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First Aid > Public health > Flashcards

Public health Flashcards

1
Q

cross sectional study

A
  • frequency of disease and frequency of risk-related factors are assessed in the present
  • What is happening?
  • measures prevalence and risk factor association
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2
Q

case-controlled study

A
  • compares a group of people with disease to a group without

- looks to see if odds of exposure or risk factor differs

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3
Q

cross sectional study in my words

A
  • takes a slice
  • takes place at the present
  • measures prevalence
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4
Q

case-controlled study in my words

A
  • always in the past
  • split by groups that do and don’t have disease
  • looks for if something was a risk factor
  • “if they have the disease, did something put them at risk”
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5
Q

cohort study in my words

A
  • “if they have a risk, did they develop the disease”
  • measure relative risk
  • can be in the past or future
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6
Q

triple blind

A

blind to analysis of data

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7
Q

case-fatality rate

A

number of fatal cases / total number of cases

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8
Q

95% is how many SDs

A

1.98 (99% = 2.58)

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9
Q

standard error

A
  • standard deviation of a number of sample means

- SD/ square root of n

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10
Q

confidence interval

A
  • accounts for variability of sample means

- = mean +- z score + standard error

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11
Q

standard error takes into account what two factors

A

standard deviation and sample size (n)

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12
Q

hawthorne effect

A
  • observer effect

- subjects change their behavior because they know they are in a study

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13
Q

Berkson’s bias

A
  • specific selection bias created by choosing hospitalized patients as control group
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14
Q

lead-time bias

A
  • using a screening method that detects a disease earlier, leading to an apparent prolongation of survival
  • example: screening for PSA diagnoses prostate cancer earlier leading to longer survival times
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15
Q

Pygmalion effect

A

researchers belief in efficacy of treatment can change its actual effect
- example: if you think people are stupid, your intervention wont work as well

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16
Q

recall bias

A
  • inaccurate recall of past exposures

- usually seen when asking questions

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17
Q

cumulative incidence

A

number of new cases of a disease / number of people at risk

  • remember to subtract people that already have the disease because they are not at risk
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18
Q

power

A

the ability to detect between groups when one actually exsists

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19
Q

power equation

A

1-beta (type II error)

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20
Q

beta

A

study does not reject the null hypothesis when it should

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21
Q

ecological study

A

like a cross sectional study but it uses population data instead of individual data

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22
Q

effect modification

A

when the effect of an exposure on an outcome is modified by another variable

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23
Q

how effect modification differs from confounding

A

stratification is used to distinguish the difference. When the confounder is removed, there is no longer a difference between the two

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24
Q

attrition bias

A

when loss to follow up is greater for one group than another

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25
Q

selection bias

A

systemic difference between groups

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26
Q

misclassification bias

A

exposure and outcome are not measured properly, it affects both group equally
- example = nonfunctioning blood pressure cuff

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27
Q

purpose of matching

A

prevent confounding variables, or differences between groups

28
Q

selection bias

A

nonrandom sampling so a group may not be representative of the population as a whole

29
Q

chi squared test

A

used for the association of two categorical variables

30
Q

definition of odds

A

probability of an event happening / probability of the event not happening

31
Q

case control vs odds ratio mnemonic

A

CCOR and CRR - cant have double letter together

- case-control uses odds ratio and cohort uses relative risk

32
Q

relative risk

A

(people who have the disease / total exposed) / (people with disease / total not exposed)

  • gives an answer in relationship to 1 - the higher the numerator, the more likely the disease was related to the risk
33
Q

attributable risk

A

(people who have the disease / total exposed) - (people with disease / total not exposed)

or, the percent of cases that are attributable to the risk

34
Q

relative risk reduction

A

1 - relative risk

or, the proportion of risk reduction attributable to intervention

35
Q

absolute risk reduction

A

difference in risk attributable to the intervention as compared to the control

36
Q

number needed to treat

A

1/ARR

37
Q

number needed to harm

A

1/AR

38
Q

which two variables are swaps of eachother

A

attributable risk and absolute risk reduction (both used to calculate NNT and NNH)

39
Q

selection bias

A

nonrandom sampling of subjects so that it can’t be extrapolated to greater population
- usually and sampling bias

40
Q

Berkson bias

A

study population from hospital is less healthy than general population

41
Q

healthy worker effect

A

subjects are healthier than general population

42
Q

non-response bias

A

participating subjects differ from non-respondents in meaningful ways

43
Q

ways to decrease selection bias

A

randomization and ensuring the right comparison group

44
Q

recall bias

A

awareness of disorder alters recall by subjects, common in retrospective trials

45
Q

measurement bias

A

information is gather in an unorganized manner

46
Q

Hawthorne effect

A

participants change their behavior because they know they are being studied

47
Q

procedure bias

A

subjects in different groups are not treated the same

48
Q

observer-expectancy bias

A

belief in efficacy changes the results

49
Q

confounding bias

A

a factor is related to both exposure and outcome, but not on causal pathway

50
Q

how to decrease confounders

A
  • repeat studies
  • crossover studies
  • matching
  • restriction and randomization
51
Q

lead-time bias

A

early detection leads to increase survival

52
Q

type 1 error (alpha)

A

when the null hypothesis is rejected, but it should not be

use: gives the p value in studies

53
Q

trick for remembering type 1 and 2 errors

A 
type 1 (1 word) = DO reject null
type 2 (2 words) = DO NOT reject null
54
Q

type 2 error (beta)

A

when you do not reject the null hypothesis, but you should

use: for the power of a study (1-beta)

55
Q

what increases power

A
  • increased sample size
  • increased effect size
  • increased precision of measurement
56
Q

t-test

A

checks difference between means

57
Q

ANOVA

A

checks difference between means of 3+ groups

58
Q

Chi squared

A

checks difference between 2 categorical variables (Chi-tegorical)

59
Q

capacity vs competency

A 
capacity = from a physician
competency = from a judge
60
Q

HMO

A
  • patients are restricted to a network
  • payment is denied if it does not fit evidence based guidelines
  • requires referral to see specialist
61
Q

point of service insurance

A
  • patients can see providers out of network, but have higher costs
  • requires referral
62
Q

preferred provider organization insurance

A
  • patients can see anyone and have higher copays

- does no require referral

63
Q

exclusive provider organization insurance

A
  • limited to certain doctors

- does not need a referral

64
Q

capitation

A
  • set amount of money per head over a period of time
65
Q

discounted fee for service

A

patient pays for each service at a discounted rate

66
Q

global payment

A

patient pays for everything associated with a single incident of care

First Aid (16 decks)

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