This document discusses key concepts related to research including definitions, types, variables, hypothesis, research design, sampling techniques, and literature review. Some key points: - Research is defined as a systematic, exhaustive, and methodical process of investigation aimed at discovery and interpretation of facts. - The main types of research are basic, applied, quantitative, qualitative, descriptive, experimental, and historical. - Variables can be independent, dependent, or intervening. Hypotheses can be simple or complex, null or alternative, directional or non-directional, associative or causal. - Research design may be experimental, quasi-experimental, or non-experimental. Sampling can use probability or non

1. Research
NMRN
Akinlose Dorcas

2. Definition
• Best (1970) defines it as a formal, systematic and intensive process of carrying out a
scientific method of analysis for the purpose of discovery and development of an organized
body of knowledge
• Too much grammar right?
• It is systematic
• Diligent
• Exhaustive (you can relate right?)
• Aim is for discovery (of facts, laws, theories, review, solve issues)
• Also to develop the body of knowledge

3. Nursing Research/purpose
• It’s all in the definition.
• Systematic investigation of phenomena (events or circumstances) related to
improving nursing care, to answer questions, find solution to specific nursing
problems and provide better care for patients save time, money and improve
skills.
• Nursing research helps to develop areas of knowledge that is uniquely
nursing (health problem, human behaviours and relationship between health
and illness state).

4. Functions/ purpose of research
 diffuse knowledge and expand its horizon
 verify or disprove, confirm or reject, or modify and re-assert existing theories
 to establish new facts.
 find answers to problems and provides new insight regarding their nature.
 explore and explain phenomena.
 predict phenomena/future circumstances.
 control occurrence of phenomena
 provide practical clues, to undertake measures that lead to social improvement, social change and social
progress.
 can be intellectually delighting and mentally satisfying,

5. Benefits of nursing research
• Contribute to the scientific base of nursing practice.
• Determine the effectiveness of nursing intervention and nursing care.
• make the science of nursing to grow.
• Generate the scientific basis or rationale for making changes in nursing
practice and patient care.
• Influence nursing decision by improving it.

6. Classes of research (Based on method of data
collection
• Quantitative
• Qualitative
• Descriptive
• Experimental
• Historical
• Aesthetic

7. Types of research
Basic:
• has goal of discovering knowledge for its own sake.
• Designed to solve immediate problem
• Done for intellectual pleasure of learning
• E.g. knowing why chicken noodles tastes better than beef
Applied: Goals of finding solutions to practical everyday problem
e.g: Research into why obesity increases with age. The problem is obesity, we want to know why
then it increases with age.

8. Steps in research process
• Easy to remember?/ Hard to forget?
•Fr.difs.soc.scoaic???
• Let’s find a nice sentence for abbreviation
• Father Richard Differentiated Infants From Sons So Others Can Solely
Concentrate On Another Info Collection.
• Remember the first letter of every word

9. Research Process
1) Formulating and delimiting the problem
2) Reviewing the related literature
3) Developing a theoretical framework
4) Identifying the research variables – independent/dependent
5) Formulating Hypotheses
6) Selecting a Research Design
7) Specifying the population

10. 8) Operationalizing and measuring the research variables.
9) Conducting the pilot study and making revisions.
10) Selecting the sample
11) Collecting the Data
12) Organizing the Data for analysis
13) Analyzing the Data
14) Interpreting the Results and Drawing Conclusions (Discussion of Findings and
Implications.
15) Communicating the Findings/Dissemination of Findings

11. VARIABLES

12. Variables
• A variable is a characteristic or factor that has values that vary or change
• For example, levels of education, intelligence, sex, temperature, or physical
endurance.
• An attribute that can vary or change….. Remember…change is the
only constant thing not variables

13. Types of variables
• Independent: also explanatory or predictors or causal variables. They cause
another variable to change. E.g. things we can accept without wondering
what made them what they are
• Dependent: Outcome or criterion variables. They are forced or caused by
other variables.
• Intervening: outcome of an event may depend on condition that come in
between the dependent and the independent variable. It a link between the
two above

14. Let us try an example
• Married people have better mental health than unmarried people.
• Independent variable: Marriage
• Dependent variable: Mental health
• Intervening variable: Maybe married people would have better mental health
than single people because lets say due to counselling received during
marital preparations. This counselling is a link btw marriage and mental
health.

15. LITERATURE REVIEW

16. • A literature review is an account of what has been published on a topic by
accredited scholars and researchers.
• It discusses published information in a particular subject area, and
sometimes information in a particular subject area within a certain time
period.
• L.R can be just a simple summary of the sources, but it usually has an
organizational pattern and combines both summary and synthesis.

17. L.R Cont’d
• A summary is a recap of the important information of the source
• A synthesis is a re-organization, or a reshuffling, of that information.
• It might give a new interpretation of old material or combine new with old
interpretations

18. Organizing L.R can be through:
• Chronological: this is when content of the review are arranged as they
occur over time, this could either be by publication or by trend.
• Thematic: Thematic reviews of literature are organized around a topic or
issue, rather than the progression of time. The only difference between a
"chronological" and a "thematic" approach is what is emphasized the most.
• Methodological: This differs from the two above in that the focusing factor
usually does not have to do with the content of the material. Instead, it
focuses on the "methods" of the researcher or writer.

19. Stages in developing a literature review.
Selecting the topic
Setting the topic in context
Looking at information sources
Using information sources
Getting the information
Organizing information (information management)
Positioning the literature review
Writing the literature review

20. Sources of Information
Books -journals - scholarly, popular - research Papers
Theses - world wide web - bibliographies
Encyclopaedias -handbooks -Maps
newspapers - Government legislation
standards
Statistics -government documents
conference proceedings -

21. HYPOTHESIS

22. Definition
• A tentative statement that proposes a possible explanation to some
phenomenon or event.
• An educated guess as to what the outcome will be
• e.g. first time mothers who attend child birth classes will demonstrate earlier
bonding than mothers who do not attend classes.
• A hypothesis should not be confused with a theory. Theories are general
explanations based on a large amount of data.

23. Examples of hypothesis
• Chocolate can cause pimples
• Getting at least 8 hours sleep can make people healthier
• Temperture change may cause butter to become rancid
• Note the may, can
• We didn’t say categorically that chocolate WILL cause pimples, we only said CAN.

24. Characteristics of Hypothesis
• Testability
• Logicality
• Relatedness
• Unitary
• Sets limit on study
• Stated in acceptable form

25. Types of Hypothesis: Simple Vs Complex
• Simple hypothesis: predicts relationship between two variables: the independent and
dependent variable
• E.g: drinking sugary drinks daily leads to being overweight., smoking leads to cancer of the
lungs
• These things are NOT always true but they are GENERALLY true
• Complex Hypothesis: test relationship between two or more IV and 2 or more DV
e.g: Individuals who smoke cigarettes, live in industrial cities, family history of cancer have an increased
risk of lung cancer
It is complex right? Remember!

26. Null Vs Alternate
• Null Hypothesis: (H0): states that no relationship exists beween 2 variables
• E.g: there is no significant association with eating surgary foods and obesity
• Alternate Hypothesis (H1): it is a claim that opposes Null hypothesis
• E.g: There is a significant association between eating surgary foods and
obesity

27. Directional Vs Non-Directional
• Directional Hypothesis: It is linear i.e the relationship between variables can also
predict the nature
• E.g: Engaging in more exercise increases weight loss
• Non-Directional Hypothesis: Just states a relationship without predicting the exact
nature or direction
• E.g: People from Oyo states are better than people from ogun state.
• This doesn’t show us how the direction of the relationship; are oyo people beter in
reading or are ogun people better in doing parties, we don’t know.

28. Associative Vs Causal
• Associative Hypothesis: Occurs when there is a change in one variable leads
to a resulting change in another variable.
• E.g: The more you whisk egg, the foamier it becomes
• Causal Hypothesis: proposes a cause and effect interaction between two or
more variables.
• E.g Whisking egg makes it foamy. (cause: whisking; effect: foamy
consistency)

29. Errors in hypothesis
• Type 1 Error: rejection of a true null hypothesis
• In simple English…….the null hypothesis is actually true i.e there wasn’t a relationship
found between variables but the researcher failed to see this.
• Type 11 Error: Failure to reject a false null hypothesis
• Here….there actually was a relationship found but the researcher was bent on saying
that there was no relationship when indeed there was
• In simple English again (lol)…Rejecting a true alternate hypothesis

30. RESEARCH DESIGN

31. Research Design
• The blueprint of the investigation to be conducted is what is referred to as
the research design.
• The research design indicates the steps that will be taken and in what
sequence
• Generally, there are several methods that can be adopted for a study,
depending on the type of research but each call for a different
methodological approach in data collection and analysis.

32. Types
• Experimental design: Researcher manipulates the predictor or independent
variable-otherwise called the treatment, program or intervention-and then
observes the outcome.
• Provides evidence of cause and effect relationship between actions
• e.g. Pts who receive pre-operative teaching need less pain medication in the first 72 hours
post operatively (Cause: pre-operative teaching Effect: Less pain).
• True and Quasi-experimental designs are the two types of experimental
designs

33. • True E.D:
• Strongest design for establishing a cause and effect relationship,
• Random assignment is used –i.e. all units in the groups involved are considered equal
• E.g: randomly assigning people into two groups and exposing them to the same intervention
such as counselling to assess their mental health
• Quasi E.D:
• Employ multiple measures or a control group without randomly assigning participants to group.
• The ability of these designs to establish a cause-effect relationship is dependent upon the degree
to which the two groups in the study are equivalent.
• E.g. exposing a group to counselling while another group is not exposed, then measuring their
mental health.

34. Non experimental design
• Do not employ multiple measures
• Do not use a control group
• Do not use any random assignment in its design.
• These are usually employed in descriptive, cross-sectional and correlated
studies.
• Most of our researches are non-experimental in nature. It is weak in looking
for cause and effect unlike experimental design.

35. SAMPLING &
SAMPLING TECHNIQUE

36. Sampling and sampling design
• A sample design is a set of rules or procedure that specifies how a sample is to be
selected.
• Sampling: the procedure by which a few subjects/cases are chosen or selected for
inclusion a in a research study
• This allows the researcher to study the subjects/sample in such a way that the
sample can be used to estimate the same characteristics in the total population.
N.b: Sampling is the procedure of selecting while sample design is how the samples
would be selected

37. Sample
• A sample is described as a finite part of a statistical population whose
characteristics are studied to gain information about that population.
Benefits of sampling
• Economical
• Timeliness
• The large size of many populations
• Inaccessibility of some of the population
• Accuracy.

38. Terms in sampling
• Population: All members of a specified group : Nursing students
• Target Population: The population to which the researcher ideally want to
generalize: Nursing students in Nigeria
• Accessible Population: The population to which the researcher has access: The
researcher lives in Lagos, so Nursing students in Unilag
• Sample: A sub-set of a population : Nursing students in clinicals (300-500 level)
• Subject: A specific individual participating in a study
• Sampling Technique: The specific method used to select a sample from a
population

39. • Representation: The extent to which the sample is representative of the population.
• Generalization: The extent to which the result of the study can be reasonably
extended from the sample to the population.
• Sampling Error: The chance occurrence that a randomly selected sample is not
representative of the population due to error involved in the sampling technique.
• Random selection error is controlled by selecting larger sample
• Non-random selection error is controlled by being aware of sampling bias and
avoiding them. E.g surveying only parents who attend out patient clinic.

40. Characteristics of a Good Sample
• Should be true representative of the population.
• Selection must be bias-free.
• Should make allowance for computation of sampling error.
• The result of the sample should be applicable to the population
• Types of Samples
• Probability sampling techniques, and
• Non-Probability sampling techniques.

41. Probability Sampling Techniques -PST
• The sample is selected in such away that each item in the population has a
chance of being selected.
• This is the type of sampling that is used in lotteries, raffle draws etc
• Two things are required to select a Probability Sampling:
• (1) Probability sampling requires that a listing of all units in that population. This listing
is called the sampling frame.
• (2) A random selection procedure must be used to select individuals off the sampling
frame to ensure that each unit of the sample is chosen on the basis of chance.

42. Four types of PST
• Simple Random sample: units are selected at random e.g. For example, if you want to
select 10 players randomly from a population of 100, you can write their names, fold
them up, mix them thoroughly then pick ten. It is like lottery or lucky dip.
• Systematic Random Sample: It is obtained by selecting the first unit on a random
basis and additional units at evenly spaced intervals until the desired number of units is
obtained (i.e. the selection of every ‘nth’ element after a random start from the available
population).
For example, there are 100 nurses in your hospital. You want a sample of 20 and you have
their names listed on a piece of paper. Divide the population by the required sample size
(100/20=5). Select any number from 1 to 5 (say no 4 ). From here, you will select every 5th
name till you have your 20 nurses.

43. Stratified Sampling.
• It is used where the population consists of subgroups of interest. The
population is divided into these subgroups (known as strata) on the sampling
frame, and simple random samples are drawn from each of the strata.
• Stratified sampling is however only possible when we know what proportion
of the study population belongs to each group we are interested in.

44. Cluster Sampling
• Used when the population is large
• When other methods are too expensive to use
• While simple random & stratified sampling uses single subjects from a
population, cluster sampling uses subjects selected in groups or clusters.
• This approach allows the researcher to overcome the constraints of cost and
time associated with a much dispersed population

45. Cluster sampling
• Let us assume you wanted to conduct interviews with nurse tutors in south western
Nigeria about trends in nursing education.
• You could decide each school in each of state in SW represents one cluster, and then
randomly select a small number e.g. 6. You would then contact the tutors in these 6
schools for interview.
• When all tutors in the 6 schools selected are interviewed, this is referred to as “one
stage cluster sampling”.
• If the subjects to be interviewed are selected randomly within the selected clusters
(schools), it is call “two-stage cluster sampling”.

46. Cluster cont’d
• You could also combine cluster sampling with stratified sampling.
• For instance, in the above example, you might want to stratify the tutors based on
some characteristics relevant to your study , (e.g. education qualification, seniority,
e.t.c) and then randomly select tutors from each of these strata.
• This type of sampling is referred to as “multi-stage sampling”.
• Notice that a multi-stage sampling procedure is carried out in phases and it
usually involves more than one sampling method.

47. Non-probability sampling techniques
• Non-probability samples are not selected according to the principle of randomness; they
are selected according to some other principles such as convenience or accessibility.
• The sample is not statistically chosen and the selection of subjects is or subjective usually
based on
• limited resources,
• Population is difficult to find e.g. gay couples
• non-availability of sampling frame,
• researcher’s experience,
• and judgment.

48. Problems of NPST
• Degree of accuracy to generalize findings on population is impossible to
assess
• Bias is easily introduced.

49. Types of NPST
• 1) Purposive Sampling: This method of sampling is used in
special situations where sampling is done with a specific
purpose in mind. E.g professors, sex workers, music artists etc.
• Snowballing is a type of purposive sampling which commonly
used when it is difficult to identify members of a sample or
where the research interest is in an interconnected group of
people.
• E.g: People who were cultist before, gays/lesbians etc

50. 2) Quota sampling:
• This is usually referred to as the most sophisticated of the NPST because it
has similar requirement as stratified sampling.
• Here, the researcher first has to identify categories (sub groups) that need to
be in the sample and the required number (quotas) in these categories.
• Selection of individuals on non random basis (e.g. convenience sampling)
from each category is then done until the quotas have been reached.

51. 3) Convenience sampling
• This method refers to situations when population elements are selected based on
the fact that they are easily and conveniently available.
• Also called Incidental sampling
• When there seems no other choice (no one else available for an interview)
researchers may also sample conveniently.
• Convenience sampling is usually quick and cheap, but does not result in
representative samples.
• Remember just as name applies ‘convenient’

52. Data collection

53. Types or Sources of Data
• Primary sources: original sources from which the researcher directly collects data that have
not been previously collected,
• e.g., collection of data directly by the researcher
• Primary data are first-hand information collected through various methods such as
observation, interviewing, mailing
• Secondary sources: sources containing data that have been collected and compiled for
another purpose.
• Secondary sources are readily available
• e.g., census reports, annual reports and financial statements of companies, hospital records

54. Advantages
• Secondary data, if available, can be secured quickly and cheaply.
• Wider reach .
• The use of secondary data broadens the database from which scientific
generalizations can be made.
• The use of secondary data enables a researcher to verify the findings based on
primary data.
• Disadvantages/limitations
• The most important limitation is the available data may not meet specific research
needs.
• The available data may not be as accurate as desired.
• The secondary data are not up-to-date and become obsolete over time
• Information about the whereabouts of sources may not be available

55. Methods of Data Collection
• Observational Methods
• This is the basic method of getting information about the world around us.
• Observation is not only one of the most pervasive activities of daily life; it is a
primary tool of scientific enquiry.
• It enables researchers to study behaviour as it occurs.
• This in turn enables the researcher to collect data firsthand, thereby preventing
contamination
• Can be direct (subjects are aware) or indirect (unobtrusive: subjects are not aware).

56. Demerits of observation
Time consuming
Requires too much effort
Bias on the part of those being observed
Past events cannot be directly observed

57. Questioning
• Can be written or oral
• Written questions are referred to as the Questionnaire.
• Questionnaire could be structured or non-structured, open ended or
close ended depending on the type and purpose of the investigation.
• Structured easier to analyze than the non-structured which often employ
qualitative analysis.
• When the questions are posted in verbal forms, it is called Interview.

58. Merits of questionnaire
• (a) Less expensive in terms of money and time;
• (b) Greater sense of anonymity by respondents;
• (c) Formalized standard for all respondents;
• (d) Large sample taken over a large geographical area;
• (e) Greater amount of data covering a broad range of topics.

59. Merits of interview
• : (a) Subjects need not be literate;
• (b) The rate of response are always higher than the case with questionnaire;
• (c) Response can be observed by the interviewer;
• (d) Clarification of questions can be provided;
• (e) Responses are not premeditated as respondents do not know what other
questions will follow;
• (f) The face to face can tell the interviewer a lot about the respondent

60. DATA PROCESSING

61. DATA PROCESSING, DISCUSSION
AND REFERENCING
• Compilation – coding of information obtained during data collection.
• Organizing the Data – This encompasses sorting, making tally count, frequency table, and
so on for easy statistical analysis.
• Statistical Analysis – Data analysis usually employs
• Descriptive statistics (such as mean and other measures of central tendency, frequency, e.t.c.)
and inferential statistical techniques like chi square, correlation coefficient, ANOVA, e.t.c.
• It is good to mention here that some software have been developed to ease the burden
hitherto associated with data analysis. Example of such packages are the SPSS (Statistical
Package for Social Sciences), Epi-info and TextBase Beta.
• Evaluation – This involves making inferences based on the result of the data analysis.

62. Discussion and References
• This entails factual and exhaustive discourse of your findings making allusion
to what other scholars have done on the subject matter.
• In scholarly writing there is however what we call plagiarism or academic
fraud.
• One can easily fall victim of this detestable crime if one writes without
acknowledging those whose ideas one has borrowed.
• The truth is, no work is ever complete without proper references.

63. THANK YOU