Content Analysis In Research
What Content Analysis
Content analysis is a data analysis technique that is commonly used in qualitative research and focuses on structuring particular topics or domains of interest from unstructured data.
It is a time consuming process that involves organizing, identifying, coding, and making categories from patterns of data that are reflective of the topics (Patton, 1990).
The topics or domains of interest are descriptive names chosen by the researcher and are sometimes also referred to as category labels (Morse, JM, & Field, 1995). Historically, early content analysis focused on linguistic and observational data.
However,
in addition to information derived from interviews and casual or structured
observations, researchers may analyze written text from special documents, archival
records, field logs, and diaries or may develop schemes to analyze visual data
from pictures or videotapes.
How It Get Started
Content analysis begins with reading the text or written transcription of an interview, notes from an observation, or some other mode of data collection. The investigator reads the completed text and determines the main ideas or topics of the transcription or observation.
The investigator then rereads the text and numbers and assigns a code to each segment or group of lines from the transcription.
Sometimes this may also be called labeling. Segments may consist of a single word or line, multiple words or lines, one or more paragraphs, or a pictorial schema and may vary according to the chosen topic or topics.
The codes developed by the investigator reflect some commonality, such as an action or behavior, an event, thought, concept, and so forth.
Line segments or groups
of lines are separated and are grouped into categories, and the categories are
grouped according to the topics that were identified by the investigator.
Selection of Domain Or Topic
Topics or domains of interest may be chosen prior to a study, as with a focused study, or after the first interview. A focused qualitative study centers on one particular area of interest or intent, such as metaphorical analysis or feminist research.
Another kind of focused study might center on a particular phenomenon
like leadership style, body adornment among adolescent girls, or a
demonstration of how caring activities are performed, to name a few.
The researcher may also choose to develop topics after a first interview or observation. Sometimes the topics seem to arise naturally from the data, whereas at other times the researcher must decide on and develop the topics from the information given.
Developing a topic may be similar to making an index for a book or file labels (Patton, 1990). The researcher reads through the transcript of the interview or observation and begins to sort and organize the interview data according to likenesses and similarities.
The researcher usually gets a sense of the main to pics that pervade the text soon after the transcribing process is complete and after the first reading.
This organization
of the data may be done by hand or by using one of the many computer software
packages that are available to assist organization of qualitative data.
Making Topics Too Specialized
JM Morse and Field (1995) suggest using between 10 and 15 main topics per study. They caution against making topics too specialized as only very small amounts of data will be able to fit into each.
On the other hand, too many topics can cause confusion, and the researcher may have difficulty in remembering what categories go into each topic as the study progresses and more data are collected.
With each subsequent interview or observation, the topics may be combined or subdivided into multiple categories as the need arises. As repetitive patterns arise, relationships between the categories and then between the two topics may be seen.
Often the relationships may occur at the same time or be concurrent with each other. For example, in a study of adolescent face care, the topics "blemish care" and "facial scrubbing" are related and occur at the same time.
In the same study, the topic "facial preparation" occurs or is antecedent to the topics of "blemish care" and "facial scrubbing," whereas the topical area "making up the face" may occur as a consequence of one of the earlier categories that was formed (Morse & Field).
Some researchers choose
to quantify part of the analysis by counting frequency and sequencing of
particular words, phrases, or topics.
Reliability and Validity Issues of Content Analysis
The major reliability and validity issues of content analysis involve the subjective nature of the researcher-determined topics or category labels.
What should be included within each topic should be clearly defined and should be clearly different from the others so that the results are mutually exclusive.
The easiest way to determine reliability in a study that uses content analysis is to have two or more readers, other than the researcher, agree that the topics are appropriate for a particular study and that data can easily be organized under each.
This is typically carried out by having the researcher randomly
choosing a part of the study and having the readers look over the text and the
topics independent of each other. A consensus of the readers would indicate the
study's reliability.
Validity in content analysis can be achieved by determining the extent that the topics represent what they are intended to represent.
If the topics are based on a conceptual framework or a particular focus, they must be justified, described, and explained in terms of being representative of that conceptual framework or focus.
Therefore, topics that are developed to reflect a conceptual framework
or focus must be consistent with the original definitions described by that
framework. However, because content analysis is often used in exploratory and
descriptive research, a conceptual orientation may not be used.
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