We share more attributes than we think: the crucial input of epidemiology
Bibliographic record
Abstract
Psychiatric epidemiology, as is the case for most domains in psychiatry, does not have strict borders in what goes under its umbrella. Still, it can be broadly defined as covering, among other subjects, the various environmental and genetic etiologies, the course and prevalence, and the two-way relation of societal factors in mental disorders, all in large samples of individuals. An interesting observation is that psychiatric epidemiology consolidates a major axiom, simple at first look, but profound in its implications: broadly speaking, humans share much more common mental attributes than we had thought. In fact, studying very large populations across the globe has taught us very clearly that there are major highways which seem to be predetermined by the simple fact that we belong to a given species. Be it the effects of prenatal factors, including genetics, of childhood adversities, of major trauma, war, economics, chronic illnesses or temperament; be it schizophrenia, post-traumatic stress disorder or phobias; all studies point increasingly in cross-national samples to similar conclusions. This makes the field of psychiatric epidemiology quite interesting, echoing its origins in the more sociological approach to mental health and now looking at the variety of biological markers and their relation to determinants of onset, course and treatment of mental health disorders. This has been, understandably, a very exciting field, which has defined the lifelong commitment of members of the WPA Section on Psychiatry Epidemiology and Public Health over the years. This Section was founded in 1967 and re-named “Epidemiology and Community Psychiatry” until 1997, when it acquired its present name. The Section gathered progressively the most prestigious experts in psychiatric epidemiology and public health, such as J. Wing, who was its president for years, and designed the famous Present State Examination (PSE), followed by the Schedule for Clinical Assessment of Neuropsychiatry (SCAN)1; H. Hafner, who conducted a unique work on the epidemiology of schizophrenia2; and N. Sartorius, who worked on behalf of the World Health Organization all over the world, and led among others the influential International Pilot Study of Schizophrenia3. Other prominent Section members pioneered the discipline by launching extensive populations surveys, such as T. Helgason in Iceland, with a birth cohort of more than five thousand probands followed up to their deaths4, and A. Leighton and J. Murphy in Canada, who set up the Stirling Country Study, a large population survey allowing to study population mental health up to the fourth generation5. To this list we can add L. Robins, who designed the Diagnostic Interview Survey (DIS)6, the first diagnostic interview usable by lay interviewers, a huge step in mental health epidemiology, whose DSM-III computerized algorithms allowed to evaluate the prevalence of mental disorders in the US in the Epidemiological Catchment Area Study, a landmark in the field under the leadership of D. Regier7. That instrument stimulated the development of the now worldwide used and continuously evolving Composite International Diagnostic Interview (CIDI)8, which, under the inspiring leadership of R. Kessler, was used in the World Mental Health (WMH) Initiative, that gathered surveys in 40 countries all around the world, and is still growing, with more than 1,000 publications so far (www.hcp.med.harvard.edu/wmh). The output from WMH covers a huge variety of subjects, including prevalence, risk factors, burden, course, treatment, conceptualizations and definitions of most mental disorders. Many of the WMH contributors are active members of our Section. Looking back, the Section has been able to organize twenty meetings all around the world. The themes of these meetings reflected the large scope of epidemiology and public health in the domain of psychiatry and mental health. Some meetings were more clinically oriented, such as “The Chronically Mentally ill” (Baltimore, US, 1982), “Primary Care and Psychiatric Epidemiology” (Toronto, Canada, 1989), and “From Epidemiology to Clinical Practice” (Turku, Finland, 1999). Others focused on longitudinal perspectives, such as “The Course and Outcome in Mental Health Disorders” (Groningen, The Netherlands, 1993), “Prediction is Psychiatric Epidemiology: from Childhood and Adolescents to Adulthood” (Lisbon, Portugal, 2010), and “Epidemiology of Mental Disorders Across Lifespan and Development” (New York, US, 2018). Some focused more on research, such as “A Search for Causes: Epidemiological Approaches” (New York, US, 1995), “Psychiatric Epidemiology and Social Sciences” (Oslo, Norway, 1991), “Theory Evidence and Psychiatric Epidemiology” (Paris, France, 2003), and “Psychiatric Epidemiology Meets Genetics: The Public Health Consequences” (Munich, Germany, 2016). Two meetings focused on “The Future of Epidemiology” (Edinburgh, UK, 1985, and Baltimore, US, 2001). Public health aspects were the focus of several more meetings: “Unmet Needs” (Sydney, Australia, 1997), “Epidemiology and Medical Economics” (Brisbane, Australia, 2006) and “From Epidemiology to Mental Health Planning” (Saskatoon, Canada, 2008). Others focused more on risk factors, such as “Mental Health and Urbanization: Challenges of Societies in Transformation” (Sao Paulo, Brazil, 2012) and “Trauma and Mental Health” (Nara, Japan, 2014). The forthcoming meeting will be held for the first time in Africa, in Morocco: “Learning from Diversities Across the World: Implications for Psychiatric Epidemiology”, scheduled for October 2022. We carry a tradition in our meetings, which is to minimize parallel sessions, in order to foster real exchange between the presenters and the audience. We thus set up a theme and then try, as much as possible, to organize sessions coherent with this theme, with highly recognized speakers and much time devoted to active discussions. The concentration of highly committed specialists during these meetings has been a great source of inspiration for many beginners in the field, and has been decisive for the career of many young researchers. The atmosphere is typically friendly, and sessions deal with a very limited number of topics, which allows beginners and experts to dig deeper. In conclusion, the broad perspective of epidemiology and public health in all areas of mental health encourages international collaboration, and crucially examines how much, in fact, humans look alike and how lessons learned from one site can be generalized to humans all over.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".