A complex systems approach to health workforce modelling: Simulating regional psychology workforce capacity and mental healthcare access to 2050
This study employs a system dynamics model to simulate Australia's regional psychology workforce and mental healthcare access through 2050, revealing that while business-as-usual scenarios rely on recruitment keeping pace with demand, combined pressures of recruitment ceilings and rising mental ill-health lead to significant system deterioration where smaller waiting queues paradoxically coexist with poorer overall access and increased unmet need.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Mental health care is not a simple line connecting a person in need to a therapist with an open chair. It is a living, breathing system where the number of available workers, the number of people seeking help, and the way people feel about the system itself all push and pull against one another. When demand rises, more people might train to become therapists, but if the system becomes too crowded or stressful, those same workers might burn out and leave. If people wait too long for an appointment, they might stop trying to get help altogether, making the problem invisible to the people who count the numbers. Understanding how these pieces fit together is difficult because they change over time in complex ways, often hiding the true state of the system behind misleadingly calm statistics.
A team of researchers in Australia set out to map these hidden movements using a computer simulation that acts like a time machine for the mental health system. They focused on a specific region in southern Queensland, building a detailed model that tracks how the population grows, how many people develop mental health challenges, and how many psychologists are available to treat them. Crucially, their model did not just count heads; it also included the human feelings that drive the system, such as the fatigue of overworked therapists, the frustration of patients waiting for care, and the decision to give up on seeking help. By running this simulation forward to the year 2050, they tested what would happen if the supply of new therapists hit a hard limit or if the number of people needing care suddenly surged due to chronic stressors like climate change.
The researchers began by calibrating their model against real historical data from 2013 to ensure it accurately reflected how the system had behaved in the past. Once the model was tuned, they created a "business-as-usual" scenario, which assumed that the region would continue to train and hire psychologists at a rate that simply matches the growing demand. Under these conditions, the system appeared stable. By 2050, the number of psychologists and the volume of therapy sessions would have grown enough to keep pace with the population, maintaining a roughly steady balance. However, this stability relied entirely on the assumption that there are no limits to how many new therapists can be trained or hired, a condition that might not hold true in the real world.
When the researchers introduced a constraint, capping the number of new psychologists hired each month, the results revealed a dangerous illusion. In this scenario, the number of people waiting for treatment actually dropped, which might look like a success on a standard report card. But the simulation showed that this smaller queue was not a sign of better care. Instead, it was a sign that fewer people were entering the system at all. Because the wait times grew longer and the system felt more strained, many people stopped trying to get help in the first place, and many who started treatment dropped out before finishing. The number of people living with untreated mental illness grew significantly, while the workforce itself became more exhausted and less passionate about their work. The visible line of waiting patients shrank, but the invisible burden of unmet need swelled.
The situation became even more complex when the researchers combined the hiring cap with a scenario where the number of people developing mental health issues increased steadily. In this combined stress test, the system faced a double blow: more people needed help, but fewer new therapists could join the workforce. The simulation showed the clearest deterioration of all. The population living with mental illness grew by tens of thousands, and the gap between the need for care and the ability to provide it widened dramatically. Yet, even in this crisis, the number of people on the waiting list remained surprisingly close to normal levels. This happened because the pressure of the system pushed people away before they could even reach the front of the line. The queue looked stable, but it was hiding a massive failure in access.
These findings suggest that relying on simple counts of waiting lists or the number of therapists can give a false sense of security. A short line does not necessarily mean that everyone who needs help is getting it; it might simply mean that the system has become so difficult to navigate that people have stopped trying. The study indicates that to truly understand the health of a mental care system, planners must look beyond the numbers of appointments and workers. They need to track how many people are giving up, how many are dropping out of treatment, and how the morale of the workforce is changing. By simulating these hidden dynamics, the researchers showed that a system can appear calm on the surface while the foundation beneath it is quietly crumbling, offering a warning that true stability requires more than just matching supply to demand.
Drowning in papers in your field?
Get daily digests of the most novel papers matching your research keywords — with technical summaries, in your language.