Introduction:

Experts of the Faculty of Psychology of the University of Havana proposed the Personal, Labor and Social Human Well-being questionnaire (BHPLS, in Spanish), that was applied to 135 Cuban workers of three social and occupational groups. Given the variety of responses, a content analysis (CA) was used for Question 1 of the mentioned questionnaire.

Objective:

To present and implement a software that allows a semi-automatic categorization in a CA used for this question.

Material and Methods:

The Kappa index test was used to evaluate experts´ agreement with respect to category schemes. We implemented a software with the Python programming language to achieve our objective, considering other similar software functionalities.

Results:

We implemented, validated and registered the software BHPLS data processing-UH® that allows to set up a categories system, load the collected data, categorize associations in a semi-automatic way, and save the results, among other functionalities. This software was validated by Psychology students and, when they performed the manual categorization, a negative Kappa agreement index (low categorization agreement between experts) was obtained whereas using the proposed software, a global Kappa index of 0.7871 with p=0.00 (high and statistically significant categorization agreement between experts) was obtained. Besides, we proposed a unified algorithm for expert’s categorizations, and carried out a Correspondence Analysis (ANACOR) on the basis of the categorizations achieved.

Conclusions:

According to the high concordance attained, we recommend the software due to its adaptability, ease of use, and “humanization'' of the process. The CA allowed us to observe similarities in social and occupational groups. The software functionalities can be applied for processing free associations in other scenarios.

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