Emmanuel Ngwakongnwi
Background: Canada has two official languages, English and French. French is the main language in Quebec while English is widely spoken in other provinces and territories. Canadian census data has shown that there is a significant portion of the population in the English speaking provinces that identify French as their mother tongue; and prefer to be served in French when they seek healthcare. This means that they are not able to speak, read, write, or understand the English language in a way that enables them to interact with others daily in English, let alone participate in research conducted in English. Thus the designation, English Language Barrier (ELB). The ELB populations can be difficult to sample for research purposes especially when language affiliation becomes an important identifying variable, thus, can be described as a potentially hard to-reach populations. Inadequate sampling compromises quality of data from which inferences are derived. Aim: The purpose of this paper is to present challenges to collecting valid research data and suggest ways by which such challenges can be overcome in ELB populations in general. Methods: To achieve this, I start by defining ELB populations, followed by a brief description of what constitutes valid data. Subsequently, I discuss evidence on data collection practices and identify major challenges. In the discussion, I present ways by which these challenges can be mitigated; and conclude with a summary of the evidence, the challenges, and suggestions to improve data collection in general. Conclusions: Collection of valid research data among ELB populations can be enhanced by using innovative sampling techniques such as respondent driven sampling, reducing bias and improving on the questionnaire.
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