Veterinarians have experienced disturbing trends related to workplace-induced stress. This is partly attributed to high levels of compassion fatigue, the emotional strain of unalleviated stress from interactions with those suffering from traumatic events. This paper presents a three-stage hybrid model designed to study the dynamics of compassion fatigue in veterinarians. A discrete event simulation that represents the work environment is used to generate client and patient attributes, and the veterinarian’s utilization throughout the day. These values become inputs to a system dynamics model that simulates the veterinarian’s interpretation of the work environment to produce quantifiable emotional responses in terms of eight emotions. The emotional responses are mapped to the Professional Quality of Life Scale, which enables the calculation of compassion satisfaction, burnout, and secondary traumatic stress measures. A pilot study using the hybrid model was conducted to assess the viability of the proposed approach, which yielded statistically significant results.
For many people, work-related stress is a fact of life. Deadlines, difficult customers or coworkers, and technology breakdowns induce detrimental changes in an employee’s mental state that ultimately affects their work and personal lives. The field of veterinary medicine in particular has experienced disturbing trends related to workplace-induced stress. A recent mental health survey by the Centers for Disease Control and Prevention showed that approximately 6.8% of male and 10.9% of female veterinarians experiences serious psychological distress (Nett 2015). This means that veterinarians are up to three times more likely to be impacted by work-related stress than the general public (Reeves 2011).
This increased susceptibility to psychological distress is believed to be a result of factors that are unique to the field of veterinary medicine. However, it also coincides with overall growing concern with the professional quality of life for healthcare providers. According to Stamm (2010), people who are exposed to traumatic situations are susceptible to developing symptoms associated with burnout, depression, and posttraumatic stress. Additionally, healthcare providers are also subject to altruism, which can lead to increases in personal satisfaction through the act of helping others. Therefore, while the professional quality of life of healthcare providers, including veterinarians, can be enhanced through compassion satisfaction, it can also be diminished by compassion fatigue.
This paper describes a hybrid simulation-based approach to proactively assessing the Professional Quality of Life (ProQOL) for veterinarian general practitioners as they are placed in various workplace scenarios. The model consists of three stages. The first is the Work Environment Model, which is a discrete-event simulation that represents the working conditions of a mid-sized veterinary clinic. The second is the Emotional Model, which uses system dynamics to simulate a veterinarian’s cognition of various stimuli from the Work Environment Model and interpretation into basic primary emotions. The final component is the Professional Quality of Life (ProQOL) computational model, which translates the quantified emotions to the ProQOL Scale to produce an indication of an individual’s compassion satisfaction, burnout, and secondary traumatic stress levels (Stamm 2010). Assessing these measures will provide a greater understanding of factors and situations that should be promoted or avoided to support veterinarian mental health and wellbeing.
The three major simulation modeling paradigms are discrete event simulation, agent-based modeling, and systems dynamics, each of which has its own distinct advantages. Discrete event simulation is wellsuited for modeling systems that can be represented as a sequence of discrete events over time at a lowmedium level of abstraction. Agent-based models employ autonomous agents with individualized behavior logic that interact and communicate with one another over time, yielding emergent global system behavior. Agent-based models can handle a wide range of abstraction. Systems dynamics is a modeling approach that represents system behavior at a high level of abstraction, in terms of stocks that change states at a rate that is defined by causal relationships, which are represented by interacting feedback loops (Borshchev and Filippov 2004).
Agent-based modeling could be used to model certain aspects of a veterinary clinic system. In particular, the veterinarian, nurses, clients, and patients could be represented as computational social agents that interact and emotionally adapt to their environment over time. However, agent-based modeling does not provide a convenient means of representing the flow of discrete entities (i.e., clients and patients) through a system with capacity-constrained resources (i.e., veterinarians and nurses) and queues – these modeling constructs are typically unavailable. By contrast, discrete event simulation is a natural choice for representing resource allocation and client and patient movements through the veterinary clinic system. The veterinarian can be modeled as a resource with an embedded model of human emotion that is triggered by the attributes of the entities that it processes. This embedded model is best abstracted by the stocks and flows of systems dynamics. Based on Plutchik’s theory of emotion, the veterinarian’s mental state can be represented as a stock moving from one state (e.g., happy) to its opposite (e.g. sad) at a rate that is determined by interactions between external stimuli and internal coping mechanisms.