Developing and validating a hostility, gratefulness and active support measuring instrument
MetadataShow full item record
South Africa is a very diverse country. There are eleven spoken official languages, different cultures, beliefs, backgrounds, educational levels, races as well as differences in socioeconomic status. Psychometric measuring instruments used in South Africa are mostly imported from Europe or America and are often not standardised for the South African context. The translation of such imported measuring instruments usually results in bias, in contravention of the Employment Equity Act (1998) which stipulates that all psychometric assessments should be bias–free, equivalent, and fair. It is of tremendous importance to take a country's political, economic and social history into account before developing a psychometric instrument, to ensure that the instrument will adhere to all legal requirements. A quantitative research design was used in this study. The sample consisted of students from tertiary institutions in North–West and Gauteng Provinces (SH–1: n = 473; SH–2: n = 476). Convenience sampling was used since the aim of the study was to test the reliability and validity of a newly developed instrument. Questionnaires were distributed amongst the participants from the tertiary institutions, to be completed within a set time and collected immediately after completion. The first objective of the study was to develop a valid and reliable measuring instrument that scientifically assesses the Hostility, Gratefulness and Active Support sub-clusters of the Soft–heartedness cluster of a new personality measure being developed for the South African context, namely the South African Personality Inventory (SAPI). Items were derived from person–descriptive terms gathered through a qualitative research design. The aim of this qualitative research design was to gather as many person–descriptive terms as possible and integrating these terms into a personality instrument. A principal component analysis was conducted to determine the item correlations, and items that did not function as expected were removed. Internal consistency coefficients were calculated to determine the item reliabilities. The second aim of this study was to determine the factor structure for the three sub-clusters of the Soft–heartedness cluster included in this study (pertaining to these three sub-clusters). A factor analysis was performed. A higher–order factor was present and a second–order analysis was performed, using the factor correlation matrix as input on the results. From the three sub-clusters assessed in this study, only two sub-clusters were extracted, and were labelled Hostility and Congenial Behaviour. This could be an indication that the positive and the negative items are clustering together in two separate groups, one indicating positive behaviour and the other negative behaviour. Finally, the construct equivalence across different race groups was evaluated by considering Tucker's phi coefficient and comparing the factor pattern matrices of the two factors obtained to compare the factor solutions between the white and African race groups respectively. The results indicated that each of the facets had similar loadings on their posited factors for both groups and that the two factors were represented by the same facets irrespective of the race groups. Recommendations were made for future research.