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Research
Methodology in
otology
BALASUBRAMANIAN THIAGARAJAN
What is ideal research?
 Should be reproducible
 Should withstand statistical analysis
 Should test a theory / hypothesis / belief
 Should be beneficial to the public
 Should be systematic / empirical / critical /
 Should have academic integrity
 Should be publishable
Desist finding questions to your answers
Confidence interval
Sample
Confidence interval
Population
Factors affecting confidence
interval
 Sample size – Larger the sample size better is the confidence interval
 Percentage – Represents the accuracy of the study
 Population size – This is least important provided the samples are
randomly selected. This is important when the group is relatively
small and contains known group of people
Confidence level
This tells the researcher how confident the actual mean falls within the
Confident interval. Standard deviation if applied tells the researcher
How much variation that can be expected with the studied sample
Size. Ideal SD value is 0.5.
Sample size calculation
Confidence level = Z This is a constant value
90% - confidence interval - Z score = 1.645
95% - confidence interval - Z score = 1.96
99% - confidence interval - Z score = 2.326
Sample size = (Z-score)2 * Std Dev* (1- SD) / (margin of error)2
((1.96)² x .5(.5)) / (.05)²
(3.8416 x .25) / .0025
.9604 / .0025
384.16
Research styles
 objective
 subjective
Ethical committee approval is a must for all types of research
Objective type
 Physical characteristics
 Testing universally applicable rules / laws
 Testing hypothesis
 Experiments
 Surveys
Avoid the lure of numbers. Observation of researcher is more vital
Subjective type
 Involves social life of groups
 This study is usually conducted by observation and the findings
documented and explanations attempted for the observations
 Usually social scientists use this modality
Always assume that your work will be scrutinised by the public
Types of objective study design
 Descriptive
 Analytical
 Interventional
Greatest danger is not failure but non submission of your work
Descriptive study design
These studies consider variance of disease in respect of time, place
and person. Classic example of this design would be an attempted
study on the incidence of age related degree of progressive sensori
neural hearing loss.
These studies provide clues that can be used to design elaborate
analytical studies.
Two types of descriptive studies are possible i.e. cross sectional and
longitudinal.
Cross sectional study (Descriptive Design)
 This study is based on single examination of cross section of
population performed at one point of time
 Results can be projected on the whole population provided the
study is random in nature
 This is a fast and inexpensive way of ascertaining incidence of a
disease
Cross sectional study - Steps
 Objective of the study should be clearly defined
 Population under study should also be defined clearly
 Disease / health problem to be studied should also be defined
clearly (diagnostic criteria should be laid down)
 Randomization of the sample should be ensured
 Double blind trial has more validity
 Make a list of variables
 Prepare a questionnaire
 Decide on a sample size
Longitudinal study (Descriptive design)
 Observations are repeated in the same population over a
prolonged period of time by means of follow up examinations
 Natural history of disease and its future outcome can be studied
 Helps in identification of risk factors in disease causation
 Also helps in finding out the incidence rate
Advantages of descriptive studies
 Provides morbidity and mortality data
 Provides clue to disease etiology
 Generates hypothesis which can be tested by analytical studies
 Provides data for planning, organizing and evaluating preventive
and curative services
 Contributes to research in terms of disease occurrence by time
place or person
Analytical study design
 Classic example of this design would be the study to ascertain odds
of developing noise induced hearing loss.
 Intensity / duration of noise exposure should be factorized.
 Age and sex of the patient (variables).
 Analytical study design could be prospective and retrospective
Prospective study design (cohort /
longitudinal)
 Difficult to perform
 Tests the hypothesis obtained by descriptive study
 Should proceed from cause to effect
 This study is carried out on healthy people on whom exposure has
occurred and disease has not
 Vulnerable groups should be followed over a period of time to
identify the risk factor
 Costly to perform
Cohort study design
Population
People without disease
Exposed Un Exposed
Disease No Disease Disease No Disease
Retrospective study (case control
study)
 Easy to design and perform
 This study is performed based on medical records
 Study includes cases with health problems and controls without
disease
 They should be matched evenly age for age and sex for sex to be
valid
 Randomisation is a must
 Cost of study affordable
Interventional study
 Interventional studies attempt to demonstrate the cause-effect
relationships by altering the natural history of the disease by
intervention aimed at reducing the exposure to the offending
agent. (Sound in this case)
 Control group should be included for comparison
 Randomization should be followed to remove bias
 Single / double blind protocol can be followed
Beware of variables
 They should be identified correctly
 Incorrect identification of variables will invalidate the entire research
 Factors that could invalidate the entire research should be listed
and factorised
 The trick is in trying to unearth surprising variables
List some of the variables in our
hypothetical project
 Intensity of noise in decibel
 Number of hours of exposure / day
 Exposure of workers to ototoxic drugs
 Surprising variable – temporary / permanent threshold shift
Common pitfalls
 Sample size
 Variables
 Improperly formulated questionnaire
 Improperly matched control
Types of sample
 Convenient sample (ideally suited for our research scenario taken
up here)
 Judgement sample (according to the one who is familiar with the
characteristics of the population under study)
 Random sample (gives the most accurate and validated result)
Sample size
 Don’t hesitate to take the help of statistician at this stage
 For any successful research the confidence level should at least be
above 90% with error value of a minimum 5-10%
 Avoid online sample calculators
Variables – dependent /
independent variables
 All experiments contain variables at least one if not more
 These can be measured / studied
 Dependent variable – is dependent on independent variable
Categorical variables
 Nominal variables – Can have two / more categories
 Ordinal variable – can have two / more categories that can be
ranked
 Dichotomous variable – can have only two categories (either or) like
male / female
Continuous variables
 These are quantitative
 Classified into interval or ratio variables
data analysis
 Attempt must be made to summarize the observed variables
 If many variables are taken into consideration then coding and
categorization should be performed
 Study of frequency distribution should be resorted to analyse
complex data
 Data should be displayed as bar diagram / pie chart / histogram /
frequency distribution curves / x-y plots
Line graphs
 Useful in tracking changes over a
period of time
 Smaller changes are better
displayed
 Can also be used to compare
changes over time even for more
than one group by changing the
colour of the line
Bar graphs
 Can be used to compare things
between different groups
 Can also be used to track
changes over course of time
 This graph suits best if the changes
are larger
Pie charts
 Best used when comparing parts
of a whole
 Cannot be used to show changes
over a period of time
Area graphs
 Similar to line graphs
 Can be used to track changes
over time
 Groups must be categorized
before displaying
X-y plot
 Used to determine relationships
between two different things
 X-axis is used to plot one variable
and the y-axis is used to plot the
other
 If both variables increase at the
same time it is positive relationship
 If one variable increases while the
other decreases it is negative
relationship
Mean / median / mode
 Mean – is nothing but an average. It is the sum of values divided by
the number of values
 Median is the value that divides the distribution into half
 Mode is the value that occurs most often
Variance / standard deviation
 This is the most preferred method of variation
 It uses all the observation
 Variations would be small if the observations are bunched closely
 Variations if averaged will always be zero because positive
deviations away from the mean would cancel out the negative
deviations away from the mean
 Squaring the average of deviations is resorted to, and this average
of squared value would always stay positive
 Standard deviation is a measure of how spread out the numbers
are. It is actually the square root of variance and is indicated by
Greek letter sigma
explanation
 Measured heights of dogs in mm
 Mean = sum of all the heights
divided by 5 (394 mm)
Explantion (contd)
calculation
 Variance can be calculated by squaring the differences and
averaging them (21704)
 Standard deviation is square root of variance = 147. This number
helps in comparison.
 Use p values / chi-square test to test hypothesis
Before choosing a topic
 Conduct feasibility study
 Is it possible to complete within the given time frame
 Affordability
 Institutional support
 Can you obtain necessary literature?
 Will the topic be relevant after the completion?
Check list
 Exact date of submission
 Any word limitations
 Intermediate deadlines to meet
 Rules regarding the publication format
 Tutorial support available
Points to be borne in mind
 No harm should come to participants in the research (physical /
mental / social)
 Children / elderly / mentally retarded should not be exploited
 No physical / environmental damage should be caused
 Anonymity / privacy should be ensured
 Nothing should be done that would bring disrepute to the institution
Interviewer conduct
 Friendly and formal
 Schedule to be followed
 Prior appointment to be sought
 Treat all interviewees the same
 Prompt don’t direct
 Do not volunteer answers
 Never be patronising
 Be patient
Some useful research topics in
otology
 Incidence of conductive deafness in children and their causes
 Incidence of noise induced hearing loss
 Measles infection – does it cause otosclerosis ?
 Acceptability of hearing aids
 Age related normal hearing in Indians
Title
 Start off with a draft title
 Keep polishing it
 Avoid question marks in title
 Include the period and place of study in the title if possible
aim
 Here the aim of the study should be stated
 Inclusion and exclusion criteria may be stated here as a
subheading (ideally done in materials and methods)
Introduction - chapter
 Should contain an outline of your research
 Should contain details of what prompted you to undertake the
study
 It should also state concisely what you plan to do and where you
plan your work
 Start writing this chapter first, edit it after completing the project
Literature review
 This is central to all research
 It informs the reader how well you have prepared for the topic
 Here you take the opportunity to acknowledge other’s work
 It also informs the reader the road you plan to take
Materials and methods
 Here the exact research methodology followed is described
 There should be a description of the tests used
 Inclusion and exclusion criteria should be discussed in detail
result
 Data should be presented
 Data analysis should be presented here
 Statistical tool used for the analysis should be discussed here
conclusion
 Take time writing this one
 Give your conclusions point by point in clear terms
 Results should not be repeated but summarized here
 Practical recommendations can be included here
Bibliography
 List down all the references and citations
 All references and citations should easily be identifiable
appendix
 The material given here is for optional reading
 Copy of questionnaire
 Interview schedule
 Copy of ethical committee approval
 Copy of institutional approval
Research methodology in otolological research

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Research methodology in otolological research

  • 2. What is ideal research?  Should be reproducible  Should withstand statistical analysis  Should test a theory / hypothesis / belief  Should be beneficial to the public  Should be systematic / empirical / critical /  Should have academic integrity  Should be publishable Desist finding questions to your answers
  • 4. Factors affecting confidence interval  Sample size – Larger the sample size better is the confidence interval  Percentage – Represents the accuracy of the study  Population size – This is least important provided the samples are randomly selected. This is important when the group is relatively small and contains known group of people
  • 5. Confidence level This tells the researcher how confident the actual mean falls within the Confident interval. Standard deviation if applied tells the researcher How much variation that can be expected with the studied sample Size. Ideal SD value is 0.5.
  • 6. Sample size calculation Confidence level = Z This is a constant value 90% - confidence interval - Z score = 1.645 95% - confidence interval - Z score = 1.96 99% - confidence interval - Z score = 2.326 Sample size = (Z-score)2 * Std Dev* (1- SD) / (margin of error)2 ((1.96)² x .5(.5)) / (.05)² (3.8416 x .25) / .0025 .9604 / .0025 384.16
  • 7. Research styles  objective  subjective Ethical committee approval is a must for all types of research
  • 8. Objective type  Physical characteristics  Testing universally applicable rules / laws  Testing hypothesis  Experiments  Surveys Avoid the lure of numbers. Observation of researcher is more vital
  • 9. Subjective type  Involves social life of groups  This study is usually conducted by observation and the findings documented and explanations attempted for the observations  Usually social scientists use this modality Always assume that your work will be scrutinised by the public
  • 10. Types of objective study design  Descriptive  Analytical  Interventional Greatest danger is not failure but non submission of your work
  • 11. Descriptive study design These studies consider variance of disease in respect of time, place and person. Classic example of this design would be an attempted study on the incidence of age related degree of progressive sensori neural hearing loss. These studies provide clues that can be used to design elaborate analytical studies. Two types of descriptive studies are possible i.e. cross sectional and longitudinal.
  • 12. Cross sectional study (Descriptive Design)  This study is based on single examination of cross section of population performed at one point of time  Results can be projected on the whole population provided the study is random in nature  This is a fast and inexpensive way of ascertaining incidence of a disease
  • 13. Cross sectional study - Steps  Objective of the study should be clearly defined  Population under study should also be defined clearly  Disease / health problem to be studied should also be defined clearly (diagnostic criteria should be laid down)  Randomization of the sample should be ensured  Double blind trial has more validity  Make a list of variables  Prepare a questionnaire  Decide on a sample size
  • 14. Longitudinal study (Descriptive design)  Observations are repeated in the same population over a prolonged period of time by means of follow up examinations  Natural history of disease and its future outcome can be studied  Helps in identification of risk factors in disease causation  Also helps in finding out the incidence rate
  • 15. Advantages of descriptive studies  Provides morbidity and mortality data  Provides clue to disease etiology  Generates hypothesis which can be tested by analytical studies  Provides data for planning, organizing and evaluating preventive and curative services  Contributes to research in terms of disease occurrence by time place or person
  • 16. Analytical study design  Classic example of this design would be the study to ascertain odds of developing noise induced hearing loss.  Intensity / duration of noise exposure should be factorized.  Age and sex of the patient (variables).  Analytical study design could be prospective and retrospective
  • 17. Prospective study design (cohort / longitudinal)  Difficult to perform  Tests the hypothesis obtained by descriptive study  Should proceed from cause to effect  This study is carried out on healthy people on whom exposure has occurred and disease has not  Vulnerable groups should be followed over a period of time to identify the risk factor  Costly to perform
  • 18. Cohort study design Population People without disease Exposed Un Exposed Disease No Disease Disease No Disease
  • 19. Retrospective study (case control study)  Easy to design and perform  This study is performed based on medical records  Study includes cases with health problems and controls without disease  They should be matched evenly age for age and sex for sex to be valid  Randomisation is a must  Cost of study affordable
  • 20. Interventional study  Interventional studies attempt to demonstrate the cause-effect relationships by altering the natural history of the disease by intervention aimed at reducing the exposure to the offending agent. (Sound in this case)  Control group should be included for comparison  Randomization should be followed to remove bias  Single / double blind protocol can be followed
  • 21. Beware of variables  They should be identified correctly  Incorrect identification of variables will invalidate the entire research  Factors that could invalidate the entire research should be listed and factorised  The trick is in trying to unearth surprising variables
  • 22. List some of the variables in our hypothetical project  Intensity of noise in decibel  Number of hours of exposure / day  Exposure of workers to ototoxic drugs  Surprising variable – temporary / permanent threshold shift
  • 23. Common pitfalls  Sample size  Variables  Improperly formulated questionnaire  Improperly matched control
  • 24. Types of sample  Convenient sample (ideally suited for our research scenario taken up here)  Judgement sample (according to the one who is familiar with the characteristics of the population under study)  Random sample (gives the most accurate and validated result)
  • 25. Sample size  Don’t hesitate to take the help of statistician at this stage  For any successful research the confidence level should at least be above 90% with error value of a minimum 5-10%  Avoid online sample calculators
  • 26. Variables – dependent / independent variables  All experiments contain variables at least one if not more  These can be measured / studied  Dependent variable – is dependent on independent variable
  • 27. Categorical variables  Nominal variables – Can have two / more categories  Ordinal variable – can have two / more categories that can be ranked  Dichotomous variable – can have only two categories (either or) like male / female
  • 28. Continuous variables  These are quantitative  Classified into interval or ratio variables
  • 29. data analysis  Attempt must be made to summarize the observed variables  If many variables are taken into consideration then coding and categorization should be performed  Study of frequency distribution should be resorted to analyse complex data  Data should be displayed as bar diagram / pie chart / histogram / frequency distribution curves / x-y plots
  • 30. Line graphs  Useful in tracking changes over a period of time  Smaller changes are better displayed  Can also be used to compare changes over time even for more than one group by changing the colour of the line
  • 31. Bar graphs  Can be used to compare things between different groups  Can also be used to track changes over course of time  This graph suits best if the changes are larger
  • 32. Pie charts  Best used when comparing parts of a whole  Cannot be used to show changes over a period of time
  • 33. Area graphs  Similar to line graphs  Can be used to track changes over time  Groups must be categorized before displaying
  • 34. X-y plot  Used to determine relationships between two different things  X-axis is used to plot one variable and the y-axis is used to plot the other  If both variables increase at the same time it is positive relationship  If one variable increases while the other decreases it is negative relationship
  • 35. Mean / median / mode  Mean – is nothing but an average. It is the sum of values divided by the number of values  Median is the value that divides the distribution into half  Mode is the value that occurs most often
  • 36. Variance / standard deviation  This is the most preferred method of variation  It uses all the observation  Variations would be small if the observations are bunched closely  Variations if averaged will always be zero because positive deviations away from the mean would cancel out the negative deviations away from the mean  Squaring the average of deviations is resorted to, and this average of squared value would always stay positive  Standard deviation is a measure of how spread out the numbers are. It is actually the square root of variance and is indicated by Greek letter sigma
  • 37. explanation  Measured heights of dogs in mm  Mean = sum of all the heights divided by 5 (394 mm)
  • 39. calculation  Variance can be calculated by squaring the differences and averaging them (21704)  Standard deviation is square root of variance = 147. This number helps in comparison.  Use p values / chi-square test to test hypothesis
  • 40. Before choosing a topic  Conduct feasibility study  Is it possible to complete within the given time frame  Affordability  Institutional support  Can you obtain necessary literature?  Will the topic be relevant after the completion?
  • 41. Check list  Exact date of submission  Any word limitations  Intermediate deadlines to meet  Rules regarding the publication format  Tutorial support available
  • 42. Points to be borne in mind  No harm should come to participants in the research (physical / mental / social)  Children / elderly / mentally retarded should not be exploited  No physical / environmental damage should be caused  Anonymity / privacy should be ensured  Nothing should be done that would bring disrepute to the institution
  • 43. Interviewer conduct  Friendly and formal  Schedule to be followed  Prior appointment to be sought  Treat all interviewees the same  Prompt don’t direct  Do not volunteer answers  Never be patronising  Be patient
  • 44. Some useful research topics in otology  Incidence of conductive deafness in children and their causes  Incidence of noise induced hearing loss  Measles infection – does it cause otosclerosis ?  Acceptability of hearing aids  Age related normal hearing in Indians
  • 45. Title  Start off with a draft title  Keep polishing it  Avoid question marks in title  Include the period and place of study in the title if possible
  • 46. aim  Here the aim of the study should be stated  Inclusion and exclusion criteria may be stated here as a subheading (ideally done in materials and methods)
  • 47. Introduction - chapter  Should contain an outline of your research  Should contain details of what prompted you to undertake the study  It should also state concisely what you plan to do and where you plan your work  Start writing this chapter first, edit it after completing the project
  • 48. Literature review  This is central to all research  It informs the reader how well you have prepared for the topic  Here you take the opportunity to acknowledge other’s work  It also informs the reader the road you plan to take
  • 49. Materials and methods  Here the exact research methodology followed is described  There should be a description of the tests used  Inclusion and exclusion criteria should be discussed in detail
  • 50. result  Data should be presented  Data analysis should be presented here  Statistical tool used for the analysis should be discussed here
  • 51. conclusion  Take time writing this one  Give your conclusions point by point in clear terms  Results should not be repeated but summarized here  Practical recommendations can be included here
  • 52. Bibliography  List down all the references and citations  All references and citations should easily be identifiable
  • 53. appendix  The material given here is for optional reading  Copy of questionnaire  Interview schedule  Copy of ethical committee approval  Copy of institutional approval

Editor's Notes

  1. What I am not Not a statistician Not an epidemiologist
  2. Ideally confidence interval should be 90 - 95% It represents how accurate your sample matches the population studied.
  3. Larger the sample size better is the confidence interval. This relationship is not linear. 95% confidence level means that your results. In lay terms it tells you the margin of error. If the confidence interval is 50% then the result is questionable.
  4. Sample size calculation for 95% confidence interval. Margin of error is another constant = .05 This equation is for unknown population size / very large population size. If the population size is small or known then calculators are available
  5. Analysis of objectively observable data
  6. Descriptive study design helps in formulation of idea for analytical / interventional studies.
  7. This study describes the data being studied. It is also known as statistical research. It just gathers accurate data but does not go behind the scene to Explain the cause. Cross sectional study: Is a single examination performed on a cross section of population At one point of time. Results can be projected across the whole population provided It is performed in a random manner. These are fast inexpensive way of determining the incidence Of a disease.
  8. A small modification of this study could make it more useful if a series of cross sectional studies Are performed at several points in time. This is known as serial survey design
  9. Objective of the study should be SMART: Specific Measurable Attainable Realistic Time bound
  10. This design checks whether outcome is related to exposure. Can be observational researcher does not influence / interventional (clinical drug trials)
  11. Tests the hypothesis obtained by descriptive study or review of literature Cohort – group of persons possessing a characteristic in common
  12. Cohort is chosen from general population Divided into 2 groups exposed and unexposed Both groups should be evenly matched Disease outcome and diagnostic criteria should be defined before hand Follow up is similar for both groups Exposed: with disease = a without disease = b Unexposed: with disease = c without disease = d Sample size a+b+c+d Exposed incidence rate:a/a+b x100 Unexposed incidence rate: c/c+d x 100 Relative risk = a/a+b ______ c/c+d
  13. Starts from a health condition and goes backwards through medical records. This study is done to find a cause in diseased patients where the disease is rare with a long latency
  14. Sparrow story
  15. Teacher wants to know how students secure marks in maths test: Dependent variable – test mark (0-100) Independent variable – revision time / IQ of the student. In experimental research the aim is usually to manipulate independent variables and then Examine the effect this change has on dependent variable. In non experimental research the researcher should not manipulate independent variables. Eg. Study of behavioural changes after using narcotics.
  16. Nominal variables – discrete and qualitative Eg. Properties: types include House, shop condo etc. Ordinal variable: qualitative ranking like good / average / bad
  17. Interval variable – difference between 10-20 degrees C is 10 Difference between 40 – 50 degrees is also 10 Ratio variables are interval variables. It is a ratio of measurements. A distance of 10 m is equal to twice the distance of 5 m. (zero is clearly defined)
  18. median – if observations are arranged in increasing order then the median is the middle of the observation
  19. All values to be considered.
  20. Mean height calculated and plotted. Difference from mean is plotted
  21. Variance is = 206 2 + 76 2 + (-224) 2 + 36 2 + (94 2) ______________________________________________________ 5