Global Collaborative Team Performance for the Revision of the International Classification of Diseases: A Case Study of the World Health Organization Field Studies Coordination Group
Bibliographic record
Abstract
Background/Objective: Collaborative teamwork in global mental health presents unique challenges, including the formation and management of international teams composed of multicultural and multilingual professionals with different backgrounds in terms of their training, scientific expertise, and life experience. The purpose of the study was to analyze the performance of the World Health Organization (WHO) Field Studies Coordination Group (FSCG) using an input-processes-output (IPO) team science model to better understand the team's challenges, limitations, and successes in developing the eleventh revision of the International Classification of Diseases (ICD). Method: We thematically analyzed a collection of written texts, including FSCG documents and open-ended qualitative questionnaires, according to the conceptualization of the input-processes-output model of team performance. Results: The FSCG leadership and its members experienced and overcame numerous barriers to become an effective international team and to successfully achieve the goals set forth by WHO. Conclusions: Research is necessary regarding global mental health collaboration to understand and facilitate international collaborations with the goal of contributing to a deeper understanding of mental health and to reduce the global burden of mental disorders around the world. Antecedentes/Objetivo: El trabajo de equipo colaborativo en salud mental global presenta retos particulares, incluyendo la formación y el control de grupos internacionales integrados por profesionales multilingües y multiculturales con diferentes antecedentes en términos de entrenamiento, competencias científicas y experiencias vitales. El propósito del estudio fue analizar el funcionamiento del Grupo de Coordinación de Estudios de Campo (GCEC) de la Organización Mundial de la Salud (OMS) utilizando un modelo científico de entrada-proceso-salida (EPS) para mejorar la comprensión de los retos, limitaciones y logros del equipo en el desarrollo de la onceava revisión de la Clasificación Internacional de Enfermedades (CIE). Método: Se llevó a cabo un análisis temático de una colección de textos, incluyendo documentos del GCEC y cuestionarios cualitativos de preguntas abiertas, acordes con la conceptualización del modelo de rendimiento de equipos de entrada-proceso-salida. Resultados: El liderazgo y los miembros del GCEC experimentaron y superaron numerosas barreras para convertirse en un grupo internacional efectivo y lograr exitosamente los objetivos establecidos por la OMS. Conclusiones: Se requiere de investigación sobre la colaboración en salud mental global a fin de entender y facilitar las colaboraciones internacionales dirigidas a comprender a profundidad la salud mental y reducir la carga de los trastornos mentales en el mundo.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 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".