Skip to main content Accessibility help
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 6
  • Print publication year: 2014
  • Online publication date: September 2014

30 - Finding the hard to reach and keeping them engaged in research



Many types of survey respondents are difficult to access, to locate, and (in longitudinal research) to stay in contact with throughout the course of a study. These types of respondents fall into two main categories. The first category includes people who are difficult to reach by nature, such as young adults whose lives are in transition, the mentally ill, the homeless, and drug users. These population groups are extremely mobile and, in some cases, less likely to maintain close ties with relatives who might serve as a means of locating or contacting them. The second category includes people who are consciously avoiding being located in an attempt to avoid contact with the justice system, immigration authorities, debt collectors, stalkers, or others. People falling into either of these two categories may lack fixed addresses, or be “cell phone only,” with episodic cell service and numbers that change frequently, or list residences or phones in the name of another person.

The hardest subjects to reach in a target population group might provide fundamentally different responses than members of the group who are relatively easier to find and survey (Groves, Fowler, Couper, Lepkowski, Singer, & Tourangeau, 2004). Not including certain segments of a population leads to nonresponse bias, which threatens the quality of survey statistics and the validity and generalizability of research findings (Cottler, Compton, Ben-Abdallah, Horne, & Claverie, 1996). The goal of maximizing power and minimizing potential nonresponse becomes even more difficult when the study population by definition is hard to reach. Researchers face a trifecta of challenges to data reliability when such studies are longitudinal: maximizing power, minimizing systematic nonresponse, and maintaining the respondent pool over time. Tracking efforts can minimize these threats by maximizing participation among sample members (Brown & Nederend, 1997), minimizing nonresponse among respondents with certain characteristics or reflecting sample subpopulations (Teitler, Reichman, & Sprachman, 2003), and reducing subject attrition in research requiring multiple waves of data collection (Cottler et al., 1996).

Related content

Powered by UNSILO
Andresen, E., Machuga, R., Van Booven, M., Egel, J., Chibnall, J., & Talt, R. (2008). Effects and costs of tracing strategies on nonresponse bias in a survey of workers with low-back injury. Public Opinion Quarterly, 72(1), 40–54.
Brown, J., & Nederend, S. (1997). Locating and Surveying Medicaid and AFDC Beneficiaries: CAHPS Field Test Experience to Date. DRU-1664-AHCPR. Prepared for Agency for Health Care Policy Research. Santa Monica, CA: RAND Corporation.
Burgess, R. D. (1989). Major issues and implications of tracing survey respondents. In Kasprzyk, D., Duncan, G., Kalton, G., and Singh, M. P. (eds.), Panel Surveys (pp. 52–74). New York: John Wiley & Sons.
Calderwood, L. (2012). Tracking sample members in longitudinal studies. Survey Practice, 5(4). [e-journal: .]
Cepeda, A., & Valdez, A. (2010). Ethnographic strategies in the tracking and retention of street-recruited community-based samples of substance using hidden populations in longitudinal studies. Substance Use and Misuse, 45(5), 700–16.
Coen, A., Patrick, D., & Shern, D. (1996). Minimizing attrition in longitudinal studies of special populations: an integrated management approach. Evaluation and Program Planning, 19(4), 309–19.
Cohen, E., Mowbray, C., Bybee, D., Yeich, S., Ribisl, K., & Freddolino, P. (1993). Tracking and follow-up methods for research on homelessness. Evaluation Review, 17(3), 331–52.
Conover, S., Berkman, A., Gheith, A., Jahiel, R., Stanley, D., Geller, P., et al. (1997). Methods for successful follow-up of elusive urban populations: an ethnographic approach with homeless men. Bulletin of the New York Academy of Medicine, 74(1), 90–108.
Corsi, K., Van Hunnik, B., Kwiatkowski, C., & Booth, R. (2006). Computerized tracking and follow-up techniques in longitudinal research with drug users. Health Services and Outcomes Research Methodology, 6(3–4), 101–10.
Cottler, L., Compton, W., Ben-Abdallah, A., Horne, M., & Claverie, D. (1996). Achieving a 96.6 percent follow-up rate in a longitudinal study of drug abusers. Drug and Alcohol Dependence, 41(3), 209–17.
Couper, M., & Ofstedal, M. (2009). Keeping in contact with mobile sample members. In Lynn, P. (ed.), Methodology of Longitudinal Surveys. Chichester: John Wiley & Sons.
Durrant, G., Groves, R., Staetsky, L., & Steele, F. (2010). Effects of interviewer attitudes and behaviors on refusal in household surveys. Public Opinion Quarterly, 74(1), 1–36.
Edelen, M., Slaughter, M., McCaffrey, D., Becker, K., & Morral, A. (2010). Long term effect of community based treatment: evidence from the Adolescent Outcomes Project. Drug and Alcohol Dependence, 107(1), 62–68.
Freedman, D., Thornton, A., & Camburn, D. (1980). Maintaining response rates in longitudinal studies. Psychological Methods & Research, 9(1), 87–98.
Fumagalli, L., Laurie, H., & Lynn, P. (2013). Experiments with methods to reduce attrition in longitudinal surveys. Journal of the Royal Statistical Society, 176(2), 499–519.
Gelberg, L., Robertson, M., Arangua, L., Leake, B., Sumner, G., Moe, A., et al. (2012). Prevalence, distribution, and correlates of Hepatitis C virus infection among homeless adults in Los Angeles. Public Heath Reports, 127(4), 407–21.
Grandone, M., & Moritz, K. (2010). Strategies for client tracking and follow-up, Global Appraisal of Individual Needs Training Manual, Normal, IL. Retrieved from .
Gregory, M., Lohr, M. J., & Gilchrist, L. (1992). Methods for tracking pregnant and parenting adolescents. Evaluation Review, 17(1), 69–81.
Groves, R., Fowler, F. J., Couper, M., Lepkowski, J., Singer, E., & Tourangeau, R. (2004). Survey Methodology. Hoboken, NJ: John Wiley & Sons.
Gwadz, M., & Rotheram-Borus, M. J. (1992). Tracking high-risk adolescents longitudinally. AIDS Education and Prevention, Fall Supplement, 69–82.
Hill, Z. (2004). Reducing attrition in panel studies in developing countries. International Journal of Epidemiology, 33(3), 493–98.
Hough, R., Tarke, H., Renker, V., Shields, P., & Glatstein, J. (1996). Recruitment and retention of homeless mentally ill participants in research. Journal of Consulting and Clinical Psychology, 64(5), 881–91.
Hunt, J., & White, E. (1998). Retaining and tracking cohort study members. Epidemiologic Reviews, 20(1), 57–70.
Leonard, N., Lester, P., Rotheram-Borus, M., Mattes, K., Gwadz, M., & Ferns, B. (2003). Successful recruitment and retention of participants in longitudinal behavioral research. AIDS Education and Prevention, 15(3), 269–81.
McCuller, W., Sussman, S., Holiday, K., Craig, S., & Dent, C. (2002). Tracking procedures for locating high-risk youth. Evaluation & the Health Professions, 25(3), 345–62.
McKenzie, M., Tulsky, J. P., Long, H., Chesney, M., & Moss, A. (1999). Tracking and follow-up of marginalized populations: a review. Journal of Health Care for the Poor and Underserved, 10(4), 409–29.
Marmor, J., Oliveria, S., Donahue, R., Garrahie, E., White, M. J., Moore, L., et al. (1991). Factors encouraging cohort maintenance in a longitudinal study. Journal of Clinical Epidemiology, 44(6), 531–35.
Menendez, E., White, M. C., & Tulsky, J. P. (2001). Locating study subjects: predictors and successful search strategies with inmates released from a U.S. county jail. Controlled Clinical Trials, 22(3), 238–47.
Nwadiuko, J., Isbell, P., Zolotor, A., Hussey, J., & Kotch, J. (2011). Using social networking sites in subject tracing. Field Methods, 23(1), 77–85.
Rhodes, B., & Marks, E. (2011). Using facebook to locate sample members, Survey Practice (2011, October 24). Retrieved April 16, 2012 from .
Ribisl, K., Walton, M., Mowbray, C., Luke, D., DavidsonII, W., & Bootsmiller, B. (1996). Minimizing participant attrition in panel studies through the use of effective retention and tracking strategies: review and recommendations. Evaluation and Program Planning, 19(1), 1–25.
Rumptz, M., Sullivan, C., Davidson, W., & Basta, J. (1991). An ecological approach to tracking battered women over time. Violence and Victims, 6(3), 237–44.
Scott, C. (2004). A replicable model for achieving over 90% follow-up rates in longitudinal studies of substance abusers. Drug and Alcohol Dependence, 74, 21–36.
Singer, E., Groves, R. M., & Corning, A. (1999). Differential incentives: beliefs about practices, perceptions of equity, and effects on survey participation. Public Opinion Quarterly, 63(2), 251–60.
Singer, E., & Kulka, R. A. (2002). Paying respondents for survey participation. In Vander Ploeg, M., Moffitt, R. A., & Citro, C. F. (eds.), Studies of Welfare Populations: Data Collection and Research Issues (pp.105–28). Washington, DC: National Academy Press.
Teitler, J., Reichman, N., & Sprachman, S. (2003). Costs and benefits of improving response rates for a hard-to-reach population. Public Opinion Quarterly, 67(1), 126–38.
Ullman, S. (2011). Longitudinal tracking methods in a study of adult women sexual assault survivors. Violence against Women, 17(2), 189–200.
Willimack, D., Schuman, H., Pennell, B.-E., & Lepkowski, J. (1995). Effects of a prepaid nonmonetary incentive on response rates and response quality in a face-to-face study. Public Opinion Quarterly, 59(1), 78–92.
Wright, J., Lampton Allen, T., & Devine, J. (1995). Tracking non-traditional populations in longitudinal studies. Evaluation and Program Planning, 18(3), 267–77.
Young, S., & Rice, E. (2011). Online social networking technologies, HIV knowledge, and sexual risk and testing behaviors among homeless youth. AIDS Behavior, 15(2), 253–60.