Terminology

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Terminology

• Scientific
• Epidemiological
• Statistical

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Scientific terminology

• Empirical Fact
• Obvious observation from experiment
• Empirical observation a process of gathering
  information by direct observation
• Evidence is said to be empirical if it is based
  on observations and measurements of reality

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Terminology cont.

• Empirical research is
• Research which is based on observed and measured
  phenomena and
• Is research that derives knowledge from actual
  experience rather than from theory or belief

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Terminology cont.

• Assumption
• A fact or statement taken for granted
• Accepted as true based on logic, without proof
• Hypothesis
• An educated prediction of the outcome of an
  experiment
• Some consider assumption to be synonymous with
  hypothesis

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Terminology cont.

• Law
• Principles that are taken to be universally
  applicable
• Newtons laws of motion
• Boyles law
• A statement of fact detailing a sequence or
  relation of phenomena that is invariable under
  given conditions (Stedmans Medical Dictionary)

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Terminology cont.

• Theory
• An explanation for some phenomenon which is based
  on observation, experimentation, and reasoning
• Hypothesis that is well confirmed or established
• Cause
• Something that makes an event happen
• Science is often interested in looking at
  cause-effect relationships

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Theory vs. hypothesis

• A theory is an explanation
• The validity of a theory rests upon its ability
  to explain phenomena
• Theories may be supported, rejected, or modified,
  based on new evidence
• A hypothesis is a testable idea
• Scientists do not set out to prove hypotheses,
  but to test them
• Often multiple hypotheses are posed to explain
  phenomena and the goal of research is to
  eliminate the incorrect ones

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Terminology cont.

• Objectivity
• Scientists are responsible for putting aside
  their biases and beliefs and seeing the world as
  it really is
• No one is ever perfectly objective
• Some scientists are less objective than others,
  which is one reason we have to critically
  evaluate research

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Scientific method

• The principles and empirical processes of
  discovery and demonstration considered
  characteristic of or necessary for scientific
  investigation . . .
• The American Heritage dictionary of the
  English language. 4th ed. 2000, Boston Houghton
  Mifflin. xxxvii, 2074 p.

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Scientific method cont.

• Generally involving
• The observation of phenomena
• The formulation of a hypothesis concerning the
  phenomena
• Experimentation to demonstrate the truth or
  falseness of the hypothesis
• A conclusion that validates or modifies the
  hypothesis

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Cause as risk factor

• A cause is a factor (or member of a set of
  factors) which results in a sequence of events
  that eventually result in an outcome
• Exposure ? Outcome
• Cause ? Effect

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Causation

• Causation is investigated by determining an
  association (link) between exposure and outcome
• Examples
• Smoking lung cancer
• Chiropractic care optimal health
• Study of causation leads to inference
• From statistical sample data to generalizations
  (to a target population) usually with calculated
  degrees of certainty (95)

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Establishing cause
Temporal Precedence
Cause
Effect
then
Time
Why this is important
Cyclical Functions
Pain levels
Time
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Theory

• A reasoned explanation of known facts or
  phenomena that serves as a basis of investigation
  by which to seek the truth Stedmans

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The Building Blocks of Theory

• Concepts
• Conceptual definitions are abstract
• Ideas for research
• Operational definitions
• Operational definitions are concrete
• Deduced from conceptual definitions
• Propositions
• Statements of relationships among concepts

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Concepts

• Abstractions that allow classification of
  observations
• When scalar values can be assigned, they may
  become variables
• Variables must be operationally defined

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Operational Definitions

• Description and explanation of the exact
  procedures for measuring or observing the
  phenomenon, event, or behavior

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Propositions

• Propositions state the nature of the relationship
  between variables (concepts)
• Hypotheses are derived from propositions
• An hypothesis is a statement about the expected
  relationship between two or more concepts that is
  based on a theory and that can be tested

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Chiropractic Concepts

• Variables
• Adjustment
• Subluxation
• Health

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Chiropractic Propositions

• Between subluxation and health
• Subluxation Health
• Between adjustment and subluxation
• Adjustment Subluxation
• Between adjustment and health
• Adjustment Health

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Chiropractic Theory and Clinical Epidemiology

• Subluxation assessment performance
• How capable are chiropractors at detecting
  subluxations
• Adjustment treatment performance
• Health outcome performanceOutcome measures may
  detect less pain, increased mobility, less
  illness, etc.

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Epidemiology

• Epidemiology
• The science concerned with the patterns of
  disease frequency in human populations
• Distribution of disease by person, place, time
• Assumptions
• Disease does not occur randomly
• Disease has identifiable causes which can be
  altered and thus prevent it from developing

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Definition of Epidemiology

• The study of the distribution and determinants of
  health-related states or events in specified
  populations, and the application of this study to
  control health problems. Dictionary of
  Epidemiology

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Aims of epidemiologic research

• Describe the health status of a population
• Explain the etiology of disease
• Predict the disease occurrence
• Control the disease distribution

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John Snow - the "father of modern epidemiology"

• In 1854 a cholera epidemic raged across Europe
• The disease is sudden and death can result in as
  little as a week
• One outbreak in London claimed 500 people in just
  ten days

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John Snow cont.

• Dr. Snow walked through London documenting the
  location of every cholera death
• Created a map which indicated that the outbreak
  had occurred within a 250 yard radius of a
  certain water pump
• The evidence pointed to the water as the main
  source of the disease

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John Snow cont.

• He had the water pumps handle removed
• His theory was proved correct because within days
  the epidemic rapidly subsided
• The medical profession did not accept his theory
• They thought miasma caused the disease
• However, this was the first known example of
  epidemiological research

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Epidemiology is used in clinical practice to

• Describe the natural history of diseases
• Discuss disease causality
• Proximate (biological)
• Distal (social environmental)
• Evaluate diagnostic testing
• Usefulness, sensitivity, specificity
• Set cutoff points, and develop screening
  strategies

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Epidemiology in clinical practice cont.

• Evaluate prognosis
• by identifying prognostic factors
• through cohort and case control studies 

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Epidemiological Reasoning

• Derive inferences regarding possible causal
  relationships
• Determine whether these relationships are
  spurious or true
• Discussion
• Associations (height weight)
• Causal relationships (overeating weight)
• Threats to validity (some of group dieting)
• Play of chance (statistical association)

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Figure 1. U.S. Mortality Data for Seven Selected
Disorders in 1997. A total of 16,500 patients
with rheumatoid arthritis or osteoarthritis died
from the gastrointestinal toxic effects of
NSAIDs. Data are from the National Center for
Health Statistics and the Arthritis, Rheumatism,
and Aging Medical Information System.
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Estimating Risk is there an association?

• Compare the risk of outcome in exposed to the
  risk of outcome in the non-exposed
• Relative Risk
• Calculated in cohort studies
• Prospective
• Odds Ratio
• Calculated in case-control studies
• Retrospective

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Relative Risk

• RR1, risk in exposed equal to risk in
  non-exposed (no association)
• RRgt1, risk in exposed greater than risk in
  nonexposed (positive association, possibly
  causal)
• RRlt1, risk in exposed less than risk in
  nonexposed (negative association, possibly
  protective)

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Relative Risk example

• Cohort study where 50 subjects exposed to dust
  (work in a coal mine) and 50 subjects work in
  offices followed for 20 years
• Exposed 20/50 develop lung cancer
• Not exposed 5/50 develop the condition
• RR4
• Exposed were 4 times more likely to develop lung
  cancer

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2X2 contingency table
Disease Present Absent
a b
c d
Exposure Present
Absent
Risk Rate of Developing Outcome in Exposed
Risk Rate of Developing Outcome in NON-Exposed
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Lung cancer example
Lung cancer Present Absent
20 30
5 45
Coal dust Present exposure
Absent
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Case-control studies Use Odds Ratio
    Outcome Outcome
    Present    Absent
 Exposure   Present a  b
 Exposure   Absent c d
OR a/c Odds of Being Exposed in Cases
OR b/d Odds of Being Exposed in Controls
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Basic biostatistics and epidemiological terms

• Populations and samples
• Prevalence and incidence
• Statistics
• Reliability
• Validity
• Bias

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Sample

• One is interested in the parameters of a
  population but must, for practical reasons,
  estimate them by describing the statistics of a
  sample
• A subset of a population
• Selected from a population
• 100,000 randomly selected US residents
• LBP patients recruited for a clinical trial
• HMO members randomly selected from files

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Sample cont.

• Sample statistics are only estimates of the
  corresponding population quantities because they
  are computed from a sample selected from the
  population
• Therefore, based upon statistics derived from
  samples, population parameters are estimated

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Populations and Samples
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The intended population represented by the sample

• Simply stated, a population is a group of people
  in a defined setting or with a certain
  characteristic
• The general population
• Adults with low back pain
• Residents of North Carolina
• Members of a California HMO
• Chiropractic students
• More to come in EBC 2

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Sample size . . .

• Affects the probability of detecting a real
  difference between groups if there is one
• Affects the probability that a difference seen
  between samples reflects a real difference
  between the groups, and is not just a random
  occurrence
• The sample must be representative of the
  population

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Sample size is not happenstance!

• To draw conclusions about the effectiveness of
  treatment (i.e. the difference between 2 groups
  outcomes) a RCT must have the statistical power
  to detect a real difference
• Sufficient numbers of subjects required to reach
  statistical significance
• Often not calculated (77 of the time
  chiropractic, 83 spine surgery journals)

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Importance of sample size

• Drawing conclusions about a population based upon
  a sample
• Study says Group A Group B
• Caution - Small numbers increase the chance of a
  Type II error
• Saying there isnt a difference, when there is
• Study says Group A ? Group B
• Caution - Small numbers increase the chance of a
  Type I error
• Saying there is a difference, when there isnt

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Prevalence and incidence

• Prevalence proportion of a defined population
  that has a condition at a given point in time
• Estimated with cross-sectional study
• Incidence proportion of a defined population
  that develops a condition over a defined period
  of time
• Estimated with longitudinal study

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Measures of morbidity

• Prevalence
• The number of affected persons in the population
  at a specific time divided by the number of
  persons in the population at that time
• A slice through the population at a point in time
  at which it is determined who has the disease and
  who does not
• The numerator includes a mix of people with
  different durations of disease, therefore
  prevalence is not a measure of risk

Morbidity - Any departure, subjective or
objective, from a state of physiological or
psychological wellbeing. A diseased state.
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Measures of morbidity

• Incidence
• The number of new cases of a disease that occur
  during a specified period of time in a population
  at risk for developing the disease
• A measure of risk
• The time period must be clearly stated

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Prevalence vs. Incidence

• Chronic incurable diseases like diabetes can have
  a low incidence but high prevalence, because the
  prevalence is the cumulative sum of incidence
  rates from past years
• Short-duration conditions such as the common cold
  can have a high incidence but low prevalence,
  because many people get a cold each year, but few
  people actually have a cold at any given time

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Prevalence and incidence illustrated
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