Table 1

Data analysis methods

Data collection tool	Data analysis method
Research questionnaire (research objectives (a), (b), (c) and (e))	Frequency tables shall be used to analyse single-response questions (thus, mostly demographics). Custom tables shall be used to analyse multiple-response questions and Likert-type response questions. Means and SDs shall also be used to analyse Likert-type response questions. Summary statistics shall be used to analyse continuous variables in the study. Exploratory factor analysis shall be used as a construct validity technique. Reliability analysis shall be used to assess the internal consistency of the questionnaire. Correlation analysis shall be used to measure the relationship of the (economic, political and legal, demographic, sociocultural and technological) factors in the study. Logistic regression analysis shall be used to determine if economic, political and legal, demographic, sociocultural and technological factors have an impact on reporting injuries and illnesses. Independent variables Economic, political and legal, demographic, sociocultural and technological factors Dependent variables Under-reporting injuries; under-reporting illnesses
In-depth interviews (research objective (d))	Inductive methods shall be used to analyse interview transcripts: Thematic content analysis Remove biases to establish overarching impressions in the data. Identify common themes/patterns from the data set. Narrative analysis Make sense of interview respondents. Highlight important aspects of responses. Highlight critical points found in other areas of the research.
Data extraction sheet (research objectives (a), (b) and (e))	Summary statistics analyse continuous variables emanating from the data extraction sheets. Frequency tables analyse the count of reported work injuries, illnesses, low-income and middle-income workers. Χ² tests of independence measure the association between reported work injuries and level of employees (low-income and middle-income workers). Χ² tests of independence measure the association between reported illnesses and level of employees (low-income and middle-income workers).