Construction and Field Application of an Indirect Sampling Method (Time-Location Sampling): An Example of Surveys Carried Out on Homeless Persons and Drug Users in France

Abstract

Since the mid-1990s, Time-Location Sampling methods have been widely used in France in quantitative research about the homeless (Marpsat and Firdion, 2000; Brousse, 2002) and drug users (Emmanuelli et al. 2003;Jauffret-Roustide et al. 2006). Adapted from methods of indirect sampling initially developed in the United States (Burt and Cohen, 1989;Dennis and Iachan, 1993), they enable the design of representative samples of hard-to-reach populations for whom there are no sample frames, by basing it on support facilities for the populations of interest: day centres, soup kitchens, accommodation services, health care, mobile teams etc. However, in transition from the theoretical protocol to its implementation, various difficulties emerge. In particular, the necessary involvement of these support services; the constraints associated with the administering of questionnaires in sometimes very particular conditions (at night, in public places or while following mobile teams) and the singular organisation of each of the services that has to be involved means that challenges occur as regards coverage of the field being investigated and the representativeness of the sample. These challenges mean that the method has to be appropriately and pragmatically adapted to the various configurations that are met with. In this perspective, we will show how the integration of qualitative methods, such as the observation of the services and the realisation of in-depth interviews with the persons in charge of them, have contributed, along the various data collections and with the accumulation of experiences, to improve the methodology of and the scope covered by quantitative surveys.

Do perception factors affect adaptation behaviours against air pollution among vulnerable occupation groups? evidence from chittagong and dehradun

“…(Reichel and Morales 2017). This strategy allows for representative samples of hard-to-reach populations for whom there are no sample frames (Quaglia and Vivier 2010). TLS used in the study is held to approximate random cluster sampling where everyone attending the cluster (location) has an equal chance of inclusion but are sampled as a group.…”