Evaluating sampling biases from third-party reporting as a method for improving survey measures of sensitive behaviors

Survey participants often misreport their sensitive behaviors (e.g., smoking, drinking, having sex) during interviews. Several studies have suggested that asking respondents to report the sensitive behaviors of their friends or confidants, rather than their own, might help address this problem. This is so because the "third-party reporting" (TPR) approach creates a surrogate sample of alters that may be less subject to social desirability biases. However, estimates of the prevalence of sensitive behaviors based on TPR assume that the surrogate sample of friends is representative of the population of interest. We used sociometric data on social networks in Likoma, Malawi to examine this assumption. Specifically, we use friendship network data to investigate whether friends have similar socio-economic characteristics as index respondents, and to measure possible correlations between the likelihood of inclusion in the surrogate sample and sensitive behaviors. From these results, we suggest approaches to strengthen estimates of the prevalence of sensitive behaviors obtained from TPR.

[1]  Megan Price,et al.  Trade-offs in using indirect sampling to measure conflict violence. , 2011, JAMA.

[2]  R. Fisher Social Desirability Bias and the Validity of Indirect Questioning , 1993 .

[3]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[4]  S. Preston,et al.  Demography: Measuring and Modeling Population Processes , 2000 .

[5]  Benjamin Armbruster,et al.  The reliability of sexual partnership histories: implications for the measurement of partnership concurrency during surveys , 2011, AIDS.

[6]  E. Gakidou,et al.  Death by survey: Estimating adult mortality without selection bias from sibling survival data , 2006, Demography.

[7]  L. Smith-Lovin,et al.  Homophily in voluntary organizations: Status distance and the composition of face-to-face groups. , 1987 .

[8]  Yoonjoung Choi,et al.  Unconventional approaches to mortality estimation , 2005 .

[9]  J. T. Boerma,et al.  Monitoring sexual behaviour in general populations: a synthesis of lessons of the past decade , 2004, Sexually Transmitted Infections.

[10]  Tian Zheng,et al.  How Many People Do You Know in Prison? , 2006 .

[11]  S. Gregson,et al.  Informal confidential voting interview methods and temporal changes in reported sexual risk behaviour for HIV transmission in sub-Saharan Africa , 2004, Sexually Transmitted Infections.

[12]  A. Ouedraogo,et al.  Estimating clandestine abortion with the confidants method--results from Ouagadougou, Burkina Faso. , 2006, Social Science & Medicine (1967).

[13]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994 .

[14]  T. Chikritzhs,et al.  Under-reporting of alcohol consumption in household surveys: a comparison of quantity-frequency, graduated-frequency and recent recall. , 2004, Addiction.

[15]  Matthew J. Salganik,et al.  Counting hard-to-count populations: the network scale-up method for public health , 2010, Sexually Transmitted Infections.

[16]  S. Helleringer,et al.  Cohort Profile: The Likoma Network Study (LNS). , 2014, International journal of epidemiology.

[17]  S. Helleringer,et al.  The Likoma Network Study: Context, data collection, and initial results. , 2009, Demographic research.

[18]  Matthew E. Brashears,et al.  Social Isolation in America: Changes in Core Discussion Networks over Two Decades , 2006 .

[19]  G. Garnett,et al.  A systematic review and meta-analysis of quantitative interviewing tools to investigate self-reported HIV and STI associated behaviours in low- and middle-income countries. , 2010, International journal of epidemiology.

[20]  Martina Morris,et al.  Network Epidemiology: A Handbook for Survey Design and Data Collection , 2004 .

[21]  S. Helleringer,et al.  Sexual network structure and the spread of HIV in Africa: evidence from Likoma Island, Malawi , 2007, AIDS.

[22]  H. Russell Bernard,et al.  Who knows your HIV status? What HIV + patients and their network members know about each other , 1995 .

[23]  jimi adams,et al.  To tell the truth: Measuring concordance in multiply reported network data , 2007, Soc. Networks.

[24]  Matthew J. Salganik,et al.  How Many People Do You Know?: Efficiently Estimating Personal Network Size , 2010, Journal of the American Statistical Association.

[25]  Matthew J. Salganik,et al.  The game of contacts: Estimating the social visibility of groups , 2011, Soc. Networks.

[26]  S. Yeatman,et al.  Best-friend reports: a tool for measuring the prevalence of sensitive behaviors. , 2011, American Journal of Public Health.

[27]  Jane Allen,et al.  Do tobacco countermarketing campaigns increase adolescent under-reporting of smoking? , 2007, Addictive behaviors.

[28]  Paul C. Hewett,et al.  The reporting of sensitive behavior by adolescents: A methodological experiment in Kenya , 2003, Demography.

[29]  S. Feld Why Your Friends Have More Friends Than You Do , 1991, American Journal of Sociology.