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BHS II Exam > 6. EBD III > Flashcards

6. EBD III Flashcards

1
Q

Screening using DMFT/DMFS

DMFT/DMFS - the # of decayed, missing, or filled teeth (T) or surfaces (S) in a mouth
● best known of all ____
● deft and defs - primary teeth, “e” is a primary tooth
indicated for ____
● limitations:
○ can be invalid if teeth are lost for ____ reasons (trauma, periodontal disease, ortho)

A

dental indices
extraction
non-carious

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2
Q 
Diagnosis -
Specific \_\_\_\_
Can involve additional information (complaint of pain, physical sign)
Screening -
Population 
\_\_\_\_
A

individual

asymptomatic

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3
Q 
Heart attack
10 patients are taking a particular blood pressure drug. 6 of those ten have a heart attack.
   ● \_\_\_\_ = 6/10 = 60%
● \_\_\_\_= 6/4 = 1.5
“probability”
 Difference is in what is in the \_\_\_\_.
A

risk
odds
denominator

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4
Q

Rare disease

• Rare disease; odds and risk are\_\_\_\_
A

similar

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5
Q

Cohort vs. Case/Control studies

• Cohort (and experimental)
	○ People with \_\_\_\_ and asking if they develop \_\_\_\_
	○ \_\_\_\_ ratio
• Case-control
	○ People with \_\_\_\_; and looking back in time to see if they have exposure to risk factor
	○ \_\_\_\_ ratio
A 
risk factor
outcome/disease
risk
disease
odds
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6
Q

Cohort

Exposed
Unexposted

Who develops the ____

• Start with \_\_\_\_ and \_\_\_\_
A

outcome
exposed
unexposed

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7
Q

Case control

What was the ____?

____ outcome
____ outcome

• Start with the cases and controls
A

exposure

cases
control

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8
Q

Event rate - the proportion of patients in a group in whom the event is ____. 40/200 = 20%

A

observed

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9
Q

Example 1: EER/CER

• Exposed event rate
• Control event rate
	○ No \_\_\_\_
A

risk factor

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10
Q

Relative risk

RR = ____ / ____

RR > 1 a person with exposure is at ____ risk(benefit)
RR < 1 a person with exposure is at ____ risk(benefit)
RR = 1 no effect

Likelihood that someone exposed to a risk factor (or treatment) will develop the disease (or experience a benefit) as compared with someone unexposed.

A

EER
CER
increased
decreased

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11
Q

It’s all relative …
RR = 3
3 times more likely to develop condition in the exposed group

* If baseline is 30% > tripling risk will bring to 90%
* If baseline at .1% > would only increase to 0.3%
* Depends on the \_\_\_\_!
A

baseline risk

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12
Q

Relative risk = EER/CER = 8/71 = 0.11. The risk of tooth loss is decreased by ____%

A

89

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13
Q

Relative Risk/Risk Ratio

Relative risk = risk of outcome in those with ____/
risk of outcome in those without the ____

____ STUDIES AND ____ STUDIES
RR = 1 no change
RR > 1 increased risk of disease among those with exposure RR < 1 decreased risk of disease among those with exposure

A

exposure
exposure
cohort
experimental

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14
Q

Odds Ratio
Odds ratio = odds of ____ in those with the outcome / odds of ____ in those without the outcome

____ STUDIES.
OR = 1 no change
OR > 1 increased frequency of exposure among cases OR < 1 decreased frequency of exposure among cases

A

exposure
exposure
case control

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15
Q

7 dental students who went to a bar develop food poisoning. Odds ratio = Odds(cases) = ____ = 2.5 = 8.33
Odds (controls) =____ = 0.3

= 8.33

• Don't need to know everyone who ate fish
• Compare those were affected and those who didn’t, and ask who ate the fish
	○ Odds of those who were food poisoned over those who weren't
A

a/c

b/d

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16
Q

Confounding

• Universally, any study that olooks at exposrue of tv and enuropshy outcomes; include things other things that make it more complicated > \_\_\_\_ goes away
A

association

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17
Q

Potential confounders

● \_\_\_\_sex
● Body mass index at 14 years
● Parental\_\_\_\_ level
● Parental social class
● \_\_\_\_ at 4 years of age
● Mother’s alcohol consumption during pregnancy
● Mother’s \_\_\_\_ use during pregnancy
A

gender
education
babysitter
tobacco

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18
Q

Tooth loss confounding?

• Potential confounders between crown and tooth loss:
	○ \_\_\_\_
• \_\_\_\_ people - adjust for potential confounders; if can't randomize, need to measure \_\_\_\_ status so you can measure the association
A

money
randomized
socioeconomic

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19
Q

Effect Modification

Definition: when the magnitude of the ____ of the primary exposure on an outcome (i.e., the association) differs depending on the level of a third ____.

* Third variable - makes relatinoship stronger
* And no varibale - goes away entirely
A

effect

variable

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20
Q

• Where ESL - may not be harmful, but can also be beneficial and can ____ them speak more efficiently

A

help

21
Q

Effect modification

* No difference bt new \_\_\_\_ and placebo
* Thought there would be a \_\_\_\_
* In this study more \_\_\_\_ than men
A

drug
relationship
women

22
Q

Effect modification

• Look at mean HDL between gender
	○ In men, there is a new drug
	○ Statistically \_\_\_\_
• Important in including more women in research studies
• Want to weed out \_\_\_\_; but bc the relationship is different bt two groups you want to see the \_\_\_\_
A

significant
confounder
difference

23
Q

Herpes Zoster

• Odds ratio
	○ People with herpes and those without, and back in time looking at exposures
• For RA
	○ No diff bt three age strata
	○ Age is not \_\_\_\_
	○ No diff bt crude odds and adjusted odds ratio
		§ The same with those exposure and not exposed
• For lupus
	○ \_\_\_\_ ratio is diff in youngest than in the two other cohorts
	○ Crude odds ratio is an average of 3 odds ratios
	○ In lupus, age is an \_\_\_\_
A

effect modifier
odds
effect modifier

24
Q

Key points:
1. Avoid or adjust for confounding - it ____ true effects
2. Effect modification - look for it and report it
3. A given variable can be a ____, an effect
modifier, both, or ____, depending on the research question …

* Avoid confounding by \_\_\_\_
* Age can be a \_\_\_\_, not always an effect modifier
A 
masks
confounder
neither
randomizing
confounder
25
Q

Types of Studies

  1. Descriptive- used to quantify ____ status in a community (____ and incidence)
  2. Analytical - assess the ____ between exposure/disease, cause/effect
	• Descriptive
		○ Improving \_\_\_\_
		○ Not trying to generalize to other clinics
	• Analytical
		○ Make a \_\_\_\_ statement
A

disease
prevalence
relationship
quality

26
Q

• Inferential

○ Want to know about the ____

A

population

27
Q

Inferential statistics

“Is it statistically significant?”
● Based on the ____ and the ____ of effect
● Depending on the ____ of data (categorical, continuous), the statistical
tests that are used will vary …
○ Correlation coefficients - used to compare ____ data
○ T-tests - used to compare ____ data
○ Chi-square tests - used to compare ____ data
○ P values - gives us the confidence to accept or reject the ____

* Large sample size - can be significant if not impressive
* Small sample - great result, but not enough to generalize
A 
sample size
magnitude
type
continuous
continuous
categorical
null hypothesis
28
Q

• Increase study size > 40 to 80; ____ will go down; but if there is a bias that’s a ____ error that is irrespective of increasing the sample

A

randomized error

systematic

29
Q

Variable

Definition: what is being observed or measured
■ Traits or \_\_\_\_ (age, gender, race)
■ \_\_\_\_ a research is trying to
manipulate (DAU attendance)
■ Outcomes that are of \_\_\_\_
(understanding of 4 handed dentistry)
A

characteristics
dimensions
interest

30
Q

Types of Data

● Discrete values
○ Daily \_\_\_\_ (yes/no)
○ Sex
○ \_\_\_\_ (male/female/trans/fluid)
● Continuous variables
○ May take any value within a \_\_\_\_ range
○ Age, \_\_\_\_, height
○ \_\_\_\_ of DAU days attended (0% → 100%)
A 
attendance
gender
defined
weight
%
31
Q

Confidence intervals

How we go from the sample → population

• Normal distribution
• Alpha is 0.05
	○ Two tailed, so 0.025
• Value falls in \_\_\_\_ > you'll be confidence
A

range

32
Q

Hypothesis testing

○ Ho (null) : there is no difference in the ____ of days of DAU attendance between those who do and do not receive kitty cafe tickets
○ Ha (alternative): Those who receive kitty cafe lottery tickets are more likely to ____ DAU

• Continuous variable here
A

%

attend

33
Q

P-values

The probability of seeing results like ours if, in
truth, there is no difference.
● Small p (e.g. 0.03) the observed results
would occur ____ if the null hypothesis were ____.
● Large p (e.g. 0.3) the observed results would occur ____ (30% of time) if null hypothesis were ____)
● Based on the p-value, we accept or reject ____.

• \_\_\_\_ p
	○ Can reject the null hypothesis
• \_\_\_\_ p
	○ Cannot reject the null hypothesis
A 
rarely
true
often
true
Ho

small
large

34
Q

The “Magical” .05 level

Most research studies are said to be statistically significant if p

A

0.05

35
Q

Type 1 errors (alpha)

At alpha = 0.05, we accept a ____% chance of rejecting ____ when it is actually ____.

A

5
Ho
true

36
Q

Type 2 errors (beta)

Failing to reject ____ when it is ____.

A

Ho

false

37
Q

T-tests
● Assume the dependent variable has a ____
● ____ test

* Same distribution between both examples
* If attendance is greater than 45% in those who didn't have lottery attendance, then there is a diff in attendance bt both groups
* Test of means
A

normal distribution

means

38
Q

Chi-square tests
● The dependent variable does not have a ____

No variable

A

normal distribution

5

39
Q

Fishers Exact tests
● The dependent variable does not have a ____

• If cell has less than \_\_\_\_ > use fishers exact test rather than chi square
A

normal distribution

5

40
Q

Correlation Coefficient

● Between two ____ variables (i.e. GRD grade and DAU attendance)

A

continuous

41
Q

Calculating Power
Ho (null hypothesis) strength level = 500
Ha (alternative hypothesis) new drug increases strength level

Ho: mean = 500 (no effect)
Ha: mean > ____

* Don't know the reality
* If we think our study is true, and matches reality > we're good
* And if no effect in both > we're good
* If study says no effect but there is an effect > \_\_\_\_
* If study says there is an effect, but there's no reality > \_\_\_\_
A

500
type 2 error
type 1 error

42
Q

Calculating Power

• Cut off is 533
	○ Greater than this > intervention has an \_\_\_\_
• Okay with 0.05 error
	○ \_\_\_\_ for research studies
A

effect

standard

43
Q

• Cut point is 533
• More likely to think that test is not true when it is true
○ ____ error

A

beta

44
Q

• Power is related to ____
○ 1 - beta
• Alternative hypothesis
○ Think direction will be in a specific way - ____ tailed
○ If can go either way -____ tailed alt hypothesis

A

beta
one
two

45
Q

Calculating Power

B = beta ~ \_\_\_\_
E = \_\_\_\_ size 
A = \_\_\_\_
N = \_\_\_\_size
A

power
effect
alpha
sample

46
Q

By convention, beta < 20% so Power > ____%

* \_\_\_\_ size comes into play
* Beta is usually less than 20 and power is greater than 80
A

80

sample

47
Q

B = beta
E = effect size
(difference between ____) A = alpha
N = sample size

• Expect big effect size - test pop will \_\_\_\_ from population without intervention a lot > large effect size (more people show up bc of lotto tickets); and vice versa
	○ \_\_\_\_ of effect will affect power calculations
	○ How well the drug/intervention is designed; should have an idea before going into study about what the ES is
A

means
differ
size

48
Q

• Alpha is usually pre-determined

○ If beta is 0.2, and alpha is ____

A

0.05

49
Q

• All comes down to ____
○ If expect ES to be largely different; then you don’t need a ____sample to be well powered
○ If smaller sample > less ____ > the sample can allow you to have a good ____ regardless of smaller effect size
• Sample size is KING for power calculations

A

sample size
large
error
beta

BHS II Exam (7 decks)

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