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

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          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.

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          Most cited references84

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          Fitting Linear Mixed-Effects Models Usinglme4

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            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

              David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                23 June 2021
                2021
                : 12
                : 655592
                Affiliations
                [1] 1Department of Psychosocial Science, University of Bergen , Bergen, Norway
                [2] 2Faculty of Social Sciences, Utrecht University , Utrecht, Netherlands
                [3] 3School of Life Sciences, Pharmacy and Chemistry, Kingston University , London, United Kingdom
                [4] 4Doping Authority Netherlands , Capelle aan den IJssel, Netherlands
                [5] 5Institute of Sport Sciences, University of Lausanne , Lausanne, Switzerland
                [6] 6Statistical Science Southampton Research Institute, University of Southampton , Southampton, United Kingdom
                [7] 7Department of Movement Sciences, KU Leuven , Leuven, Belgium
                Author notes

                Edited by: Sara Giovagnoli, University of Bologna, Italy

                Reviewed by: Adrian Hoffmann, Heinrich Heine University of Düsseldorf, Germany; Renato Sobral Monteiro-Junior, Unimontes, Brazil

                *Correspondence: Dominic Sagoe dominic.sagoe@ 123456uib.no

                This article was submitted to Quantitative Psychology and Measurement, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2021.655592
                8260852
                1f51b03f-331d-41e3-9711-f920fd31c25f
                Copyright © 2021 Sagoe, Cruyff, Spendiff, Chegeni, de Hon, Saugy, van der Heijden and Petróczi.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 19 January 2021
                : 18 May 2021
                Page count
                Figures: 6, Tables: 7, Equations: 1, References: 84, Pages: 19, Words: 14249
                Categories
                Psychology
                Systematic Review

                Clinical Psychology & Psychiatry
                randomized response,crosswise model,direct question,prevalence,quality assessment,efficiency,survey

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