Estimating the Prevalence of Illicit Drug Use Among Students Using the Crosswise Model

Shamsipour, Mansour; Yunesian, Masud; Fotouhi, Akbar; Jann, Ben; Rahimi-Movaghar, Afarin; Asghari, Fariba; Akhlaghi, Ali Asghar

doi:10.3109/10826084.2014.897730

Cited by 26 publications

(40 citation statements)

References 18 publications

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“…In addition, CM also helped to reduce item nonresponse. This finding complements the results of Shamsipour et al (2014) who showed that applying CM in a survey on drug use decreased item nonresponse compared to asking directly. Furthermore, although being relatively complex, most of the respondents understood the mechanics of CM and, even more importantly, that it protected their privacy.…”

Section: Discussionsupporting

confidence: 59%

“…Despite its potential to elicit more truthful answers, there are only few studies that have empirically applied CM so far. The thematic foci of these studies varied, covering tax evasion at the firm level (Kundt et al, 2013), plagiarism and cheating among students (Jann et al, 2012, Höglinger et al 2014, and illicit drug use of students (Shamsipour et al, 2014), all of which representing presumably sensitive topics for the respondents. To assess the effectiveness of CM in providing privacy protection, the studies compared it to more conventional questioning methods such as asking respondents directly (direct questioning, DQ) which deliver no additional individual privacy protection.…”

Section: Introductionmentioning

confidence: 99%

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Applying 'Benford's Law' to the Crosswise Model: Findings from an Online Survey on Tax Evasion

Kundt

2014

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Applying "Benford's law" to the Crosswise Model: Findings from an online survey on tax evasion Terms of use: Documents in THORBEN KUNDT Zusammenfassung/ AbstractMany surveys on sensitive topics such as tax evasion suffer from the reluctance of respondents to provide truthful answers which can cause downward-biased estimates. This paper addresses this problem by making use of a recent survey method (Crosswise Model) designed to provide positive incentives for respondents to answer sensitive questions more truthful. We extend the Crosswise Model by applying the so-called "Benford Illusion" which allows us to increase the precision of the Crosswise Model that is less statistically efficient than other methods. To test the effectiveness of the model in providing privacy protection, we carried out an online survey in which the respondents were randomly allocated into two splits differing only by the questioning technique applied. Our results suggest that the Crosswise Model can help to increase privacy protection compared to a simple direct questioning approach. As a consequence, survey estimates of tax evasion using the Crosswise Model are likely to become more valid. At the same time, we show that were able to obtain an efficient estimator without substantially decreasing privacy protection, even for a relatively small sample size.

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Section: Discussionsupporting

confidence: 59%

Section: Introductionmentioning

confidence: 99%

Applying 'Benford's Law' to the Crosswise Model: Findings from an Online Survey on Tax Evasion

Kundt

2014

SSRN Journal

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“…In an investigation of illicit drug use among students, crosswise estimated a higher prevalence than direct questioning. Lack of biological confirmation of self-reported behavior was mentioned as a limitation of that study (10). Another study on high-risk behaviors among students showed higher estimates by crosswise in comparison with the network scaleup (NSU) method.…”

Section: Discussionmentioning

confidence: 85%

“…Crosswise was determined as the more valid method based on the more is better assumption, since it was less likely to be affected by the self-protective no and social desirability biases (1,10,19). However, the higher estimated prevalence may be the artificial features' results of this method and not an outcome of its higher validation.…”

Section: Discussionmentioning

confidence: 99%

“…One limitation attributed to the current study was that crosswise requires high-level of understanding skills. In Iran, this technique is so far conducted more as an experience among educated groups such as students and athletes (10)(11)(12). This method is not used in Iranian general population where people have different levels of literacy and understanding skills and are stigmatized for being infected with STIs.…”

Section: Introductionmentioning

confidence: 99%

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Does Crosswise Method Cause Overestimation? An Example to Estimate the Frequency of Symptoms Associated With Sexually Transmitted Infections in General Population: A Cross Sectional Study

et al. 2018

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Background: Crosswise, as an indirect questioning method, is not applied to the general population. The current study aimed at assessing the feasibility of crosswise among Iranian general population to estimate the frequency of sexually transmitted infection (STI) symptoms. Methods: To estimate the frequency of STI-associated symptoms among the general population of Kerman, Iran, in 2014, participants were inquired to specify whether their "yes or no" answers to a set of paired questions (sensitive/non-sensitive) were the same (concordance) or different (discordance). Based on the frequency of concordance response and known prevalence of positive response to non-sensitive questions, the frequency of positive responses to the sensitive questions was estimated. The estimations were compared with the results of a population-based survey, conducted at the same time and setting, in which participants directly responded to the sensitive questions. Results: The current study recruited 128 people aged 18 -60 years (50% male). The estimated frequency for genital ulcer in crosswise method was 53.1% and 34.9% in males and females, respectively. The estimated frequency of urethral discharge in crosswise method was 72.3%. The crosswise method outcomes were significantly different from those of the survey (P > 0.05). Conclusions:The estimated frequency of STI-associated symptoms in crosswise was unexpectedly higher than that of obtained by the population-based survey. Hence, experts in the field of STIs did not accept the crosswise estimations. This overestimation could be a result of differences in the ability of people, with various socioeconomic levels, to understand conceptually how to answer the questions along with the influence of study setting and administration method of questionnaires on the participants self-reports.

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Multiple sensitive estimation and optimal sample size allocation in the item sum technique

2017

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For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved.

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Estimating the Prevalence of Illicit Drug Use Among Students Using the Crosswise Model

Abstract: Our findings suggest that the CM is a fruitful data collection method for sensitive topics such as substance abuse.

Cited by 26 publications

References 18 publications

Applying 'Benford's Law' to the Crosswise Model: Findings from an Online Survey on Tax Evasion

Applying 'Benford's Law' to the Crosswise Model: Findings from an Online Survey on Tax Evasion

Does Crosswise Method Cause Overestimation? An Example to Estimate the Frequency of Symptoms Associated With Sexually Transmitted Infections in General Population: A Cross Sectional Study

Multiple sensitive estimation and optimal sample size allocation in the item sum technique

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