Daisee White Paper

Getting past "compensation effects": The importance of monitoring and managing claimant distress

Dr Claire Ashton-James, PhD

Background

Injury compensation systems vary across countries and jurisdictions, but they generally share a common goal: restoring injury victims to health and returning them to work. A universal challenge faced by compensation systems is that the recovery trajectories of injured persons who make a claim are generally worse than those of injured persons who do not make a claim (or whose injuries fall outside compensation schemes)(1-3).

Compensable injuries, especially transport injuries, typically involve more severe physical and emotional trauma than injuries for which people do not make a claim. However, even accounting for the severity of injuries sustained, those who seek or receive compensation are still more likely to have worse outcomes. Compensation claimants experience:

  • more severe and persistent pain and disability
  • poorer mental health and
  • delayed return to work(2, 4).

What accounts for "compensation effects" on recovery?

Several factors contribute to the relationship between “exposure” to the compensation system and poorer claimant outcomes. In the past, it was thought that poor recovery was explained by overclaiming and exaggeration of symptoms (malingering). More recent research, however, indicates that the claimants’ experience of the claims process is a critical predictor of their likelihood of recovery and return to work(4-10). When the claims experience is experienced as positive and fair, claimants have better health and return to work outcomes. In a study of people who had been involved in a transport injury compensation process, those who perceived the claims process as being fair were 2.8 times more likely than claimants who perceived the process as unfair to report good health 12-24 months after injury(11). Along similar lines, a survey of 10,946 injured workers involved in ten Australian workers’ compensation schemes found that having a positive claims experience was strongly associated with having returned to work after accounting for injury, worker, claim and employer factors: 84.3% of those reporting a positive claims experience had successfully returned to work compared with 65% of workers reporting a negative or neutral claims experience(12).

On the other hand, when claimant interactions with the compensation system are experienced as adversarial, difficult to understand, or unfair, claimants can experience significant distress. Claims-related distress encompasses a range of unpleasant negative emotional states including confusion, agitation, anger, fatigue, hopelessness or helplessness, fear, anxiety, feelings of depression, and loss of motivation(13).

Claimant distress is of course associated with claimant dissatisfaction, complaints, and likelihood of engaging a lawyer. Beyond these costs to the insurer, claimant distress slows and impairs recovery from injury and delays return to work. Research conducted in NSW found that psychological distress in those with a musculoskeletal injury was associated with significantly longer settlement times (an additional 17 weeks) and considerably higher costs (an additional $41, 575.00 or 4.3 times more expensive)(14).

Claimant distress may undermine recovery from injury in several ways:

  • The physiological effects of “high arousal” negative emotions include the release of adrenaline and cortisol, hormones which prepare us for “fight or flight” but at the same time suppress our immune response and disrupt healing processes(15)
  • High-arousal negative emotions (acute stress responses) can cause sensory changes and sympathetic nervous system dysfunction which increase sensitivity to pain(16)
  • Stress and anger induce muscle tension at the site of injury, increasing pain and limiting movement(17, 18)
  • Stress and anger disrupt “endogenous opioid” analgesic function, meaning that the body’s “natural pain killers” do not work as effectively(19)
  • The experience of distress is disruptive of sleep, and sleep disruption exacerbates pain and reduces functioning(20)
  • Emotional distress (particularly anxiety and anger) increases pain sensitivity and delays wound healing(21, 22)
  • When people are highly distressed, they can become socially withdrawn – reducing their access to social support. Social support can be informational, instrumental, or emotional and may involve helping claimants to navigate the compensation system, facilitating communication with the insurer and healthcare providers, or providing reassurance, hope, and care. Social isolation is associated with significantly worse long-term pain and disability following injury(23)
  • Emotional distress – particularly anger provoked by perceived injustice – is associated with higher levels of conflict in interactions with case managers, higher levels of dissatisfaction with compensation awards, lower expectations of recovery, higher incidence of litigation, and delayed return to work(9).

The prevalence and predictors of claim-related distress

Sustaining and recovering from a traumatic injury is psychologically distressing for most people, but it can be particularly distressing for those claiming compensation(7). A 2020 survey of 3755 injured workers in the Australian compensation system found that 41.5% of claimants reported moderate to severe symptoms of psychological distress(24). (Previous reports of the prevalence of compensation-related stress have ranged from 23-54%, depending on the compensation system)(5, 11, 12).

The prevalence of psychological distress among people involved in motor vehicle accidents may be even higher. It is estimated that one in two persons suffer elevated levels of psychological distress (e.g. anxiety, depression, post-traumatic stress symptoms) soon after a motor vehicle crash, and many of these continue to experience elevated distress one year later(13).

Certain claimant characteristics (“vulnerabilities”) may predispose them to experience stress during the claims process.

Pre-injury characteristics

Persons who have experienced a traumatic injury requiring extended hospitalisation or time spent in intensive care, the presence of post-traumatic stress symptoms, unemployment at the time of injury, history of psychiatric disorder or other mental health concerns, exposure to traumatic events prior to injury, and older age place individuals at higher risk of experiencing distress during the claims process (compensation-related stress), and in turn poorer recovery, higher health care costs, and a higher likelihood of developing chronic pain(8, 25, 26).

Post-injury characteristics

Pain severity, dependence on others for self-care, sleep disturbances, attributions of blame for the injury, time spent in ICU, depression, post-traumatic stress symptoms, and negative expectations of recovery are associated with heightened levels of emotional distress, and in turn, higher levels of disability(8, 25).

Importantly, while each of these claimant characteristics are predictive of claimants’ experience of stress and/or perceived injustice during the claims process, it is the experience of distress, rather than the presence of these characteristics, that is the most important predictor of claimants’ health outcomes(8, 9). In other words, certain claimant characteristics are only predictive of poor outcomes to the extent that these claimants experience high levels of distress in the claims process (see Figure 1).

Figure 1: Understanding “compensation effects”: The role of claimant distress

Sources of claim-related distress

The commonest sources of claim-related distress include:

  • Confusion or lack of clarity surrounding compensation processes
  • Difficulty filling in forms; significant paperwork
  • Feelings of stigmatization
  • Delayed reimbursement of medical expenses
  • Delays in communication or limited communication
  • Perceived lack of responsiveness to claimant concerns
  • Number of medical assessments
  • Perceived unfairness of compensation received
  • Perceived unfairness of medical treatments offered
  • Perceived lack of trust; having to prove and injury or disability
  • Perceived respect with which claimants are treated by the case managers
  • Claim duration and inability to move on with life during the claims process(5, 6, 11, 27-29).

Notably, communication with case managers plays a critical role in claimant’s experience and perceptions of fairness(6, 7). When claimants perceive that the process is “open and honest”, that they are treated with respect and dignity, and that there is good communication between the various people and organisations involved in the claim, they are more likely to feel like the system is working to protect their best interests, and that the system is helping, rather than hindering, their recovery(12).

Consistent with this, when a NSW-based insurer experimentally instituted a new claims settlement approach which involved a consistent non-adversarial communication protocol with a focus on prompt approval of treatments and proactive resolution of disputes, the system observed reduced depression and improved return to work compared to usual claims handling(30).

Getting past “compensation effects”

We have identified several claimant characteristics and compensation processes that predict a person’s likelihood of experiencing claim-related emotional distress. If claimants who are experiencing, or are at risk of experiencing distress, are accurately identified in a timely manner, their claims experience can be managed more effectively, and the impacts of claimant distress on recovery and return to work can be mitigated.

The benefits of identifying and managing claimant distress

Two key studies demonstrate the impact of timely and effective distress management on claimants’ health outcomes. Sterling and colleagues (Qld) identified claimants with high distress less than 4 weeks after motor vehicle accidents and randomly allocated a group to a stress management training program. Compared to claimants with high distress who received usual care alone, those who received the stress management intervention reported significant improvements in stress over 6 weeks(34). Importantly, claimants’ levels of stress reported after the trial period predicted their pain-related disability, pain severity, and quality of life after 12 months. Changes in claimants stress symptoms as a result of the stress management intervention accounted for a substantial portion (50%) of variance in their disability 12 months after their claim was made(35).

Nicholas and colleagues (NSW) found that claimants with high levels of distress who were referred to a psychologist to help them cope with distress within the first few weeks of their claim returned to work sooner, had lower healthcare costs, and were less likely to develop a chronic pain condition requiring ongoing treatment. Indeed, two years after making a claim, the average number of lost workdays experienced by high distress claimants who received early psychological support was less than half of those who received usual care. In addition, their claims costs were 30% lower, as was the growth trajectory of their costs over 11 months (29).

The benefits of identifying and managing claimant distress has only recently been recognized, primarily in response to the two ground-breaking studies described above. Recognition for the need to manage claimant distress is spreading among compensation schemes and we are aware of several further trials of early distress management interventions which are currently underway. Importantly, however, current approaches to the identification and management of claimant distress present several implementation challenges. We explore each of these challenges below, and describe how AI-powered systems offer reliable and cost-effective solutions. Box 1 describes additional benefits for the job satisfaction, wellbeing, and retention of claims agents.

Box 1: The hidden benefits of managing claimant distress for the insurer

The benefits of early identification and management of claimant distress extend beyond claimant recovery and return to work. More distressed claimants, including those with post-traumatic stress symptoms or higher levels of perceived injustice, pain and anxiety may also be more challenging for case managers to satisfy and engage. For instance, claimant anger related to perceived unfairness is associated with a higher likelihood of lawyer involvement(11) and less satisfaction with the injury compensation system, regardless of access to benefits and services(36). Other forms of distress, including depression and anxiety, have also been associated with lower client satisfaction with care (37, 38).

Unmanaged claimant distress may also increase the administrative load and emotional labour of claims personnel - contributing to case manager turnover(39, 40). Prolonged exposure to others’ distress, and a lack of confidence responding to others’ distress, is associated with emotional exhaustion(41). In turn, emotional exhaustion reduces one’s capacity for empathy, further challenging the ability of claims personnel to communicate effectively (i.e., listen, take another’s perspective) and respond to claimant concerns(42).

Hence, the early identification and management of claimants who are experiencing or are at high risk of experiencing compensation-related stress contributes not only to the health outcomes of claimants but also to claimant satisfaction with the compensation process, and relatedly, to the satisfaction and retention of claims personnel.

Identifying and managing claimant distress: Challenges and opportunities

Identification challenges

Claimant distress is typically identified using surveys administered by the compensation scheme within the first three weeks of a claim being made. Survey measures of distress typically ask claimants to report how anxious, depressed, irritable, or prone to getting angry they have been feeling in the past week, and/or how often they have experienced symptoms of distress (e.g., difficulty concentrating, difficulty falling asleep or staying sleep, feeling overly alert, jumpy, or easily startled).

Certain survey measures have demonstrated reliability (i.e. they are accurate in their “diagnosis”) and predictive validity (i.e. high scores are consistently associated with high levels of claimant distress and poorer recovery from injury)(43-46). However, the survey method of identifying claimant distress has several limitations.

  1. Survey measures rely on self-reports being accurate. Many claimants express a reluctance to disclose distress, or indicators of distress for fear that their suffering will be discounted (perceived as exaggerated).
  2. Surveys add to the administrative burden of both claimants and case managers. Indeed, the effectiveness of survey measures depends on them being completed by claimants, reviewed by case managers, and used as a mechanism for flagging claimants with high levels of distress or high risk of becoming distressed during the claims process.
  3. Unless they are endlessly repeated, surveys measure distress at only one time-point during the claims process – typically in the early stages before claimants have had significant “exposure” to the system. Hence, survey measures do not capture distress as it emerges, in real time.
It may be most effective to monitor and identify distress as it emerges during the claims process

One approach to monitoring claimant distress in real time would be to train case managers (or agents) to monitor claimant distress during their interactions. However, the ability to accurately perceive the emotions of others is highly variable across individuals and situations(47-49). Certain case managers may have higher emotional intelligence than others, and may find the task relatively easy, while others may find it more difficult(50). Moreover, our ability to perceive the emotions of others accurately varies depending on our own mood, demands on our attention, time constraints, and our empathy for others – which varies depending on who we are interacting with(49, 51, 52). Hence, relying upon the agents who are interacting with claimants to detect distress may be prone to error.

AI-driven opportunities for the rapid and accurate identification of claimant distress

Advanced conversational intelligence platforms offer a more reliable and cost-effective solution to the need to predict and monitor claimant distress. Recent technological advances in speech analytics combines machine learning and natural language processing to detect changes in claimant attitudes and emotions from moment to moment, across the duration of a call. These advanced AI-powered systems use subtleties in spoken language (e.g., changes in vocal attributes, volume, speech rate, pauses, turn taking and cross-talk) to identify patterns in the “sentiment” expressed by conversational partners. Unlike previous generations of speech analytics, these new AI-powered systems can cover 100% of calls, can transcribe with over 95% accuracy, and can identify signals of claimant distress within minutes after call (rather than days or weeks).

These technologies represent an opportunity to monitor all claimant conversations for signs of distress - not just initial conversations, but every conversation across the lifecycle of the claim. Furthermore, machine learning is capable of tracking claimant distress moment-to-moment, and is able to pin-point the time, and context in which claimant distress emerges during the call. As conversational data accumulates, these AI-powered systems continually improve their ability to surface insights into the “triggers” of claimant distress in the claims process. While we understand processes that generally trigger claimant distress, this technology can detect system-specific and organization-specific triggers of claimant distress. These insights may help claims to evaluate the real impact of claims processes on claims outcomes.

Management challenges

When claimant distress is identified in a timely and accurate manner, there is great potential for it to be managed and successfully resolved. As described above, there is strong evidence that when claimants in distress are identified early and triaged for targeted distress management programs, they have superior outcomes compared to high-distress claimants who do not receive additional support. The implementation of distress management interventions is challenging, however. A clear barrier to the effectiveness of early distress management programs is claimant reluctance to be involved (lack of engagement)(33). There is a risk that when claims agents recommend psychological treatments for distressed claimants, claimants may interpret this as a sign that the insurer does not believe their pain, or thinks it is “all in their head”. In such cases, suggesting early distress management interventions can be counterproductive, creating more conflict.

Claimants may be more likely to engage with distress management interventions if they are delivered by allied health professionals (i.e. physiotherapists) rather than psychologists (30). However, psychologically-informed care requires additional specialist training, limiting the availability of these resources. Furthermore, the quality and fidelity of distress management interventions delivered by non-psychologist allied health providers requires quality control and monitoring.

Finally, these approaches to claimant distress management are somewhat reactive. In consideration that a significant source of claimant distress is the claims process itself, it may be that claimant distress is most efficiently and effectively managed directly by the insurer, “at the source”.

AI-driven opportunities to optimise the management of claimant distress

Distress management “at the source” could take several forms, all of which can be implemented with the help of AI technologies.

Claims agents can use empathic communication and conflict resolution skills to de-escalate claimant distress in real time – as it arises. Often it is not the experience of anger, irritation, or fear that causes distress, but rather others’ response (or lack of response) to our emotions. AI software can measure empathy and active listening and contrast the outcomes where this language is used versus interactions where it is not used. These “emotion-handling skills” are also imperative for building and maintaining trust and claimant satisfaction. Claimants who are distressed and have lost trust in their agent are more likely to seek legal representation. Hence, it is in the interests of both the insurer and the claimant that claims agents demonstrate excellent empathic communication and conflict resolution skills.

Emotion-handling skills can be learned. However, “one-shot” approaches to communication training are notoriously ineffective in changing behaviour in the long term. Communication skills develop over time, in response to consistent, specific, accurate, timely. This means that feedback should be

  • Objective; derived from a reliable evaluation framework
  • Self-relevant; based on agent’s actual communication behaviour, as demonstrated in conversations with actual claimants
  • Accessible on demand; claims agents should be able to regularly monitor their performance
  • Available in near real-time, immediately or very soon after the agent ends a difficult conversation with a claimant.

A key function of AI-driven conversational intelligence is continual monitoring, evaluation, and reporting (feedback). Every recorded conversation can be transcribed and analysed, providing claims agents with a “read out” of caller sentiment and agent empathy. In the same way that these technologies can be configured to identify changes in claimant sentiment and signs of claimant distress, they can also be used to identify signs of agent empathy and demonstrate the impact of agent empathy on claimant distress (how effective were agents’ efforts to manage claimant distress?). This information provides agents with specific and actionable feedback and insight into their communication behaviour overall, and the impact of their communication on claimant sentiment specifically. Specific information about the impact of communication behaviour on claimant sentiment and distress offers agents an opportunity to learn “what works” and “what doesn’t work”. This consistent feedback optimises our ability to learn from experience, increasing “speed to competency”.

An added benefit of automated conversational intelligence systems is that feedback is objective and unbiased (does not reflect the views of a colleague), and individual conversation outcomes can be kept confidential (providing only aggregated data for review by managers). If feedback on individual conversations is confidential, the claims agent can learn without fear of reputational harm. The experience of shame significantly undermines individuals’ ability to learn and adapt their behaviour.

Aggregated data on claims agent’s ability to manage claimant distress may be used to identify those agents whose emotion handling skills are highly effective, and those who may benefit from additional supervision and training. In cases where claims agents fall below a certain threshold score for empathic communication, or in cases where there is evidence that claimant distress is not resolved by a claims agent within a given interaction, it may be necessary to triage distress or unsatisfied claimants into the care of claims agents who have demonstrated exceptional skills in the management of claimant distress.

Finally, AI-driven speech analytics can help to uncover systemic issues that may be the cause of claimant distress. For example, when websites or other technology are not functioning as intended, information about processes is not clear or readily available, or when there are unexpected delays in claims processing, AI systems can be used to unearth systemic issues that may be going under the radar.

Summary and conclusion

Claimant distress is predictive of poorer health outcomes and return to work. The claims process, and interactions with claims agents, can contribute to claimant distress. When claimant distress is identified early and managed effectively, claimant outcomes are significantly improved. The challenge for insurers is that current systems for identifying and managing claimant distress are sub-optimal. AI-driven conversational analytics technology offers solutions to many of these challenges, including

  • continual monitoring and identification of claimant distress in real time
  • continual monitoring and feedback on claims agent communication behaviour (i.e., empathy) and the impact of their communication behaviour on claimant distress (i.e., emotion-handling skills).
  • identification of high performing claims agents who may be deployed as “specialists” for high distress claimants who may be difficult to manage.

If embraced, these technological advances have the potential to significantly reduce the incidence of litigation, chronic pain, and disability resulting from compensable workplace and motor vehicle accident injuries.

References


  1. Harris I, Mulford J, Solomon M, van Gelder JM, Young J. Association between compensation status and outcome after surgery: a meta-analysis. Jama. 2005;293(13):1644-52.
  2. Gabbe BJ, Simpson PM, Harrison JE, Lyons RA, Ameratunga S, Ponsford J, et al. Return to work and functional outcomes after major trauma. Annals of surgery. 2016;263(4):623-32.
  3. Grant G, Studdert DM. Poisoned chalice-A critical analysis of the evidence linking personal injury compensation processes with adverse health outcomes. Melb UL Rev. 2009;33:865.
  4. O'donnell ML, Creamer MC, McFarlane AC, Silove D, Bryant RA. Does access to compensation have an impact on recovery outcomes after injury? Medical Journal of Australia. 2010;192(6):328-33.
  5. Grant GM, O’Donnell ML, Spittal MJ, Creamer M, Studdert DM. Relationship between stressfulness of claiming for injury compensation and long-term recovery: a prospective cohort study. JAMA psychiatry. 2014;71(4):446-53.
  6. Kilgour E, Kosny A, McKenzie D, Collie A. Interactions between injured workers and insurers in workers’ compensation systems: a systematic review of qualitative research literature. Journal of occupational rehabilitation. 2015;25(1):160-81.
  7. Murgatroyd DF, Cameron ID, Harris IA. Understanding the effect of compensation on recovery from severe motor vehicle crash injuries: a qualitative study. Injury prevention. 2011;17(4):222-7.
  8. Meaghan L, Grant G, Alkemade N, Spittal M, Creamer M, Silove D, et al. Compensation seeking and disability after injury: the role of compensation-related stress and mental health. The Journal of clinical psychiatry. 2015;76(8):0-.
  9. Giummarra MJ, Cameron PA, Ponsford J, Ioannou L, Gibson SJ, Jennings PA, et al. Return to work after traumatic injury: increased work-related disability in injured persons receiving financial compensation is mediated by perceived injustice. Journal of occupational rehabilitation. 2017;27(2):173-85.
  10. Harris IA, Young JM, Jalaludin BB, Solomon MJ. The effect of compensation on general health in patients sustaining fractures in motor vehicle trauma. Journal of orthopaedic trauma. 2008;22(4):216-20.
  11. Elbers NA, Collie A, Hogg-Johnson S, Lippel K, Lockwood K, Cameron ID. Differences in perceived fairness and health outcomes in two injury compensation systems: a comparative study. BMC Public Health. 2016;16(1):1-13.
  12. Collie A, Sheehan L, Lane TJ, Gray S, Grant G. Injured worker experiences of insurance claim processes and return to work: a national, cross-sectional study. BMC Public Health. 2019;19(1):1-12.
  13. Craig A, Tran Y, Guest R, Gopinath B, Jagnoor J, Bryant RA, et al. Psychological impact of injuries sustained in motor vehicle crashes: systematic review and meta-analysis. BMJ open. 2016;6(9):e011993.
  14. Guest R, Tran Y, Gopinath B, Cameron ID, Craig A. Psychological distress following a motor vehicle crash: a systematic review of preventative interventions. Injury. 2016;47(11):2415-23.
  15. Gouin J-P, Kiecolt-Glaser JK. The impact of psychological stress on wound healing: methods and mechanisms. Immunology and Allergy Clinics. 2011;31(1):81-93.
  16. Carter LE, McNeil DW, Vowles KE, Sorrell JT, Turk CL, Ries BJ, et al. Effects of emotion on pain reports, tolerance and physiology. Pain Research and Management. 2002;7(1):21-30.
  17. Burns JW, Quartana PJ, Gilliam W, Matsuura J, Nappi C, Wolfe B. Suppression of anger and subsequent pain intensity and behavior among chronic low back pain patients: The role of symptom-specific physiological reactivity. Journal of behavioral medicine. 2012;35(1):103-14.
  18. Burns JW, Quartana PJ, Bruehl S. Anger inhibition and pain: conceptualizations, evidence and new directions. Journal of behavioral medicine. 2008;31(3):259-79.
  19. Bruehl S, Burns JW, Chung OY, Quartana P. Anger management style and emotional reactivity to noxious stimuli among chronic pain patients and healthy controls: The role of endogenous opioids. Health Psychology. 2008;27(2):204.
  20. Sivertsen B, Lallukka T, Petrie KJ, Steingrímsdóttir ÓA, Stubhaug A, Nielsen CS. Sleep and pain sensitivity in adults. Pain. 2015;156(8):1433-9.
  21. Bement MH, Weyer A, Keller M, Harkins AL, Hunter SK. Anxiety and stress can predict pain perception following a cognitive stress. Physiology & behavior. 2010;101(1):87-92.
  22. Woo K. Wound-related pain: anxiety, stress and wound healing. Wounds UK. 2010;6(4):92-8.
  23. Karayannis NV, Baumann I, Sturgeon JA, Melloh M, Mackey SC. The impact of social isolation on pain interference: a longitudinal study. Annals of Behavioral Medicine. 2019;53(1):65-74.
  24. Collie A, Sheehan L, Lane TJ, Iles R. Psychological distress in workers’ compensation claimants: prevalence, predictors and mental health service use. Journal of occupational rehabilitation. 2020;30(2):194-202.
  25. Spittal MJ, Grant G, O’Donnell M, McFarlane AC, Studdert DM. Development of prediction models of stress and long-term disability among claimants to injury compensation systems: a cohort study. BMJ open. 2018;8(4):e020803.
  26. Ioannou LJ, Cameron PA, Gibson SJ, Gabbe BJ, Ponsford J, Jennings PA, et al. Traumatic injury and perceived injustice: Fault attributions matter in a “no-fault” compensation state. PloS one. 2017;12(6):e0178894.
  27. Murgatroyd DF, Casey PP, Cameron ID, Harris IA. The effect of financial compensation on health outcomes following musculoskeletal injury: systematic review. PloS one. 2015;10(2):e0117597.
  28. Lippel K. Workers describe the effect of the workers' compensation process on their health: a Quebec study. International journal of law and psychiatry. 2007;30(4-5):427-43.
  29. MacEachen E, Kosny A, Ferrier S, Chambers L. The “toxic dose” of system problems: why some injured workers don’t return to work as expected. Journal of occupational rehabilitation. 2010;20(3):349-66.
  30. Schaafsma F, De Wolf A, Kayaian A, Cameron ID. Changing insurance company claims handling processes improves some outcomes for people injured in road traffic crashes. BMC Public Health. 2012;12(1):1-9.
  31. O'donnell ML, Lau W, Tipping S, Holmes AC, Ellen S, Judson R, et al. Stepped early psychological intervention for posttraumatic stress disorder, other anxiety disorders, and depression following serious injury. Journal of Traumatic Stress. 2012;25(2):125-33.
  32. Kelly JM, Bunzli S, Ritchie C, Kenardy J, Smeets R, Sterling M. Physiotherapist-delivered Stress Inoculation Training for acute whiplash-associated disorders: A qualitative study of perceptions and experiences. Musculoskeletal Science and Practice. 2018;38:30-6.
  33. Nicholas M, Costa D, Linton SJ, Main C, Shaw W, Pearce G, et al. Implementation of early intervention protocol in Australia for ‘High Risk’injured workers is associated with fewer lost work days over 2 years than usual (stepped) care. Journal of occupational rehabilitation. 2020;30(1):93-104.
  34. Sterling M, Smeets R, Keijzers G, Warren J, Kenardy J. Physiotherapist-delivered stress inoculation training integrated with exercise versus physiotherapy exercise alone for acute whiplash-associated disorder (StressModex): a randomised controlled trial of a combined psychological/physical intervention. British journal of sports medicine. 2019;53(19):1240-7.
  35. Elphinston RA, Sterling M, Kenardy J, Smeets R, Armfield NR. The mechanisms of effect of a physiotherapist-delivered integrated psychological and exercise intervention for acute whiplash-associated disorders: secondary mediation analysis of a randomized controlled trial. Pain reports. 2020;5(5).
  36. Thompson J, Berk M, O’Donnell M, Stafford L, Nordfjaern T. The association between attributions of responsibility for motor vehicle accidents and patient satisfaction: a study within a no-fault injury compensation system. Clinical rehabilitation. 2015;29(5):500-8.
  37. Bui Q-UT, Ostir GV, Kuo Y-F, Freeman J, Goodwin JS. Relationship of depression to patient satisfaction: findings from the barriers to breast cancer study. Breast cancer research and treatment. 2005;89(1):23-8.
  38. Kavalnienė R, Deksnyte A, Kasiulevičius V, Šapoka V, Aranauskas R, Aranauskas L. Patient satisfaction with primary healthcare services: are there any links with patients’ symptoms of anxiety and depression? BMC family practice. 2018;19(1):1-9.
  39. Goodwin RE, Groth M, Frenkel SJ. Relationships between emotional labor, job performance, and turnover. Journal of Vocational Behavior. 2011;79(2):538-48.
  40. Back C-Y, Hyun D-S, Jeung D-Y, Chang S-J. Mediating effects of burnout in the association between emotional labor and turnover intention in Korean clinical nurses. Safety and health at work. 2020;11(1):88-96.
  41. Ashton-James CE, McNeilage AG, Avery NS, Robson LH, Costa D. Prevalence and predictors of burnout symptoms in multidisciplinary pain clinics: a mixed-methods study. Pain. 2021;162(2):503-13.
  42. Gleichgerrcht E, Decety J. Empathy in clinical practice: how individual dispositions, gender, and experience moderate empathic concern, burnout, and emotional distress in physicians. PloS one. 2013;8(4):e61526.
  43. Scott W, Trost Z, Milioto M, Sullivan MJ. Further validation of a measure of injury-related injustice perceptions to identify risk for occupational disability: a prospective study of individuals with whiplash injury. Journal of occupational rehabilitation. 2013;23(4):557-65.
  44. Dunstan DA, Covic T, Tyson GA, Lennie IG. Does the Örebro Musculoskeletal Pain Questionnaire predict outcomes following a work-related compensable injury? International Journal of Rehabilitation Research. 2005;28(4):369-70.
  45. Ritchie C, Hendrikz J, Kenardy J, Sterling M. Derivation of a clinical prediction rule to identify both chronic moderate/severe disability and full recovery following whiplash injury. PAIN®. 2013;154(10):2198-206.
  46. Sullivan MJ, Adams H, Horan S, Maher D, Boland D, Gross R. The role of perceived injustice in the experience of chronic pain and disability: scale development and validation. Journal of occupational rehabilitation. 2008;18(3):249-61.
  47. Lee T-H, Choi J-S, Cho YS. Context modulation of facial emotion perception differed by individual difference. PLOS one. 2012;7(3):e32987.
  48. Hamann S, Canli T. Individual differences in emotion processing. Current opinion in neurobiology. 2004;14(2):233-8.
  49. Trilla I, Weigand A, Dziobek I. Affective states influence emotion perception: Evidence for emotional egocentricity. Psychological research. 2021;85(3):1005-15.
  50. Elfenbein HA, MacCann C. A closer look at ability emotional intelligence (EI): What are its component parts, and how do they relate to each other? Social and Personality Psychology Compass. 2017;11(7):e12324.
  51. Decety J, Echols S, Correll J. The blame game: the effect of responsibility and social stigma on empathy for pain. Journal of cognitive neuroscience. 2010;22(5):985-97.
  52. Kommattam P, Jonas KJ, Fischer AH. Perceived to feel less: Intensity bias in interethnic emotion perception. Journal of Experimental Social Psychology. 2019;84:103809.