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Flashcards in The Use of Data Deck (48)
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1
Q

Define disease

A

Symptoms, signs, diagnosis; a bio-medical perspective

2
Q

Define illness

A

Ideas, concerns, expectations; experience of patients (their perspective)

3
Q

What are the medical factors which affect the uptake of care (going to get care)?

A

New symptoms, visible symptoms, increasing severity, duration etc

4
Q

What are the non-medical factors which affect the uptake of care (going to get care)?

A

Crisis, peer pressure “wife sent me”, patient beliefs, expectations, social class, economic, psychological, environmental, cultural, ethnic, age, gender, media etc

5
Q

What is the Lays Referral concept of the uptake of care?

A

Going from family → community → traditional/cultural healing → medical system

6
Q

Where can people get info which influences their decision for uptake of care?

A

Peers, family, internet TV, health pages of newspaper or women’s mag, “What should I do? Booklet, SHOW website, Practice leaflet or website

7
Q

What are the three main aims of epidemiology?

A
  1. Description
  2. Explanation
  3. Disease control
8
Q

Define description in epidemiology

A

To describe the amount and distribution of disease in human populations

9
Q

Define explanation in epidemiology

A

Elucidate natural history and aetiology of disease by combining data from epidemiology with data from biochem/occupational health/genetics

10
Q

Define disease control in epidemiology

A

Provide bases for preventative measures/public health practices/therapeutic strategy for disease control

11
Q

What is epidemiology used for?

A

Compares groups to detect difference in:

Aetiology
Scope for prevention
Identify high risk group

12
Q

What are the fundamental measures?

A

Clinical medicine deals with the individual patient and epidemiology deals with populations.

Rates: numerator = events and denominator = population at risk

13
Q

What is the risk part of formulating ratios in fundamental measures?

A

Everyone in the denominator must have possibility of entering the numerator, and vice versa.

14
Q

What does incidence indicate about a disease?

A

It is the number of new cases of a disease in a population in a specified period of time. Incidence tells us something about trends in causation and the aetiology of disease.

15
Q

What does prevalence indicated about a disease?

A

It is the number of people in a population with a specific disease at a single point in time or in a defined period of time.

Prevalence tells us something about the amount of disease in a population. It is useful in assessing the workload for the health service but is less useful in studying the causes of disease.

16
Q

What is relative risk?

A

Measure of the strength of an association between a suspected risk factor and the disease under study.

17
Q

What is the equation to work out relative risk?

A

(Incidence of disease in exposed group) / (incidence of disease in unexposed group)

18
Q

Give four examples of sources of epidemiological data

A

Mortality data
Hospital activity statistics
Reproductive health statistics
Cancer statistics

19
Q

What is health literacy?

A

People having the knowledge, skills, understanding and confidence to use health information, to be active partners in their care, and to navigate health and social care systems.

20
Q

Name an initiative in Scotland to improve health literacy

A

Making It Easy - A Healthy Literacy Action Plan

21
Q

What are the SIGN guidelines aims?

A

Aid in understanding and help make clinical decisions

Reduce variations in practice and provide best care no matter where Pt is

Improve healthcare across Scotland

22
Q

What are the two types of studies?

A

Descriptive and analytical

23
Q

What are descriptive studies?

A

Describe amount and distribution of disease in a given population

  • No definitive conclusions, does give clue to risk factors and aetiology
  • Cheap, quick, overview
24
Q

What are analytic studies?

A
Two types:
Cross sectional (disease frequency/survey): observations in a point in time 

Case Control: comparison of 2 groups

  • Pt with the disease (cases)
  • Pt who do not have disease (controls)

These results are compared to highlight factors on risk of disease

25
Q

How are the cases and control compared in analytical studies?

A

The average exposure to aetiological factors of each group compared to identify significant differences which indicates which factors increase (or reduce) risk of disease

26
Q

What are the result from case studies in analytical studies expressed as?

A

‘Odds ratios’ or ‘relative risk’

27
Q

What are cohort studies?

A

Baseline data on a group without disease, who are then followed until disease developed enough to allow analysis

28
Q

How are cohort studies analysed?

A

Original group separated into subgroups according to original exposure status and these subgroup are compared to determine incidence of disease according to exposure

29
Q

What are trials?

A

Trials are experiments used to test ideas about aetiology or to evaluate interventions.

30
Q

What is the definitive method of assessing any new treatment?

A

Randomised controlled trial

31
Q

How are randomised controlled trials carried out?

A
  1. At risk groups; a study group and a control group.
  2. Alteration made to the study group only
  3. Data collected same way
32
Q

What is the aim of randomised controlled trials?

A

Determine whether modification of the factor (changing the exposure) alters the incidence of the disease

33
Q

How is a trial of a new treatment carried out?

A

Intervention group receive the new therapy, the control group receive the current standard therapy (or placebo) and treatment outcomes compared in two groups

34
Q

What are six factors to consider when interpreting results?

A
  1. Standardisation
  2. Standardised mortality ratio
  3. Quality of data
  4. Case definition
  5. Coding and classification
  6. Ascertainment
35
Q

What are standardisation factors to consider?

A

Adjusting for effects of differences of cofounding variable (i.e. age)

36
Q

What is standardised mortality ratio?

A

Standardised death rate converted to ratio, e.g. standard is 100, 120 means 20% more death than expected

37
Q

What is the factor ‘case definition’?

A

Decide if an individual has the condition of interest or not; varying definition from study maker to interpreter

38
Q

What is the factor ‘coding and classification’?

A

When data collected it is converted to a set of codes, to assist in data storage and analysis

39
Q

What is the factor ‘ascertainment’?

A

Completeness of data. One group looking harder than another

40
Q

What is bias?

A

Trend in the collection, analysis, interpretation, publication or review of data that can lead to conclusions that are systematically different from the truth.

41
Q

What are four different types of bias?

A

Selection Bias
Information Bias
Follow up Bias
Systematic Error

42
Q

Define selection bias

A

Study sample is not truly representative of the whole study population about which conclusions are to be drawn

43
Q

Define information bias

A

Arises from systematic errors in measuring exposure or disease

44
Q

Define follow up bias

A

Arises when one group of subjects is followed up more assiduously than another

45
Q

Define systematic error

A

A form of measurement bias where there is a tendency for measurements to always fall on one side of the true value

May be caused by:
Instrument
Wrong technique

46
Q

Define a cofounding factor

A

Associated independently with both the disease and with the exposure under investigation and so distorts the relationship between the exposure and disease.

Age, sex and social class

47
Q

Name ways to deal with a cofounding factor

A

Restriction eligibility criteria
Subjects in different group can be matched for likely cofounding factors
Results adjusted

48
Q

What are the 9 criteria for causality

A

Temporality: exposure comes before disease [only absolute criterion]

Strength of association: relative risk ratio

Consistency: repeated observation of association in differing populations

Specificity: single exposure leads to single disease

Biological gradient: dose
response relationship i.e. exposure UP = risk UP

Biological plausibility: association agrees with biology of disease

Coherence: association does not conflict with biology of disease

Analogy: another relationship exists that can be used as a model for current

Experiment: suitably controlled experiment to prove association as causal(uncommon in human populations)