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Physics and Math > Chapter 11 - Reasoning About the Design and Execution of Research > Flashcards

Chapter 11 - Reasoning About the Design and Execution of Research Flashcards

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1
Q

Scientific Method Steps:

A

Generate a testable question

Gather data and resources

Form a hypothesis

Collect new data

Analyze the data

Interpret the data and existing hypothesis

Publish

Verify results

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2
Q

Hypothesis:

A

proposed explanation or proposed answer to our testable question

In the form of an if-then statement, which will be tested in subsequent steps

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3
Q

Experimentation:

A

manipulating and controlling variables of interest

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4
Q

Observation:

A

involves no changes in the subject’s environment

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5
Q

Finer method:

A

method to determine whether the answer to one’s question will add to the body of scientific knowledge in a practical way and within a reasonable time period

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6
Q

Finer Method Questions:

A

Is the necessary research study going to be feasible?

Do other scientists find this question interesting?

Is this particular question novel?

Has someone asked this question before and published it?

Would the study obey ethical principles?

Is the question relevant outside the scientific community?

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7
Q

Basic science research:

A

research conducted in a lab, not on people

Easiest to design b/c experimenter has the most control

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8
Q

Control/standard:

A

acts as method of verifying results

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9
Q

Positive controls:

A

those that ensure a change in the dependent variable when it is expected

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10
Q

Negative controls:

A

ensure no change in the dependent variable when no change is expected

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11
Q

Placebo effect:

A

an observed or reported change when an individual is given a sugar pill or sham intervention

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12
Q

Independent variable vs, Dependent Variable:

A

Independent variable: variable that is manipulated

Dependent variable: variable that is measured or observed

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13
Q

What needs to happen in order for a relationship to be considered causal?

A

If the change in the independent variable always precedes the change in the dependent variable, and the change in the dependent variable does not occur in the absence of experimental intervention, the relationship is said to be causal

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14
Q

Accuracy (validity):

A

ability of an instrument to measure a true value

Ex: accurate scale should register a 170lb person as 170 pounds

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15
Q

Precision (reliability):

A

ability of an instrument to read consistently, or within a narrow range

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16
Q

Systematic error:

A

when bias is considered

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17
Q

How to overcome error from random chance?

A

Random chance can also introduce error into an experiment

Can be overcome by using a large sample size

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18
Q

Human Subjects Research:

  1. consists of what
  2. experimental approach
A

Consists of experimental and observational studies

Experimental Approach - b/c subjects are in a less-controlled conditions, the data analysis phase is more complicated than in laboratory studies

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19
Q

Randomization:

A

method used to control for differences between subject groups in biomedical research

Uses an algorithm to determine the placement of each subject into either a control group that receives no treatment, or one or more treatment groups

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20
Q

Blinded:

  1. definition
  2. what happens without blinding
A
  1. means they do not have information about which group the subject is in
  2. Without blinding, the placebo effect would be greatly reduced in the control group, but still present in the treatment group
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21
Q

Single-blind experiments:

A

only the patient or assessor (person who makes measurements on the patients or performs subjective evaluations) is blinded

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22
Q

Double-blind experiments:

A

the investigator, subject, and assessor all do not know the subject’s group

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23
Q

Confounding variables:

  1. types of Variables:
A

Binary: yes vs. no, better vs. worse

Continuous: amount of weight lost, percent improvement in cardiac output

Categorical: state of residence, socioeconomic status

24
Q

Regression analysis:

A

may demonstrate linear, parabolic, exponential, logarithmic or other relationships

25
Q

Observational studies:

  1. what they are
  2. three categories (just list)
A
  1. draw on available data and analyze it
  2. cohort studies, cross-sectional studies, case-control studies
26
Q

Observational studies - Cohort studies:

A

those in which subjects are sorted into two groups based on differences in risk factors (exposures), and then assessed at various intervals to determine how many subjects in each group had a certain outcome

Ex: a study in which 100 smokers and 100 nonsmokers are followed for 20 years while counting the number of subjects who develop lung cancer in each group

27
Q

Observational studies - Corss-sectional studies:

A

attempt to categorize patients into different groups at a single point in time

Ex: a study to determine the prevalence of lung cancer in smokers and nonsmokers at a given point in time

28
Q

Observational studies - Case-control studies:

A

start by identifying the number of subjects with or without a particular outcome, and then look backwards to assess how many subjects in each group had exposure to a particular risk factor

Ex: a study in which 100 patients with lung cancer and 100 patients without lung cancer are assessed for their smoking history

29
Q

Hill’s criteria:

  1. what it is
  2. criteria (just list)
A
  1. components of an observed relationship that increase the likelihood of causality in the relationship
  2. temporality

strength

dose-responsive relationship

consistency

30
Q

Hill’s Criteria - Temporality:

A

the exposure (independent variable) must occur before the outcome (dependent variable)

31
Q

Hill’s Criteria - Strength:

A

as more variability in the outcome variable is explained by variability in the study variable, the relationship is more likely to be causal

32
Q

Hill’s Criteria - Dose-responsive relationship:

A

as the study or independent variable increases, there is a proportional increase in the response

33
Q

Hill’s Criteria - Consistency:

A

the relationship is found in multiple settings

34
Q

Bias:

A

result of flaws in the data collection phase of an experimental or observational study

Systematic error

35
Q

Confounding:

  1. what it is
  2. third party variable
A
  1. an error during analysis
  2. Data may or may not be flawed, but an incorrect relationship is characterized

Third party variables called confounding variables or confounders

Third variable that could effect both variables

36
Q

Selection bias:

  1. definition
  2. volunteers
A

the subjects used for the study are not representative of the target population

  • People who volunteer may be vert different from people who do not volunteer*
  • May also apply in cases where one gender is more prevalent in a study than another*
  • Measurement and assessment of selection bias occurs before any intervention*
37
Q

Detection Bias:

  1. results from what
  2. influence of prior studies
A
  1. results from educated professionals using their knowledge in an inconsistent way
  2. Because prior studies have indicated that there is a correlation between two variables, finding one of them increases the likelihood that the researcher will search for the second
    * Ex: high blood pressure and diabetes mellitus are more common in the obese population; so a physician will screen obese population for these things more than a patient of healthy weight*
38
Q

Hawthorne effect (observation bias):

A

posits that the behavior of study participants is altered simply because they recognize that they are being studied

Ex: patients in a study for a given weight loss drug may begin exercising more frequently or make dietary changes

39
Q

Ethical Tenets - Beneficence:

A

obligation to act in the patient’s best interest

is must be our intent to cause a net positive charge for both the study population and general population, and we must do our best to minimize any potential harms

Research should be conducted in the least invasive, painful, or traumatic way possible

40
Q

Four core ethical tenents: (just list)

A
  1. Beneficence
  2. Nonmaleficence
  3. Autonomy
  4. Justice
41
Q

Ethical Tenets - Nonmaleficence:

A

obligation to avoid treatments or interventions in which the potential for harm outweighs the potential for benefit

42
Q

Ethical Tenets - Autonomy:

A

responsibility to respect patients’ decisions and choices about their own healthcare

43
Q

Ethical Tenets - Justice:

A

responsibility to treat similar patients with similar care, and to distribute healthcare resources fairly

44
Q

Respect for persons:

A

includes the need for honesty between the subject and the researcher; prohibits deception

45
Q

Informed consent:

A

a patient must be adequately counseled on the procedures, risks and benefits, and goals of a study to make knowledgeable decision about whether or not to participate in the study

Investigator cannot exert a coercive influence over the subjects

Also includes the need to respect the subjects’ wishes to continue with or cease participation in a study

46
Q

Vulnerable persons:

A

(children, pregnant women, prisoners) require special protections above and beyond those taken with the general population

47
Q

Justice - as it applies to selection and execution of research:

A

applies to both the selection of a research topic and the execution of the research

The only way to determine the selection of a research question to maintain justice is through random chance

When there is risk associated with a study, it must be fairly distributed so as to not unduly harm any group

48
Q

Morally relevant differences:

  1. what they are
  2. examples
  3. what are not considered morally relevant differences
A
  1. differences between individuals that are considered an appropriate reason to treat them differently
  2. ex: age, population size
  3. Not considered: ethnicity, sexual orientation, financial status
49
Q

Population:

A

complete group of every individual that satisfies the attributes of interest

50
Q

Parameter:

A

information that is calculated using every person in a population

51
Q

Sample:

  1. what they are
  2. must represent what
  3. what is the gold standard
A
  1. any group taken from a population that does not include all individuals from the population
  2. Samples will be representative of the population
  3. Random samples are considered the gold standard
52
Q

Statistic:

A

information about a sample

Can be used to estimate population parameters

53
Q

Internal validity:

A

support for causality

54
Q

External validity (generalizability):

  1. studies with low generalizability
  2. studies with high generalizability
  3. example
A
  1. Studies with low generalizability have very narrow conditions for sample selection that do not reflect the target population
  2. High generalizability have samples that are representative of the target population
  3. ex: a psoriasis study with low generalizability will have people only diagnosed within the year, high generalizability would have participants with a distribution of time since diagnosis
55
Q

Statistically significant:

A

not the result of random chance

56
Q

Clinical significance:

A

notable or worthwhile change in health status as a result of our intervention

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