Midterm Flashcards

1
Q

Issues connected to ethics

A
  • no coercion
  • no persuasions (figure of authority)
  • voluntary participation
  • research should not add risk
  • participants can skip sections in the questionnaire/surveys, refuse to answer all questions during interviews
  • benefits should be provided in any case
  • treating people fairly & with respect
  • discourage people from withdrawing if they decide not to do so
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2
Q

Main Principles in Ethics

A

protect participants from harm

  • research with human participants requires Ethics approval
  • balance between potential harm and benefits of research
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3
Q

Ethics Review Board (ERB)

A
  • usually, universities have two Ethics Review Boards
    1) Full Research Ethics Board
  • they receive greater than minimal risk research, committee of faculty members, REB, community & other members
    2) Delegated REV Review
  • they have minimal risk review, individual will review (REB officers)
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4
Q

Tri-Council Policy Statement Core Principles

A
concern for human welfare
- means seeking concrete ways to promote the physical and mental wellbeing of participants and protect them from harm
justice
- treat people fairly and equitable
respect for persons
- intrinsic values of human beings
- incorporates dual moral obligation to respect autonomy and protect those who have limited autonomy (vulnerable groups, disabilities, PTSD)
- people should choose freely
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5
Q

Hypothesis

A
  • 2 variables
  • expresses relationships between variables
  • expressed as prediction or expected future outcome
  • logically linked to research question and theory
  • possible to test it to see if it is false or true
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6
Q

null hypothesis

A

no relationship or no effect between variables

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7
Q

alternative hypothesis

A

states that independent variable has an effect on dependent variables

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8
Q

sampling

A

process of selecting observations in research

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9
Q

probability sampling

A

involves random selecting

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10
Q

probability sampling techniques

simple random sampling

A

simple random sampling

  • researcher assigns a single number to each element in the sampling frame without skipping any number in the process
  • a table of random numbers is then used to select elements for the sample

limitations:
- entire list of population should be accessible but not usually the case
- could be quite extensive and expensive
small random sample may not be representative of the population of specific ethnic groups

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11
Q

probability sampling techniques

systematic random sampling

A

systematic random sampling
- design requires a list of certain types of population to be researched
systematically takes every 10th, 20th, element into sample

weakness
- periodicity of people in the list could be done in such a way that sampling will represent only specific gender, race, age, etc.

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12
Q

probability sampling techniques

stratified sampling

A

stratified sampling

  • method for obtaining a greater degree of representativeness
  • it is necessary to divide the population into different subgroups or strata, & then randomly selects final subjects proportionally from the different strata
  • stratification is process of grouping members of a population into relatively homogenous strata before sampling (could be race, gender, age, socioeconomic status)
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13
Q

probability sampling techniques

cluster sampling

A

cluster sampling

  • one of most efficient ways of sampling
  • may be used when not possible to compile a list of all elements that compose the larger population
  • useful when clusters occur naturally such as in schools, universities, hospitals. cluster becomes a unit of analysis and therefore considered a representative of population
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14
Q

non-probability sampling

A

Not random sampling

Selective

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15
Q

non-probability sampling techniques

quota sampling

A

quota sampling

  • gather data from individuals in the same proportion as they are represented in population, (gender, sex, age, race, education)
  • could be face-to-face, email, phone, mail

weakness
- allows research to decide whom to include or not include into study, therefore creates biases

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16
Q

non-probability sampling techniques

reliance on available subjects

A

reliance on available subjects
- accidental sampling, procedure that relies on available subjects

weakness
- findings would represent the opinions only of people with characteristics of those passing the sampling point of specified times

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17
Q

non-probability sampling techniques

purposive/judgemental

A

purposive/judgemental sampling

  • method which researchers used own judgement/knowledge in selecting sample members
  • especially used when research to be conducted among specific sub-groups of people
18
Q

non-probability sampling techniques

snowball sampling

A

snowball sampling

  • term refers to process of accumulation as each located subject suggests other subjects
  • used primarily for exploratory purposes. appropriate when members of the specific population are difficult to find and located in multiple places.
19
Q

Operationalization

A

definition of variable in terms of specific activities to measure or indicate with empirical evidence (i.e., survey questionnaire, method of observing events in a field, etc)
- process of moving from concept to a specific activity or measure that allows research to observe it empirically

20
Q

Conceptualization

A

the process by which concepts are formed through the selective organization of sensory experience
- process of specifying what we mean by a term

21
Q

paradigms

A
  • address philosophical dimensions of social science
  • set of fundamental assumptions and beliefs as to how the world is perceived
  • framework perspective or models from which we see, interpret and understand
22
Q

ontology

A

the view of how we perceive reality

23
Q

epistemology

A

studies knowledge & development of knowledge

24
Q

anxiology

A

branch of philosophy which studies values

- what do we know, what do we values?

25
positivism and post positivism | Paradigms
- both start with testing the theory in form of hypothesis & involve statistical tests in their research process - uses qualitative data
26
Interpretivism/Constructivism | Paradigms
- opposite to positivism and post positivism - believes knowledge is subjective - works with qualitative approach - idiographic approach
27
Pragmatism | Paradigms
- refuses to join debates between interpretivisim and positivism - accepts mixture of ontology, epistemology, and axiology - uses both qualitative and quantitative to better understand reality
28
Tranformative | Paradigms
- focuses on change and transformation | - participatory and collaborative (work together) - different research approach quantitative or qualitative
29
inductive approach
- form of reasoning that moves from specific cases to general cases - aims to develop a theory
30
deductive approach
- form of reasoning that moves from general to specific cases - aims to test a theory
31
nomothetic approach
- focuses on numbers and strives to produce general statements - quantitative
32
idiographic approach
- specific case | - qualitative
33
Ratio Measures
a level of measurement that describes a variable whose attributes have all the qualities of nominal, ordinal, and interval measures and in addition are based on a true zero point - most precise, ordered - exact value - equal intervals - natural zero, not arbitrary example: weight, height, pulse, blood pressure, time
34
nominal measures
Variables whose attributes have only the characteristics of exhaustiveness and mutual exclusiveness. - assign numbers to objects where different numbers indicate different objects - the numbers have no real meaning other than differentiating between objects - no natural order example: gender: 1 = 1 female, 2 = male, 3 = other race, martial status, religion, type of care, etc
35
ordinal measures
variables whose attributes may be logically rank ordered - assign numbers to object but the numbers have meaningful order/rank example: socioeconomic status: low, middle, high size: small, medium large customer satisfaction: not satisfied, satisfied, very satisfied patients ranking pain from 1-10
36
interval measures
A level of measurement that describes a variable whose attributes are rank ordered and have equal distances between adjacent attributes - ordered categories distance between value is known example: school tests, temperature
37
Scales of Measurement
Ratio: Absolute zero Interval: Distance is meaningful Ordinal: Attributes can be ordered Nominal: Attributes are only named: weakest
38
Exploratory Research
usually qualitative methods - could be the first stage of sequence of studies. usually "what" question example: what factors contribute to - generates a new idea
39
Explanatory Research
explains relationships, tests hypothesis' example: how does salary influence employee satisfaction? how does ROOM TEMPERATURE influence STUDENT UNDERSTANDING of material during class? - relationships between variables
40
Descriptive (Description) Research
focuses on how, who and what. what is the description of settings example: what is the current level of employee satisfaction in university 1. provided detail, highly accurate data 2. document causes process or mechanism 3. report on background or context of situation