The authors of this article declare no conflict of interest
Practitioners frequently inform us that variable ‘total details’ is not suitable for lie detection purposes in real life interviews. Practitioners cannot count the number of details in real time and the threshold of details required to classify someone as a truth teller or a lie teller is unknown. The authors started to address these issues by examining three new verbal veracity cues: complications, common knowledge details, and self-handicapping strategies. We present a meta-analysis regarding these three variables and compared the results with ‘total details’. Truth tellers reported more details (
Los profesionales dicen con frecuencia que la variable “detalles totales” es adecuada para la detección de mentiras en las entrevistas de la vida real. No pueden contar el número de detalles en tiempo real y se desconoce el umbral de detalles necesario para clasificar a alguien como sincero o mentiroso. Los autores comenzaron a abordar estos temas analizando tres nuevos indicadores verbales de veracidad: las complicaciones, los detalles de conocimiento público y las estrategias de falta de capacidad. Se presenta un meta-análisis de estas tres variables y se comparan los resultados con los “detalles totales”. Los sujetos que dicen la verdad dan más detalles (
From verbal cues to deception that have been frequently examined, total details emerged as the best diagnostic cue (
Complications are occurrences that affecs the story-teller and make a situation more complex (“Initially we did not see our friend, as he was waiting at a different entrance”) (Vrij,
Common knowledge details refer to strongly invoked stereotypical information about events (“The event had an Oscars theme so everybody was dressed up”). Lie tellers are thought to report more common knowledge details than truth tellers. Truth tellers have personal experiences of an event and are likely to report these (
Self-handicapping strategies refer to justifications as to why someone chooses not to provide information (“There isn’t much to say about the actual bungee jump as it took only a few moments”). A real life example occurred with Dominic Cummings, a former advisor to the British Prime Minister Boris Johnson. Cummings travelled from London to Durham during lockdown. This is what he said when he was asked whether he had discussed this trip with Johnson: “At some point during the first week, when we were both sick and in bed, I mentioned to him what I had done. Unsurprisingly, given the condition we were in, neither of us remember the conversation in any detail.” (https://inews.co.uk/news/dominic-cummings-lockdown-statement-pm-adviser-said-meant-barnard-castle-431111). For lie tellers, not having to provide information is an attractive strategy. However, they are also concerned about their credibility and believe that admitting lack of knowledge and/or memory appears suspicious (
A detail is a unit of information and each new piece of information counts as a detail. This means that many details can occur in a statement, far too many to count in real time. Complications and common knowledge details are clusters of details. Therefore, fewer of them occur in a statement which makes them easier to count in real time. To return to the example mentioned earlier, the sentence “Initially we did not see our friend, as he was waiting at a different entrance” contains seven details but only one complication and the sentence “The event had an Oscars theme so everybody was dressed up” contains four details but only one common knowledge detail. Someone who just listens to those two sentences will have difficulty in counting the details but should be able to spot the complication and common knowledge detail. Self-handicapping strategies are also relatively easy to spot in real time as it typically contains a statement why some information cannot be provided followed by a justification for it.
Note that the coding of complications, common knowledge details, and self-handicapping strategies occurs in addition to frequency of details coding and not instead of such coding. Frequency of details coding can be further specified, for example in contextual details. Again, this would occur in addition to the coding of complications, common knowledge details, and self-handicapping strategies. For example, the sentence “We spent a couple of hours at the National Museum” includes two contextual details (a time detail – couple of hours – and a location detail – National Museum) but the entire sentence constitutes one common knowledge detail. Contextual details are typically reported more often by truth tellers than by lie tellers (
Most verbal deception research examines verbal cues to truthfulness, that is, verbal cues that truth tellers report more frequently than lie tellers. For example, all 19 CBCA criteria, including the variable ‘total details’, are cues to truthfulness. Only examining cues to truthfulness poses a problem for practitioners: how many details should someone report to classify as a truth teller or a lie teller? This question is impossible to answer. The number of details reported is not only dependent on veracity but also on the interviewee and situation. That is, some individuals are more talkative than other individuals and some events can be described in much more detail than other events (
Truth tellers will report more complications (Hypothesis 1) and fewer common knowledge details (Hypothesis 2) and self-handicapping strategies (Hypothesis 3) than lie tellers.
The procedure applied for conducting this meta-analysis followed the APA Meta-Analysis Reporting Standard (
We searched the literature for empirical studies examining complications, common knowledge details and/or self-handicapping strategies and used the following inclusion criteria: (1) the study involved one interviewee rather than pairs or groups (see for studying groups,
The first moderator was the deception scenario. This is an important moderator for applied reasons as it examines whether effects can be generalised across scenarios. We distinguished between two categories: i) trip/memorable event, when the participants discussed a trip they had made or a memorable event which was out of the ordinary, and ii) spy mission, where the participants performed a spy mission (Moderator 1). A second moderator was the level of motivation, because research has found that cues to deception are more evident in motivated rather than unmotivated senders (
Following
We conducted the literature search in October 2020, and used the following databases: PsycINFO, PsycARTICLES, Web of Science, and Scopus. We looked for any type of work (article, review, book chapters, etc.) that included terms (“complication*” OR “common knowledge” OR “self-handicapping”, in title/abstract/keywords) and (“decept*” OR “deceit” OR “lie” OR “lying” OR “truth*”, in title/abstract/keywords) but did not include the terms (“collect*” OR “pair*”, in title/abstract/keywords). We limited our research to the psychological, social sciences, and art and humanities areas, and to sources produced from 2017 onwards. We also: i) contacted scholars who previously published articles in which complications, common knowledge details, or self-handicapping strategies were reported; ii) visited the webpages of scholars working on these types of detail; iii) searched the reference list of the selected papers; iv) searched the 2019-2020 conference programs of the European Association of Psychology and Law (EAPL), and the 2017-2020 conference programs of the American Psychology and Law Society (AP-LS), and the International Investigative Interviewing Research Group (iIIRG); v) and conducted a search on ResearchGate.
The selection process was conducted by two researchers with experience in the field. Inter-rater agreement was calculated via Cohen’s k and was 1.00 (100% of agreement). Appendix A shows the illustration of the selection process via the Prisma diagram (
A coding protocol was applied to extract all the relevant information needed for the meta-analysis from the selected papers.
The following variables were coded: (a) truth tellers’ and lie tellers sample sizes; (b) mean and standard deviation of complications, common knowledge details, self-handicapping strategies, and total details; (c) the deception scenario; (d) whether or not an incentive was provided; (e) whether the participants provided an oral or a written statement; and (f) whether or not any interviewing technique (e.g., model statement, sketching while narrating, etc.) was used. Regarding (b), the descriptives required to compute the effect sizes were obtained from three different outcome variables: i) “initial recall” – this refers to the first statement provided by interviewees who were asked to provide more than one statement, or the only statement provided by interviewees who provided only one recall; ii) “second recall” – this refers to “new” information (complications, common knowledge details etc) not already mentioned in the initial recall provided by the interviewee in a second recall; and iii) “total recall” – this refers to the sum of initial and second recall.
Regarding Moderator 4 (presence of manipulation), for “initial recall” and “second recall” data, we coded each study as “manipulation present” if the interviewees were exposed to any manipulation at any of these recall stages and as “manipulation absent” if they were not. For “total recall” data, we coded manipulation as “present” if participants were exposed to any manipulation at their “initial recall”, at “second recall”, or at both (see Appendix B for more information concerning the coding of Moderator 4). Inter-rater agreement for non-categorical moderators was analysed via percentage of agreement and was 100%. Inter-rater agreement for categorical moderator was calculated via Cohen’s k and was 1.00.
Effect sizes were computed as
The effect sizes obtained from the selected sources were analysed via standard meta-analytic procedures (
Heterogeneity was explored using the Q statistic (indicating a lack of homogeneity if significant), and the I2 statistic, which estimates what proportion of the observed variance is related to real differences in the analysed effect sizes. An I2 of 70% or more is deemed as a high difference, 50% as moderate, and 25% as low (
Publication bias was explored via the trim and fill method.
We also carried out meta-analyses via the Bayesian model averaging method (
One-hundred and twenty-one records were found through the database search, and three records through other sources. After removing the duplicates, 105 records were screened in their titles and abstracts. Eighty-three records did not relate to verbal credibility assessment and were thus excluded. One was excluded because, although focusing on verbal credibility assessment, it did not analyse complications, common knowledge details, or self-handicapping strategies (
In the end, 14 studies were included in the meta-analysis, and all of them employed a between-subjects design for veracity (participants were either asked to tell the truth or to lie). Three articles included two independent subgroups, where one was exposed to a manipulation (e.g., the model statement) and the other was not (
In the end, we analysed the 14 articles that fit eligibility criteria. Appendix C reports main characteristics of included studies, which are marked in the reference list with an asterisk.
*
A random-effects meta-analysis of the 18 samples for “frequency of complications” (
A random-effects meta-analysis on the 12 samples for “frequency of common knowledge details” (
Finally, a random effects meta-analysis on the 13 samples for the “frequency of self-handicapping strategy” (
A random-effects meta-analysis on the 17 samples focusing on “new complications” (
A fixed effect meta-analysis on the 10 samples focusing on “new common knowledge details” (
A fixed-effect meta-analysis on the 10 samples focusing on “new self-handicapping strategies” (
The meta-analysis showed support for all three hypotheses and revealed that truth tellers reported more complications and fewer common knowledge details and self-handicapping strategies than lie tellers. Findings were very similar for first initial recall, the ond recall (where only new information after first recall was examined), and for total recall (initial and second recalls combined). The finding that the pattern of results obtained in a first recall tends to repeat itself in a second recall should increase confidence amongst practitioners when they use these variables in a two recall interview when attempting to detect deceit. It may also indicate robustness of the findings.
All effect sizes were moderate but they were somewhat larger for complications (
Although complications can be coded in probably most statements, common knowledge details and self-handicapping strategies do not always occur (
Truth tellers may also include common knowledge details in their statements and perhaps particularly so when they do not see the relevance of describing the experience in more detail. These common knowledge details will be impossible to distinguish from those reported by lie tellers. A possible solution is to stress to interviewees that they should report every detail they can remember even the insignificant ones. An alternative solution is to expose interviewees to a model statement, an example of a detailed account (
Truth tellers may also admit lack of memory when an event happened some time ago and, as a result, may include self-handicapping strategies in their statement (“I cannot remember which restaurants we went to in the evenings, because we went there three months ago”). Admitting lack of memory is a CBCA criterion and truth tellers report those more frequently than lie tellers (
Complications was not only a stronger veracity indicator than common knowledge details and self-handicapping strategies, it was also a more diagnostic veracity indicator than total details. This was particularly the case in the second recall (
A possible benefit of total details is that the cue always can be examined, because even brief statements (perhaps with the exception of ‘no comment’) always include details. Very short statements may not include complications. Whether total details emerges as a strong veracity cue in short statements is an empirical question. This may not be the case, because verbal cues to deception are more likely to occur in longer statements because words are the carriers of verbal cues to veracity (
The moderators did affect only the results for new self-handicapping strategies in the second recall. It means that effect sizes were mostly homogeneous across studies. Yet, this should be taken with some caution because of the (i) low number of studies and (ii) unbalanced groups (
We note four limitations. First, all the available research comes from Vrij’s lab. This is not uncommon in deception research. For example, in a meta-analysis of Strategic Use of Evidence (SUE) research, Granhag was an author on every publication (
A second limitation is that all studies are lab-based studies but field studies testing hypotheses seem relevant. This could be a challenge due to the difficulty in obtaining ground truth in field studies. Third, the number of studies on which this meta-analysis was based was limited. Although this is not uncommon in this field (
Fourth, we stated that examining complications, common knowledge details, and self-handicapping details is advantageous compared to coding total details because the former three variables can be coded in real time whereas the latter variable cannot. Note that there is yet no empirical evidence that the former three variables can be coded in real time.
Several issues merit further research, such as in which types of setting complications, common knowledge details and self-handicapping strategies (1) can be examined and (2) yield the strongest effects. We already know that common knowledge details and self-handicapping strategies cannot be examined in certain situations and the search for alternative cues to deceit that occur in such settings seems urgent (
Researchers should examine whether complications, common knowledge details, and self-handicapping strategies indeed can be counted in real time. In our training of practitioners, we focus on complications and self-handicapping strategies and our experience is that they can be counted in real time. However, we have never formally examined this. In addition, we have never examined whether practitioners can also count common knowledge details in real time. Finally, it seems likely that new verbal veracity indicators other than complications, common knowledge details, and self-handicapping strategies do exist. The field is in particular need of cues that lie tellers report more frequently than truth tellers (cues to deceit). In that respect, although it does not constitute a new cue to deceit, separating self-handicapping strategies into two types, one that does include admitting lack of memory and another type that includes admitting lack of perceptual experiences, may be a first step. We hope this meta-analysis stimulates researchers to address these and other issues.
Cite this article as: Vrij, A., Palena, N., Leal, S., & Caso, L. (2021). The relationship between complications, common knowledge details and self-handicapping strategies and veracity: A meta-analysis.
Funding: The time the first author spent working on this article was funded by the Centre for Research and Evidence on Security Threats (ESRC Award: ES/N009614/1).
There is some debate about whether the frequentist and the Bayesian approaches should be employed together. On the one hand, it has been suggested that the two frameworks might be epistemologically incompatible (
We carried out a Bayesian meta-analysis for the following reasons. First, with the Bayesian approach there is no need to select either a fixed-effect or a random-effects model as it accounts for model uncertainty. Hence, the Bayesian approach can be applied when there is no certainty about heterogeneity (in contrast to a random-effects model which presumes that it is non-zero), which can be particularly the case when there is no solid background to assume the presence (vs. absence) of heterogeneity.
Second, it permits to explore the plausibility of our a priori choices concerning the application of either the fixed effect (for common knowledge details and self-handicapping strategies relative to second and total recalls) or random-effects (all remaining analyses) standard meta-analyses as outlined in the main text of this article after taking into account the observed data.
Third, in addition to the significance testing of the global effect size obtained via the standard meta-analytic approach, a Bayesian meta-analysis returns a Bayes factor, which provides the amount of evidence in support of the alternative hypothesis (the presence of an effect) against the null hypothesis (the absence of an effect). We interpreted Bayes factors cut-offs as outlined by
Fourth, a Bayesian approach provides a posterior distribution of the global effect size, whose utility is twofold: i) the probability of each value of the global effect size can be calculated and is shown graphically and ii) future research on the topic can use the resulting posterior distribution of both the effect size and of τ as an informative prior distribution. Therefore, any new experiment can build on previous evidence in a cumulative manner.
Last, with the Bayesian approach it is possible to obtain the probability of the presence of an effect (in our case, a difference between truth tellers and lie tellers in the examined variables), rather than a dichotomic answer “significant/not significant”.
We conducted a Bayesian model averaging meta-analysis (
with the left-hand side of the formula relating to posterior inclusion odds and the right-hand side of the formula relating to the prior inclusion odds. In essence, a Bayesian model averaged meta-analysis: i) can quantify the evidence in support for the presence of an effect while accounting for uncertainty relative to choosing a fixed effect or a random-effects meta-analysis, ii) can provide evidence for the presence/absence of between-studies heterogeneity, and iii) returns posterior odds for each of the four models once the observer data are taken into account. The higher a posterior odd, the more plausible a specific model.
We had 12 meta-analyses, the result of three interviews (first recall, second recall and total recall), and four dependent variables (total details, complications, common knowledge details, and self-handicapping strategies). When conducting the standard meta-analyses, we opted (a priori) for a fixed-effect model when analysing common knowledge details and self-handicapping strategies concerning “second recall” and “total recall” (four analyses), and a random-effects model for the remaining eight analyses. However, especially when research on a specific topic is still in its development, it is not always possible to rule out uncertainty concerning the correct model selection (fixed-effect vs. random-effects).
A series of Bayesian model averaging meta-analyses was conducted to explore such uncertainty and to evaluate our choices. The results showed that we chose, a priori, the model with higher posterior probabilities in five out of 12 cases. The seven cases where the analyses showed that the model we chose was less probable than its alternative (
Concerning the presence of an effect,
On the one hand, the results of this Bayesian meta-analysis reflect the conclusions obtained via the frequentist framework (
On the other hand, results concerning heterogeneity were less clear-cut. The Bayesian framework found the posterior probabilities of the examined models generally supporting the lack of between-study variance. Indeed, after observing the data, model b (τ fixed at 0) received higher posterior probability than model d (τ ≠ 0) in most cases- except for self-handicapping strategies in initial and second recall. Yet, as
Notwithstanding this, it is possible that the results obtained here are due to method invariance across experiments, as all studies come from Vrij’s lab and imply a consistent coding system and a shared research design.
In conclusion, it is essential to understand why the selected studies showed no heterogeneity, as well as to explore the external validity of the obtained results, by answering questions as: Do complications, common knowledge details and self-handicapping strategies still work in scenarios that are different from those included in this meta-analysis? Is the lack of heterogeneity due to method invariance and to the fact that all studies come from the same lab or to other reasons? And, lastly, do the conclusions obtained here apply to real-life material? We hope that future studies will shed light on the potential of the complications approach.