The initial goal of precision psychiatry isn't complex machine learning or perfect biomarkers. It's about systematically collecting basic, meaningful data—like cognitive function—that we already know correlates with treatment outcomes. This simple act of consistent measurement provides a powerful foundation for better understanding patients.

Modern psychiatry defines disorders by a checklist of symptoms (e.g., via the DSM), treating the syndrome itself as the disease. This is unlike the rest of medicine, which views symptoms like a cough as signals of various underlying causes. This flawed approach has stalled progress by focusing on labels instead of mechanisms.

For individuals whose symptoms have been repeatedly dismissed, a serious diagnosis can feel like a relief. It provides validation that their suffering is real and offers a concrete problem to address, overriding the initial terror of the illness itself.

Asking "How are you?" often elicits a reflexive "fine." Using a 1-5 scale (where 1 is a crisis and 5 is euphoric) bypasses this, providing a simple, concrete language for people, especially teens, to express their actual state. This creates a shorthand for seeking help and helps identify patterns in emotional well-being over time.

In clinical trials, patients "vote with their feet." High rates of discontinuing an optional (adjuvant) phase of treatment provide a clearer, real-world signal of toxicity and their personal risk-benefit analysis than formal Quality of Life surveys. Their actions speak louder than their written responses.

A diagnosis like autism may function like the 19th-century term 'dropsy' (swelling). It accurately describes a collection of symptoms but doesn't necessarily identify a single, unified underlying cause. The label captures a surface-level phenomenon, not a fundamental 'thing' in the world.

Instead of a categorical disease model (virus present/absent), mental health should adopt a dimensional approach like internal medicine. Just as blood pressure exists on a spectrum, psychological traits do too. Treatment decisions can be based on evidence-backed cutoffs for risk, eliminating the need for arbitrary diagnostic boxes.

Despite hype around genetics and multi-omics, their value in stratifying psychiatric patients is limited. Genetic variants have small effects, and peripheral samples like blood poorly reflect brain biology (e.g., blood serotonin comes from platelets, not the brain). Direct brain function measures are more reliable.

Before the DSM, psychiatric disease definitions were bespoke to different schools of thought. The DSM's great achievement was creating a common diagnostic umbrella. While imperfect, this standardization was a crucial foundational step for the field to begin communicating and researching consistently.