Verifiability and Symptom Endorsement in Genuine, Exaggerated, and Malingered Pain

Abstract

The current study has investigated whether pure malingering, in which reported symptoms are nonexistent, partial malingering, in which existent symptoms are exaggerated, and genuine symptoms could be differentiated by applying the verifiability approach (VA) and the Self-Report Symptom Inventory (SRSI). The logic behind the VA is that deceivers' statements contain more nonverifiable information, whereas truth tellers' accounts include more verifiable details. The SRSI taps into over-reporting by including a mix of genuine symptoms and implausible complaints (pseudosymptoms). We checked if participants (N = 167) allocated to one of three conditions (pure malingerers vs. exaggerators vs. truth tellers) can be differentiated in their pain symptom reports' (non)verifiability and symptom endorsement. Findings revealed that deceptive reports were lengthier than truthful statements. However, this difference was not produced by a discrepancy in non-verifiable details, but rather by a higher production of verifiable information among malingerers and exaggerators. Thus, contrary to previous findings, our results indicate that pain reports rich in verifiable information should raise doubt about their veracity. Further, truth tellers endorsed less symptoms of the SRSI than exaggerators, but not than pure malingerers. Pure malingerers and exaggerators did not differ in symptom endorsement. Thus, our findings revealed that when compared with truth tellers, exaggerators exhibited stronger overreporting tendencies than (pure) malingerers. However, due to inconsistent findings, further investigation of the efficacy of these methods in differentiation between exaggerated and malingered reports is required.

Discriminating deceptive from truthful statements using the verifiability approach: A meta‐analysis

“…Liars realize that their account is more likely to be believed when it is perceived to be rich in detail (G. Nahari, Vrij, Fisher, 2012), posing them with a dilemma; providing too little information will make them look deceptive, whereas providing too much detail would allow the investigative authorities to detect their deception by further investigation (G. Nahari, 2018). The VA predicts that liars solve this dilemma by (1) selectively leaving out details that investigators can verify (i.e., verifiable details; G. Nahari, Vrij, & Fisher, 2014a, 2014b; for example, "I sent an email to my boss around 3:00 this afternoon," and (2) including more details that are difficult to verify (i.e., unverifiable details; G. Nahari, Leal, et al, 2014).…”

“…The decision whether a detail is verifiable is made based on the following checklist (taken from A. . A verifiable detail includes perceptual or contextual information which can be potentially checked, defined as (1) activities that were carried out with identifiable or named persons who the interview can consult ("I went to a restaurant with my sister"), (2) activities that have been witnessed by identifiable or named persons who the interviewer can consult ("When I left for work, my neighbour was taking out the mail"),…”

“…Due to these limitations, there are less opportunities for liars to embed their lie within truthful details, a strategy that is commonly used by liars (Leins et al, 2013). Nonetheless, researchers have expanded VA to a wide range of other scenarios including insurance claims (A. C. Harvey, Vrij, Leal, et al, 2017; A. C. Harvey, Vrij, Nahari, & Ludwig, 2017; G. Nahari, Leal, et al, 2014; A. Vrij, Nahari, et al, 2016), autobiographical memories (Bogaard et al, 2020), feigning symptoms of an illness (Akca et al, 2020; I. Boskovic, Bogaard, et al, 2017; I. Boskovic, Dibbets, et al, 2019; I. Boskovic, Gallardo, et al, 2019), statements about one's occupation (L. Jupe, Vrij, et al, 2016), and future travel plans (L. M. Jupe, Leal, et al, 2017). Not all of these scenarios may be equally suitable for VA because the effectiveness of the VA “depends on the possibility for truth tellers to provide verifiable details and for liars to fool investigators” (A. Vrij & Nahari, 2019, p. 119).…”

“…Nahari, Leal, et al, 2014;A. Vrij, Nahari, et al, 2016), autobiographical memories (Bogaard et al, 2020), feigning symptoms of an illness (Akca et al, 2020;I. Boskovic, Bogaard, et al, 2017;I.…”

The Development of a Short Version of the SIMS Using Machine Learning to Detect Feigning in Forensic Assessment

“…Malingering is the dishonest and intentional production or exaggeration of physical or psychological symptoms in order to obtain external gain (Tracy & Rix, 2017). Although malingering is coded in both the ICD-11 (World Health Organization, 2019) and the DSM-5 (American Psychiatric Association, 2013), it is not a binary "present" or "absent" phenomenon: it may exist in specific domains (e.g., psychological, cognitive, and medical domains), it is often comorbid with formal disorders (Mazza et al, 2019c;Rogers & Bender, 2018), and it can be classified into several types (Akca et al, 2020;Lipman, 1962;Resnick, 1997). Due to the considerable variation produced by these nuances, it is difficult to measure the prevalence of malingering in clinical and forensic populations.…”