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Title: Session 3 Quantitative data: how are they collected and used Qualitative: data Qualitative research


1
Session 3Quantitative data how are they
collected and used Qualitative
dataQualitative research methods and designs
2
Session objectives
  • By the end of this session you will be able to
  • Identify main types of types of data collection
    methods
  • The differences between surveillance, monitoring
    and research data
  • Identify some common terms used in epidemiology
    will be examined
  • Identify the five types of quantitative data
  • Understand some common epidemiological terms
  • Some measurements of health status
  • Understand some basic measures of risk
  • Understand why sample size is important

3
Main types of types of quantitative data
collection methods
  • Quantitative data have different characteristics
    from qualitative data
  • To be valid and objective, data must be collected
  • Systematically
  • From a complete or truly representative sample
  • In the same way by all collectors
  • NB We will be exploring quantitative data and
    data collection techniques later in the course

4
Characteristics of quantitative data
  • Quantitative data can be either counted or
    measures
  • They can be used
  • To describe and summarise
  • To compare between groups
  • To estimate / predict effect sizes

5
What can quantitative data tell us?
  • Epidemiologic triad
  • Who, When, Where
  • The size of the problem
  • To some extent Why
  • But not
  • How it feels to be in an affected group
  • Are interventions appreciated and why,
  • What was the experience of the people involved

6
Types of quantitative data
  • Continuous (Ratio)
  • Continuous
  • Discreet
  • Ordinal
  • Interval
  • Binomial
  • Categorical (nominal)

7
Continuous (ratio) data
  • Regular and ordered numerical data
  • Discrete or continuous
  • Has a true zero
  • Precise relationship between numbers e.g. 10
    is twice 5
  • in family (discrete)
  • Age (continuous)
  • Concept of normal distribution
  • Mean average
  • Median middle
  • Mode most common

8
Frequency Distribution
If there are enough observations, and if
observations are random/systematic (ie not
biased) In normal distributions Mean Median
Mode
9
Confidence Intervals (eg, 95)
Range of values between which we are 95
confident that the true value in the population
lies If we sample a population randomly and
without bias 100 times the true average value
will lie within the CIs 95 times (and outside it
5 times)
10
Ordinal data
  • Data points are in a specific order, and the
    order denotes a meaning
  • Placement in a race
  • House numbers in a street
  • A, B, C
  • Monday, Tuesday, etc

11
Interval data
  • Scaled measure with even and known distance
    between data-points, BUT
  • 0 does not mean nothing
  • Although the distance between data-points is
    regular, it is not continuous - 10 is NOT twice
    5
  • e.g. temperature scale (30OC is not twice as hot
    as 15OC)

12
Binomial data
  • Two categories, which can be used for
    stratification (sub-analysis)
  • Mutually exclusive
  • Yes/no
  • In/out
  • Male/female
  • Dead/alive

13
Categorical data
  • Variables have discrete sub-categories, which can
    be used for stratification (sub-analysis)
  • Mutually exclusive
  • Sub-categories have no relationship to one-another

14
The differences between surveillance, monitoring
and research data
  • Provide framework for understanding the structure
    of health status in populations
  • For being able to describe the health of defined
    populations at a point in time
  • For being able to compare same population at
    different times
  • For being able to compare different populations

15
Data collections data quality
  • Is a particular data collection a result of
    routine activity or a special effort?
  • Surveillance
  • Surveys
  • Monitoring
  • Research
  • Uses and misuses

16
Surveillance and surveys
  • Surveillance
  • Routine data collections
  • Notifications (eg of communicable diseases)
  • Monitoring (specific conditions, eg air quality,
    RTAs)
  • Special events (eg adverse drug reactions
    outbreaks, terrorist activities)
  • Registries (births, cancers, immunisation)
  • Surveys
  • Specific data collections
  • Epidemiological studies

17
Routine repository data collections
  • Completeness of repository data collections
    depends on source
  • Generally excellent-to-fairly-complete
  • Laboratory notifications (usually automated
    notifications)
  • Research data (vested interest)
  • Routine event-based (eg births and deaths)
  • Routine (legislated) notifiable diseases
  • Generally poor-or-quality-not-known
  • Special interest group

18
Data quality
  • Depends on several important factors
  • Collection forms - should not be complicated, esp
    for large collections (KISS principle)
  • Timeliness data collection should happen ASAP
    after event
  • Accuracy data recorder should
  • be capable of recording/conveying relevant
    detail
  • understand the purpose of data collection

19
Counting numbers and causes
  • Cultural differences in the ways diseases and
    deaths are understood and reported
  • Diagnostic capacity varies, even within one State
  • ICD 10 coding systems are an attempt at
    international standardisation
  • Some jurisdictions use DRGs (as a part of health
    care funding mechanism), but the codes are not
    transportable

20
Epidemiological Indices
  • Numerator and denominator
  • Incidence and prevalence
  • Rate
  • demographic
  • birth
  • growth
  • mortality
  • incidence
  • attack
  • prevalence
  • case fatality
  • Ratio and proportion
  • Burden of disease studies

21
Numerator and Denominator
  • Numerator
  • Number of new events/cases during a specified
    period, the portion used to calculate a rate or
    ratio
  • Denominator
  • The total population at risk in a
    fraction/calculation of risk ratio or rate

22
Rates
  • Incidence
  • New cases in specified period
  • cum. Person-years observation
  • Cumulative incidence
  • New cases in specified period_
  • Total persons disease free at start
  • (Point) prevalence rate
  • people with disease during a (usually short)
    time
  • total population under study
  • Example Household study 6524 children lt5 Did
    child have diarrhoea on day of survey or during
    previous 15 days
  • 982 had diarrhoea
  • Period prevalence 982/6524 15.1
  • (Barros, Victoria, Forsberg et al Bull WHO,
    86(1)59-65,1991

23
Mortality (Deaths)
  • Deaths are a commonly used measure of disease
  • Mortality rates (the proportion of cases which
    are fatal) are high in important diseases in
    developing countries and are quite a good measure
    of disease (not so true in developed countries)
  • Deaths from communicable diseases are generally
    high, and are much lower in western countries

24
Measures of morbidity and mortality
  • Morbidity is a general term which refers to
    incidence of disease, including
  • The illnesses experienced, by
  • The number of people who are ill, and
  • The length of time they are ill for
  • Attack rate
  • The proportion of people in a population who
    develop a specific disease
  • __ _ Number of cases__________
  • Total population (usually per 100,000)
  • Case fatality rate
  • The proportion of cases of a specified disease
    who die as a direct cause of that disease
  • deaths from disease in a specified time
    period and place
  • Total cases of the disease in the time
    period and place
  • The death rate
  • An estimate of the person-time death rate in the
    population who die during a specified period
    (usually 1 year) (may be different time period,
    eg during an outbreak)
  • deaths in a specified time period and place
  • Population in the same area at risk of
    dying

25
Demographic growth
  • (Crude) Birth rate
  • Live births in a geographical area in a given
    year
  • Mid-year or average population in the same area
  • Population growth rate
  • (Live births deaths) in a geographical area in
    a given year
  • Mid-year or average population in the
    same area
  • Migration
  • inbound
  • outbound

26
Ratio and Proportion
  • Ratio
  • One quantity divided by another
  • Many types, some have special rules
  • Risk Rate ratio, relative risk, odds ratios
  • Proportion
  • Numerator expressed as a
  • Decimal fraction (eg 0.2)
  • Vulgar fraction (eg 1/5)
  • Percentage (eg 20)

27
Burden of disease studies
  • Adjusted measures
  • PYLL (Potential years of life lost)
  • A measure of the impact of deaths from disease on
    society, the years which would have been lived
    had the disease not happened
  • QALYs (Quality adjusted life years)
  • Overall life expectancy reduced by the years lost
    due to chronic disease, disability etc
  • DALYs (Disability adjusted life years)
  • Life expectancy adjusted for long-term disability
    taking treatments into account widely used but
    criticised as they are based in part on guesswork

28
Some common epidemiological terms describing the
measurements of health status
  • Indicators what are they?
  • Epidemiological indicators
  • Economic indicators
  • The DALY
  • The QALY
  • Some qualitative health indicators
  • Social indicators

29
Health indicators
  • Can a common measure be used as an advocacy
    tool?
  • Epidemiological indicators
  • Economic indicators
  • Social indicators
  • Fatal and non-fatal indices

30
Epidemiological indicators
  • Numerator and denominator
  • Incidence and prevalence
  • Rate
  • Demographic vital statistics (birth, population
    growth and change, mortality)
  • Ratios and proportions
  • incidence
  • attack
  • prevalence
  • case fatality
  • Premature mortality (potential) years of life
    lost ((P)YLL) is the standard measure
  • What standard to use?

31
Economic indicators
  • Burden of disease studies
  • Health Expectancies
  • eg disability free life expectancy (DFLE)
  • Health Gaps
  • DALY (DALY YLL YLD)
  • QALY
  • Quantified burden of disease
  • Death
  • Disability
  • Years lost due to disability (YLD)
  • Non-fatal disease measurement
  • Card sort
  • Visual analogue
  • Time trade off
  • Standard gamble
  • Person trade off

32
The DALY
  • First used extensively in the World Bank 1993
    Annual Report Investing in Health (see World
    Bank website)
  • A summary measure of population health
  • Measures fatal and non-fatal outcomes
  • Allows estimates of health impact/ effectiveness
  • 1 DALY 1 year lost of healthy life

33
The QALY
  • Another way of summarising population health
  • Common measure for fatal and non-fatal outcomes
  • Covers more than the DALY, includes some impacts
    of disability
  • Estimates of health impact/ effectiveness
    possible

34
Qualitative health indicators
  • Opportunity - resilience, ability to withstand
    stress, reserve
  • Perceptions - satisfaction, self-rating
  • Social function - participation, limitations in
    social roles, contact, intimacy
  • Psychological function - happiness, reasoning
    capacity, distress, behavior
  • Physical function - mobility, sleep, performance,
    fatigue
  • Impairment - symptoms, signs, diagnosis,
    physiological measures

35
Social health indicators
  • Housing / shelter
  • Food
  • Education
  • Employment

36
Basic measures of risk
  • Higher incidence in a group in the population
  • Basic rate
  • Higher exposure rate in disease group that
    comparison group
  • Risk ratio, odds ratio

37
Exercise 3 Data types
38
Exercise 3 Data types (Answers)
39
Sampling techniques
  • How are populations sampled in order to study
    them?
  • How do you know how many people to sample?
  • A sample should reflect the characteristics of
    the population from which it is drawn
  • 2 basic kinds of sampling techniques
  • Based on probability sampling (random)
  • Based on convenience sampling (purposive)

40
Sample Size Calculations
A Range of values within which we are 95 sure
the true value is situated
41
Sampling techniques
  • A sample ought to possess all the characteristics
    of the population from which it is drawn to be
    fully representative of this population
  • Some common sampling methods
  • Total population
  • Simple random
  • Systematic
  • Cluster
  • Stratified and matched ( one sample per stratum
    or group to be compared)
  • Latin squares

42
Total population
  • All members of a population are identifiable
  • All members are contactable
  • Possible with notifiable diseases (eg
    meningococcal disease, Q-fever) and other events
    (eg childbirth)
  • Less successful with common diseases
  • Unlikely to be successful without
    population-bases registries

43
Simple Random Sampling
  • Each member of the population (or sampling unit)
    has an equal chance of being selected
  • Requires a sampling frame
  • Required sample is randomly chosen one-by-one
    from numbers representing each unit
  • Often costly and time consuming

44
Systematic Sampling
  • Population is listed systematically say by
    number or alphanumerically
  • Sampling fraction (k) is calculated by dividing
    the population (N) by the sample size (n)
  • eg N 18,000
  • n 900
  • k 20
  • The first member of the sample is selected by
    choosing a random number between 1 and the
    sampling fraction (1 and 20)
  • Every 20th member is then sampled until the list
    is exhausted

45
Cluster Sampling
  • The population is grouped into clusters or
    primary sampling units (PSUs)
  • A PSU could be a village, a district, a refugee
    camp, a school or hospital, or any well-defined
    group of persons or households
  • You do need to know the population size of each
    PSU
  • Clusters (for WHO studies usually 30) are chosen
    in Stage I with a probability according to size
  • In Stage 2, an equal number of sampled persons or
    households is chosen randomly

46
Stratified and matched sampling
  • Strata / matching criteria are identified prior
    to commencement
  • May be structured to reflect population, to may
    be deliberately constructed to collect more from
    specific groups
  • Strata groups which will be compared have equal
    numbers

47
Accuracy - the aim of every study
48
Confidence Intervals
Vaccination Coverage Town A 20 10 Town
B 45 10 Town C 60 10 Different ?
C
A
B
0 10 20 30 40
50 60 70 80 90
100
49
Is there a difference between 2 groups? (two
proportions?)
Look at confidence intervals
(a)
No difference detected
Definite difference detected
(b)
Not sure Test (do ?2 or t-test calculate p
value)
(c)
50
Part two Qualitative data
  • By the end of this session you will be able to
  • Understand some common qualitative data
    collection methods - how and when they are used
  • Focus groups
  • Nominal group techniques
  • Delphi methods, In-depth interviews
  • Visual materials and unobtrusive methods
  • Action research in community health settings
  • Combined quantitative and qualitative methods
    when, how and why

51
What can qualitative data tell us?
  • The experience of the disease/health event
  • How it feels to be in an affected group
  • Are interventions appreciated and why,
  • What was the experience of the people involved
  • And to some extent Why
  • But nothing about the epidemiologic triad,
  • Who is affected
  • When did it happen
  • Where do they fit in to their community
  • The size of the problem

52
How are they used?
  • To understand peoples perceptions and meanings
    of a situation or process
  • To delineate attitudes
  • To explain practices and processes

53
When they are used?
  • To inform background to study
  • To identify common experiences
  • To frame quantitative questions
  • To enrich quality of data
  • To understand some quantitative results needing
    further exploration
  • Sometimes, to understand causality in terms of
    the above

54
Theoretical Frameworks
55
Some commonly used qualitative data collection
methods
  • Interactive
  • Interviews
  • In-depth interviews
  • Focus groups
  • Nominal group techniques
  • Participant observation
  • Delphi methods
  • Diary
  • Unobtrusive
  • Observation
  • Visual materials
  • Secondary analysis of existing data

56
Interviews
  • Face to face, telephone, and, internet-based
    techniques
  • Structured ltltlt semi-structured gtgtgt unstructured
  • Structured questionnaire (large surveys needing
    consistent approach)
  • Interviewee Respondent
  • Semi-structured Interview schedule, aide
    memoire (small scale studies)
  • Unstructured conversation geared towards
    research topic (small scale studies)
  • Semi- and un-structured interviews are designed
    to elicit meaning and context to responses
  • Interviewee Informant

57
In-depth interviews
  • Dynamic process
  • Theme list rather than interview schedule
  • Often take 1-2 hours
  • Questions may evolve as the interviews progress
    and the researcher develops and integrates
    understanding
  • Researcher can use prompts and go back to
    previous questions if it helps understanding
  • Needs a skilled interviewer taped if possible
    and transcribed

58
Focus groups
  • Groups of 4-10 people based on a common
    experience
  • eg New mothers, women at work, bus drivers
  • Held usually at neutral location
  • Usually take no more than an hour
  • Should be a relaxed and friendly process
  • Theme list the basis for discussion
  • Not much time for evolution
  • Needs a skilled moderator and scribe
  • Taped if possible
  • Transcribed later for analysis

59
Nominal group techniques
  • People recruited on the basis of particular
    characteristics of interest, often quite
    complicated to identify, access and recruit
  • Eg IDUs, NESB people, mothers of children with a
    handicap
  • Data collection be singly or in groups
  • Used to canvas variety and common features of
    personal opinions, feelings, meanings
  • Does not identify strength of feeling

60
(Participant) observation
  • Ethnographic technique
  • Researcher may, or may not, belong to the studies
    group
  • Used to record an ongoing processes and reflect
    on meanings of practice
  • Studies of sick care
  • Studies of food handling
  • Studies of infant rearing
  • Can be useful in recording qualitative
    information of unknown scope in a systematic way

61
Observation
  • Ethnographic technique
  • Researcher may or may not belong to the studies
    group
  • Used to record an ongoing processes and reflect
    on meanings of practice
  • Studies of sick care
  • Studies of food handling
  • Studies of infant rearing

62
Delphi methods
  • Recruitment of representative group
  • Series of sets of questions with increasingly
    structured framework
  • Eg NPHP core public health functions

63
Diary methods
  • Systematic recording of reflections of a process
  • Reflections used as the raw data for further
    analysis
  • Introspective data collection however analysis
    can be illuminating
  • Think of some famous historical diaries and how
    they tell us stories

64
Visual and published materials
  • Paintings and drawings graffiti
  • Often the author is identifiable and
    contactable
  • Photographs
  • Treatment of various subgroups e.g. asylum
    seekers
  • Advertisements
  • e.g. doctors and depressed patients study
  • Printed materials eg newspaper articles
  • Risk communication study
  • Web materials esp website chatrooms

65
Secondary analysis
  • Meta analysis other syntheses of sets of
    studies
  • Some researchers return to pre-existing datasets
    (their own and other peoples) and reanalyse them
    using new frameworks and insights
  • Handle with care why were the data originally
    collected?

66
Action research in community health settings
  • With respect to a specific research question,
    action research combines
  • Published research to identify the relevant
    issues
  • A focus group of stakeholders to identify key
    issues, needs, concerns
  • Brings the findings of both back arms back to
    the group
  • The group themselves organises what action to
    take with respect to the problem

67
Combined methods and triangulation
  • Triangulation is a powerful way of collecting
    data where an outcome measure may need to be
    verified
  • MCH Nurses administration of immunisation
  • Coverage study
  • ACIR
  • Vaccine use
  • Users study
  • MCH opinion

68
Recruitment and Sampling techniques (1)
  • Probability and non-probability sampling
  • Sample size
  • Depends on study objectives, generally 20-30
  • Notion of saturation
  • If any statistical analysis is to be done,
    minimum of 5 participants for each cell,
    usually at least 30

69
Recruitment and Sampling techniques (2)
  • Theoretical (grounded theory)
  • Where are the data and where will you find them
  • Quota
  • Snowball
  • Purposive (judgemental)
  • Convenience

70
Qualitative data analysis
  • Grounded theory (thematic analysis)
  • Content analysis
  • Discourse analysis
  • Semiotics / post-structuralism

71
Ethical considerations
  • Today some methods are becoming harder to
    undertake because of ethical constraints around
  • Privacy issues
  • Observation techniques
  • Recruitment techniques

72
References
  • Good summaries to be found in
  • Kerr, Taylor and Heard (eds) Handbook of Public
    Health Methods. McGraw Hill, 1998
  • Liamputtong and Ezzy. Qualitative research
    Methods, OUP, 2004
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