In this research methods in psychology video its content analysis. Quantitative data is great we
can make tables, charts, work out averages and do statistics on it. But what about when the
data has been collected, and it's in the form of words? Well there is a way to turn this into this!
So let's look at content analysis, its strengths and weaknesses and a classic study that looked at
the different sexual choices of males and females. INTRO
Let's start with a definition of content analysis, it is an indirect observational
method. We observe human behaviour through the things humans make, a word we can use
for things humans make is an artifact. So I could perform a content analysis on
1950’s advertisements, the art of the middle ages, films from the late victorian age or greek pots.
But generally when we conduct content analysis it is on the written word and
the process allows us to give a quantitative description of qualitative human communication.
To start a content analysis you begin by deciding the research question,
and then selecting an appropriate sample. So your sample could be a selection of diary entries,
tweets or children's books. You usually won't be able to analyse every possible example so you will
have to decide how you select your sample. Examples of behavior you are recording are
called coding units or behavioral categories, these are linked to your research question, and
in the same way as we discussed in the observation video, they need to be operationalised. That means
defined so they can be as precisely measured as possible and then recorded in a frequency table.
Lonely Hearts Let's discuss a particularly
interesting content analysis by Waynforth and Dunbar in 1995. This should help us understand
the process of content analysis a little better. The researchers were interested in theories of
mate choice in sexual relationships and how these match ideas from evolutionary psychology.
In short the evolutionary theory is this, both men and women want to have children to pass on their
genes. However because of their biology they should have different reproductive strategies.
Men will look out for younger and attractive mates as indications of fertility,
whereas women on the other hand will look for older mates because men are fertile for longer
than women, but will also look for males with resources, like a house, a good job and money
to provide for a potential family, and males tend to get more resources as they age.
So that's the evolutionary theory. To test these ideas 881 lonely heart adverts
were taken from 4 newspapers in america. The ages were recorded, and coding frames
for physical attractiveness included terms like athletic, attractive, cute, fit, good-looking,
healthy, nice body (for both sexes); handsome, hunk, muscular, rugged, tall, well-built
(for males); or buxom, petite, pretty, shapely, slender, slim (for females).
Coding frames for wealth status included terms referring to home-ownership,
professional status, being well-off, a business-owner or university-educated,
or suggesting an above-average lifestyle. When this qualitative data was converted to
qualitative data it backed up the evolutionary theory. Men looked for significantly younger
mates and females significantly older mates. Men showed off their resources
more than women, 41.7(M) 24.5 (F) women asked for resources more than men 4(M)18.2 (F) and women
mentioned their own attractiveness more than men 34.4(M) 49.5(F) and men asked for attractive
partners more than women 44.4 (m) 22.3 (f) So you can see from this example of content
analysis how a large set of qualitative data, that wasn't created for the researchers can be
used by psychologists, turned into quantitative data and provide evidence to a research question.
Conducting a content analysis and testing for reliability.
So if you were asked to complete a content analysis this is what you would do.
Firstly you need to decide measurable categories to record,
this would be linked to the content you have collected so for example looking for
sexist references in a set of interviews or advertisements. Then you would need to
carefully work through the recordings or pages and tally each time one of the categories appears.
You may, in the same way as an observation, want to check the reliability of a content analysis.
That is, is it repeatable, do you get the same data by doing it again. And the same options
that you had for an observation are possible Test-retest and Inter-rater reliability.
Test-retest reliability would simply involve running the content analysis again
on another occasion on the same data and comparing the results of the two sets of data.
Inter-rater reliability would mean you would get a second rater,
so two researchers complete the content analysis separately. Tallying using the same set of
agreed operationalised categories of course. Then they can compare the two sets of data.
Now for both test-retest and inter-rater reliability we are looking at how much
correlation we have between the two sets of data. Researchers when conducting a test of
correlation will generally accept a correlation coefficient of 0.8 between the ratings as showing
the data is reliable. Evaluations
So evaluations, what is good and bad about the use of content analysis in psychological research?
Well the positives first. As the material was not created
for research but are real artifacts created by people they have high external validity.
This should be a true reflection of how people behave and as long as we have carefully selected
our sample we should be able to apply these findings to other groups and situations.
It's also generally easy to get a sample, this data already exists in the real world
and is often freely accessible. Replication is also possible
by other researchers who can analyse the data with the same behavioral categories.
However as with any type of research that requires interpretation of meaning,
there is the possibility of observer bias, with the researcher applying behavioural categories
in a way that matches their research question. We can also suggest content analysis can lack
validity, the data is created for other purposes than research and is a record of opinions,
not behavior. Dairies, letters and tweets may not be truthful records.
Thematic Analysis Before I finish I want to very quickly discuss
a variation on content analysis called thematic analysis, rather than starting using predetermined
categories first then counting the frequency of these categories like in content analysis,
in thematic analysis the researcher starts by attempting to discover the deeper meanings in
the text or interviews by carefully reading first, spotting patterns that can be coded,
and then identifying themes from that process, we would call those themes “emergent”. This is
a more flexible way of analysing the qualitative data with theories coming after the discovery
of themes. And this is intended to stop the researcher imposing their own ideas on the texts.
But of course thematic analysis as a form of content analysis
shares the many of the strengths and negatives of content analysis.
So that was content analysis, I have 6 tutorial videos covering the 2017,18 and 19
AS and A-level research methods sections, these videos have worked examples to every question and
are full of exam tips. Patrons at the neuron level and above can access these, and many,
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next research methods video, case studies