Week 2: methods Flashcards

1
Q

methods of measuring individual differences

A
  • Survey / self-report measures
    • Observational measures
  • Performance measures
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2
Q

Self-report measure

A

Typically involve presenting a list of statements and asking participants the extent to which they agree/disagree with them

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3
Q

self-report advantages

A

Low cost and easy to administer in large scale (even online)

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4
Q

self-report disadvantages

A

– Respondents’ tendency to give socially desirable answers
– Respondents’ tendency to agree (acquiescence bias)
– Only measures thoughts, (explicit) attitudes, and self-perception
– Requires respondents’ self-awareness (introspection)

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5
Q

Experience sampling method

A
  • Ask participants to report their thoughts, feelings, and/or behaviours repeatedly over a certain period of time (e.g., 2 or 3 weeks)
    • Response frequency could be daily (diary studies) up to several times a day
    • Alternatively, participants could be signalled by a mobile device to fill in a brief questionnaire at a random time
    • Potential problem:
      – The very act of self-monitoring can influence what is being measured
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6
Q

Observational measures

A

Typically involves recording what is being done or how often something is done through observation by a third person (from tally to videotaping)

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7
Q

observation advantages:

A

can be used when it is impossible or inappropriate to give instructions to a participant; can be used in naturalistic settings

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8
Q

observation limitations

A

– can only measure overt behaviours
– scoring may be influenced by observer biases
* Computerised scoring (as in eye tracking) can minimise observer biases

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9
Q

Performance measures

A
  • Intelligence, reading/math performance, etc.
    • Typically accuracy measures (in terms of error rates, percentage correct, percentiles, etc.)
    • Response times (RT) as additional performance indicator
    • Differences across individuals reflect differing abilities,
  • Differences across tasks reflect differences in information processing mechanisms
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10
Q

performance measures advantages

A

objective (rather than self-report which relies on self-awareness)

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11
Q

performance measures limitations

A

their relationship with real-world behaviours (i.e., ecological validity) is not always clear

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12
Q

Can we measure the unconscious mind?

A

Cognitive tasks like implicit association test and priming are used to measure unconscious cognitive processing

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13
Q

Priming paradigm

A

participants are exposed to a certain stimulus (prime), and their response to a subsequent stimulus (target) is measured
* The prime is supposed to activate mental representations which could affect processing of the subsequent stimulus
* In masked priming, the prime is presented followed by a junk visual material (mask). This prevents the prime from entering conscious processing

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14
Q

Masked priming task - Moret-Tatay et al. (2020)

A

○ When the name matches the picture, participants are faster than without the masked prime.

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15
Q

Factor analysis

A

Factor analysis is a statistical technique used to reduce a large number of variables into fewer “factors”

The rationale is to analyse the patterns in which variables (items) vary together (covariance); variables (items) indicating the same underlying construct are expected to covary

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16
Q

Exploratory factor analysis (EFA)

A

does not assume a particular factor structure but uses the data to determine:
– The number of factors
– Correlations between a variable (item) and a factor, called factor loadings, are computed and examined
– The higher the factor loading (regardless of sign), the more important the variable is to the factor

in EFA the number of factors as well as criteria for including a variable in a factor is the researcher’s decision

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17
Q

Confirmatory factor analysis (EFA)

A

the researcher hypothesises a factor structure and tests how well it fits the actual data – i.e., the number of factors and which measured variable is related to which factor (also called latent variable) is prespecified
* Then the factor loadings, factor correlation and some fit indexes are estimated

18
Q

Structural brain imaging methods

A

CT scan

MRI

19
Q

MRI

A

used to measure brain volume, grey matter volume, white matter volume, etc., which have been associated with individual differences in behaviour (e.g., intelligence)
§ White matter consists primarily of myelinated axons
§ Gray matter consists primarily of neuronal cell bodies

strong magnetic field causes hydrogen atoms to align in the same orientation
* When radio wave passed through the head, atoms emit electromagnetic energy as they “relax”.
* MRI scanner detects emitted radiation

20
Q

functional brain imaging methods

A

fMRI

PET scan

21
Q

fMRI

A

Functional imaging methods such as fMRI measure dynamic physiological changes in the brain in vivo and associate them with different patterns of mental processes/behaviour
* fMRI does not measure neuronal activation directly but the downstream consequence of neural activation, i.e., increased blood flow and blood oxygen consumed in a certain brain region

fMRI studies, a magnetic resonance signal that is affected by the amount of deoxyhaemoglobin in the blood, called BOLD signal (Blood Oxygen-Level Dependent), is measured
* The rationale is that when neurons consume oxygen they convert oxyhaemoglobin to deoxyhaemoglobin, which has strong paramagnetic properties and distorts the local magnetic field

22
Q

PET (positron emission tomography)

A

a radioactive tracer is injected to the bloodstream and the amount of radioactivity in each voxel of the brain is measured

23
Q

Functional imaging: 2 methods to see which activation is related to the specific process?

A

Subtraction method

Conjunction method

24
Q

Conjunction method

A

(joint activation for tasks)

25
Q

Subtraction method

A

(difference in activation for tasks)

26
Q

2 approaches to understand the brain:

A
  • Functional specialisation: where?

Functional integration: how? Networks…

27
Q

Functional integration

A

i.e., the way in which different regions work together in terms of networks
* Network analysis is based on covariations between the BOLD signal in different brain regions, called functional connectivity
* No causality can be inferred, nor whether the connectivity is direct or indirect via some third region(s)

28
Q

Diffusion Tensor Imaging (DTI)

A
  • Aims at specifying tracts fibre tracts with white matter connecting cortex / subcortical areas
    • Important to investigate network architecture of the brain
    • Not just activated grey matter areas!
       Diffusion of water molecules along neural tracts
29
Q

Electrophysiological measures

A

Electroencephalography (EEG) – records electrical signals generated by the brain through electrodes placed at different points on the scalp

30
Q

event-related potentials (ERPs)

A

A common usage of EEG is the electrophysiological changes elicited by particular stimuli and cognitive tasks, referred to as event-related potentials (ERPs)
– Certain ERP has been identified to be linked to a certain cognitive process, and hence reveals the happening of the process

31
Q

Association versus causation

A

correlation does not necessarily imply causation
* Causal relationship needs to be tested by experiments, which is unfeasible in some circumstances

32
Q

Different levels of explanations to individual differences

A
  • Genetic explanations
    • Socio-cultural explanations
  • (Neurobiological explanations)
33
Q

What is a gene?

A

Genes are made up of DNA, and DNA contains the instructions for building proteins. These proteins control the structure and function of all body cells.
* A gene is the basic physical and functional unit of inheritance

34
Q

genotype

A

internal genetic code or blueprint for constructing and maintaining a living individual, is inherited and is found within all the cells, tissues and organs of the individual

35
Q

phenotype

A

the outward manifestation of the individual, including physical appearance, intelligence, and personality
* Genes can be turned on and off by the environment (of the cell)

36
Q

study of heritability

A

is estimated by studying similarities and differences between individuals who share their genes to varying degrees:
– family studies
– between parent and child, siblings, or between other family members
– twin studies
– between identical (monozygotic) twins and non-identical (dizygotic) twins
– adoption studies
– between adopted children & biological/adoptive parent

37
Q

The genotype-first approach of genetic studies

A

focus on a single gene that is known to exist in multiple variants (polymorphisms) and that may be linked to the phenotype of concern

E.g., a genetic variant may be known to encode the mu-opioid receptor which is related to susceptibility to physical pain
* Then the extent to which this variant explains variations in a phenotype (e.g., susceptibility to social pain) is examined

38
Q

the phenotype-first approach

A

starts with a given trait (e.g. novelty seeking) and determine which gene(s) among the entire genome contribute most to variations in that trait

Genome-wide association studies

39
Q

Cross-cultural research

A

Cross-cultural research commonly involves comparison of traits (or relationships between traits) across two or more cultures
– i.e., culture is the unit of analysis

to identify individual-level variables that explain the cultural differences
– e.g., differences in mathematics attainment due to differences in number word formation (i.e., 32  “three ten two” in Japanese vs. “two and thirty” in German)

40
Q

The heritability of intelligence

A

is found to be 50% (this is variance across a population)