Proceedings of the International Workshop ‘Integration of International Expertise in the Development of a Mental Health Surveillance System in Germany’
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Bibliographic record
Abstract
In 2019, the Robert Koch Institute (RKI) as the national Public Health Institute in Germany was commissioned by the Federal Ministry of Health to develop a concept for continuous health reporting on mental health in Germany. Meaningful data is required since mental health has strong public health relevance due to high prevalence and burden of psychological distress and mental disorders and the improvable care situation. Furthermore there is still unexploited potential to promote positive mental health. In Germany, almost one in three adults (27.8%) fulfils the criteria of a mental disorder within one year [1, 2]; the prevalence of emotional and behavioral disorders in children and adolescents is estimated at 10 to 20% [3]. Depressive disorder ranks globally as well as nationally among the most significant causes of Years Lost due to Disability (YLDs) [4, 5]. Additionally physical and mental health is closely interwoven: mental disorders deteriorate the course of somatic illnesses and vice versa, somatic illnesses represent a risk factor for the emergence of mental disorders. Against this background, the WHO has included mental disorders in its list of central non-communicable diseases [6]. Moreover, the establishment of Mental Health Information Systems is one of the four priority objectives of the WHO's Mental Health Action Plan. Besides mental disorders, this action plan targets on mental well-being as an integral component of health in general In order to face this task, a German indicator-based Mental Health Surveillance System (MHS) is under development. The proceeding comprises a consensus process among public mental health experts and stakeholders. Together with experts from Canada and Europe, representatives of 21 national and international institutions were invited to the workshop 'Integration of International Expertise in the Development of a Mental Health Surveillance System in Germany', held in Berlin, Germany on November 28-29, 2019. Main goals were (a) to share experience on existing mental health surveillance systems, (b) to present objective and methods of the German approach to the national expert committee, (c) to strengthen international collaboration and (d) to discuss central challenges and controversial issues. The introduction into the development of a national MHS at the Robert Koch Institute (S1) was given by Elvira Mauz (RKI, Berlin) by outlining the project's background and workflow. Daniel Chisholm (WHO Europe, Copenhagen) reported on indicators development for the WHO Mental Health Atlas in the context of Mental Health Action Goals and Sustainable Development Goals (S2). Emily Hewlett (OECD, Paris) focused on the international comparability of mental health indicators (S3), whereas Daniela Schuler (Swiss Health Observatory, Neuchtel) presented the national MHS in Switzerland (S4). Wolfgang Gaebel (LVR-Klinikum, Dsseldorf) presented indicators for mental healthcare quality which where developed for international comparison for the Danube Region (S5). Heather Orpana (Public Health Agency Canada, Ottawa) gave an overview of MHS Systems in Canada with a special focus on Positive Mental Health (S6). In two discussion sessions the following questions were addressed of (a) how a balance of indicators between mental health promotion, prevention and care of mental disorders might be achieved and (2) which mental disorders should be the focus within a German MHS.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it