it lead the respondent
into an answer. E.g. “Wouldn‟t you say that…”,
“Isn‟t it fair to say…”
Designing effective questionnaire
 Composing a draft question; POINTS TO
NOTE!.
 Be specific. Avoid words like “regularly”,
“often”, or “locally” – as everyone‟s idea of
what is regular, often or local will be
different.



Designing effective questionnaire
 Composing a draft question; POINTS TO NOTE!
 Keep your questions short & simple as possible.
 Avoid multiple ideas or two questions in one will
confuse and be misunderstood
 E.g. How many cups of coffee or tea do you drink
in a day? To make the question simple, separate
the it into two:
 How many cups of coffee do you drink during a
typical day?
 How many cups of tea do you drink during a
typical day?



Designing effective questionnaire
 Composing a draft question; POINTS TO NOTE!
 Make sure question and answer options match.
 Example: Have you had pain in the last week?
 [ ] Never [ ] Seldom [ ] Often [ ] Very often
Solution
 Reword either question or answer to match.
 The questions should be: How often have you had
pain in the last week?
 [ ] Never [ ] Seldom [ ] Often [ ] Very Often




Designing effective questionnaire
 Composing a draft question; POINTS TO NOTE!
 Encourage the respondent to consider each possible
response to avoid the uncertainty of whether a missing
item may represent either an answer that does not
apply or an overlooked item.
 Example: Which one of the following do you think
increases a person‟s chance of having a heart attack
the most? (Check one.)
 [ ] Smoking [ ] Being overweight [ ] Stress
 See solution on next page




Designing effective questionnaire
 Composing a draft question; POINTS TO NOTE!
 Solution:
 Which of the following increases the chance of
having a heart attack?
 Smoking: [ ] Yes [ ] No [ ] Don‟t know
 Being overweight: [ ] Yes [ ] No [ ] Don‟t know
 Stress: [ ] Yes [ ] No [ ] Don‟t know




Designing effective questionnaire
 Composing a draft question; POINTS TO NOTE!
 Avoid branching as much as possible to avoid
confusing respondents.
 Example :( 1) Do you currently have a life insurance
policy? (Circle: Yes or No)
 If no, go to question 3.
 (2) How much is your annual life insurance
premium?



Designing effective questionnaire
 Composing a draft question; POINTS TO NOTE!
 Solution: If possible, write as one question.
 How much did you spend last year for life
insurance? (Write 0 if none).



Designing effective questionnaire
 Desensitise questions by using response
bands.
 Questions which ask women about their age
are best presented as a range of response
bands.
 Example
 instead of asking the respondent to write down
her age, you can give a range of ages such as
20-29, 30-39 etc.

Designing effective questionnaire
 Do not use jargon or specialist language
 Avoid questions which require participants to
perform calculations
 Avoid offensive questions or insensitive questions
which could cause embarrassment
 Avoid asking „difficult‟ questions, e.g. where the
respondent may struggle to answer (people hate
to look stupid by not knowing the „answer‟).
Sequencing of questionnaire
 Three major sections in a
questionnaire:
 The basic information sought
 The socio-demographic information useful
in obtaining the profile of the respondent
 The identification sections to be used by
the interviewer
Sequencing of questionnaire
 Points to consider
 Put the most important items in first half of
questionnaire.
 Don‟t start with awkward or embarrassing
questions – respondents may just give up.
 Start with easy and non-threatening
questions.
 Go from the general to the particular.

Sequencing of questionnaire
 Points to consider
 Go from factual to abstract questions.
 Go from closed to open questions.
 Leave demographic and personal questions
until last
 Arrange questions in logical order. Sudden
changes in subject confuse the respondent
and cause indecision.

Formatting the questionnaire
 Appearance of your questionnaire matters!
 The questionnaire should be clear and easy to
read.
 It should be easy for the interviewer to navigate
around.
 Provide adequate space for respondents to answer
open-ended questions.
Formatting the questionnaire
 Use clear headings and numbering if
appropriate.
 Questionnaire should be legible
 It is important not to split the question, or
question and response categories between two
pages.
 Questions must be numbered (1,2,etc) and sub-
sections clearly labelled (e.g. 1a, 1b, etc).
Piloting & revising the questionnaire
 Pre-testing
 administering questionnaire to a limited number of
potential respondents
 Helps identify potential problems
 Respondents should be informed that they are
being interviewed for a pilot study
How to administer the questionnaire
 ways of administering questionnaires:
 self-administered (sent by post, email,
or electronically online).
 Interview administered ( administered
by telephone, skype or face to face

Advantages of self-administered
questionnaires
1. Cheap and easy to administer
2. Preserve confidentiality
3. Can be completed at respondent‟s
convenience
4. Can be administered in a standard manner

Advantages of interview administered
questionnaires
 Allow participation by illiterate people.
 Allow clarification of ambiguity

Participant observation
 the researcher is involved in the
situation being measured;
 E.g., a nurse who would be washing
his or her hands, along with the other
staff.
 The nurse researcher might do this
„covertly‟ (secretly)- ethical concerns
Non-participant observation
 The researcher is not involved directly in the
practice being measured.
 Both participant and non-participant observation
can raise concerns about something called the
Hawthorne effect (or sometimes performance
bias).
 The Hawthorne effect is where the behaviour of
those being watched changes because they know
they are being watched.
Using existing data
 It is also possible to take existing data and
subject those data to analysis.
 E.g. use of existing hospital records.
 It would be a waste of time collecting new data
when existing data are available.
 An important and relatively new way of using
existing data is in the meta-analysis associated
with systematic reviews.
CHAPTER NINE
SAMPLING A POPULATION
 Learning objective
 After completing this chapter, the student should be able to:
 Define common concepts used in
sampling
 Explain the term „sampling‟
 Enumerate the steps involved in the
development of a sample design
 Describe the two main types of sampling
designs

Definitions
 Research setting
 The environment in which research is carried out.
 E.g. laboratory or a 'real' setting such as hospital
 A research population/Target population
 a large collection of individuals or objects that is the main
focus of a scientific query.
 Study Population
 This is the population from which the sample actually
was drawn.
 Subset of target population

Sampling
 Process of selecting a portion of the population
to represent the entire population.
 a subset of the entire population.
 must be representative
Reasons for Sampling
 Less costs
 Less field time
 More accuracy
 When it‟s impossible to study the
whole population

Steps involved in sample design
1. Define target population
2. Decide on the Sampling Unit e.g.
geographical area such as a village
3. Decide on the sampling frame (list of units
from which the sample is to be selected)
4. Determine the sample size.
5. Decide on sampling Procedure
Types of sampling design
 Two main types:
 Probability sampling
 Non-probability sampling
Probability (random) sampling

 Each member has an equal chance of
being selected.
 It ensures representativeness
 Types
1. Simple random,
2. Stratified random,
3. Cluster sampling
4. Systematic sampling.

Simple random sampling
 Individuals have an equal and
independent chance of being selected for
the sample.
 Used when the population is uniform or
has similar characteristics in all cases.
 Refer to examples in the handbook

Stratified sampling
 Applied to a population that is not homogeneous
 The population is divided into several sub-
populations that are individually more
homogeneous
 these sub populations are called “strata”
 A simple random sample is then taken from each
group.
 Example, dividing the population into males and
females and then doing a simple random sampling
of each strata
Cluster/multistage sampling
 Used for large-scale surveys, when the population
represents broad geographic areas or large numbers of
people.
 The process of sampling moves through stages until the
final sample has been selected.
 E.g. to sample all nursing students in the Ghana, you
would proceed as follows:
 Prepare a list of regions and draw a random sample.
 Prepare a list of nursing schools in those selected
regions and take a random sample of the schools.
 Then prepare a list of students from these schools
and make a random selection of a sample of
students.

Systematic sampling
 Involves the selection of every kth case from a list or
group, such as every 10th person on a patient list.
 Procedure;
1. Establish the desired sample size (n)
2. Determine the size of the population (N).
3. Calculate the sampling interval (K) = N/n
4. E.g. a sample of 200 from a population of 40,000,then
our sampling interval would be as follows
K=40,000/200 = 200
5. Every 200th element on the list would be sampled.
6. The first element should be selected randomly
7. If number 73 is selected from a table. The people
corresponding to numbers 73, 273, 473, 673, and so
forth would be sampled.

Non-probability (non-random)
 Each member does not have an equal chance of
being selected as a participant in the study.
 Units of the sample are chosen on the basis of
personal judgment or convenience.
 Other name: deliberate sampling, purposive
sampling and judgment sampling.
 Advantages
 ease of recruitment,
 easier monitoring and follow-up,
 higher response rates
Non-probability sampling
 Convenience sampling
 Researcher includes whoever happens to
be available or participants that are easiest
to obtain.
 It is also called “accidental” or
“haphazard” sampling.
 Example: distributing questionnaires to
nursing students in a class
 Disadvantage: available subjects might be
atypical of the population of interest

Snowball sampling
 also called network sampling or chain sampling
 Its a variant of convenience sampling.
 Researcher ask participants to suggest or refer
someone else who might be eligible
 Snowball samples are useful when certain people
are hard to contact, for example a person trying to
contact drug users might use a snowball sample

Purposive/Judgmental sampling
 Based on the belief that researchers‟
knowledge about the population can be
used to hand-pick sample members.
 subjects sampled may be:
 typical of the population or
 particularly knowledgeable about the
issues under study
Sampling
methods
Probability
sampling
Simple
random
Systematic

cluster stratified
Non-
probability
convenience
Snow
-balling
Purposive quota
Quota Sampling
 The researcher identifies population
strata and determines how many
participants are needed from each
stratum.
 Ensures the inclusion of representatives
from certain elements in the population.
 For example ensuring that all tribes are
represented in a study.
DATA PROCESSING
AND ANALYSIS
Isaac Amankwaa
157
 Key topics
 Data processing
 Tabulation of data
 Analysing quantitative data
 the student should be able to:
 Mention the processes involve in processing
research data
 Mention the importance of tabulating data
 Explain how quantitative data is analysed

Editing Data
 It is a process of examining the collected
raw data to detect errors and omissions
and to correct these when possible.
 It involves a careful scrutiny of the
completed questionnaires.

Editing Data
Purpose of editing
 For consistency between and among
responses.
 For completeness in response
 To better utilize questions answered out of
order.
 To facilitate the coding process.

Data Processing
 Types of Editing
 Field Editing
 Done on the same day as the interview to
catch technical omissions, check legibility
of handwriting, and clarify responses
 Office Editing
 Performed by a central office staff; often done
more rigorously than field editing
Coding of data
 It involves assigning of numbers to each
response of the question.
 Purpose
 to translate raw data into numerical data, which
may be counted and tabulated.
 E.g. the variable sex can be represented as:
 1 = Male
 2 = Female.
 Missing values can be entered as a code ‘9’
or ’99’ or ’999’ instead of entering it as blank.


Coding of data
 Pre-coding
 This is when codes are entered on the
questionnaires (or checklists) themselves.
 For each questionnaire a box is inserted in
the right margin of the page.
 These boxes should not be used by the
interviewer.
 They are only filled in afterwards during data
processing.
Summarizing (classification) of data
Data can be summarized using:
 Data master sheets;
 manual compilation or
 compilation by computer

Summarizing (classification) of data
Data Master Sheets
 All the answers from individual
respondents are entered by hand
onto the data master sheet.


Summarizing (classification) of data
Data Master Sheets
 In a study carried out by students of a nursing
school about the smoking habits of the
inhabitants of their town.
 The questionnaire had only 17 questions, of
which 9 were asked of everyone, 4 exclusively
to smokers and 4 exclusively to non-smokers.
 The data was processed by hand as seen in
the next slide
No Q1
Sex
Q2
Age
Q6
No.
of
Cig
Q7
Age
of
onset
Q 9
Tried to
Q 14
Cough > 2
weeks
Q
14
Coug
h
/chest
pain
reduce stop
Yrs
Cat
No
Cat
Yrs
Cat
yes No Yes No Yes No Yes N
o
1 M 18 10 12 1x √ √ √
2 M 35 30 20 NR 1x √ √
3 M 54 15 14 10x 3x √ √
Etc.
total 31 AV
35
Av
20
Av 20 26 4 +
1
NR
19 12 5 26 11 2
0
Summarizing (classification) of
data
Compilation by hand (without
using master sheets)
 Used for a small sample (e.g.< 30)
 This can be done by
 manual sorting
 tally counting

Summarizing (classification) of
data
Compilation by hand (contd)
 Manual Sorting (Procedure)
 Take one question at a time, for example, ‘use of
health facility’,
 Sort the questionnaires into different piles
representing the various responses to the question,
(e.g., hospital/ health centre/ traditional practitioners)
 then count the number in each pile

Summarizing (classification) of
data
Compilation by hand (contd)
 Tally counting (Procedure)
 One member of the compiling team reads out the
information while the other records it in the form
of a tally (e.g., /// representing 3 subjects, ////
representing 4 subjects who present a particular
answer).
 After tally counting, add the tallies and record the
number of subjects in each group.
Summarizing (classification) of
data
Compilation by hand (contd)
 After doing either manual or tally
counting, check the total number of
subjects/responses in each
question to make sure that there
has been no omission or double
count.
Computer Compilation
 The computer should not be used
 For small samples
 if data is mainly generated by open questions
(qualitative data)
 The larger the sample, the more beneficial in
general the use of a computer will be.

Computer Compilation
 Steps in Computer
 Choosing an appropriate computer program
(e.g. STATA, SPSS, ect)
 Data entry
 Verification or validation of the data
 Programming (if necessary)
 Computer outputs/prints

Computer Compilation-steps
1. Choosing an appropriate computer
program
 You need to identify an appropriate statistical
package
 Examples include Epi Info, SPSS, STATA, etc.
2. Data entry
 First develop a data entry format
 This is followed by coding of information on the
data collection instrument
 e.g., Male: M or 1, Female: F or 2
Computer Compilation-steps
3. Verification
 This is done to correct mistakes that occurred
during data entry
 E.g. of mistakes that can seen on a print out
included
 exceptionally long or short lines,
 blanks that should not be there,
 alphabetic codes where numbers are expected.
Computer Compilation-steps
4. Programming
 A certain amount of basic knowledge of
computer programming is needed to give the
appropriate commands.
Computer Compilation-steps
5. Computer outputs
 This involves printing the analysis
generated by the computer
 This is followed by a careful scrutiny
of the individual tables, graphs, and
statistical tests to ensure they make
sense
Classification of data
 This involves putting the collected data
into groups that have common features
 This helps convey a meaning to the
researcher.
 Classification is done in two ways:
1. Classification according to attributes.
2. Classification according to the class intervals

Classification according the
attributes
Data is classified on the basis of
common characteristics that can
be:
 Descriptive e.g. sex, marital status
 Numeral e.g. weight and height

Classification on the basis of
the interval
The numerical feature such as
income, age and weight can be
measured quantitatively classified
by way of intervals.

Tabulation of Data
 Tabulation is the process of
summarizing raw data and displaying
it in the form of statistical table for
further analysis
 This can be done manually (small
study) or by the use of computers
(large numbers)

Advantages of Tabulation
 It simplifies complex data.
 It facilitates comparison and summarisation.
 It facilitates computation.
 It presents facts in minimum possible space.
 Facilitates detection of errors and omissions
 Tabulated data are good for references and
they make it easier to present the information
in the form of graphs and diagrams.

Basic Principles of Tabulation
1. Tables should be clear, concise & adequately titled.
2. Every table should be distinctly numbered for easy
reference.
3. Column headings & row headings of the table should
be clear & brief.
4. Units of measurement should be specified at
appropriate places.
5. Explanatory footnotes concerning the table should be
placed at appropriate places.
6. Source of information of data should be clearly
indicated.
7. Abbreviations should be avoided.

Analyzing Quantitative Data
 Quantitative studies normally produce
numbers
 In quantitative study, data that describe both
the characteristics of the participants and
the findings of the study.
 This can be presented in two main ways:
 Descriptive analysis
 Inferential analysis
Descriptive Analysis
 Descriptive analysis describes the main
characteristics of a collection of data.
 Four main areas of descriptive statistics
are:
 Frequencies
 Averages
 Charts
 Variability

Descriptive Analysis
 Frequency counts
 An enumeration of how often a certain
measurement or a certain answer to a specific
question occurs.
 Example, asking 100 nurses working in SDA
hospital whether they had experienced any back
pain in the past six months. Responses to be
given include:
 Severe,
 Minor and
 None.
 The number of responses to each of the
possible answers can be presented as
follows:

Possible
answer
Frequency of answer
severe 7 respondents answered YES
minor 45 respondents answered YES
none 48 respondents answered YES
Diagnosis Frequency %
Arrested hydrocephally 1 4.2
Brain trauma 3 12.5
Brain damage 2 8.3
Brain damage (RTA) 1 4.2
Cerebral palsy 1 4.2
Chicken pox encephalitis 1 4.2
Congenital abnormality 1 4.2
Down’s syndrome 6 25.0
Dysgenic features 1 4.2
Microcephaly 2 8.3
Multiple handicap birth 1 4.2
Not recorded 1 4.2
William’s syndrome 3 12.5
total 24 100.0
FREQUENCIES OF TYPES OF LEARNING DISABILITIES
Descriptive Analysis
 Percentages
 Allow us to quickly summarize and put
some meaning behind our findings.
 In percentage terms, 25 per cent of our
sample has been diagnosed with Down’s
syndrome.
Averages/ Measures of Central
Tendencies
 It give the reader a good idea of some
of the central, or average, values of a
set of data.
 The three types of averages are
 Mean
 mode
 median
E.g. a nurse consultant interested in how
long patients are seen at the OPD
Possible answer Frequency of
answer
10 minutes 3 patients
20 minutes 1 patient
30 minutes
40 minutes
50 minutes
60 minutes 1 patient
Charts: visual presentation of
data
 Variables can be represented as charts.
 Examples of charts are the bar chart, the
histogram and the pie chart.
 These charts help present data graphically.
 Bar charts and pie charts tend to be used for
categorical-type data, and histograms tend
to be used for continuous-type data.

Bar chart








Mainly used for categorical-type data
Frequencies
of variables
appear here
Variables
appear here
Pie Chart
 This is a circular chart divided into segments,
illustrating the different frequencies,
proportional to the size of the frequency to all
the other frequencies.

Discussing your Research
Finding
 Key topics
 Interpreting the findings
 Contextualising the findings
 Evaluating the study and making
recommendations
 After reading this topic, the student must be able
to:
 offer a good interpretation of research results
 discuss research findings in relation to existing
literature
 make recommendations based on study findings

Introduction
 This is the most difficult part of the
research process. It involves:
 interpreting your results and what they
mean
 Looking for opportunities to point out the
importance of your findings
 Pointing out the issues that arose out of
your study
Introduction
Discussion therefore involves
 interpreting the findings,
 contextualising the findings and the
study in relation to the literature,
 evaluating the study and making
recommendations.
Interpretation of Results
 Provide a brief summary of the findings
 do not repeat the statistics nor
 repeat verbatim quotes in the results section
and
 do not come up with new findings not already
covered in the results.
 Explain why certain trends were obtained.
Contextualising the findings and the
study in relation to the literature
 Clearly define whether the data confirm your
hypotheses (quantitative study) or whether a new
theory has been generated (qualitative studies).
 If a hypothesis was not supported by the data,
are there any alternative ideas for further re-
search and further hypotheses?
 Could any anomalous findings in a quantitative
study lead to an exploratory qualitative study to
try to explain such anomalies?
Contextualising the findings and the
study in relation to the literature
 It is essential that you provide
suggestions for future studies in the
area
 Provide proposals for more effective
designs and alternative methods of
analysis.
 Mention the limitations.

Evaluating the study and making
recommendations
 Summarise the general strengths and
limitations of the study so you can make
clearer to the reader the main points you are
trying to convey.
 Provide recommendations that might apply to:
 developments in policy,
 changes to nursing practices
 future recommendations for researchers to further
study in this area.
 Finally there should be one or two sentences
that summarise your overall findings and main
conclusion.

Reporting/Disseminating Research
Finding
 Findings of research must be communicated
especially if they have the potential to
impact nursing practice and patient care.
 Common forums for communication of study
findings include
 publication in various nursing journals,
 oral and
 poster presentations at professional
meetings/conferences, and/or in the workplace.
Research Reports
 A research report should have the ff sections:
An abstract or summary
An introduction
Methodology or method
Results/findings
Discussion