Respondent-driven sampling: A new method for studying street children with findings from Albania

Abstract

Sampling methods to study street children often rely on convenience approaches. Respondent-driven sampling (RDS) is a relatively new methodology for sampling hard-to-reach populations utilizing peer-driven recruitment. It includes both field and analytical procedures to account for non-random recruitment patterns and generates statistically valid samples. This article describes RDS and assesses its effectiveness to recruit a diverse sample of street children, defined as children aged 10–17 years who engage in economic activity on the street in Tirana, Albania. This is the first publication on the use of RDS among street children. This article describes the demographic profile of street children and assesses whether they are sufficiently networked to justify the use of RDS as a sampling approach. Beginning with 10 initial recruits, 293 street children were recruited within 9 weeks. The sample included children of various ethnicities and principal work activities, as well as those with both a short and long history of street work. Males greatly outnumbered females (93.9% vs. 6.1%) and 20.6% of children reported sometimes sleeping away from home. Children had dense social network ties, irrespective of whether they slept at home every day. They also formed social networks related to ethnicity and type of work, but less so with respect to gender. Examination of recruitment patterns revealed important biases that may exist in other methods utilized to study this population. The importance of analytical adjustments applied in RDS is also demonstrated. RDS could be an important breakthrough for researchers and policymakers, providing a more accurate profile of street children's characteristics.