Predictive validity of integrity tests for workplace deviance across industries and countries in the past 50 years: A meta-analytic review

Abstract

The current meta-analysis provides a comprehensive and updated review on integrity-testing findings across industries and countries in the past 50 years (k = 150, N = 67,016). Integrity tests were coded into the types of overt tests, covert tests, biodata, organizational measures, value/moral reasoning/situational judgment tests, integrity-related cognitive ability tests, and novel measures. The criterion measures of workplace deviance included CWBs, unethical pro-organizational behaviors, and other workplace deviant behaviors. For the information source, both computer and manual searches were performed to locate relevant published and unpublished papers. A variety of sources were examined to avoid publication bias, and publication bias analyses were conducted to uphold the methodological rigor. Results indicated that all the integrity tests analyzed were significant in predicting workplace deviance, with an overall mean validity estimate corrected for indirect range restriction and measurement error as .43 (95% CI [.32; .52]; p < .001). Among the tests, the value-oriented tests and cognitive ability tests indicated relatively large validity estimates of .60 (95% CI [.41; .75]; p < .001) and .65 (95% CI [.53; .74]; p < .001), respectively. The relationship between integrity tests and workplace deviance was found to be significantly moderated by the type of integrity test, industry, country, and criterion source. The effect size of integrity tests was largest in predicting deviance in the military and law enforcement sector, and relatively large in the work samples of Canada, Germany, Israel, Romania, and the United States. However, the moderating effects of the nature of deviance, validation sample, validation strategy, publication status, medium of test, and gender, were nonsignificant. Compared with previous reviews, our study was unique in its cross-cultural direction, which included primary studies of integrity testing in countries with different languages (e.g., publications in Chinese) and associated cultural variations. New insights and comparisons with previous meta-analytic findings were discussed.

Keywords

integrity testing psychological assessment preemployment selection cross-cultural counterproductive work behaviors unethical pro-organizational behaviors workplace ethics meta-analysis

Introduction

Are integrity problems and deviance in the workplace due to “bad apples” or “bad barrels”? According to the interactionist model, there is no simple answer to this question, nor should the question be a simple “either-or” (e.g., Ashkanasy et al., 2006; Markowitz & Levine, 2020). The “bad apple” argument attributes workplace deviant behaviors to dispositional and individual factors (Carless et al., 2007; DeShong et al., 2017; Paulhus & Williams, 2002), while the “bad barrel” argument explains the issues by situational and organizational characteristics (Crelinsten, 2003; Gioia, 1992; Hochstetler et al., 2002; Zimbardo, 2004). Different integrity tests based on varying assumptions and models have thus been developed according to different schools of thought (e.g., “the bad apples,” “the bad barrels” or their interplay such as “a bad apple spoils the barrel,” etc.) for predicting integrity problems and deviant behaviors of employees in an organization (Baloch et al., 2017; Barrett, 2001; Forsyth et al., 2012). Despite the different and varying tests, very limited comparative research investigating the differential validities of integrity measures applied across industries and countries exists. There is also a paucity of research that includes Asian findings or studies that consider possible cultural differences when the tests are put into practice. Given such, this meta-analysis will systematically and empirically review the validity and utility of different integrity tests that predicted deviant work behaviors across industries and countries. Insights will be drawn from the past 50 years of research to provide implications and contributions to empirical and practical developments in the domains of psychological assessment and workplace ethics.

Integrity testing and workplace deviance

Given the multiple types of integrity tests that were constructed according to different assumptions and theoretical beliefs stemming from the never-ending “bad apples–bad barrels” debate (May & Van Niekerk, 2019; Monga, 2016), the development of integrity testing for accurate measurements of integrity in the workplace has thus become complex and multidimensional (e.g., Palanski & Yammarino, 2009; Wanek, 1996) In fact, the multitude and variety of integrity tests available in the field reflects the importance and recognition of integrity testing for preemployment selection and talent development (Brown et al., 2019). Today, integrity testing is a widespread and substantial tool used in a broad spectrum of jobs and industries (e.g., Blumen et al., 2017; Byle & Holtgraves, 2008) for reducing the risk of hiring deviant employees that prone to counterproductive work behaviors (CWBs) (Byle & Holtgraves, 2008; Fine, 2012; Kuhn, 2020), unethical pro-organizational behaviors (UPBs) (Castille et al., 2018; Fehr et al., 2019), and certain integrity problems (Marcus et al., 2007; Ones et al., 1993; Schmidt et al., 2016). Nevertheless, the research effort spent on investigating the predictive validity of integrity tests specific to negative work performance has not kept pace with the prevalence in practice when compared with the mass publications on predicting overall job performance. Given such a knowledge gap, the focal criterion on workplace deviance instead of general job performance in this study aims to align with the recent shift in both research and practice (e.g., Kabiri et al., 2021; Mackey et al., 2021). Our study will thus focus on the differential predictive validity of multiple integrity tests on various workplace deviant behaviors.

Different typologies of deviant workplace behaviors and the focus on organizational workplace deviance as the criterion measure in this study

Workplace deviance is generally defined as “voluntary behaviour that violates significant organizational norms and in so doing threatens the well-being of an organization, its members, or both” (Robinson & Bennett, 1995, p. 556). Sometimes the term “workplace deviance” is used interchangeably with “counterproductive work behaviors.” Yet despite the big overlap between the two terms, they are not identical (Bennett & Robinson, 2000; Hollinger, 1986; Sackett et al., 2006). In particular, there is a subset of workplace deviance that is described as “unethical pro-organizational behaviors” and is not subsumed under CWBs, but represents intentional deviant behaviors that are believed to do good for the organization (Umphress et al., 2010). Employees engaging in UPBs might commit to a pro-organizational clause up front, but would still end up with adverse consequences that harm the organization, such as the loss of reputation and lawsuits (e.g., noble cause corruption; withholding negative information about a product or service of the company with an intention to safeguard the organizational reputation) (Bolino & Grant, 2016).

Workplace deviance would thus be better and more broadly defined with different typologies to classify deviant and counterproductive behaviors. One of these typologies is the four-class typology of work deviance, which includes production deviance, property deviance, political deviance, and personal aggression (Bennett & Robinson, 2000). There is also a five-dimension typology of workplace deviance, which includes CWBs on abuse against others, production deviance, sabotage, theft, and withdrawal (Spector et al., 2006). Dalal (2005) proposed an 11-dimension typology to further classify deviant work behaviors (Dalal, 2005). Additional dimensions proposed by other researchers include task-related or non-task-related dimensions and legal or illegal dimensions (Bowling & Gruys, 2010).

According to another two-dimensional model proposed by Bennett & Robinson (2000), workplace deviance can also be categorized into two types, including “organizational workplace deviance” (OWD) and “interpersonal workplace deviance” (IWD). OWD refers to misbehaviors that are destructive to the organization and violate organizational norms, such as absenteeism, presenteeism, time banditry, theft, knowledge sabotage, cyberloafing/cyberslacking, and damaging company property (Bennett & Robinson, 2000; Malachowski, 2005; Mercado et al., 2018). IWD consists of deviant behaviors that hurt other employees and customers in the organization, such as bullying, harassment, violence, abusive acts, and workplace incivility (Arab et al., 2013; Bennett & Robinson, 2000; Milam et al., 2009).

In the present study, a broad definition of “workplace deviance” is adopted. OWD would be focused on as the criterion measure, with a consideration on the differential predictive validities of integrity tests on varying types of OWD. Nevertheless, the present study attempts to echo the two landmark studies previously mentioned and paint a clearer picture of workplace deviance with better specificity. Given such, IWD is excluded. Employee turnover, one of the criteria measures in Van Iddeginke's classic meta-analysis (2012a), is also excluded because it may not be a good indicator of organizational deviance due to various reasons. On the other hand, both CWBs and UPBs are included because of their nature of illegitimate and voluntary behaviors that violate organizational norms and impede organizational functioning, regardless of their anti-organization or pro-organization intention (Barling et al., 2009; Bowling, Burns, Stewart, & Gruys, 2011). In addition, new forms of OWD, including cyberslacking, which involves distraction and putting off work to “surf the internet” (O’Neill, Hambley, & Chatellier, 2014), are included in this meta-analysis to provide an updated picture of contemporary workplace deviance. Some other types of workplace misbehavior that are usually out of the scope of CWBs and UPBs, such as the violation of disciplines, are also included in the category of WDBs. Therefore, the criterion of OWD constitutes CWBs, UPBs, and WDBs in this study. The potential moderating effect of these three different natures of deviance will also be explored.

Different types of integrity tests with varying assumptions and focuses

Among the different types of integrity tests, the overt integrity tests (clear-purpose tests) and covert integrity tests (personality-based tests) are two essential types of tests that have been applied across settings since the 1980s (Frost & Rafilson, 1989; Sackett, 1994; Sackett et al., 1989, 1998; Sackett & Harris, 1984). Overt (clear-purpose) integrity tests include questions that inquire about workplace deviant attitudes and behaviors directly and explicitly with assumptions about both “apple” and “barrel” theories (Cunningham et al., 1994; Nicol & Paunonen, 2002; Sackett & Harris, 1984; Wanek, 1999). Covert (personality-based) integrity tests are personality-oriented trait tests that assess psychological characteristics and traits related to a broader range of CWBs, with an inclination to the “apple” side that attributes behaviors to dispositional factors (Alliger & Dwight, 2000; Byle & Holtgraves, 2008; Neuman & Baydoun, 1998; Sackett et al., 1989).

However, given the multifaceted nature of integrity and deviance, there exist other types of integrity measures with different focuses in practice that have received increasing attention in recent years. Some major types of these integrity measures included biodata (Aita et al., 2018; McDaniel, 1989), vetting (Delarosa, 2015; Jeske et al., 2019; Minor et al., 2018), integrity-related cognitive ability tests (Dilchert et al., 2007; McHenry et al., 1990; Oppler et al., 2013), value-oriented tests (Grabowski et al., 2019; Matherne III & Litchfield, 2012), moral reasoning tests (Fisher et al., 2021; Galić, 2016), situational judgement tests (de Leng et al., 2018; Husbands et al., 2015; Olaru et al., 2019), organizational measures for person–job fit or person–organization fit (Dalal et al., 2020; Diefendorff & Mehta, 2007; Fine & Edward, 2017; Kong, 2016; Zhang et al., 2019), and other novel measures (Cohen et al., 2016; Halliday, 2019; Ion et al., 2017).

These relatively nonconventional types of integrity measures have brought new perspectives to examine different dimensions of the construct of integrity. For instance, integrity-related cognitive ability tests (e.g., Tureary, 1999; Wonderlic, 2002) were used to investigate the linkage between cognitive ability and workplace deviance. It was found that cognitive ability could be a “forgotten trait (intelligence)” that relates to workplace deviance as job applicants with a higher cognitive ability were found to engage in CWB less frequently (Dilchert et al., 2007). It was explained that integrity-related cognitive ability may be linked to deviant work behaviors in two ways (Dilchert et al., 2007). First, it was hypothesized that employees with higher intelligence would have better foresight in inhibiting their CWBs for long-term benefits, and vice versa for employees with lower levels of cognitive abilities, who might be less thoughtful and more impulsive (Gottfredson, 1998). Another chain of reasoning hypothesized that lower cognitive abilities would be associated with lower education attainment, which makes an individual prone to unfavorable jobs, status, and monetary compensation within an organization. In many cases, this would then be followed by frustration and perceived unfairness in these employed individuals, which may then lead to retaliatory behaviors against the organization (Lau, Au, & Ho, 2003; Skarlicki & Folger, 1997). This presented an additional utility of cognitive ability testing in the workplace as it has long been used for predicting overall job performance mostly with the well-known g (general cognitive) ability (Schmidt & Hunter, 1998; Schmidt et al., 2016).

Likewise, specific to the needs of integrity assessment in some professions, value-oriented tests that comprised of moral reasoning and integrity-based situational judgement tests have been gaining in importance. These tests aimed to assess the inner values and beliefs of job applicants and incumbents to uphold professional work ethics (de Leng et al., 2018; Husbands et al., 2015). They not only captured a new dimension core to the integrity construct, but also have the advantage of easy administration in groups with empirically supported predictive validity (Becker, 2005; de Meijer et al., 2010). While value-oriented measures tend to investigate the “inners,” integrity-oriented organizational measures look at both personal and situational factors in affecting workplace deviance. Some organizational measures aimed at evaluating the degree of person–job fit (Fine & Edward, 2017; Iliescu et al., 2015; Johnson & Johnson, 1996, 2000), whereas others examining person–organization fit (Cable & Judge, 1996; Colquitt, 2001; Dalal et al., 2020; Di Stefano & Scrima, 2016; Furnham & Gunter, 2015; Rahim et al., 2001; Spector & Jex, 1998). These integrity-oriented organizational measures adopted the interactionist assumption in associating integrity testing and workplace deviance.

Apart from the above, there were integrity measures developed in response to contemporary occupational needs with unique perspectives. For example, there has been a trend on “cyber-vetting” in which some employers might evaluate applicants’ social media information (e.g., Instagram, Facebook) as integrity checking to inform personnel decisions (Cooper et al., 2020; Delarosa, 2015; Ghoshray, 2012; Jeske et al., 2019). In addition, there were some relatively novel integrity measures developed in the recent decade, which included the assessment of grit (Duckworth et al., 2007; Duckworth & Quinn, 2009; Ion et al., 2017), guilt-proneness (Cohen et al., 2014, 2016), core self-evaluations (Debusscher et al., 2016; Judge et al., 2003; Kluemper et al., 2019), emotional intelligence (Greenidge & Coyne, 2014; Greenidge et al., 2014; Ma & Liu, 2019; Wong & Law, 2002), attachment style (Brennan et al., 1998; Richards & Schat, 2011), insomnia (Yuan et al., 2018), music preference (Halliday, 2019), and time perspective (Carelli et al., 2015; Wojtkowska et al., 2019; Zimbardo & Boyd, 2015),

A detailed list of integrity tests included in the current meta-analytic review is shown in Table S1. Biodata measures are not listed because they are usually based on the generic measures of background checking and resumes of applicants and incumbents.

Literature review on the use of integrity tests for predicting workplace deviance

According to the two classic empirical studies on the validities of different selection methods conducted by Schmidt and fellows (1998; 2016), integrity testing provided the highest incremental validity on predicting overall job performance when combined with a general mental ability test (composite validity of .78). The advantage of using integrity testing was further supported by Ones, Viswesvaran, Schmidt, and fellows (1993) when they consistently and systematically reviewed the empirical evidence of using integrity tests to predict both productive and counterproductive job performance (Ones et al., 1993, 1996; Schmidt & Hunter, 1998). According to Ones et al.’s landmark meta-analysis of integrity tests (1993), they reported an overall validity (corrected for predictor range restriction and criterion unreliability) of .34 and .47 for integrity tests to predict job performance and CWBs, respectively. Specifically, the predictive validity of integrity tests on CWBs was reported to be substantial, with a true validity estimate of .55 for overt integrity tests and .32 for covert integrity tests. These findings provided the foundational support for the effectiveness of integrity tests in predicting overall job performance and CWBs (e.g., theft, disciplinary problems, and absenteeism). As expected, this study was well-cited by integrity test providers for evidence-based practice.

Van Iddekinge's team conducted another meta-analysis (2012a) and found considerably lower criterion-related validity of integrity tests on predicting job performance and CWBs in comparison to the data reported by Ones et al. (1993). In Van Iddekinge et al.'s meta-analysis (2012a), the overall reported validity was .15 for job performance and .32 for CWBs after corrected for measurement error. Their results reported a corrected validity estimate of .18 for job performance and .36 for CWBs. In addition, the corrected (for measurement error) validity estimate was .38 for overt tests and .27 for covert tests (Van Iddekinge et al., 2012a). Given such, Van Iddekinge et al. (2012a) expressed concern about the possible inflated validity estimates of integrity testing and offered cautionary conclusions and suggestions for further examination on the predictive validity of integrity assessment.

Inferring from these different findings on the varying predictive validities of integrity testing, Sackett and Schmitt (2012) concluded the need for more specific research questions and evidence to shed better light on how integrity testing would function. In particular, there has been a call for moderator analyses on this aspect to investigate potential moderators of this integrity testing–performance/deviance linkage.

Potential moderators

Following Sackett and Schmitt's (2012) views and the issues raised in the “Ones–Van Iddekinge dialogue,” the current meta-analysis will examine a comparable set of moderators and add four additional ones (industry, country, medium of test, and gender) that merit investigation. This study will also adopt the research practices that have been less debated on from each previous study to provide better insight into the issues identified in the field.

In Ones et al.’s research (1993), the moderators of predictor type (type of integrity tests, overt vs. covert), admission criteria (self-admission vs. external measure), breadth of criteria (narrow vs. broad counterproductivity), validation strategy (concurrent vs. predictive), and validation sample (applicants vs. employees) were investigated. They found that overt integrity tests appeared to be better at predicting counterproductivity than covert integrity tests. The conclusion, however, was deemed premature because other potential moderators were not examined. For example, it was reported that criteria breadth might be a moderator with a higher predictive validity on narrow criteria, while admission criteria might not. It was also possible that validation strategy could be a moderator, in which concurrent validity would be higher than predictive validity in the integrity tests included in the research. Moreover, the validation sample was found to be a moderator, with larger validity estimates found in employee samples than applicant samples.

Most of these moderators were also investigated in Van Iddekinge and his team's research (2012a), and they also examined publication status (published vs. unpublished studies) as a moderator. Consistent with Ones’s findings (1993), Van Iddekinge's study (2012a) found that overt tests had higher corrected validities in predicting counterproductivity than covert tests. In addition, validation strategies of concurrent designs reported larger validities than predictive designs. Likewise, larger corrected validities were indicated in incumbent samples than applicant samples (Van Iddekinge et al., 2012a). However, different from Ones's meta-analysis, Van Iddekinge's team reported a larger corrected validity for broad criteria measures than narrow ones. They also found admission criteria to be a significant moderator, in which self-reported counterproductivity had larger validity estimates than external measures. Regarding the moderator analysis of publication status, they found that the corrected validities from published studies were somewhat larger than those from unpublished studies.

In the current meta-analysis, moderators examined in the previous two meta-analyses and potential new moderators will be investigated. The first research focus will be on comparing our findings on the effects of those previously studied moderators with the results in Ones et al. (1993) and Van Iddekinge et al.'s (2012a) reviews. Considering the inclusion of relatively new studies from across different countries and industries, as well as the increase in integrity assessments conducted via a computer-mediated medium since the previous meta-analyses, additional moderator analyses will be carried out on the country, industry, and medium of test (computer-mediated test vs. non-computer test vs. mixed).

Specifically, as most integrity tests were developed in North American and European countries, it is speculated that integrity tests will have larger predictive validity in these sampling countries due to the more indigenous operationalization of the integrity constructs and measures in their “country of origin.” In addition, “industry” could be a potential moderator because industries with clearer guidelines and criteria for assessing integrity problems and deviant behaviors might enable easier measurement and prediction by integrity tests. An example could be the clear disciplinary guidelines in the military and law enforcement industry. Moreover, with newer findings on the possible gender differences in CWBs (Gonzalez-Mulé et al., 2013), the present study will look into gender as a possible demographic moderator. Likewise, the potential moderating effect of the “medium of test” will also be explored due to the trend of using computer-mediated tests.

Aiming to be one of the few updated meta-analytic studies on integrity testing that integrates findings across countries and industries, it is our hope that the addition of these new moderators would bring new insight to the field and increase the generalizability of findings across settings. A summary of the proposed moderators is shown in Table S2.

Objectives of the present study

With the objective to contribute to the body of knowledge pertaining to integrity testing in the workplace, we aim to review and provide a quantitative summary to the overall and differential predictive validities of various integrity assessments. By including previously analyzed moderators as well as newer and potential moderators in the analyses, the study would provide a clearer picture on the predictive validity of integrity tests in different working populations and contexts. In addition, this research endeavors to adhere to the emphasis on methodological rigor by correcting for statistical artifacts of measurement error and range restriction as discussed in the “Ones–Van Iddekinge dialogue.” Answers to the long-debated questions about the validity and generalizability of integrity testing that have been asked since 1980s may be found.

Practically, the present study would guide the evidence-based and ethical use of integrity tests in organizational practices for upholding professional work ethics when an absolute “pass or fail” does not exist for integrity assessment. By incorporating the results on integrity research in both the East and West in the past 50 years and a broader coverage on the types of integrity measures (e.g., novel measures) and criteria of workplace deviance (e.g., UPBs) across industries, a clearer picture on the use of integrity tests would be made more possible. To the best of our knowledge, this is the first meta-analysis on integrity testing that includes publications in Chinese with a consideration of the assumptions and implications of cultural differences as represented by different countries in the present study.

Method

Literature search

We examined a variety of sources to avoid publication bias. We performed computer and manual searches to locate relevant published and unpublished papers including journal articles, book chapters, technical reports documented by test publishers, theses and dissertations, working papers, and conference papers. The time frame for literature search was set from 1917 to November 2021 (if feasible in some databases for tracing back to 1917 at the time of World War I when psychological testing was first officially introduced in army recruitment; Terman et al., 1917). Among the searched papers, the earliest identified relevant paper was published in 1975. As such, the current study covers studies in the past 50 years that were available.

Computer search (based on combinations of keywords such as “integrity test / covert test/ overt test / biodata” and “deviance/CWB/ UPB/misconduct”) involved seven databases: APA PsycInfo, APA PsycArticles, MEDLINE via OVID, Social Science Citation Index, China Journal Net, CINAHL, and ProQuest Dissertations and Theses Database. It yielded 7,723 articles. Manual search involved an issue-by-issue search of papers published in 10 academic journals in the past 10 years. We also inspected the reference lists of selected papers and book chapters (e.g., Ones et al., 1993; Van Iddekinge et al., 2012a). Moreover, we contacted prominent scholars and active consultants in the concerned field as well as test publishers for unpublished papers and technical reports.¹ A manual search added 148 studies. Altogether, we located 7,871 studies. After applying some exclusion criteria (Figure S1 in the supplementary materials), we included 119 studies, which provided 150 independent samples with a pooled sample size of 67,016 (marked with an asterisk in the References section). The present meta-analysis included 97 new studies different from the two classic reviews.² Among these new additions, some of them covered novel measures and some were written in Chinese that represented more updated research in the past 10 years. This literature selection process, and details of the inclusion and exclusion criteria, are illustrated in Figure S1.

Coding scheme

Two authors coded the information on sample characteristics (sample size, gender, validation sample, sampling industry, and country), type of integrity test, validation strategy, criterion measure, medium of test, publication status, and effect size of each independent sample. Table S2 indicates the coding scheme and Table S3 shows the codes of the included studies. The initial rate of agreement on the coding between the coders was 96%, in which inconsistencies were resolved by discussion between the coders.

Meta-analytic procedures

Statistical analyses were performed by the psychmeta and metafor packages of the statistical program R (Viechtbauer, 2019), and the statistical software Comprehensive Meta-Analysis (CMA) Version 3. The observed validity coefficient(s) within each primary study was identified and regarded as the effect size statistics, in which most primary studies reported zero-order correlation(s) between the overall integrity test score and an overall criterion score. For studies that reported other varieties of effect sizes, such as t-value, z-score, β-weights, and chi-square (χ²), they were converted to Pearson's correlation coefficients (Cohen, 1992; Lipsey & Wilson, 2001). For samples reporting effect sizes between multiple scales of a particular integrity test and the criterion variable (e.g., correlations between each of the five scales of a Big Five personality test and the criterion of CWB), a single estimate was computed when standard deviations of these variables and the intercorrelations among these variables were available (Cheng & Chan, 2008; Hunter & Schmidt, 1990). Otherwise, a simple average was computed when such information was unavailable (Cheng & Chan, 2008).

Hunter and Schmidt's (2004) psychometric meta-analytic procedure was employed to correct the statistical artifacts of measurement error and indirect range restriction in order to obtain the “true” correlation between integrity tests and workplace deviance. Missing reliability coefficients of the variables were estimated and substituted by the sample size-weighted mean reliability of the multi-item measure of that variable across the samples (Cheng & Chan, 2008; Sverke et al., 2002). The mean reliability of multi-item measures of integrity test was .78, while the mean reliability for deviance measures was .83. After the correction for measurement error and indirect range restriction, 26 out of the 150 corrected validities were found to exceed the value of 1.0 resulting from the artifact adjustment. As there seemed no consensual way to adjust such effect sizes (Neuber et al., 2021; Wang et al., 2019), the original uncorrected, attenuated correlation of these 26 effect sizes were used for analyses as reference to some updated practices (Neuber et al., 2021). A 95% confidence interval was used for the estimated correlation coefficients.

In this meta-analytic review, the random-effects model was adopted and decided a priori as heterogeneity was expected owing to the variety of integrity tests applied across different industries and countries (Hunter & Schmidt, 2004; Hunter et al., 1990). The results of the random effects model are conservative in that their 95% Confidence Intervals (CIs) are often broad, thus reducing the likelihood of type-II errors (Cheung et al., 2012).

The presence of heterogeneity for identification of moderators was tested by the Cochran's Q homogeneity test (Cochran, 1954) and I² statistic (Higgins & Thompson, 2002) by the CMA statistical software. Moderator analyses were also performed by the same software. Abiding to the practice of reliable subgroup analysis, only the estimates of a subgroup that involved at least three independent samples was included (Cheng & Chan, 2008; Choi et al., 2015).

Publication bias analysis

Given the possible tendency to submit or publish studies based on the strength or direction of the results (Dickersin, 2005), the potential publication bias was examined by the funnel plot (Kepes et al., 2012), Egger's regression intercept (Egger et al., 1997), Begg's rank correlation test (Begg & Mazumdar, 1994), and the trim-and-fill method (Duval & Tweedie, 2000) conducted by the metafor package of statistical program R.

Results

Description of studies

Table 1 provides a summary of the characteristics of the 150 included samples, with the observed and corrected validities.

Table 1.

Overall and subgroup analysis of the moderating effect on the relationship between integrity tests and workplace deviance

Moderator	Subgroup	Q	k	N	ρ	95% CI	p-value
Overall effect^a	/	441397876.88**	150	67016	.43**	[.32, .52]	<.001
Integrity test type		24.40**	150	67016			<.001
	Integrity-related cognitive ability tests		5	7821	.65**	[.53, .74]	<.001
	Value, moral reasoning, situational judgement tests		8	2171	.60**	[.41, .75]	<.001
	Organizational measures		30	11193	.48**	[.28, .63]	<.001
	Covert tests		54	21380	.39**	[.31, .48]	<.001
	Overt tests		33	7944	.38**	[.31, .45]	<.001
	Novel measure		14	3324	.27*	[.039, .47]	.022
	Biodata		3	11941	.50	[−.25, .88]	.182
	Mixed measure		3	1242	.65**	[.43, .80]	<.001
Industry		15.49*	150	67016			<.05
	Military and law enforcement		24	29404	.50**	[.29, .66]	<.001
	Customer services, retail, and sales		24	6521	.47**	[.34, .58]	<.001
	Manufacturing		7	2094	.45**	[.21, .63]	<.001
	Business, banking, and finance		13	4272	.43*	[.16, .64]	.003
	General		73	22633	.40**	[.27, .52]	<.001
	Medical, pharmaceutical, and healthcare		6	997	.24**	[.17, .31]	<.001
	Education		3	1095	.36	[−.15, .72]	.17
Criterion source		6.87*	150	67016			<.05
	Employee record		24	25909	.48**	[.25, .67]	<.001
	Self-report		108	32727	.45**	[.34, .54]	<.001
	Other-report		18	8380	.22*	[.065, .37]	.006
Nature of deviance		1.25	150	67016			.534
	WDB		40	30689	.47**	[.30, .61]	<.001
	CWB		99	33810	.42**	[.30, .53]	<.001
	UPB		11	2517	.30*	[.01, .54]	.041
Country		17.35*	150	67016			<.05
	Israel		11	3860	.47**	[.38, .55]	<.001
	Germany		6	2028	.45*	[.18, .65]	.002
	Canada		8	2226	.44**	[.33, .54]	<.001
	United States of America		68	41384	.43**	[.31, .54]	<.001
	Romania		9	2280	.37*	[.08, .60]	.013
	China		10	1994	.28**	[.20, .35]	<.001
	Turkey		4	1298	.53	[−.20, .88]	.142
	United Kingdom		3	900	.13	[−.15, .40]	.36
	Others^b		28	10831	.49**	[.28, .65]	<.001
Validation sample		.00	150	67016			.983
	Applicants		37	18885	0.43**	[.36, .49]	<.001
	Incumbents		113	48131	0.43**	[.30, .54]	<.001
Validation Strategy		.25	150	67016			.619
	Concurrent		109	32327	.41**	[.35, .47]	<.001
	Predictive		41	34689	.47**	[.23, .65]	<.001
Publication status		1.07	150	67016			.302
	Published		141	64792	.43**	[.33, .53]	<.001
	Unpublished		9	2224	.32*	[.11, .50]	.003
Medium of test		4.32	150	67016			.115
	Computer-mediated tests		66	26069	.44**	[.28, .57]	<.001
	Non-computer tests		81	40136	.42**	[.30, .54]	<.001
	Mixed		3	811	.28**	[.17, .38]	<.001
Gender		.51	150	67016			.916
	Majorly male		37	17298	.45*	[.12, .69]	.010
	Mixed		39	11479	.44**	[.29, .56]	<.001
	Majorly female		33	11002	.41**	[.29, .52]	<.001
	Unspecified		41	27237	.41**	[.22, .57]	<.001

Note: Q = Cochran's Q homogeneity test (Cochran, 1954); ρ = validity estimate corrected for indirect range restriction and measurement error; 95% CI = lower and upper bounds of the 95% confidence interval for ρ; k = number of validity coefficients; N = sample size; WDB = workplace deviance behaviors; CWB = counterproductive work behaviors; UPB = unethical pro-organizational behaviors.

Twenty-six studies were found to have the correlation coefficients corrected for indirect range restriction and measurement error exceeded the value of 1.0. As such, the original uncorrected, attenuated correlation of these 26 effect sizes were used for analyses. The uncorrected estimated correlation coefficient of the overall effect (r_raw) is .29, p < .001. the estimated correlation coefficient corrected for measurement error only of the overall effect (r_c) is .33, p < .001. The proportion of variability due to heterogeneity between studies rather than sampling error (I²) is 100%.* p < .05; ** p < .001.

“Others” covered sampling countries of Australia, Barbados, Belgium, Colombia, Croatia, India, Italy, Korea, Mexico, Pakistan, Peru, Poland, Spain, South Africa, Thailand, The Netherlands, Ukraine, and the United Arab Emirates with two or less than two studies included in this review.

Overall validity of integrity tests for predicting workplace deviance

Figure S2 shows the forest plot of the pooled effect size and the effect sizes from the 150 samples, whereas Table 1 presents the meta-analytic validity estimates for integrity tests and the criteria of workplace deviance. Across the 150 independent samples, the overall observed mean validity estimate was .29, the mean validity estimate corrected for measurement error was .33, and the mean validity estimate corrected for indirect range restriction and measurement error was .43 (ρ = .43; CI [.32; .52]; p < .001). This indicated a statistically significant relationship between integrity tests and workplace deviance.

Moreover, heterogeneity was considerable in view of the significant Q statistics (Q = 441397876.88, p < .001) and high I² value of 100%, which suggested the relationship between integrity tests and workplace deviances was subjected to certain moderating effects. The statistics are reported in Table 1.

Moderator analyses

Table 1 presented the results of moderator analyses. Among the moderators examined by the subgroup analyses, it was indicated that the “type of integrity test,” “industry,” “country,” and “criterion source / admission criterion” were significant moderators. However, the “nature of deviance,” “validation sample,” “validation strategy,” “publication status,” “medium of test,” and “gender,” were statistically nonsignificant in moderating the relationship between integrity tests and workplace deviance. All subgroup analyses were based on the corrected validity estimates whenever applicable.

The significant moderating effect of the type of integrity test

The “type of integrity test” significantly moderated the relationship between integrity tests and workplace deviance (Q = 24.40, p < .001), in which the subgroup of “mixed measures” (k = 3) was excluded because the focus of the present study was on estimating the validity of using a single integrity test. Among the different types of integrity test included, except biodata, all of the tests showed significant validity for predicting workplace deviance but with varying effect sizes. When comparing the validity estimates of the examined test types, covert tests (k = 54; ρ = .39; CI [.31; .48]; p < .001) and overt tests (k = 33; ρ = .38; CI [.31; .45]; p < .001) showed comparable validity in associating with workplace deviance. Subgroup analysis also revealed the validity estimate was largest in the integrity-related cognitive ability tests (k = 5; ρ = .65; CI [.53; .74]; p < .001), followed by the second largest validity estimate of the value, moral reasoning, and situational judgment tests (k = 8; ρ = .60; CI [.41; .75]; p < .001) After that, organizational measures showed a significant effect size of .48 (k = 30; ρ = .48; CI [.28; .63]; p < .001). Remarkably, the validity estimates of value-oriented tests, cognitive tests, and organizational measures were all larger than the covert and overt tests. For novel measures, results indicated that this new test type had a significant effect size, but the corrected validity (k = 14; ρ = .27; CI [.039; .47]; p < .05) was smaller than other types of integrity tests. Further, the effect size of “biodata” was nonsignificant (k = 3; ρ = .50; CI [−.25; .88]; p = .18).

The significant moderating effect of industry

Subgroup analysis showed that “industry” was a significant moderator (Q = 15.49, p < .05) of the association between integrity tests and workplace deviance. For this “industry” moderator, the validity estimate was highest in the “military and law enforcement” industry (k = 24; ρ = .50; CI [.29; .66]; p < .001), which was followed by the “customer services, retail, and sales” industries (k = 24; ρ = .47; CI [.34; .58]; p < .001). The corrected validity indicated in the industry of “manufacturing” sector (k = 7; ρ = .45; CI [.21; .63]; p < .001), “business, banking, and finance” (k = 13; ρ = .43; CI [.16; .64]; p < .05), and “general” (k = 73; ρ = .40; CI [.27; .52]; p < .001), were also significant. Notably, the validity estimate of the “medical, pharmaceutical, and healthcare” industry was significant (k = 6; ρ = .24; CI [.17; .31]; p < .001), but the effect size was relatively small when compared to those in other industries. In addition, the effect size was found to be nonsignificant in the “education” sector (k = 3; ρ = .36; CI [−.15; .72]; p = .17).

The significant moderating effect of country

“Country” was found to be a significant moderator (Q = 17.35, p < .05). Among the countries included, the corrected validity estimates with significant effect sizes ranged from the smallest magnitude of .28 in China (k = 10; ρ = .28; CI [.20; .35]; p < .001) to the largest magnitude of .47 in Israel (k = 11; ρ = .47; CI [.38; .55]; p < .001). In-between were the significant validity estimates in ascending order of .37 in Romania (k = 9; ρ = .37; CI [.08; .60]; p < .05), .43 in the USA (k = 68; ρ = .43; CI [.31; .54]; p < .001), .44 in Canada (k = 8; ρ = .44; CI [.33; .54]; p < .001), and then .45 in Germany (k = 6; ρ = .45; CI [.18; .65]; p < .001). The corrected validity estimates of the “Others”³ subgroup was .47 (k = 31; ρ = .47; CI [.27; .63]; p < .001). However, the effect sizes found in the subgroups of Turkey (k = 4; ρ = .53; CI [−.20; .88]; p = .14) and United Kingdom (k = 3; ρ = .13; CI [−.15; .40]; p = .36) were nonsignificant.

The significant moderating effect of criterion source

The “criterion source” (admission criterion) that included the subgroups of “self-report” (k = 108), “other-report” (k = 18), and “employee record” (k = 24), was a significant moderator (Q = 6.87, p < .05). Specifically, the corrected validity estimate was largest in the “employee record” subgroup (ρ = .48; CI [.25; .67]; p < .001), which indicated the most profound effect of integrity tests on predicting the criterion of workplace deviance as measured by objective employee record. The “self-report” criterion source (ρ = .45; CI [.34; .54]; p < .001) and “other-report” criterion source (ρ = .22; CI [.065; .37]; p < .01) also indicated significant validity in moderating the integrity tests and workplace deviance relationship. However, the source of “other-report” showed the smallest validity estimate of .22 that ranged from .065 to .37 with a significant level at p < .01.

The nonsignificant moderating effect of the “nature of deviance”

The moderating effect of the “nature of deviance” (Q = 1.25, p = .534) was found to be nonsignificant. Subgroup analyses revealed the significant effect sizes of CWBs (k = 99; ρ = .42; CI [.30; .53]; p < .001) and WDBs (k = 40; ρ = .47; CI [.30; .61]; p < .001) as indicated by a validity estimate of .42 and .47, respectively. Remarkably, the validity estimate of UPBs was significant but smaller in magnitude with an effect size of .30 (k = 11; ρ = .30; CI [.01; .54]; p < .05).

The nonsignificant moderating effect of “validation sample,” “validation strategy,” and “publication status”

Results showed that the “validation sample” (Q = .00, p = .983), “validation strategy” (Q = .25, p = .619), and “publication status” (Q = 1.07, p = .302) were nonsignificant moderators of the relationship between integrity tests and workplace deviance. For the “validation sample,” the subgroups of “applicants” and “incumbents” indicated comparable and significant effect sizes. The mean validity estimate was .43 for both “applicants” (k = 37; ρ = .43; CI [.36; .49]; p < .001) and “incumbents” (k = 113; ρ = .43; CI [.30; .54]; p < .001). Similarly, for the “validation strategy,” the validity estimate was .41 for “concurrent study” (k = 109; ρ = .41; CI [.35; .47]; p < .001) and .47 for “predictive study” (k = 41; ρ = .47; CI [.23; .65]; p < .001).

For the subgroup analysis of “publication status,” the validity estimate was .43 for “published study” (k = 141; ρ = .43; CI [.33; .53]; p < .001) and .32 for “unpublished study” (k = 9; ρ = .32; CI [.11; .50]; p < .05). Although both groups showed significant effect sizes, it should be interpreted with caution when the number of included samples in the group of “unpublished study” was much smaller than those included in the “published study” group.

The nonsignificant moderating effect of “medium of test” and “gender”

Results showed that the “medium of test” (Q = 4.32, p = .115) and “gender” (Q = .12, p = .989) were nonsignificant in moderating the relationship between integrity tests and workplace deviance. Regarding the “medium of test,” the validity estimate was .44 for “computer-mediated test” (k = 66; ρ = .44; CI [.28; .57]; p < .001) and .42 for “non-computer test” (k = 81; ρ = .42; CI [.30; .54]; p < .001). The effect size of the “mixed media” subgroup was .28, which was also significant but smaller in magnitude (k = 3; ρ = .28; CI [.17; .38]; p < .001).

For “gender” subgroups, the validity estimates were .41 for “majorly female” group (k = 33; ρ = .41; CI [.29; .52]; p < .001), .45 for “majorly male” group (k = 37; ρ = .45; CI [.12; .69]; p < .05), .44 for “mixed genders” group (k = 39; ρ = .44; CI [.29; .56]; p < .001), and .41 for “unspecified” group (k = 41; ρ = .41; CI [.22; .57]; p < .001).

Publication bias analysis

Publication bias analyses revealed an asymmetric funnel plot and a significant p-value (p < .001) of the Egger's regression intercept that indicated potential publication bias. In addition, Begg's test reported a significant p-value (p < .001) that suggested potential publication bias. However, the trim-and-fill method suggested the imputation of 17 studies, with an adjusted effect size of .42 (p < .001) of integrity tests on workplace deviance. This value was comparable to the unimputed value. Overall, possible publication bias was noted but not a serious concern in the present meta-analysis.

Discussion

Inspired by a handful of important research in integrity testing, the present meta-analysis is the first of its kind to encompass a wide range of integrity measures for the workplace that have been used in the past 50 years. This study also covered a broader range of contemporary workplace deviant behaviors across industries. Compared with previous reviews, our study was unique in its cross-cultural direction, which included primary studies of integrity testing in countries with different languages (e.g., publications in Chinese) and associated cultural variations. We aimed to conduct a comprehensive and updated review on the relationship between integrity tests and workplace deviance, with a spirit to provide theoretical, empirical, and practical insights for research and application in the domains of psychological assessment and workplace ethics.

The overall relationship between integrity tests and workplace deviance only scratched the surface of the wide field of integrity testing

Our findings revealed a significant relationship between integrity tests and deviant work behaviors, indicating an overall corrected mean validity estimate of .43. Implying the predictive value of integrity tests on workplace deviance, the current results were in line with the corrected validities found in the landmark analyses done by Ones et al. in 1993 and Van Iddekinge et al. in 2012a, which was between .47 and .36, respectively. It is in this regard that the present findings provided an important puzzle piece in response to the “Ones–Van Iddekinge dialogue” on the controversial validity of integrity testing. Such empirical findings provided a theoretical implication of the value of integrity testing in looking at the dark side of workplace behaviors.

The overall analysis, however, only scratched the surface of the wide field of integrity testing. Deeper investigations by subgroup analyses indicated that the relationship between integrity tests and workplace deviance was moderated by the type of integrity tests, industry, country, and criterion source. However, such relationship was not moderated by the nature of deviance, validation sample, validation strategy, publication status, medium of test, and gender. These results implied the possibility of generalizing integrity testing in the prediction of various genres of workplace deviance across working populations of different genders, and media of testing. The results also revealed that the effect sizes of integrity tests were unlikely to be compromised by the validation strategy nor publication status. These are important practical implications for practitioners to consider when applying integrity testing in the workplace.

Cognitive, values, and organizational measures could outperform conventional covert and overt integrity tests in predicting workplace deviance

Examination of the significant moderating effect of different types of integrity tests revealed that integrity-related cognitive ability tests yielded the largest validity estimate in predicting workplace deviance. The findings supported the theories proposing that intelligence might affect someone's foresight in inhibiting deviant acts (Gottfredson, 1998), education attainment, or job choices as well (Lau et al., 2003; Skarlicki & Folger, 1997). It also demonstrated that cognitive ability, which is sometimes regarded as a “forgotten trait” when discussing misconduct and counterproductivity (Dilchert et al., 2007), may in fact be a factor that increases the proneness or prohibition of an employee's negative work behaviors (Gottfredson, 1998).

Second to cognitive measures, the type of value, moral reasoning, and situational judgement tests was also revealed to be a significant and strong predictor of deviant work behaviors. These value-oriented measures assessed the inner values and moral beliefs of their applicants or incumbents, including moral disengagement, ethical decision-making, and moral identity (Aquino & Reed II, 2002; Chen et al., 2016; Collins, 2009). Not being commonly used to assess the “bright side” of good job performance, these value-oriented measures could nevertheless be important predictors of the “dark side” of integrity-related workplace deviance. Indeed, the essence of integrity is “the quality of moral consistency, honesty, and truthfulness with oneself and others” (American Psychological Association, 2020). The emphasis on “consistency” of inner values defining “integrity” could be a reason to explain for the largest validities of value measures because deviant work behaviors would be more likely when there is incongruence between an employee's inner beliefs and the perceived organizational values.

Organizational-oriented measures ranked third as a predictor of workplace deviance. While values and cognitive ability appear to be more dispositional in nature and are considered as the “apples,” organizational measures are more based on an interactionist model that considers both personal (“apples”) and situational (“barrels”) factors to assess the person–organization fit and person–job fit (Cable & Judge, 1996; Iliescu et al., 2015). This provided insights into the importance of looking at both dispositional and situational factors when applying integrity tests on predicting workplace deviance.

Comparing overt tests and covert tests in predicting workplace deviance, both types of tests were significant predictors and showed comparable validities in the present study. These findings were different from the previously reported pattern in Ones et al. (1993) and Van Iddekinge et al.’s (2012a) reviews, when overt tests were found to outperform covert tests. The difference might be due to the investigation of a wider array of integrity tests and workplace deviant behaviors in this study, versus the focus on two types of integrity tests and CWBs in the previous reviews. In addition, a closer look into the primary studies of this meta-analysis suggested that the inclusion of newer covert tests and faking-resistant measures (e.g., Thibault & Kelloway, 2020; Trent et al., 2020) with well-tested psychometric properties may be another reason for the improved validity of covert tests. Nevertheless, Ones et al. and Van Iddekinge et al.'s studies generally agreed that both overt and covert integrity tests had significant correlations with CWBs, while our findings provided further empirical support to the validities of both types of tests on predicting workplace deviance.

Among the different integrity tests, novel measures reported a significant but smallest mean validity in association with deviant work behaviors. These novel measures also indicated the largest variation of validity estimates ranging from .039 to .47, with a larger mean validity for measures such as music preference (Halliday, 2019), insomnia scale (Yuan et al., 2018), core self-evaluation (Kluemper et al., 2019), guilt-proneness (Cohen et al., 2016), and emotional intelligence (Greenidge et al., 2014), but a smaller mean validity for attachment style (Richards & Schat, 2011), time perspective (Wojtkowska et al., 2019), and grit (Ion et al., 2017). Given the large variations observed and the very distinct nature of these novel measures, the present findings are relatively exploratory and preliminary, which open for further examination. In general, the present findings revealed significant validities of most types of integrity tests, suggesting their substantial value in predicting workplace deviance.

Predictive validity of integrity testing varied across industries and most significant in the law enforcement profession

The relationship between integrity tests and workplace deviance was found to be significantly moderated by industry in our study. This indicated the effect of integrity tests in predicting workplace deviance would be better in certain industries. In this review, the integrity tests yielded the largest predictive validity on deviance in the military and law enforcement profession, which was followed by the second largest predictive validity of integrity tests in the field of customer services, retail, and sales. The validity estimates were also significant, with moderately large magnitude in the manufacturing industry and the business/banking/finance sector. In contrast, the predictive validity was relatively small but significant in the medical, pharmaceutical, and healthcare sector, while the validity in the education sector was nonsignificant. For the “general” subgroup that consisted of work samples across industries, the validity was significant and moderate in magnitude. Inferring from the findings, it implies that industries with clearer criteria on misconducts (e.g., inappropriate weapon use and discipline problems in law enforcement), more observable misbehaviors (e.g., substandard efficiency and theft of products in manufacturing), and better scrutiny of deviance (e.g., customer complaint system in the service industry, fraud in the finance sector) would be more predictable by integrity measures. On the other hand, certain professions (e.g., medical and educational) with vague and obscure criteria may make measuring possible mistakes and wrongdoings difficult. These may consequently weaken the integrity test and deviance relationship as the observation and reporting of such deviant work behaviors could be barricaded.

Predictive validity of integrity tests varied with countries that called for indigenous measures

Investigation of the relationship between integrity tests and workplace deviance across different countries, which was not previously examined in other studies, revealed that “country” was a significant moderator. Among the countries, significant and larger predictive validities were found in Canada, Germany, Israel, Romania, and the United States. The smallest but significant validity estimate was found in China, while the effect sizes were nonsignificant in Turkey and the United Kingdom. The varying validities across countries, specifically the relatively small validity in China and nonsignificant validities in several other countries, implies that integrity testing would have differential predictive validity across countries and that further examination of cultural differences is needed. Indeed, as most of the existing integrity measures were rooted and developed in the Western cultures, it calls for a closer look at the operationalization of integrity for developing more indigenous integrity tests with higher validity in these non-origin countries and cultures.

The significant moderating effect of criterion source that addressed the need for more objective or multiple measures on employees' misbehaviors

The criterion source (admission criteria) was revealed to be a significant moderator of the integrity–deviance relationship, in which the employee record of misbehaviors yielded the largest validity, followed by the significant validity of “self-report.” The subgroup of “other-report” consisting of ratings by supervisors or peers indicated a smaller yet significant validity. Again, our findings were different from previous findings when self-report measures were found to outperform external measures and employee records (Ones et al., 1993; Van Iddekinge et al., 2012a). A possible explanation on the different results could be the improvement of employee records with the advanced human resources analytics in recent decades (Safrinal et al., 2021; Shamim et al., 2020). This improvement may have facilitated record-keeping, making employee records a more reliable criterion source than self-report and other-report measures.

Implying the generalizability of integrity testing from the nonsignificant moderating effect of different natures of deviance, validation samples, validation strategy, and publication status

The nature of deviance as a criterion was found to be nonsignificant in its moderating effect. Results indicated that CWBs, UPBs, and WDBs all had a significant validity estimate in associating with integrity tests. Nevertheless, the mean predictive validity of integrity tests on UPBs was relatively small in magnitude. Such difference might be because UPBs are a newly defined type of workplace deviance in recent decades (Umphress et al., 2010). Most of the existing integrity measures have thus not been designed or validated to capture the UPB construct. More focal research to investigate this specific workplace deviance of UPB and relevant measures would be required to strengthen such a predictor–criterion linkage.

Similarly, the moderating effect of validation samples, validation strategy, and publication status examined in previous reviews was not shown to be a significant moderator in our study. For validation samples, the current results showed comparable effect sizes of both incumbents and applicants. Likewise, both concurrent and predictive validation strategy indicated significant and comparable predictive validities in this review. This provides some support for the ecological validity and utility of integrity testing in real work settings. It also helps to respond to the query of possible overestimation of the predictive validity of integrity testing in practice for preemployment “prediction,” when previous reviews reported a larger validity for validation strategy of concurrent design that imposed such a query.

In addition, the potential moderating effect of “publication status” examined in Van Iddekinge et al.’s (2012a) study was not replicated in this review. Nevertheless, our findings reported a consistent pattern indicating that the significant validity estimates from published studies were somewhat larger than those from unpublished studies. However, given the notable imbalanced number of nine unpublished primary studies and 141 published studies in this review, the present findings are premature in addressing the possible moderating effect of publication status and concern of publication bias.

Potential applications of integrity testing to the contemporary diversified and digitalized workplace

The potential moderators of “gender” and “medium of test” of the relationship between integrity tests and workplace deviance had not yet been investigated prior to the present study. Examination of these moderating effects revealed them to be nonsignificant. For all the “gender” subgroups of “majorly female” “majorly male,” “unspecified,” and “mixed,” the mean validity estimates were comparable and significant. These preliminary findings are of important practical value when being applied and generalized to increasingly welcoming workplaces inclusive of conventional and unconventional LGBTQ (lesbian, gay, bisexual, transgender, queer/questioning) workforces.

The preliminary findings for the “medium of test” were also encouraging. Specifically, comparable and significant effect sizes of integrity tests in predicting deviance that were delivered by both computer- and non-computer media were shown. The predictive validity of integrity tests was also significant in the “mixed-media” subgroup. With the increasing prevalence of computer-mediated and online integrity tests, the present findings strengthened the confidence of transforming current practices to those in line with the digital world, if not the metaverse.

Limitations and future research directions

Some methodological and practical limitations of the present study should be addressed and may provide possible directions for future research. Methodologically, the artifact adjustment of 26 coded primary studies with a corrected effect size value that exceeded 1.0 might have limited the estimation of a more precise “true” validity on the predictor–criterion relationship. Unfortunately, there is not yet any consensual way of handling such effect-size outliers. For example, some researchers have used the original uncorrected, attenuated correlation for analyses as we adopted in this study (Neuber et al., 2021), while others have used the method of Winsorization to cap the effect size value at .80 (Aguinis et al., 2013; Wang et al., 2019). No matter what approach is used, there is still no guarantee of the absence of bias as invalid effect sizes are possible for all kinds of corrections. Researchers should thus pay attention to these kinds of statistical artifacts in meta-analytic studies.

In addition, despite the effort to collect unpublished studies from various sources, the relatively small number of unpublished studies included in this dataset could still result in publication bias. Indeed, the publication bias analyses carried out in this review did indicate a possible publication bias, although it could also be attributed to heterogeneity (Sterne et al., 2011) and/or “true” differences between large and small samples (Kepes et al., 2012). Particularly, the funnel plot asymmetry was atypical (Sterne et al., 2011) and the adjusted overall effect size after imputation of missing studies did not show any significant difference in magnitude from our unimputed results. Nevertheless, it is suggested that future meta-analyses of integrity testing should include as many unpublished studies as possible to reduce the possibility of publication bias.

Moreover, attention should be given to the imbalanced number of studies across moderator levels that might entail unfair comparisons (Cooper & Richardson, 1986) and second-order sampling errors (Hunter & Schmidt, 2004). Likewise, the lack of investigation of the intercorrelations among moderators, which might distort the overall picture as the unique effect of moderators could confound the results, should be noted (Ones et al., 1993; Wang et al., 2019).

Practically, the limitation of collecting sufficient studies on popular integrity tests that assess workplace deviance, such as biodata and structured interviews, may have impeded the application and generalizability of the current findings in real work settings. In particular, the increased use of “cyber vetting” (Jacobson & Gruzd, 2020; Raymond, 2019; Schroeder et al., 2020) as an integrity measure in preemployment selection was not included in this analysis. Besides, following the practices of previous meta-analyses in their exclusion of polygraphy or psychophysiological measures due to dubious validities (Ones et al., 1993; Van Iddekinge et al., 2012a), the newer theoretical perspective of “ethical impulse” (Kish-Gephart et al., 2010; Sonenshein, 2007) and the controversial misguided practices of sole reliance on polygraph for hiring (White, 2020) could not be testified in this meta-analysis.

In addition, although the present study included studies across 26 counties with a good will to uncover some cultural differences assumed in different countries, the cross-cultural dimensions and implications should be carefully and thoroughly examined in future studies to explain the cultural influences on integrity testing in depth. Therefore, it would be valuable if future reviews could cumulate and investigate further on these missing puzzles to provide more practical and up-to-date insights.

Conclusion

The present meta-analysis aims to serve as an updated and balanced overview of the use of integrity tests on predicting workplace deviance across industries and countries.

In conclusion, our findings lend support to the criterion-related validity of integrity tests. Theoretically, it provided support to the interactionist model in looking at the dark side of workplace behaviors. Empirically, the present study provided refined quantitative input to the important “Ones–Van Iddeginke dialogue” about the “true” validity of integrity testing by upholding methodological rigor. Practically, results from the moderator analyses responded to the call for specific focus on investigating the utility of integrity tests in the domains of psychological assessment and workplace ethics. It is our hope that the present attempt would encourage more research efforts, as well as scrutiny in practice, on integrity testing in both the East and West.

Supplemental Material

sj-docx-1-pac-10.1177_18344909231171729 - Supplemental material for Predictive validity of integrity tests for workplace deviance across industries and countries in the past 50 years: A meta-analytic review

Supplemental material, sj-docx-1-pac-10.1177_18344909231171729 for Predictive validity of integrity tests for workplace deviance across industries and countries in the past 50 years: A meta-analytic review by Rebecca Wing-Man Lau, Darius Kwan-Shing Chan, Fan Sun and Grand Hak-Land Cheng in Journal of Pacific Rim Psychology

Footnotes

Acknowledgments

The authors would like to acknowledge Wai Chan and Fiona Ho for their valuable advice on this research. The authors would also like to thank Vince Ho, Ingrid Mak, and other fellows of the Psychological Services Group for their support.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Contribution statement

Lau conceived the research idea, performed the literature search, and wrote the manuscript. Lau and Sun jointly analyzed the data and discussed the results. Chan supervised Lau and Sun by providing guidance and feedback throughout the research and manuscript preparation process. Cheng reviewed the methodology, data analyses, and results. All authors discussed and contributed to the final manuscript.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Rebecca Wing-Man Lau

Grand Hak-Land Cheng

Supplemental material

Supplemental material for this article is available online.

Notes

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