Published April 1, 2021 | Version v1
Video/Audio Open

Integrity test for the assessment of whiplash-associated disorders

  • 1. Instituto de Biomecánica de Valencia
  • 2. Department of General Psychology, University of Padua
  • 3. MAZ, Mutua Colaboradora con la Seguridad Social nº 11
  • 4. Department of Psychology, University of Padua

Description

Whiplash-related injuries are controversial, partly due to suspicion of symptom faking, associated to the existence of potential secondary gain or compensation, which is reported to have negative effects on recovery of claimants. Therefore, it is useful to provide clinicians with tools to assess the risk of feigned symptomatology, in contexts where the effect on compensation is concerning.

We present a study to determine if such a tool can be developed, combining measurements derived from biomechanical evaluation, behavioural tests and evidence from self-reports, as indicators of malingered pain related disability.

The study sample consisted of 105 participants, including patients who reported neck pain, classified by two independent examiners as “true” or “biased” responders, and recovered patients who were asked to “fake” the symptoms of former painful episodes. Patients passed the autobiographical Implicit Association Test (aIAT), an self-report questionnaire based on rare and impossible symptoms, and a physical assessment of neck motion patterns.

The answers to questions related to “possible” and “rare” symptoms, and a combination of maximum angular velocity, harmonicity and variability of neck motion were chosen to fit a linear discriminant model. The model had limited sensitivity (78%), and a higher specificity (85%).

The fitted model is conservative, i.e. there is low risk of “blaming” patients for exaggerating, which is the weak point of previous approaches. Sensitivity may be improved by increasing the sample of participants.

Files

BritSpine2021-0091_HeliosDeRosario.mp4

Files (10.0 MB)

Name Size Download all
md5:484a4468bdf1cb6ee5cedf446468c9bf
10.0 MB Preview Download

Additional details

Funding

Back-UP – Personalised Prognostic Models to Improve Well-being and Return to Work After Neck and Low Back Pain 777090
European Commission

References

  • Monaro, M., Toncini, A., Ferracuti, S., Tessari, G., Vaccaro, M. G., De Fazio, P., Pigato, G., Meneghel, T., Scarpazza, C., & Sartori, G. (2018). The Detection of Malingering: A New Tool to Identify Made-Up Depression. Frontiers in Psychiatry, 9. https://doi.org/10.3389/fpsyt.2018.00249
  • Sartori, G., Agosta, S., Zogmaister, C., Ferrara, S. D., & Castiello, U. (2008). How to accurately detect autobiographical events. Psychological Science, 19(8), 772–780. https://doi.org/10.1111/j.1467-9280.2008.02156.x
  • Sartori, G., Agosta, S., Zogmaister, C., Ferrara, S. D., & Castiello, U. (2008). How to accurately detect autobiographical events. Psychological Science, 19(8), 772–780. https://doi.org/10.1111/j.1467-9280.2008.02156.x