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Quantitative and qualitative methods to survey hard-to-reach populations 1 |
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| Session Organisers | Dr Alessandra Gaia (University of Milano-Bicocca) Dr Daniele Zaccaria (University of Applied Sciences and Arts of Southern Switzerland (SUPSI)) |
| Time | Wednesday 19 July, 14:00 - 15:00 |
| Room | U6-01e |
Survey researchers often face the challenge to collect data on so called “hard-to-reach population” or “hard-to-survey” populations. These terms refer to population subgroups that are rare, marginal, hidden, elusive or excluded from mainstream society and thus hard-to-locate, sample, contact or interview. Examples include sex workers, illegal immigrants, victims of trafficking, drug users, displaced populations, homeless, institutionalised people, but also groups that – while not being excluded or marginalised – are rare and elusive (e.g. elites), hard-to-persuade to take part in surveys or hard-to-interview (for example due to lower cognitive abilities, like the oldest-old).
Exclusion of hard-to-reach population subgroups from data collection may lead to biased estimates on topics of relevance for social science research (e.g. poverty, inequalities, physical and mental health, social care, housing, migration, wellbeing, and social exclusion); ultimately, lack of information on hard-to-reach population subgroups lead to policy agendas which may not take into account the needs of the most vulnerable in society, and exacerbate social inequality and conflict.
However, meeting the need for high quality data is complex. To overcome this challenge, a number of quantitative and qualitative research methods have been developed, including: techniques to estimate the size of hard-to-reach populations (e.g. capture-recapture), sampling strategies (e.g. Respondent Driven Sampling), and data collection methods to ask questions about sensitive topics, including indirect questioning techniques (e.g. the Item Count Technique), adoption of proxy respondents, passive data collection through new technologies, participatory mapping, visual methods, etc.
We welcome submission on empirical or theoretical comparison of different research techniques, theoretical discussion of challenges faced by social researchers in surveying hard-to-reach populations and elaborations on the ethical principles guiding research on these population subgroups.
Keywords: Hard-to-reach populations, hard-to-survey populations, indirect questionning techniques, Respondent Driven Sampling, Passive data collection
Dr Charlotte Clara Becker (University of Cologne) - Presenting Author
Ms Leonie Diffené (University of Cologne)
Migrants' family structures, such as parent-child relationships, have been the center of demographic research for many years. So far, however, it has been difficult to capture the entirety and complexity of migrants' family networks. Therefore, questions like how many nuclear and extended family members migrants have and what their relationships look like remain unanswered. This lack of knowledge is due to multiple reasons. Firstly, migrants are often underrepresented in national surveys, and their family members are less likely to participate in cross-household surveys, given that - by definition - many of them live abroad. Secondly, even in large-scale analyses using register data, migrants and their relatives often have to be excluded since no information is available for family members who live outside the area covered by the registry. Such data collection problems can be addressed by focusing on individual migrants and asking them to provide extensive information on their family members. The ERC-KINMATRIX research project has implemented this approach, collecting data on the composition of family networks of 25 to 35-year-olds across nine European countries and the US with an overall sample size of around 10,000 participants. Specifically, the study invited participants to create a full family tree, asking them for the exact number of kin existing across categories. Using these data, we compare first- and second-generation migrants family networks with those of natives. Our objective is to reconstruct the so-called kinship matrix that provides information on the presence and availability of both nuclear and more extended family members, such as parents, siblings, aunts/uncles, cousins, and half-/step-relatives. Knowing more about migrants' comprehensive family structures could shed light on what kind of support is provided by the family and what kind of social policies might be needed to further promote integration.
Dr Ursula Till-Tentschert (EU Agency for Fundamental Rights (FRA)) - Presenting Author
Dr Rossalina Latcheva (EU Agency for Fundamental Rights (FRA))
Mr Jaroslav Kling (EU Agency for Fundamental Rights (FRA))
Roma and Travellers are among the people who are most vulnerable to human rights violations in the European Union (EU). The EU Agency for Fundamental Rights (FRA) has consistently demonstrated this using robust statistical data since 2008. The results of FRA’s surveys in 2008, 2011, 2016, 2019 and 2021 show that the EU’s and Member States’ efforts result in limited and uneven progress to combat discrimination, poverty and social exclusion. The surveys show the persisting impact of antigypsyism and the problems many Roma and Travellers still face in enjoying their fundamental rights regarding equal access to employment, education, healthcare and housing.
According to the UNECE Guide on Poverty Measurement, there is a strong need to improve inclusiveness of statistics and availability of disaggregated data for measuring poverty by paying stronger attention to fieldwork approaches for hard to reach populations. Tourangeau et al. (2014) distinguish between populations that are hard to sample, hard to identify, hard to find or contact, whose members are hard to persuade to take part, and whose members are willing to take part but nonetheless hard to interview. Surveys including hard to reach populations vulnerable to poverty face several measurement issues beyond but also related to sampling and coverage – such as the definition of a household, how to approach and identify these populations and how to minimise non-response. Fieldwork tools (e.g., respondents might be illiterate), the interview mode and the setting of the fieldwork (e.g., recruiting facilitators/interviewers of the target population) have to be adjusted as well.
The talk will build on FRA’s experience in surveying Roma and Travellers across the EU and discuss the human rights based principles it applies in surveying hard-to-reach populations, its survey and sampling design, as well as the role of fieldwork materials,
Dr Ai Rene Ong (American Institutes for Research) - Presenting Author
Professor Michael Elliott (University of Michigan)
Professor Sunghee Lee (University of Michigan)
Respondent driven sampling (RDS) is a sampling method that leverages the respondents' networks to reach more members of the target population. In RDS, the personal network size (PNS) of the respondents (the size of the respondents' social network) is important in both the study operations and in estimation. Measurement error in the PNS can introduce biased estimates for RDS when RDS estimators are used, especially if the misreporting of PNS is associated with the outcome to be estimated. This study examined how respondents report their PNS by testing the common PNS question wordings. This study used two sets of data; 1. semi-structured in-depth interviews conducted over Zoom with 19 adult respondents of various ages, gender identities (transgender, nonbinary, cisgender), race, and sexual orientations, 2) an RDS web survey targeting the adult LGBT population (n = 394). Thematic analysis conducted on the semi-structured interview transcripts showed a large variation in how respondents define "knowing" someone; for some respondents, it covers a larger network than the "recruitable" network (the network of people respondents are likely to think of recruiting to an RDS study). Meanwhile, the web-RDS showed that the more restrictive PNS questions yielded more realistic ranges for a "recruitable" network, including a smaller proportion of rounded responses.