Objectives: Precarious employment (PE) is a determinant of poor health and health inequality. However, the evidence of health consequences and mechanisms underlying the associations, are still limited due to a lack of a comprehensive multidimensional definition and measurement instrument. The Employment Precariousness Scale (EPRES) is a Spanish, multidimensional scale, developed to measure degree of PE. The aim of this study was to translate the EPRES-2010 into Swedish, adapt it to the Swedish context and to assess the psychometric properties of the Swedish EPRES.
Method: EPRES was translated, adapted and implemented for data collection within the research project PRecarious EMployment in Stockholm (PREMIS). During 2016-2017, questionnaire data were collected from 483 non-standard employees in Stockholm, Sweden, sampled with web-based respondent-driven sampling. Analyses included item descriptive statistics, scale descriptive statistics and exploratory factor analysis.
Results: The final EPRES-Se (Swedish version of the EPRES),consisted of six dimensions and 23 items. There was a high response rate to all items and response options. Global Cronbach's alpha was 0.83. Subscales 'vulnerability', 'rights' and 'exercise rights' had reliability coefficients between α=0.78-0.89 and item-subscale correlations between r=0.48-0.78. 'Temporariness' had poor reliability (α=-0.08) and inter-item correlation (r=-0.04), while 'disempowerment' showed acceptable psychometric properties (α=0.5; r=0.34). Exploratory factor analysis confirmed the original EPRES factor structure.
Conclusions: 'Vulnerability', 'wages', 'rights', 'exercise rights' and 'disempowerment' worked in the Swedish context; however, 'temporariness' would need revising before implementing the EPRES-Se in further research. Continued work and validation of EPRES-Se is encouraged. In order to enable international comparisons and multinational studies, similar studies in other European countries are also called for.
Keywords: epidemiology; occupational & industrial medicine; public health; statistics & research methods.
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