The computer revolution has not only improved analysis in quantitative studies but has also been useful in qualitative analysis. For many decades, quantitative research has been conducted using handwritten notes and interviews, and transcribed verbatim by hand. Ideas and messages are distinguished by underlined text, written codes in the margins or pages, or otherwise highlighted segments of print. This article examines the use of computer software.

Introduction

Data are organised through and paste system while sorting is done thematically. Not all researchers still accept the role of the computer. They argue that it distances the researcher from the text. This is the work of computer software.

Nevertheless, computer software programs have been found useful in that they enhance qualitative analysis by performing several basic data manipulation procedures which ordinarily could not have been possible using free hand.

For instance, creation and insertion of codes into text files (see Table 7.1), indexing, construction of hyperlinks and selective retrieval of text segments (Kelle 1997).

Essentials of Computer Software in Qualitative Data Analysis

The following must be taken into consideration while choosing qualitative data analysis (QDA) software:

How complex is the data

How complex is the analysis?

Meeting the goal of summarising individual topics

Description of the way different topics are related to each other.

Ability to import and export data

The number of socio-demographic variables involved

Resources available

Staff

Time

Computer facilities (MacQueen, 2002)

Characteristics of a simple qualitative study.

Limited descriptive goals, e.g. to summarise the range of responses on five or fewer major topics.

-Limited data needed to achieve the goal. E.g.20IDI,10FGDs

-Analysis will be done by 1-2 people.

-Little or no socio-demographic data to be used during the analysis, e.g. sex and ethnicity.

Software needs based on study complexity:

Moderately Complex

An explanatory goal

A moderate amount of data, 10-20 FGDs, 20- 50 IDIs.

The analysis team is to have 2-4 people.

More than five major topics are to be covered by the study, with overlapping issues within at least some of the topics.

Limited socio-demographic data to be used during the analysis, e.g. not more than 20 variables.

Complex Study

A major scientific goal, e.g. theoretical modelling or hypothesis testing.

Data collection on a large set of topics that are organised into hierarchies or networks of information.

Very large volumes of text, e.g. <1000 pages or>100 text files.

Detailed quantitative measures or descriptions will be the qualitative results. Coordination of one large analysis team (>5 people) or multiple small teams with discreet analytic tasks (MacQueen 2002)

An example of a software package for qualitative analysis is Open Code Computer Software.

Open Code Computer Software

Open Code computer software  is a tool used for coding qualitative data generated from interviews or observations. It has been developed to specifically follow the first steps of the Grounded Theory Method. However, it can also be used as a tool for classifying and sorting any kind of qualitative information. It aims at creating a self-instructive programme that is easy to understand and use.

Features of the Open Code are:

• to import documents typed in any word processing program
• to assign codes to segments of the text
• to produce lists showing frequencies of use
• to search for single codes or combined codes in the documents
• to produce lists of search results
• to print the results from any of the functions

Documents

Documents (text files) are imported into a project, where freely made up and assigned to the lines. In functions like Windows of Open Code, one views a document in the project and does most of the coding.

A project can consist of many documents. The names of the documents are displayed in a LIST BOX at the top, where one can select the one to work with. The text of the active document is displayed in the document grid, which takes up the main part of the window. The controls to the right of the document LIST BOX are the coding tools.

One selects a group offline by clicking on the row numbers of the document. The existing codes in the selected area are shown in the Assigned Codes list box. One can enter a code in the Assign code textbox and add it to the selected text lines by clicking the Add button. The Remove button can be used to delete a code.

In the menus, one can select other features. In the File menu, one can create a new project or open an existing one and import documents from text files. Functions to delete or rename documents are also found in the File menu.

A document consists of text lines with codes, but also a comment. One can view and update the comment and get some statistics as the number of offline users. This function is used by selecting Document Information in the File menu.

File Menu

In computer software, Use Print in the File menu (or press Ctrl+P) to print the active document. One can change the font size and line spacing. In the Code menu, one will find functions to list codes and search and a function to globally rename a code. Code lists and search results can be printed.

Also, most software helps to construct indices. Most software enables one to conduct simple word searches. A hyperlink enables one to cross-reference or link a place of text in one file with another in the same or different file.

Data Display

This means laying out or taking an inventory turning attention to capturing the difference, or richness of each theme, separating qualitative and quantitative aspects and taking note of differences between individuals or among sub-groups.

Data Reduction

This simply means organising the information to show the essential concepts and relationships. Data reduction usually takes place once all the data is in and one is already familiar with the content. Data reduction aims to have a general sense of the data and to distinguish between primary and secondary themes. It also enables the process of separating the essential from the non-essential.

To get this wider perspective on the data, Ryan and Bernard (2000) suggested that it would be helpful to use visual devices. For instance, matrices, diagrams, or taxonomies can be developed for each thematic file that has remained primary to the study. For instance, the ZY Index table is a good example.

It tries to identify and explain the “core meaning” of the data. It not only tries to ensure essential meanings of qualitative data, but it also ensures that the interpretation offered is “trustworthy”. Interpretation of data also tries to ensure the question of how to approach interpretation when a study includes both qualitative and quantitative data-collection methods.

Data Interpretation

Data interpretation involves communicating the essential ideas of a study to a wider audience and remaining faithful to the perspectives of the participants (Ulin et al. 2002). Interpretation of data aims to identify ways in which most of the emerging themes and sub-themes, connections, and contradictions fit and what it all means.

The meaning generated from the data must not only reflect the perspective of the participants, but it must also address the interest of the larger population in such a way that it answers questions of social and theoretical importance.

Integration of Qualitative Findings into Mixed Methods Design

Triangulation of methods has been used to generate data. It has proved better than when a single method of data collection is used, as the methods corroborate each other. But the problem so far is how to integrate the methods in a single report. The first step in integrating qualitative to quantitative findings is to first of all analyse each data separately using a procedure associated with its paradigm.

Having done this, the integration of the findings will now depend on the objective of each component and the study design. This determines whether both findings have equal weight in the study design or not. Although the two components of a mixed-method design are conducted sequentially, one is considered the main study (Ulin et al. 2002).

Linking Qualitative and Quantitative Analysis

Linking qualitative and quantitative analysis may be fairly straightforward especially when these data are conducted sequentially. But this may not be the case in a situation when they both have equal weight (TashakkoriandTeddie 1998). In a situation where data from qualitative and quantitative research do not agree, the researcher must look for explanations that reconcile the initial explanations. This may require additional analysis of either or both types of data.

However, in a situation where some findings prove interpretations and allow readers to draw their own to provide sufficient information on the data collection and analysis strategies to allow readers to evaluate for themselves the credibility of your interpretations and perhaps to arrive at different conclusions (Ulin et al. 2002).

How to Organise a Qualitative Report

Modifications resulting from the need to make the scientific reports outline fit the research material. The type of information required by the audience should influence the outline. It is also important to take into consideration the theoretical background for the study. Such writing should also conform to standard scientific reports, but with certain variations in the

ordering of contents as the case may be. The following are some of the approaches that can be used to organise our report.

Problem-solving approach

State the problem and describe the importance of the research topic and its implications, e.g. for health policies or practices, or its impact on theory.

Briefly describe your methods. State what one has learned, e.g. about individual reproductive health themes and concepts. Offer your conclusions.

Narrative approach

Tell the story chronologically by illustrating a problem or process, e.g. factors hindering the use of healthcare services, step-by-step or from multiple perspectives

In your conclusion, explain why and how the process occurs. For example, if your study examines access to modern healthcare facilities in more than one community, you might organise your findings site by site.

Policy approach

Present a conclusion on why a process or behaviour occurs or fails

Use the data to show how you arrived at this conclusion. Journalistic and policy-oriented reports typically follow this pattern for busy readers who have little time for reading lengthy articles until they have grasped the relevance of the material.

Analytic approach

Organise findings in terms of the theoretical or conceptual framework used to develop the study. Use computer software to describe what is learned and how it fits into the larger framework. Regardless of the format chosen, the basic principles that hold for all scientific writing must be followed, that is, demonstrate a knowledge of available scientific literature, and get your facts right. Read similar posts on our research page of the site.