Shedding light on the onset of psychiatric illness: looking through a developmental lens
Bibliographic record
Abstract
Understanding the mechanisms driving the onset of major psychiatric illnesses such as depression, bipolar disorder and schizophrenia has been far more challenging than expected. Contributing factors include that symptoms associated with each of these disorders overlap during different phases of emerging illness1 and over the course of established illness.2 In addition, while there is evidence supporting specificity of familial segregation,3 at least some genetic risk factors appear to be shared4 and treatment response crosses currently defined diagnostic boundaries.5 But does it follow, as some propose,6 that psychiatric illnesses are really different manifestations of a common origin—in other words that different psychiatric illnesses derive from pluripotent or shared beginnings and specific outcomes depend on mediating and moderating influences? Epidemiological and high-risk prospective studies provide compelling evidence to the contrary. In fact, a developmental perspective has illuminated clear distinctions in the early trajectories between illness such as schizophrenia and bipolar disorder.7 Further longitudinal studies of children over the peak risk period have highlighted the inadequacy of current cross-sectional approaches to psychiatric diagnosis that do not take into account the developmental and emergent course of psychopathology against the backdrop of family history and other predictive risk factors.8 Using bipolar disorder as an example, longitudinal studies of high-risk offspring of affected parents followed through childhood into adulthood have clearly demonstrated that psychopathology is in evolution—a moving target. What first manifests as anxiety or sleep problems in high-risk children might evolve into a depressive disorder in adolescence followed by an index hypomanic or manic episode in emerging adulthood.9 However, this evolving developmental trajectory differs between distinct end-stage illnesses. For example, clinical and neuroimaging evidence supports that the trajectory into schizophrenia is consistent with a neurodevelopmental process,10 which is distinctively different from the prototypical developmental trajectory …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".