Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Publisher: Elsevier
Languages: English
Types: Article
Subjects: QH75
Tools for social research are critical for developing an understanding of conservation problems and assessing the feasibility of conservation actions. Social surveys are an essential tool frequently applied in conservation to assess both people’s behaviour and to understand its drivers. However, little attention has been given to the weaknesses and strengths of different survey tools. When topics of conservation concern are illegal or otherwise sensitive, data collected using direct questions are likely to be affected by non-response and social desirability biases, reducing their validity. These sources of bias associated with using direct questions on sensitive topics have long been recognised in the social sciences but have been poorly considered in conservation and natural resource management.\ud \ud We reviewed specialized questioning techniques developed in a number of disciplines specifically for investigating sensitive topics. These methods ensure respondent anonymity, increase willingness to answer, and critically, make it impossible to directly link incriminating data to an individual. We describe each method and report their main characteristics, such as data requirements, possible data outputs, availability of evidence that they can be adapted for use in illiterate communities, and summarize their main advantages and disadvantages. Recommendations for their application in conservation are given. We suggest that the conservation toolbox should be expanded by incorporating specialized questioning techniques, developed specifically to increase response accuracy. By considering the limitations of each survey technique, we will ultimately contribute to more effective evaluations of conservation interventions and more robust policy decisions.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Bunnefeld, N., Hoshino, E., Milner-Gulland, E.J., 2011. Management strategy evaluation: a powerful tool for conservation? Trends Ecol. Evol. 26, 441-447.
    • Catania, J. A., Binson, D., Canchola, J., Pollack, L. M., Hauck, W., Coates, T. J., 1996. Effects of interviewer gender, interviewer choice, and item wording on responses to questions concerning sexual behavior. Public Opin Q. 60, 345-375.
    • Chaudhuri, A., Christofides, T., 2013. Indirect questioning in sample surveys. Springer.
    • Corstange, D., 2009. Sensitive questions, truthful Answers? Modeling the list experiment with LISTIT. Polit. Anal. 17, 45-63.
    • Eichhorn, B.H., Hayre, L.S., 1983. Scrambled randomized response methods for obtaining sensitive quantitative data. J. Stat. Plan. Inference 7, 307-316.
    • Esponda, F., Guerrero, V.M., 2009. Surveys with negative questions for sensitive items. Stat. Probab. Lett.
    • Fisher, R., 1993. Social desirability bias and the validity of indirect questioning 20, 303-315.
    • GAO, 1999. Survey methodology: an innovative technique for estimating sensitive survey items. Washington, DC.
    • GAO, 2006. Estimating the undocumented population: a “grouped answers” approach to surveying foreign-born respondents. DIANE Publishing.
    • GAO, 2007. Estimating irregular migration in a survey: the “two-card follow-up” method. U.N. Sixth coordination meeting on international migration. New York.
    • Gavin, M.C., Solomon, J.N., Blank, S.G., 2010. Measuring and monitoring illegal use of natural resources. Conserv. Biol. 24, 89-100.
    • Glynn, A.N., 2013. What can we learn with statistical truth serum?: design and analysis of the list experiment. Public Opin. Q. 77, 159-172.
    • Groenitz, H., 2014. A new privacy-protecting survey design for multichotomous sensitive variables. Metrika 77, 211-224.
    • Groves, R.M., 2006. Nonresponse rates and nonresponse bias in household surveys. Public Opin. Q. 70, 646-675.
    • Holbrook, A.L., Krosnick, J.A., 2010. Social desirability bias in voter turnout reports: tests using the item count technique. Public Opin. Q. 74, 37-67.
    • Jann, B., Jerke, J., Krumpal, I., 2012. Asking sensitive questions using the crosswise model: an experimental survey measuring plagiarism. Public Opin. Q. 76, 32-49.
    • Javeline, D., 1999. Response effects in polite cultures - a test of acquiescente in Kazakhstan. Public Opin. Q. 63, 1-28.
    • Jepson, P., Jarvie, J.K., MacKinnon, K., Monk, K.A., 2001. The end for Indonesia's lowland forests? Science 292, 859-861.
    • Jones, J.P.G., Andriamarovololona, M.M., Hockley, N., 2008. The importance of taboos and social norms to conservation in Madagascar. Conserv. Biol. 22, 976-86.
    • Keane, A., Jones, J.P.G., Edwards-Jones, G., Milner-Gulland, E.J., 2008. The sleeping policeman: understanding issues of enforcement and compliance in conservation. Anim. Conserv. 11, 75- 82.
    • Knapp, E.J., Rentsch, D., Schmitt, J., Lewis, C., Polasky, S., 2010. A tale of three villages: choosing an effective method for assessing poaching levels in western Serengeti, Tanzania. Oryx 44, 178- 184.
    • Lande, R., 1998. Anthropogenic, ecological and genetic factors in extinction and conservation. Res. Popul. Ecol. (Kyoto). 40, 259-269.
    • Landsheer, J.A., Heijden, P. Van Der, Gils, G. Van., 1999. Trust and understanding, two psychological aspects of randomized response. Quality & Quantity 33, 1-12.
    • Langhaug, L.F., Cheung, Y.B., Pascoe, S.J.S., Chirawu, P., Woelk, G., Hayes, R.J., Cowan, F.M., 2011. How you ask really matters: randomised comparison of four sexual behaviour questionnaire delivery modes in Zimbabwean youth. Sex. Transm. Infect. 87, 165-73.
    • Langhaug, L.F., Sherr, L., Cowan, F.M., 2010. How to improve the validity of sexual behaviour reporting: systematic review of questionnaire delivery modes in developing countries. Trop. Med. Int. Health 15, 362-81.
    • Makkai, T., Mcallister, I., 1992. Measuring social indicators in opinion surveys: a method to improve accuracy on sensitive questions. Soc. Indic. Res. 27, 169-186.
    • Martín-López, B., Montes, C., Ramírez, L., Benayas, J., 2009. What drives policy decision-making related to species conservation? Biol. Conserv. 142, 1370-1380.
    • Miller, J.D., 1985. The nominative technique: a new method of estimating heroin prevalence., in: Rouse, B.A., Kozel, N.J., Richards, L.G. (Eds.), Self-Report Methods of Estimating Drug Use: Meeting Current Challenges to Validity. NIDA - National Institute on Drug Abuse, pp. 104-24.
    • Milner-Gulland, E.J., Bukreeva, O.M., Coulson, T., Lushchekina, A.A., Kholodova, M. V, Bekenov, A.B., Grachev, I.A., 2003. Reproductive collapse in saiga antelope harems. Nature 422, 135.
    • Moro, M., Fischer, A., Czajkowski, M., Brennan, D., Lowassa, A., Naiman, L.C., Hanley, N., 2013. An investigation using the choice experiment method into options for reducing illegal bushmeat hunting in western Serengeti. Conserv. Lett. 6, 37-45.
    • Näher, A.-F., Krumpal, I., 2011. Asking sensitive questions: the impact of forgiving wording and question context on social desirability bias. Quality & Quantity 46, 1601-1616.
    • Newing, H., 2011. Conducting research in conservation: social science methods and practice. Routledge.
    • Nielsen, M.R., Jacobsen, J.B., Thorsen, B.J., 2013. Factors determining the choice of hunting and trading bushmeat in the Kilombero Valley, Tanzania. Conserv. Biol.
    • Nuno, A., 2013. Managing social-ecological systems under uncertainty: implications for conservation. Imperial College London. PhD thesis.
    • Nuno, A., Bunnefeld, N., Milner-Gulland, E.J., 2013a. Matching observations and reality: using simulation models to improve monitoring under uncertainty in the Serengeti. J. Appl. Ecol. 50, 488-498.
    • Razafimanahaka, J.H., Jenkins, R.K.B., Andriafidison, D., Randrianandrianina, F., Rakotomboavonjy, V., Keane, A., Jones, J.P.G., 2012. Novel approach for quantifying illegal bushmeat consumption reveals high consumption of protected species in Madagascar. Oryx 46, 584-592.
    • Roberts, J.M., Brewer, D.D., 2006. Estimating the prevalence of male clients of prostitute women in Vancouver with a simple capture-recapture method. J. R. Stat. Soc. Ser. A (Statistics Soc. 169, 745-756.
    • Sandbrook, C., Adams, W.M., Büscher, B., Vira, B., 2013. Social research and biodiversity conservation. Conserv. Biol. 27, 1487-90.
    • Sheppard, S.C., Earleywine, M., 2013. Using the unmatched count technique to improve base rate estimates of risky driving behaviours among veterans of the wars in Iraq and Afghanistan. Inj. Prev. 19, 382-386.
    • Silva, R. de S. e, Vieira, E.M., 2009. Frequency and characteristics of induced abortion among married and single women in São Paulo, Brazil. Cad. Saude Publica 25, 179-187.
    • Simon, P., Striegel, H., Aust, F., Dietz, K., Ulrich, R., 2006. Doping in fitness sports: estimated number of unreported cases and individual probability of doping. Addiction 101, 1640-4.
    • Sirén, A. H., J. C. Cardenas, J.C., Machoa, J.D., 2006. The relation between income and hunting in tropical forests: an economic experiment in the field. Ecology and Society 11, 44.
    • Sirken, M.G., 1972. Stratified sample surveys with Multiplicity. J. Am. Stat. Assoc. 67, 224-227.
    • Solomon, J.N., Jacobson, S., Wald, K.D., Gavin, M.C., 2007. Estimating illegal resource use at a Ugandan park with the randomized response technique. Hum. Dimens. Wildl. 12, 75-88.
    • Tian, G.-L., Yu, J.-W., Tang, M.-L., Geng, Z., 2007. A new non-randomized model for analysing sensitive questions with binary outcomes. Stat. Med. 26, 4238-4252.
    • Tourangeau, R., Yan, T., 2007. Sensitive questions in surveys. Psychol. Bull. 133, 859-883.
    • Trappmann, M., Krumpal, I., Kirchner, A., Jann, B., 2014. Item sum: a new techniques for asking quantitative sensitive questions. J. Surv. Stat. Methodol. 2, 58-77.
    • Treves, A., 2009. Hunting for large carnivore conservation. J. Appl. Ecol. 46, 1350-1356.
    • Treves, A., Karanth, K.U., 2003. Human-carnivore conflict and perspectives on carnivore management worldwide. Conserv. Biol. 17, 1491-1499.
    • Tsuchiya, T., Hirai, Y., Ono, S., 2007. A study of the properties of the item count technique. Public Opin. Q. 71, 253-272.
    • Underwood, F.M., Burn, R.W., Milliken, T., 2013. Dissecting the illegal ivory trade: an analysis of ivory seizures data. PLoS One 8, e76539.
    • Vakilian, K., Mousavi, S.A., Keramat, A., 2014. Estimation of sexual behavior in the 18-to-24-yearsold Iranian youth based on a crosswise model study. BMC Res. Notes 7, 28.
    • Van den Hout, A., van der Heijden, P.G.M., Gilchrist, R., 2007. The logistic regression model with response variables subject to randomized response. Comput. Stat. Data Anal. 51, 6060-6069.
    • Vitos, M., Lewis, J., Stevens, M., Haklay, M., 2013. Making local knowledge matter, in: Proceedings of the 3rd ACM Symposium on Computing for Development - ACM DEV '13. ACM Press, New York, USA.
    • Warner, S.L., 1965. Randomized response: a survey technique for eliminating evasive answer bias. J. Am. Stat. Assoc. 60, 63-69.
  • Inferred research data

    The results below are discovered through our pilot algorithms. Let us know how we are doing!

    Title Trust
  • No similar publications.

Share - Bookmark

Funded by projects

  • FCT | SFRH/BD/43186/2008

Cite this article