3. Contents
• Introduction
• Definition
• Various steps in research process
• Formulating hypothesis
• Types of study design
• Heirarchy of evidence
• Ethical issues in research
• Study settings and eligibility criterias
4. • Sampling
• Bias
• Contamination
• Outcome measures and endpoints in research
• Representation of data
• Descriptive and inferential statistics
• Writing of a report
5. Introduction
• “All progress is born of inquiry. Doubt is often better than
over-confidence, for it leads to inquiry, and inquiry leads to
invention.”
–Hudson Maxim (1853-1927)
6. • Research in the field of dentistry has witnessed a tremendous
upsurge in the last two decades unveiling newer innovations in
techniques, methodologies, and material science.
• The recent focus in dental research is an evidence-based
approach which offers a bridge from science to clinical
practice.
7. Definition
• Research can also be defined as a scientific and systematic
search for pertinent information on a specific topic.
8. • formulating the research problem,
• an extensive literature survey,
• developing the hypothesis,
• preparing the research design,
• sample size estimation,
• collecting the data, execution of the project, data analysis,
• Hypothesis testing, generalizations and interpretation and
• preparation of the report.
9. Formulating the research problem
• Formulation of a general topic into a specific research
problem.
• 2 types
research hypothesis
question
10. Research question
• Question that you are trying to answer
• narrowly constructed
• addresses the important factors of the problem.
• Three types of questions are identified in research,
• questions of description;
• questions about relationships between phenomena;
• questions of comparison.
11. • The PICO question is a gold standard in all studies related to
clinical comparative studies.
• The parts of a well-built research question (PICO question)
• Includes
• Patient/population/problem (P),
• Intervention (I),
• Comparison (C), and
• Outcome (O).
12. Developing the hypothesis
• Hypothesis is defined as a ‘‘supposition arrived at from an
observation or reflection.
• A hypothesis is a statement that can be proved or disproved.
• If a typically framed research question would be:
• ‘‘Is chlorhexidine (CHX) chip in conjunction with scaling and
root planing (SRP) more effective in periodontal therapy than
SRP alone?’’ then, a hypothesis would state:
• ‘‘The use of SRP and CHX chip is efficacious in the reduction
of probing depth when compared to SRP alone.’’
13. • 2 types:- a. null hypothesis (Ho)
b. alternative hypothesis (Ha)
• Null hythpothesis:-
• difference seen is purely accidental or
• may arise due to bias in sampling.
• The investigators seek to accept or reject the null hypothesis as
the outcome of research.
• For example,
the adjunctive use of a CHX chip along with SRP does not
have a beneficial effect in the reduction of probing depth
compared to SRP alone.
15. Approach to research
1. Quantitative
2. Qualitative
• Quantitative research:-
• based on the measurement of quantity or amount.
• applicable to phenomena that can be expressed in terms of
quantity.
• the results are given in numbers or proportions
16. • Qualitative research:-
• concerned with subjective assessment of attitudes, opinions,
and behavior.
• results are described in words rather than numbers.
• Evaluating the awareness and perceptions of pregnant women
about proper oral hygiene during pregnancy would be an
example of qualitative research.
17. Types of study design
1. experimental
observational
2. cross-sectional
longitudinal
3. prospective
retrospective
18. • Study designs broadly can be classified as
1. observational
2. experimental
19. Observational:
• are referred to as observational as the investigators merely
observe what is happening rather than attempting to intervene
in anyway.
• The design does not involve a specific intervention other than
normal standard care.
20. Various observational studies:-
i. Correlational
ii. Case reports & case series
iii. Cross-sectional study
iv. Case-control study
v. Cohort study
vi. Ecological study
vii. Systematic reviews
viii. Metaanalysis
21. Correlational study:-
• intend to explore a correlation between two variables.
• A correlation would not necessarily mean causation.
• For eg:- on the correlation between coronary heart disease and
chronic periodontitis or obesity and periodontal disease etc.
• It would also include studies investigating relationships
between socio economic status, smoking, various
periodontopathogens, inflammatory markers, and periodontal
disease.
22. Case reports and case series
• descriptive studies in which the possibility of an association
between an observed effect and a specific environmental
exposure is based on detailed clinical evaluations and histories
of the individual(s).
• E.g.: Periodontal findings in a patient with Mauriac syndrome:
A case report.
• Labial piercing resulting in gingival recession – A case series
23. Cross sectional study
• provide a snapshot picture of a community at a point in time,
• do not involve following a group of individuals over time,
• e.g. prevalence and risk of gingival overgrowth in patients
treated with diltiazem or verapamil.
24. Case – control study
• Typically examines multiple exposures in relation to a disease;
• subjects are defined as cases and controls, and exposure
histories are compared.
• A case control study starts with patients who already have the
outcome and looks backwards to possible exposures.
• E.g.: Association between periodontitis and low birth weight
25. • Limitations of a case control study are
• bias (because of the retrospective nature)
• and the difficulty to establish the correct temporal relationship
between the exposure and disease
26. Cohort study
• take a large population who are already taking a particular
treatment or have an exposure,
• prospective retrospective
follow them forward overtime where both exposure and out
and then compare them for comes have already occurred
outcomes with a similar group when the study begins.
that has not been affected by the -- later examines only prior
treatment or exposure being outcomes and no future ones
Studied.
27. Ecological study
• It examines the rates of disease in relation to a factor described
on a population level.
• The units of analysis are populations or groups of people
rather than individuals.
28. Systematic reviews
• Usually focus on a clinical topic and answer a specific
question.
• An extensive literature search is conducted to identify studies
with sound methodology.
• The studies are reviewed, assessed, and the results
summarized according to the predetermined criteria of the
review question.
• E.g: A systematic review of guided tissue regeneration for
periodontal infrabony defects.
29. Meta-analysis
• Whenever possible, the results of a systematic review are
statistically pooled together to generate a Meta-analysis.
• It is not necessary that every systematic review should
culminate in a meta-analysis.
30. Experimental
• where something specific is done in the study – i.e., using a
treatment, strategy, or other intervention, that is recorded and
analyzed.
• Experimental studies are commonly classified by their
objective – that is, by whether they investigate a measure that
prevents disease occurrence or a measure that treats an existing
condition.
• The investigator assigns individuals to two or more groups that
either receive or do not receive the preventive or therapeutic
agent.
31. Randomized controlled clinical trials
(RCTs)
• carefully planned projects
• introduce a treatment or exposure to study its effect on real
patients.
• They include methodologies that reduce the potential for bias
(randomization and blinding)
• allow for comparison between intervention groups and control
groups (no intervention).
32. • An experiment that can provide sound evidence of cause and
effect.
• also called random allocation, implies that the subjects are
randomly assigned exposures then followed forwards to
achieve an outcome.
33. Controls
• Clinical trial– comparative in nature
• A clinical trial which includes a comparative group is called a
controlled clinical trial
• No treatment control
• Minus active (Placebo) control
• Benchmark control
• Positive control
• Historical control
34. Blinding
• Methodologies to reduce potential for bias that allows for
comparison of groups.
• Also called masking is intended to limit the occurrence of
conscious and unconscious bias in the conduct and
interpretation of a clinical trial.
• double blind single blind open-label trial
36. • Parallel group:- each participant is randomly assigned to a
group, and all the participants in the group receive (or do not
receive) an intervention.
• Crossover trials – the subject acts as his/her own control with
the same subject being allocated for both treatments, receiving
them at different times. The possibility of a ‘‘carryover’’ of the
effect of the intervention provided in the first period into the
second intervention period is an important concern in this
study design.
37. • Split-mouth – separate parts of the mouth of each
participant (i.e., the left and right) are randomized to receive
(or not receive) an intervention.
• A split mouth study design can be used mostly when two
treatment modalities have to be compared, in the same patient
who acts as his own control.
38. • Factorial – each participant is randomly assigned to a group
that receives a particular combination of interventions or
non-interventions.
• group 1 receives therapy X and therapy Y,
• group 2 receives therapy X and placebo Y,
• group 3 receives placebo X and therapy Y,
• group 4 receives placebo X and placebo Y).
• E.g: A comparison of the effectiveness of the Charters’, scrub,
and roll methods of toothbrushing in removing plaque.
39. Single centre Vs. multicentre trials
• A clinical trial conducted according to a single protocol but at
more than one site, and therefore, carried out by more than one
investigator is a multi-center trial.
• Multicenter studies offer the potential for increased
recruitment and generalizability from conduct of the trial in
several regions of the country (or world) and also take the
contributions of multiple investigators with complementary
expertise.
40. Pilot study
• to be done before the starting of a fully-fledged research
project.
• A pilot study is usually carried out on members of the relevant
population, but not on those who will form part of the final
sample.
• Can reveal deficiencies in the design of a proposed experiment
or procedure and
• then be addressed before time and resources are expended on
large scale studies to check the feasibility or to improve the
design of the research.
41. The hierarchy of evidence
• Evidence-based dentistry has been defined as “the
conscientious, expedient, and judicious use of current best
evidence in making decisions about the care of individual
patients.”
• The principles and methods of evidence-based dentistry have
established their roots well in the present era, where various
decisions regarding patient care are based on choosing the
‘‘best’’ evidence from the ‘‘available’’ evidence.
42. • Understanding “strength of evidence” and the idea of a
“research design hierarchy” is at the heart of evidence-based
dentistry.
• Evidence is graded based on its strength into different levels
where systematic reviews and randomized controlled trials
represent the highest levels of evidence, whereas case reports
and expert opinion are the lowest.
43.
44. • For questions related to diagnosis, prognosis or causation,
other study designs such as cohort studies or case-control
studies will often be more appropriate.
• For these types of studies, it may be more appropriate to view
it not as a hierarchy, but as categories of evidence, where the
strongest design which is possible, practical and ethical should
be used.
45. Implementation of research
• the various ethical norms and standards in human
experimentation,
• the eligibility criteria for the participants,
• sampling methods and sample size calculation,
• various outcome measures that need to be defined and the
• biases that can be introduced in research.
46. Ethical issues in research
• History of clinical research----several tragedies-----unwitting
participation ------harmed mercilessly.
• The brutal Nazi experiments on prisoners during the world war
II, where human subjects were forcefully and ruthlessly tested
to justify their suppositions was severely criticized and this
inhuman attitude toward human participants prompted the
evolution of various codes and reports.
47. • The Nuremberg code which was put forward in 1947 was a ten
point statement which defined the conditions under which
acceptable human experimentation should be carried out.
• The Good Clinical Practice (GCP) guidelines by the US Food
and Drug Administration, 1996 regulates the proper conduct of
trials in the United States.
48. • “The conduct of research in human subjects does not connote
just to the designing of the study and procuring the signature
of the subject on the informed consent form. It also involves
protecting the rights, interests, and safety of research subjects
throughout the study duration.”
….silverman (2007)
49. • Subject safety monitoring is the responsibility of several
groups, including
research ethics committees or Institutional Review Boards
(IRBs),
investigators
their research staffs,
sponsors, and
data monitoring committees, also called data and safety
monitoring boards,
50. • All research involving human participants should be cleared
by an appropriately constituted Institutional Ethics Committee,
also referred to as Institutional Review Board (IRB), to
safeguard the welfare and the rights of the participants.
• The IRB is not necessarily constituted by medical people alone
but also has nonmedical people representing the community,
ethicists, clergy or lawyers.
51. • Once the research protocol and informed consent forms are
approved, the committee undertakes periodic reviews of the
study with detailed reports, to ensure that the conditions are
met in regard to the safety and wellbeing of participants.
• Informed consent should be obtained from every patient (or
legal guardian, if necessary) and has to be included in the trial
proposal.
52. • This implies that the patient is aware of and understands all the
implications involved in the study which are known to the
researchers, and is willing to accept these as a condition of
his/her involvement in the study.
53. • It is also important in an epidemiological study that the
research is designed in such a manner that the privacy and the
confidentiality of data are preserved and at the same time the
community health needs are addressed.
54. Study setting and eligibility
(inclusion/exclusion) criteria
• It usually establishes the boundaries of the study with respect
to the sample, sampling area and the time period of the study.
• Prior to the commencement of the study, the study population
should be defined, along with the characteristics of the
subjects that are to be included (inclusion criteria).
• The characteristics of the subjects which are not to be included
in the study (exclusion criteria) need to be established.
55. Sampling
• A sample (n) is a ‘‘Finite’’ part of a statistical population
whose properties are studied to gain information about the
‘‘WHOLE’’.
• A sampling frame, refers to a list of available population
members, for example a list of patients, or the census data etc.
57. • A purposive (non-probability/deliberate) sample is one which
is selected by the researcher subjectively.
• Convenience sampling :- where the population elements are
selected for inclusion in the sample based on the ease of
access.
• Quota sampling
• The population is first segmented into mutually exclusive
sub-groups, just as in stratified sampling. Then judgment is
used to select the subjects or units from each segment based on
a specified proportion, which makes the technique one of
non-probability sampling.
58. • A non-purposive (probability) sample is one in which every
unit in the population has a chance (greater than zero) of being
selected in the sample, and this probability can be accurately
determined.
• Types of probability sampling:
Simple Random Sampling
Stratified random Sampling
Systematic Random Sampling
Cluster Random sampling
59. Simple random sampling
• also known as chance sampling
• where each and every subject in the population has an equal
chance of inclusion in the sample and each one of the possible
samples has the same probability of being selected.
• Methods of simple random sampling include coin toss, random
selection of numbers, lottery, and computer generation of
numbers.
60. Systematic sampling
• a systematic method
• the selection process starts by picking some random points in
the list and then every nth element is selected until the desired
number is secured.
61. Stratified sampling
• The population is stratified into a number of non-overlapping
subpopulations or strata and sample items are selected from
each stratum.
• If the item selection from each stratum is based on simple
random sampling, then the entire procedure, first stratification
followed by simple random sampling, is known as stratified
random sampling.
• E.g. strata of age groups; gender (male/female) etc.
62. Cluster sampling and area sampling
• Cluster sampling involves grouping the population and then
selecting the groups or the clusters rather than individual
elements for inclusion in the sample.
• When all the units within a cluster are selected, the technique
is referred to as one-stage cluster sampling.
• If a subset of units is selected randomly from each selected
cluster, it is called two-stage cluster sampling
63. Multi-stage sampling
• Technique is meant for larger data extending to a considerably
large geographical area like an entire country.
• In multi-stage sampling the first stage may be to select large
primary sampling units such as states, districts, towns, and
finally certain families within towns.
64. Sample size estimation
• The calculation of the size of the sample to be surveyed in a
research project is pivotal as it would facilitate the researcher
with some information on the timeframe, logistics of the
project and also the future generalizability and relevance of the
results.
• what is the result of other studies which used a similar
intervention?
• Or what is the range of the present level of or rate of
occurrence of the event that we are interested in?
• what is the level of α or β errors that we are willing to accept?
65. • To what extent our result could be due to chance?
• Conventionally, 5% for type 1 and 20% for type II error is
accepted.
• what is the result we are expecting?
• That is, what is the clinically meaningful difference?
66. • For field survey
n = 4pq
l2
• For quantitative data
n = 4s2
l2
67. The observational unit (subject vs. site)
• The unit of observation in an experiment or observational
study is the smallest unit with a unique set of important
characteristics which is independent of other similar units in
that its response cannot be affected by these other units.
68. • In clinical trials, usually the subject or the mouth is selected as
an observational unit.
• The study should be designed and analyzed in such a way that
the randomization process should randomize the experimental
units (the mouths) rather than sub-units (the teeth) to the
different treatments.
69. Examiner training and
standardization/calibration
• The clinical examiners who are assessing patients are
well-trained and calibrated in order to achieve good
reproducibility of data with minimal error and bias.
• Hefti and Preshaw introduced the term ‘‘Examiner alignment
and assessment’’ as a more descriptive term for the process of
training examiners who will participate in a clinical trial.
70. Bias and confounding
• ‘‘opinion or feeling that favors one side in an argument or one
item in a group or series.’’
• In an epidemiological perspective, bias is present when the
results from the study are systematically distorted and so are
consistently above (or below) what they should be.
• Sackett in 1979 identified 24 biases.
71. Selection Bias
• When the study participants are not representative of the
population of interest.
• This bias usually happens during the selection of subjects for
control and test groups where the investigator assigns subjects
such that they differ with respect to extraneous factors.
72. Observer or measurment bias
• When an examiner consistently over/under reports a variable
(a characteristic).
• This must be resolved in training and calibration sessions.
73. • Recall bias :-
• An information bias in which the subjects with disease (cases)
tend to recall past exposures better than controls.
• Attrition bias :-
• when subjects quit the study before its completion.
• These drop outs in the clinical trial cause bias in the results
due to the decreased sample size in one group or may be both,
and also the decreased follow up time period.
74. • Migration bias
• Another kind occurs either when individuals drop out of
study or move from one group to another.
• Publication bias
• Studies which show significant results are more likely to
be published in journals than those with insignificant or
negative results.
75. • Allocation bias
• When treatment groups in an experimental study are not
comparable with respect to the variables influencing the
response of interest.
76. Confounding
• Confounding is a mixing of the effect of an exposure with the
effect of another variable that is associated with the exposure
and is an independent risk factor for the disease.
• Confounding factors are variables, which compete with the
hypothesized risk factor as explanations for the observed
response.
77. Contamination
• It occurs when an intervention administered to an intervention
group of an experimental study percolates into the control
group.
• This is usually seen in a split mouth study or in a crossover
study where the intervention from one site filters into the
control treatment.
• It could also be seen with respect to information which is
given from one group by word of mouth to the members in the
other group.
78. Hawthrone effect
• Roethlisberger and Dickson in 1939.
• Individual behaviour may be altered when participant knows
he is being observed.
• Subjects who are singled out to participate in a mouthwash
trial consciously tend to improve their oral hygiene and may
show lower plaque scores.
79. Rosenthal effect (experimenter effect)
• The expectations and biases of an experimenter can be
communicated to experimental subjects in unintentional ways
and these clues may significantly affect the outcome of the
experiment.
• Experimenter effects can be avoided by using double blinded
studies where the experimenters’ expectations and biases are
not communicated to the study subjects.
81. • Reliability is the extent to which an experiment, test, or any
measuring procedure yields the same result on repeated trials.
• Validity refers to whether a study is able to scientifically
answer the questions, it is intended to answer.
• Sensitivity is the probability (usually expressed as a
percentage) that a subject with the disease will have a positive
test result.
• Specificity is the probability that a subject who is free of the
disease will have a negative test result.
82. • The best tests are the ones that are good at detecting most of
the people with the condition (high sensitivity) and at
excluding people who do not have the condition (high
specificity).
83. Outcome measure and endpoints in research
Lab measures
• Biological
tests on cell
cultures
• Mechanical
tests on
clinical
materials
Clinical
measures
• Various
indices
Pt-based
measures
• Patient
perceptions
• questionnaire
84. Primary question
that the study is
designed to
answer
Trial is powered to
answer such a
question
Primary
Other outcome of
intrest
Often includes
unintended and
unanticipated
effects of the
intervention
Secondary
85. • End points :- An endpoint is any measurement that is thought
to be related to the disease process and that is used to assess
treatment efficacy.
• Researchers are usually faced with the challenge of selecting
an endpoint that provides clear, unequivocal evidence of a
benefit to the patient.
86. True
How a patient feels,
functions or survives
Pain, bleeding on
brushing, and oral health
related quality of life
Surrogate
Intermediate endpoints,
biological markers,
Probing depth, measures
of inflammation,
microbiological
measures and
immunologic measures
87. Representation of data
• All the data are entered manually on paper or directly entered
into a spread sheet or database or directly into a computer.
• Analysis of data :-
establishment of categories,
the application of these categories to raw data through coding,
tabulation and
then drawing statistical inferences.
88. • Data file can take the form of a spreadsheet with
• individual people the rows and
• the variables columns.
89. • A variable is something that can be changed, such as a
characteristic or value.
• two types of variables – dependent and independent.
• The variable(s) we measure as the outcome of interest is the
dependent variable (Y variable), or response/effect. The
independent or the X variable causes an effect that is seen
on the dependent variable.
90. 1. quantitative
• Data can
2. qualitative
• (i) Quantitative data which measure either how much or how
many of something, i.e., a set of observations where any single
observation is a number that represents an amount or a count.
• (ii) Qualitative data which provide the quality of observations,
i.e., it describes something.
91. • Qualitative data:-
i. Nominal/categorical data:- variables with no inherent order
or ranking sequence.
Dichotomous/binary data
ii. Ordinal/rank data:- variables with an ordered series.
iii. Interval :- do not have a true zero but has an arbitary zero.
iv. Ratio scale:- has a definite “0” as the starting point true zero
point.
92. • Quantitative data:-
i. Discrete/discontinuous:- in the form of integers and has no
intermediate points.
ii. Continuous:- can be divided into fractions of whole numbers
like height, weight.. etc.
93. • Paired versus unpaired data:-
• Unpaired (independent or unmatched) data are obtained from
two groups that are unrelated to each other.
• Paired or matched data are where the measurements are taken
on the same individual or matched groups as in a split mouth
or same group before and after or cross over designs.
94. Statistical analysis
• In research, usually both descriptive and inferential statistics
are used to analyze the results and draw conclusions.
95. Descriptive statistics
• include the numbers, tables, charts, and graphs used to
describe, organize, summarize, and present raw data.
measures of central tendency
• They include
measures of dispersion
96. • Variability, in a statistical sense, is a quantitative measure of
how close together or spread out the distribution of scores is.
• The two measures which quantify variability are
• the standard deviation (SD):- individual observations in a
study sample,
• the standard error (SE):- the SE quantifies the variability of
observed sample means if the study were repeated many times.
97.
98. Inferential statistics
• To draw conclusions and predictions based on analysis of
numeric data.
• Inferential statistics are frequently used to answer cause and
effect questions.
• To investigate differences between and among groups.
99. • Two approaches to quantify this uncertainty are
(i) Hypothesis testing, which is associated with P values, and
(ii) Estimation, which is associated with confidence intervals
(CIs).
100. • Hypothesis testing:- For any study to make any inference
about any relationship between the proposed
intervention/treatment and the outcome, hypothesis testing is a
fundamental requisite.
• Statistical inference is achieved usually by means of
hypothesis testing using P value (Probability value).
101. • P-value refers to the probability of detecting a statistically
significant difference that is not the result of the treatment but
the result of chance.
• The most commonly used criteria are probabilities of 0.05
(5%, 1 in 20), 0.01 (1%, 1 in 100), and 0.001 (0.1%, 1 in
1000).
102. Estimation
• While the P value is based on a single value or point estimate
derived from the data, a second form of statistical inference,
interval estimation.
• In estimation,
the sample study provides an estimate of the effect of the
intervention in the population and
consideration of sampling error yields an interval, known as a
confidence interval, which is reasonably certain to contain the
(unknown) true population effect.
• The confidence interval (CI) is used to estimate the upper and
lower limits of the variability in the sample data.
103. Odds ratio and relative risk
• Risk ratio is ratio of probabilities of 2 events.
Or,
incidence of disease in exposed group
incidence in non-exposed.
• Odd’s ratio:- probability of event occurring
probability of event not occurring
104. Inference of statistical test
• To draw inferences – statistical tests are used.
• 2 types:- 1. parametric tests
2. non-parametric tests
105.
106. • Parametric tests:-A statistical test which concerns population
parameters and requires assumptions about these
parameters.
• Parametric data have an underlying normal (Gaussian)
distribution which allows for more conclusions to be drawn as
the shape can be mathematically described.
• T-test, correlation, regression, analysis of variance (Anova).
107. Non-parametric tests
• These tests rely more on the differences in medians rather than
on the estimation of parameters (such as the mean or the
standard deviation) and hence also referred to as
distribution-free methods.
108. Intention to treat analyses (ITI)
• avoid the biases that would be otherwise introduced by the
alternatives of either omitting the results or analyzing the
results according to the treatments that these patients actually
received.
• It is most suitable for pragmatic trials of effectiveness rather
than for explanatory investigations of efficacy.
• including all patients, regardless of whether they actually
satisfied the entry criteria, the treatment actually received, and
subsequent withdrawal or deviation from the protocol
109. • Intermediate or interim analyses:-
• Sometimes the investigators in a clinical trial may wish to
perform significance tests at intermediate stages to evaluate
treatment effects and if one treatment is found to be superior,
the trial can be stopped early and all the patients will go on to
receive the most effective treatment.
110. Clinical vs. statistical significance
• To be clinically important requires a substantial change in an
outcome that matters.
• While statistical significance answers the question, “Is this a
real effect?”,
• clinical significance answers the question, “Is this an important
effect?”.
• One cannot be inferred from the other.
• The results of a study may show statistical significance but
may be clinically insignificant.
111. Writing of a report
• The report should be structured and should have the following
contents.
• Title
• Abstract
• Introduction
• Materials and methods
• Results
• Discussions
• Conclusion
• Bibliography or references
112. • Title:- should reflect the content and emphasis of the project
described in the report.
• Abstract:- A primary objective of an abstract is to
communicate to the reader the essence of the paper. The
abstract should concisely describe the topic, the scope, the
principal findings, and the conclusions.
113. • Introduction :- objective of the research
methodology adopted
background information of the problem
scope of study with various limitations.
• Materials and methods:- the experimental details,
computation procedures
theoretical analysis
114. • Results:- Relevant data, observations, and findings of the study
are summarized.
• Discussion:- the analysis and interpretation of the results.
What do the results mean?
How do they relate to the objectives of the project?
To what extent have they resolved the problem?
How do they differ from other reports
and what could be the possible reasons?
115. • Conclusion:-
the final summing up of the most significant results/ findings
where the researcher should again put down the results of his
research clearly and precisely at the end of the document.
Directions for future work can also be included in this section.
• Bibliography or references:- contain a complete list of all the
sources (books, journal articles, websites, etc.) that are cited
directly in a document.
116. • Each reference entry has four parts: the name of the author, the
year of publication, the title, and further publication
information.
• Tables and figures:- Representation of data in the form of
tables and graphs makes it very easy for the reader to interpret
the results of a study in a comprehensive manner.
117. • Plagiarism:-
To use someone else’s exact words without quotation marks
and appropriate credit, or to use the unique ideas of someone
else without acknowledgment, is known as plagiarism.
• Paraphrasing:-
When a written passage is paraphrased, you rewrite it to state
the essential ideas in your own words. The paraphrased
material must be properly referenced because the ideas are
taken from someone else whether or not the words are
identical.
118. • CONSORT:- (Consolidated standards of reporting trials)
• STARD (standard for reporting diagnostic accuracy)
• PRISMA (Preferred Reporting Items for Systematic Reviews and
Meta-Analyses) formerly QUOROM (Quality of Reporting of
Meta-analyses),
• MOOSE (Meta-analysis Of Observational Studies in Epidemiology),
• QUADAS(Quality Assessment of studies of Diagnostic Accuracy included
in Systematic reviews)
• STROBE:- Strengthening the Reporting of Observational studies in
Epidemiology.
119. Conclusion
• Research in dentistry continues apace.
• In order to conduct clinically relevant research, we need to ask
the important research questions of the day.
• So that we may undertake research that generates the highest
quality of data so that our findings can be translated into
everyday clinical practice.
