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dc.titleUncovering the Hidden: Innovative Methods for Data Collection from Hard-to-Reach Populations
dc.contributor.authorLupica, Carina
dc.contributor.authorMertehikian, Yasmin Amira
dc.contributor.authorCaravedo, Sofía
dc.contributor.authorSilvera, Christian
dc.contributor.orgunitGender and Diversity Division
dc.date.available2026-08-05T00:08:00
dc.date.issue2026-08-05T00:08:00
dc.description.abstractThis document examines the challenges involved in collecting data on hidden or hard-to-reach populations, which are characterized by limited statistical visibility due to structural, social, legal, or stigmatization-related barriers. These limitations create information gaps that directly affect the quality of the design, implementation, and evaluation of public policies, as well as the efficient allocation of resources and the ability to promote inclusive growth. Drawing on a review of the literature and applied experiences, this document systematizes and compares different innovative methods used to access these populations, many of which originated in public health and were subsequently adapted to social analysis. The most widely used approaches include time-location sampling (TLS), targeted sampling (TS), respondent-driven sampling (RDS), and snowball sampling, each with strengths and limitations depending on the context, the density of social networks, and the objectives of the research. The document also highlights the value of complementing these methods with qualitative techniques, such as mystery shopping and vignette studies, to capture deeper dimensions of social experiences. The document emphasizes that there is no single method applicable to all situations; therefore, methodological choices should respond to the context and characteristics of each population. From an operational perspective, the participation of community members themselves and the development of trusting relationships with key stakeholders are essential to improving access and the quality of information, alongside ethical considerations such as anonymization, the use of respectful language, and the creation of safe environments. Ultimately, researching these populations requires balancing the production of evidence with the ethical responsibility to avoid exacerbating existing vulnerabilities, recognizing that the most effective approaches combine methodological plurality, contextual sensitivity, and a commitment to inclusion and to making historically marginalized realities visible.
dc.format.extent68
dc.identifier.doihttp://dx.doi.org/10.18235/0014443
dc.identifier.urlhttps://publications.iadb.org/publications/english/document/Uncovering-the-Hidden-Innovative-Methods-for-Data-Collection-from-Hard-to-Reach-Populations.pdf
dc.identifier.urlhttps://publications.iadb.org/publications/spanish/document/Definir-lo-oculto-Metodos-innovadores-para-la-recoleccion-de-datos-de-poblaciones-de-dificil-acceso.pdf
dc.identifier.urlhttps://publications.iadb.org/publications/portuguese/document/Definir-o-oculto-Metodos-inovadores-para-a-coleta-de-dados-de-populacoes-de-dificil-acesso.pdf
dc.language.isoen
dc.publisherInter-American Development Bank
dc.subjectEvaluation
dc.subjectData Management
dc.subjectTrust
dc.subjectStrategy
dc.subjectPublic Policy
dc.subjectDiversity and Inclusion
dc.subjectSocial Network
dc.subjectLabor Force
dc.subjectHealth
dc.subjectHIV
dc.subjectMigrant
dc.subjectCommunicable Diseases
dc.subject.jelcodeC80 - Data Collection and Data Estimation Methodology • Computer Programs: General
dc.subject.jelcodeC81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data • Data Access
dc.subject.jelcodeC82 - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data • Data Access
dc.subject.jelcodeC83 - Survey Methods • Sampling Methods
dc.subject.jelcodeJ18 - Public Policy
dc.typeTechnical Notes
idb.identifier.pubnumberIDB-TN-03376
idb.operationRG-T4469
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