Functionality of the Crosswise Model for Assessing Sensitive or Transgressive Behavior: A Systematic Review and Meta-Analysis

Abstract

Tools for reliable assessment of socially sensitive or transgressive behavior warrant constant development. Among them, the Crosswise Model (CM) has gained considerable attention. We systematically reviewed and meta-analyzed empirical applications of CM and addressed a gap for quality assessment of indirect estimation models. Guided by the PRISMA protocol, we identified 45 empirical studies from electronic database and reference searches. Thirty of these were comparative validation studies (CVS) comparing CM and direct question (DQ) estimates. Six prevalence studies exclusively used CM. One was a qualitative study. Behavior investigated were substance use and misuse (k = 13), academic misconduct (k = 8), and corruption, tax evasion, and theft (k = 7) among others. Majority of studies (k = 39) applied the “more is better” hypothesis. Thirty-five studies relied on birthday distribution and 22 of these used P = 0.25 for the non-sensitive item. Overall, 11 studies were assessed as high-, 31 as moderate-, and two as low quality (excluding the qualitative study). The effect of non-compliance was assessed in eight studies. From mixed CVS results, the meta-analysis indicates that CM outperforms DQ on the “more is better” validation criterion, and increasingly so with higher behavior sensitivity. However, little difference was observed between DQ and CM estimates for items with DQ prevalence estimate around 50%. Based on empirical evidence available to date, our study provides support for the superiority of CM to DQ in assessing sensitive/transgressive behavior. Despite some limitations, CM is a valuable and promising tool for population level investigation.

Experimental validation of specialized questioning techniques in conservation

“…We gathered basic demographic data (respondent age, gender, and years of education) alongside birth month. Birth month is often used as an alternative statement in crosswise model designs (Sagoe et al., 2021 ) or as a randomizer for RRT (Ibbett et al., 2021 ). Yet, in many contexts, people do not know their Gregorian birth date; therefore, it was important to determine how prevalent knowledge of birth month was so that we could assess its feasibility as an alternative statement.…”

“…The crosswise model presents participants with one innocuous question with known prevalence and one question that is sensitive. Respondents report whether their answer is the same for both questions or yes to only one question (Sagoe et al., 2021 ; Yu et al., 2008 ). Developed for lower‐education contexts and with reduced complexity compared with other SQTs (Lau et al., 2011 ), the bean method asks respondents to secretly move specific‐colored beans from one jar to another, depending on their answer (Jones et al., 2020 ) (examples of applications of all methods in conservation are given in Appendix S1 ).…”

Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models

“…This also enables the interviewee to mask his or her answer to the sensitive question. Therefore, it has received considerable attention in the scientific community (e.g., Sagoe et al, 2021 ; Schnell & Thomas, 2021 ). It is clear that the crosswise model is mathematically equivalent as Warner’s model.…”

Hidden figures: Revisiting doping prevalence estimates previously reported for two major international sport events in the context of further empirical evidence and the extant literature

“…The “higher must be better” assumption ( 55 ), which is widely observed and criticised outside the doping context ( 56 ), appears to be present in doping prevalence studies. However, in most cases, the empirically obtained prevalence estimates have been compared to the “official” WADA laboratory reports of Adverse and Atypical Analytical Findings.…”