4.3 Review

Suitability of Measurement Tools for Assessing the Prevalence of Child Domestic Work: A Rapid Systematic Review

Publisher

MDPI
DOI: 10.3390/ijerph18052357

Keywords

PRISMA; child domestic work; child labour; prevalence methods; critical appraisal; measurement properties

Funding

  1. Millby Foundation as part of the Invisible Girls Research Programme at the London School of Hygiene and Tropical Medicine

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Child domestic work (CDW) is a hidden form of child labor that has been understudied. More sensitive, task-based methods are recommended for better inclusion of CDWs in household surveys. Researchers should also consider the possibility of CDWs being disguised as distant or non-relatives in their analyses.
Child domestic work (CDW) is a hidden form of child labour. Globally, there were an estimated 17.2 million CDWs aged 5-17 in 2012, but there has been little critical analysis of methods and survey instruments used to capture prevalence of CDW. This rapid systematic review identified and critically reviewed the measurement tools used to estimate CDWs in Low- and Middle-Income Countries, following PRISMA guidelines (PROSPERO registration: CRD42019148702). Fourteen studies were included. In nationally representative surveys, CDW prevalence ranged from 17% among 13-24-year-old females in Haiti to 2% of children aged 10-17 in Brazil. Two good quality studies and one good quality measurement tool were identified. CDW prevalence was assessed using occupation-based methods (n = 9/14), household roster (n = 7) and industry methods (n = 4). Six studies combined approaches. Four studies included task-based questions; one study used this method to formally calculate prevalence. The task-based study estimated 30,000 more CDWs compared to other methods. CDWs are probably being undercounted, based on current standard measurement approaches. We recommend use of more sensitive, task-based methods for inclusion in household surveys. The cognitive and pilot testing of newly developed task-based questions is essential to ensure comprehension. In analyses, researchers should consider CDWs who may be disguised as distant or non-relatives.

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