Hope Theory Gets a Dynamic Systems Makeover

The Problem With Hope

Hope feels like a personal quality. Some people have it. Some people don't. We say things like "she's a hopeful person" as though hope were a personality trait, like extraversion or patience. This intuition has guided decades of psychological research. But it might be wrong.

In 2022, a team of researchers led by Rachel Colla at the University of Melbourne published a paper that quietly dismantles this entire framework (Colla et al., 2022). Their argument is not that hope doesn't matter. It's that we have been measuring it the wrong way, studying it with the wrong tools, and designing interventions based on assumptions that don't hold up under scrutiny.

The paper, published in Frontiers in Psychology, is called "A New Hope for Positive Psychology: A Dynamic Systems Reconceptualization of Hope Theory." It has already accumulated 64 citations. But its real impact may take years to register, because it asks a question that most researchers have been too polite to ask: What if hope isn't a thing you have, but a process you participate in?

The Standard Model of Hope

To understand what Colla and her colleagues are arguing against, you need to understand the dominant model. It was developed by psychologist C. R. Snyder in the early 1990s, and it has been the foundation of hope research ever since.

Snyder's theory breaks hope into two components. The first is "agency," which is essentially the motivation to pursue a goal. The second is "pathways," which is the ability to figure out how to get there. If you have both, you are hopeful. If you are missing either one, you are not.

This model has been enormously influential. It has been used to predict academic performance, recovery from illness, and resilience in the face of trauma. It has generated hundreds of studies and dozens of scales. It is the basis for most hope interventions in schools and clinics.

But Colla and her team noticed something strange. When they looked at the research landscape, they found that the vast majority of studies measured hope as a static trait. They gave people questionnaires and asked them to rate statements like "I can think of many ways to get the things in life that are most important to me." Then they correlated those scores with other outcomes.

The problem, Colla argues, is that this approach treats hope as a stable internal property, like height or eye color. But hope does not behave that way. It fluctuates. It depends on context. It emerges from interactions between people and their environments.

What the Data Actually Shows

The Colla team conducted a systematic review of hope theory research, focusing specifically on studies with university students. They found that the evidence for Snyder's model is real but limited.

The correlations between hope scores and positive outcomes are consistent, but they are not particularly strong. More importantly, the researchers found that the way hope is measured in most studies cannot capture the dynamic nature of the phenomenon. A student who scores high on hope in September may score low in December, depending on what has happened in between. But almost no studies track these changes.

The authors write that the current approach "may impede the advancement of the next wave of growth in this field" (Colla et al., 2022). This is academic code for something more blunt: we have been asking the wrong questions.

The Dynamic Systems Alternative

Colla and her colleagues propose a fundamental shift. Instead of treating hope as a property of individuals, they argue that hope should be understood as a dynamic system. This means looking at how hope emerges from the interactions between a person's thoughts, emotions, behaviors, and environment over time.

This is not just a semantic change. It changes what you study and how you study it.

In a static model, you give a questionnaire once and correlate the score with something else. In a dynamic systems model, you track how hope changes moment to moment, day to day, and week to week. You look for patterns of stability and change. You ask what conditions allow hope to emerge and what conditions suppress it.

The researchers draw on systems thinking from other fields, including biology, physics, and economics. They argue that hope is not a single variable but a complex system with multiple interacting components. These components include cognitive factors (like goal setting and problem solving), emotional factors (like optimism and fear), social factors (like support from others), and environmental factors (like resources and opportunities).

How They Studied It Differently

To demonstrate their approach, Colla and her team describe a methodological framework that uses qualitative and longitudinal data. They conducted interviews with young people and analyzed their narratives about hope. Instead of asking "How hopeful are you on a scale of 1 to 7?" they asked "Tell me about a time when you felt hopeful. What was happening? Who was there? What changed?"

This may sound like a simple shift, but it reveals something the questionnaires miss. Hope is not a single feeling. It is a story that people tell themselves about their future. And that story changes depending on who is listening, what has happened recently, and what options seem available.

The researchers found that young people described hope not as a stable trait but as something that "emerges" in specific contexts. A student who felt hopeless about their academic future might feel hopeful after a conversation with a mentor. A young person who felt hopeful about their career might lose that hope after a rejection. These shifts were not random. They followed patterns that could be studied and understood.

Why This Matters for Interventions

If hope is a static trait, then interventions should focus on increasing that trait. You might teach people goal-setting skills or cognitive strategies to boost their sense of agency. This is what most hope interventions do.

But if hope is a dynamic system, then interventions should focus on changing the conditions that allow hope to emerge. This is a fundamentally different approach.

Instead of trying to make individuals more hopeful, you might change the environments they inhabit. You might design schools that create more opportunities for students to experience success. You might train mentors to have conversations that help young people see new pathways. You might create social structures that reduce the barriers to goal pursuit.

This is not about "fixing" people. It is about designing systems that support hope.

What the Research Does Not Prove

It is important to be clear about what Colla and her colleagues are not claiming.

They are not saying that Snyder's theory is wrong. They are saying it is incomplete. The static model captures some of what hope is, but it misses the dynamic, contextual, and relational aspects.

They are not saying that hope cannot be measured. They are saying that current measurement tools are insufficient for understanding how hope works in real life.

They are not saying that individual-level interventions are useless. They are saying that these interventions may be limited if they do not also address the systems in which people live.

These are open questions. The dynamic systems approach is a proposal, not a proof. It will take years of research to test whether this framework actually leads to better predictions and more effective interventions.

But the proposal is compelling because it aligns with something that most people already sense intuitively. Hope does not feel like a fixed trait. It feels like something that comes and goes, depending on what is happening around us.

The Lived Experience of Hope

The most powerful part of the Colla paper is the attention to lived experience. The researchers argue that the current approach has silenced the voices of the people they are trying to study.

When you give someone a questionnaire, you are imposing your categories on their experience. You are assuming that hope means the same thing to everyone. You are assuming that the dimensions you have identified are the ones that matter.

But when you ask someone to tell you their story, you get something different. You get the texture of their actual life. You get the moments when hope appeared and the moments when it disappeared. You get the relationships, the setbacks, the small victories.

The researchers found that young people's narratives about hope were richer and more complex than any questionnaire could capture. They described hope as something that was shared with others, not just held inside themselves. They described hope as something that required action, not just thought. They described hope as something that could be lost and regained, sometimes in the span of a single day.

This is not just a methodological point. It is a philosophical one. The way we study hope shapes what we think hope is. If we only measure it as a trait, we will only see it as a trait. If we listen to people's stories, we will see it as something more.

The Research Agenda

Colla and her team propose a specific research agenda for the future of hope studies. It includes three elements.

First, they call for more longitudinal studies that track hope over time. This means following people for months or years, not just measuring them once. It means looking for patterns of change and stability.

Second, they call for more qualitative research that captures the lived experience of hope. This means interviews, narratives, and observations. It means letting people tell their own stories.

Third, they call for interdisciplinary collaboration. This means bringing in insights from systems theory, complexity science, and other fields that study dynamic processes. It means not treating hope as an isolated variable but as part of a larger system.

This agenda is ambitious. It will require funding, time, and a willingness to challenge established methods. But the payoff could be substantial. If we understand hope as a dynamic system, we might be able to design interventions that actually work.

What This Actually Means

• ▸Hope is not a personality trait you either have or lack. It is a state that emerges from the interaction between your goals, your environment, and your social connections. If you feel hopeless, the first question to ask is not "What is wrong with me?" but "What conditions am I in?"

• ▸Current hope interventions focus on teaching individuals to set goals and find pathways. This helps, but it is not enough. The next generation of interventions should also focus on changing environments, building supportive relationships, and creating opportunities for small successes.

• ▸Measuring hope once on a questionnaire tells you very little. Hope fluctuates. If you want to understand someone's hope, you need to track it over time and in context. A single score is almost meaningless.

• ▸The stories people tell about their hope matter. If you want to help someone become more hopeful, listen to their narrative. Ask them what makes hope appear and what makes it disappear. The answers will be specific to their life, not generic.

• ▸This research does not prove that the dynamic systems approach works. It is a proposal for a better way to study hope. But the proposal is grounded in a careful critique of what has come before. It deserves to be taken seriously, because the current approach has reached its limits.