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Economic migration and the socio-economic impacts on the emigrant's family: A case of Ward 8, Gweru Rural district, Zimbabwe.

Everson NdlovuRichard Tigere
Published in: Jamba (Potchefstroom, South Africa) (2018)
Gweru Rural district in the Midlands province of Zimbabwe has witnessed an increasing number of outward migrations of breadwinners, leaving behind a desperate environment for families. This study was motivated by the realisation that most of the sick left behind, the elderly and children would visit the health centres unaccompanied, risking taking prescribed drugs incorrectly, thus further compromising their health. The study sought to establish the socio-economic effects of international migration on family members left behind in ward 8 of Gweru Rural. The study adopted a qualitative case study approach. Focus group discussions, questionnaires and structured individual interviews were used to elicit for data. Non-probability sampling design was used because of small samples available. Convenience and purposive sampling techniques were particularly used. Data were manually analysed and presented both qualitatively and quantitatively. The study revealed that international migration particularly to South Africa, especially by non- professionals, was not yielding the much expected economic gains; instead it was characterised by more negative social effects on the emigrant's family. The study recommends that emigrants should consider migrating with their loved ones and, where it is not feasible, to put in place sound alternative caregiving arrangements. The study has provided an insight into international migration and its effects on left-behind families. However, a more comprehensive and quantitative survey remains critical to delving deeper into this migration phenomenon, particularly on how both the emigrant and left-behind spouses handle the issue of conjugal rights.
Keyphrases
  • south africa
  • healthcare
  • public health
  • machine learning
  • electronic health record
  • risk assessment
  • deep learning
  • middle aged
  • big data
  • drug induced
  • community dwelling