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
Subtraction method
(difference in activation for tasks)
26
2 approaches to understand the brain:
- Functional specialisation: where? Functional integration: how? Networks…
27
Functional integration
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
Diffusion Tensor Imaging (DTI)
* 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
Electrophysiological measures
Electroencephalography (EEG) – records electrical signals generated by the brain through electrodes placed at different points on the scalp
30
event-related potentials (ERPs)
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
Association versus causation
correlation does not necessarily imply causation * Causal relationship needs to be tested by experiments, which is unfeasible in some circumstances
32
Different levels of explanations to individual differences
* Genetic explanations * Socio-cultural explanations * (Neurobiological explanations)
33
What is a gene?
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
genotype
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
phenotype
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
study of heritability
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
The genotype-first approach of genetic studies
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
the phenotype-first approach
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
Cross-cultural research
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
The heritability of intelligence
is found to be 50% (this is variance across a population)