1.1: Background
Many research projects require the collection of semi-structured qualitative
data. This includes situations where interview guides containing a series of
open-ended questions are consistently administered to each person in the sample,
though the content, length, and complexity of responses to the questions may
vary widely between respondents. For example, HIV/AIDS risk behavior studies
sponsored by the Centers for Disease Control and Prevention (CDC) frequently use
semi-structured interview instruments. These instruments typically include 20 to
50 open-ended questions, and sample sizes may include several hundred
individuals residing in multiple communities. Some projects utilize as many as
20 or 30 different interviewers. Written summaries or verbatim transcripts from
tape recordings are generated following each interview, and the final
computerized databases contain hundreds and sometimes thousands of pages of
text.
One challenge in conducting this type of research concerns the organization
and management of the data prior to analysis. Multiple interviewers may work on
different WindowsTM or Macintosh® platforms; conversion of files
between systems can be time-consuming. Even when all research staff use the same
platform, variations in margin, font, and other preferences affect the physical
data organization. Also, response segments relevant to a specific question may
be placed in different locations within the write-up for each respondent.
Further complications occur when interviewers make independent changes to the
data collection protocol, such as altering the number, wording, or intention of
the questions on the interview guide.
Under these conditions, it is difficult for study coordinators to monitor and
ensure the consistency of data collection and write-up across the sample. Even
when interviews are conducted in a comparable manner, inconsistent organization
of the interview notes may mean that study coordinators must reformat the data
into a standard layout prior to analysis. Not only does this waste financial
resources and staff time, it causes delays in generating research findings.
Occasionally, these barriers are so large that the data are never fully
analyzed.
1.2: Summary of "CDC EZ-Text" Functions
"CDC EZ-Text" Version 3.06 (EZ-Text) is a new qualitative software program
developed to assist researchers in creating, managing, and analyzing
semi-structured qualitative databases. EZ-Text helps solve the problem of
consistency across interview write-ups by allowing a researcher to design a
series of qualitative data entry templates tailored to his/her questionnaire.
Data can be typed directly into the templates or copied from word processor
documents and can accommodate special non-English alphabet characters such as:
Ö, Æ, Ø, é, á, í, ó, and ñ. Following data entry, investigators can create
on-line codebooks, apply codes to specific response passages, develop case
studies or case series, conduct database searches to identify text passages that
meet user-specified conditions, and export data in a wide array of formats for
further analysis with other qualitative or statistical analysis software
programs. Project managers can merge data files generated by different
interviewers for combined cross-site analyses. The ability to export and import
the codebook helps to coordinate the efforts of multiple coders simultaneously
working with copies of the same database file.
1.3: Notice to Users
EZ-Text was jointly designed and developed by staff from Conwal Incorporated
and the Centers for Disease Control and Prevention (CDC). Its primary purpose is
to help meet CDC's own public health research needs. Other investigators may
determine that the program is useful for different purposes. However, neither
CDC nor Conwal Incorporated make any expressed or implied guarantees that this
software program will be an appropriate or useful tool for addressing the needs
of other potential users. No warranty is made or implied for the use of the
software for any particular purpose. CDC, Conwal Incorporated, and their staff
or subcontractors are not responsible or liable in any way for any consequences
resulting from the use or misuse of the EZ-Text program or its documentation.
The EZ-Text software program and its associated documentation are in the
public domain; they may be freely copied and distributed without restriction.
However, potential users should understand that there is no formal mechanism
available for technical support beyond the help files included with the program
installation diskettes. To obtain a copy of "CDC EZ-Text" Version 3.06
free of charge, researchers can copy installation disks from the
CDC web site.
Trade names are used for identification purposes only or for examples; no
endorsement of particular products is intended or implied. The use of trade
names or trademarks in the EZ-Text documentation does not imply that such names,
as understood by the Trade Marks and Merchandise Marks Act, may be used freely
by anyone.
1.4: Suggested Citation for CDC EZ-Text
Carey, James W.; Wenzel, Patrick H.; Reilly, Cindy; Sheridan, John;
Steinberg, Jill M.; and Harbison, Katherine (1998). " CDC EZ-Text": Software
for Collection, Management and Analysis of Semi-structured Qualitative
Databases (Version 3.06). Atlanta: Developed by Conwal Incorporated for the
Centers for Disease Control and Prevention.
1.5: Suggested Applications
A central assumption behind the design of the EZ-Text program is that the
user wishes to examine the same set of topics with each individual in his/her
sample. As noted above, this may entail use of the same semi-structured
interview instrument with each respondent. EZ-Text might also be used to collect
and analyze semi-structured behavioral observation data.
However, EZ-Text is not likely to be very helpful to researchers
administering highly unstructured ethnographic studies where the set of
discussion topics or behavioral observation categories vary greatly among each
person in the sample. Similarly, EZ-Text is not a substitute for statistical
analysis software. In our view, EZ-Text helps address a specific set of needs
related to semi-structured qualitative data, especially when it is collected and
coded by different individuals following a common protocol on a multi-site
research project. If investigators do not wish to generate and analyze a
semi-structured qualitative database, we recommend that they choose a different
software tool (Weitzman and Miles 1995).
If your needs include the use of this software tool, then follow the simple
instructions in this guide.
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