9.1.8 - Additional research methods and techniques Flashcards

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1
Q

Define “content analysis” and its 3 steps.

A

The process of identifying and counting categories, themes, phrases or keywords that may occur in the data

Example:
1. Analysing the recording of an observation study
2. Identifying categories
3. Allocating each observation to each one of the categories

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2
Q

Define the 3 types of correlation.

A

Positive - as the value of one variable increases/decreases, the value of the other variable tends to also increase/decrease

Negative - as the value of one variable decreases, the value of the other variable tends to increase and vice versa

No - there is no linear trend between the two variables

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3
Q

Define ‘falsifiability’.

A

The capacity for a theory or hypothesis to be proven wrong

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4
Q

Define ‘empirical research’.

A

Primary data gathered directly through experimental and observational methods

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5
Q

Define ‘research review’.

A

A comprehensive and concise summary of research done on a particular topic with an emphasis on integration and interpretation of primary research articles

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6
Q

What is a longitudinal study? (2 points)

A

An observational research method which takes place over a long period of time - sometimes 10 to 20 years

Involves tracking the same participants through a period of development

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7
Q

How does a longitudinal study work? (3 points)

A

Participants will be visited several times for data to be collected and any changes in behaviour will be recorded

They are given the same type of tasks each time they are visited to check on any improvements in performance

The data of each test is compared to see how the passage of time affects whatever it is being tested for

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8
Q

What are the 2 advantages of longitudinal studies?

A

Increased internal validity - participant variables do not affect the data as same participants used throughout the study

Increased reliability - same data tests are repeated at regular intervals

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9
Q

What are the 2 disadvantages of longitudinal studies?

A

Lack of consistency in results - subject to research bias as researchers may change over the years

Duration of the study varies (weeks, months, years), causing sample attrition as participants may withdraw over time - disrupts the sample size and data collection

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10
Q

What is a cross-sectional study? (3 points)

A

A study that looks at different participants over a short period of time

Takes place at one specific moment in time and compares different groups of people at that time

The participants are tested once, usually to find a simple relationship between one variable and another

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11
Q

What are the 2 advantages of cross-sectional studies?

A

Less time-consuming and more cost-effective - participants only need to be tested once

Less impacted by sample attrition - easier to retain participants as the study is short and commitment over a long period is not required

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12
Q

What are the 2 disadvantages of cross-sectional studies?

A

Reduced internal validity:
+ Participants used are not the same so the results are subject to participant variables
+ Data is less rich and insightful as it is for a snapshot in time - harder to analyse developmental trends over long periods

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13
Q

What is a meta-analysis? (2 points)

A

Can be thought of as ‘conducting research about previous research’

A study about studies to get an integrated result

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14
Q

How does a meta-analysis work? (2 points)

A

A researcher reviews previously published studies on a topic and analyses the various results to find general trends across the studies

Researchers pool data on a particular topic using secondary data because the data studied are not gathered first-hand

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15
Q

What are the 2 advantages of meta-analyses?

A

Less time-consuming and less expensive - no need for new studies to recruit ppts/ find a lab/equipment

Fewer ethical considerations due to no direct contact with patients - no need to abide by BPS

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16
Q

What are the 2 disadvantages of meta-analyses?

A

Low reliability - difficult to replicate currently due to BPS guidelines

Low internal validity - no control over details on how the research was carried so subjective researcher bias could have influenced data analysis