The first platform built to predict mental health crises — before they happen

Dr. Hans Rocha IJzerman left the Netherlands at 18 to play basketball in America. He ended up in rural Pennsylvania, at a small Benedictine college in the hills — Saint Vincent, where Fred Rogers, the beloved American television host known as Mister Rogers, had studied theology and first developed the convictions that would define his life’s work. The Benedictine monks who shaped the college had followed the same Rule for fifteen centuries: welcome every stranger, attend to every individual, treat no person as interchangeable with any other. It was something you could actually feel — in the way strangers were welcomed, in the weight given to listening, in the assumption that every person in the room had something irreplaceable to offer.

For a young Dutch kid far from home, navigating a culture not his own, something about that community lodged deep. Not the theology — but the underlying conviction that every human being is specific, irreducible, and not interchangeable with any other.

It's a conviction his own life has never let him forget. His family is Brazilian, Dutch, and French all at once — his children grow up navigating languages and worlds that don't map cleanly onto each other. The idea that a single instrument, designed for a single 'average' human, could capture what any one of them is going through has always felt, to him, self-evidently absurd.

For two decades, that conviction sat uneasily alongside the dominant logic of his own field.

Early in his career, Hans immersed himself in the study of honor culture — fascinated by how profoundly context shapes behavior and self-understanding. The lesson the data kept teaching was the same one he’d felt instinctively: who a person is changes what everything means. The same action, the same word, the same experience — interpreted through a different life, a different culture, a different self — is not the same thing.

But mainstream psychology, including his own field, kept reaching for the average. Measure large groups. Find the central tendency. Build tools around that center. It was practical. It was scalable. And for a long time, Hans worked within that logic too — because it was the field’s logic, and because the tools to do otherwise didn’t yet exist. What changed, slowly and then undeniably, was the evidence.

The moment the research made this undeniable came through an unexpected subject: romantic love. Hans and his collaborators set out to test whether the standard instruments used to measure relationship quality actually measured the same thing across different people. The answer was no — clearly, empirically, reproducibly no. Of course people experience love differently depending on who they are. And if that was true for love, the implications for depression, anxiety, loneliness, and every other psychological construct that clinical tools relied on were significant. The average wasn't just imprecise. It was systematically missing something.

The clinical cost of that gap was something Hans saw through his partner, Daniela, a psychologist with 15 years of practice. She encountered it constantly — the difficulty of interpreting scale scores that didn't mean what they appeared to mean, the real risk of sending someone down the wrong treatment pathway because the instrument hadn't been built to understand them as an individual. Paul Meehl had spent decades arguing that clinicians needed better actuarial tools to translate assessment data into good decisions. Decades later, the tools still hadn't caught up.

And then there was the experience — shared, in some form, by most families — of trying to find the right mental health care for someone you love. Not care in the abstract. The right care, for this person, now. Even with clinical training and with system knowledge. The mismatch between individual need and available support is not a minor inefficiency. It causes harm that compounds.

A scientist who had spent years working within the mainstream — and slowly, reluctantly, became convinced it was asking the wrong question. A clinician who saw daily what happened when tools ignored those differences. A family that had felt the cost firsthand. That combination is what became Entrelacs.

Entrelacs isn't built for the average patient — because that patient doesn't exist. It's built for the actual, specific, irreducibly individual human being who needs care.