Research Notes

Eric Green

Research Notes is a podcast about the reasoning behind research. Each episode features a conversation with the author of a study discussed at ghrbook.com. We trace how the research question was formed, how causal logic was mapped, how analytic decisions were made, and how uncertainty was interpreted. For teachers, students, and practitioners in global health, epidemiology, and data science, Research Notes makes research reasoning visible.

ตอน

  1. 3 วันที่แล้ว

    What do we mean by 'clinically meaningful'?

    What does “clinically meaningful” actually mean in psychiatry? Compass Pathways recently reported Phase 3 results for COMP360, a synthetic psilocybin treatment for treatment-resistant depression. The company said 39% of treated patients achieved a “clinically meaningful” reduction in symptoms. But who decides what counts as meaningful? And how should we interpret a 3–4 point difference on a scale like MADRS? In this episode of Research Notes, I talk with Dr. Jerrold “Jerry” Rosenbaum, Stanley Cobb Professor of Psychiatry at Harvard Medical School and director of the Massachusetts General Hospital Center for the Neuroscience of Psychedelics. Dr. Rosenbaum was not involved in the Compass study, but he has been closely watching the field and was quoted in STAT News saying the results “probably meet the bar for approval” but do not “shout out to you that this is miraculous.” We discuss: What makes a treatment effect clinically meaningful in psychiatryHow clinicians think about response, remission, and symptom scales like MADRSWhy Compass introduced a new category of “clinically meaningful” improvementHow restrictive trial criteria can make psychiatric studies hard to interpretWhy average effects may hide meaningful benefit in subgroupsWhether a 3–4 point difference on MADRS matters clinicallyWhy durability, cost, and functional unblinding matter for psychedelic treatmentsA key point from Dr. Rosenbaum: psychiatric trial outcomes are not just numbers on a page. They are consensus-based tools meant to approximate something much messier and more human — whether a person is suffering less, functioning better, and able to live their life again. For more: https://ghrbook.com/notes/clinically-meaningful.html

    27 นาที

  2. 25 ก.พ.

    Episiotomy, Hemorrhage & DAGs

    In this interview, I speak with Dr. Judith Lieber (London School of Hygiene & Tropical Medicine) about her recent paper in The Lancet Global Health examining episiotomy and postpartum haemorrhage in women with moderate or severe anaemia.I originally came across this paper while searching for a real-world example to teach directed acyclic graphs (DAGs). It turned out to be a perfect case: clinically important, analytically rigorous, and explicit about how a DAG guided the study design and adjustment strategy.The study draws on data from the WOMAN-2 trial — a large, international trial of tranexamic acid conducted in Pakistan, Nigeria, Tanzania, and Zambia, focused on postpartum bleeding in women with moderate or severe anaemia. Judy joined the trial team toward the end to conduct exploratory analyses using this rich dataset of over 15,000 women.In this conversation, we focus primarily on methods:-How drawing the DAG clarified the causal question-How it determined what to adjust for — and what to avoid adjusting for-The challenge of distinguishing confounders from mediators-Using proxies when key confounders (like shoulder dystocia) are unmeasured-Conducting a quantitative bias analysis to bound potential unmeasured confounding-Balancing complexity and readability when building a DAGWe also discuss Judy’s pathway into epidemiology, her work at LSHTM’s Clinical Trials Unit, and her current project tackling time-varying treatment decisions with another (even more complicated) DAG.This is a practical, applied conversation about how causal diagrams are actually used in real research — not as theoretical exercises, but as tools for clarifying assumptions, structuring models, and understanding limitations.If you teach causal inference, work with observational data, or are trying to move beyond “control for everything” regression thinking, this is a great example of DAGs in action.

    14 นาที
  • 2 ตอน

เกี่ยวกับ

Research Notes is a podcast about the reasoning behind research. Each episode features a conversation with the author of a study discussed at ghrbook.com. We trace how the research question was formed, how causal logic was mapped, how analytic decisions were made, and how uncertainty was interpreted. For teachers, students, and practitioners in global health, epidemiology, and data science, Research Notes makes research reasoning visible.

ข้อมูล

  • ผู้จัดทำ
    Eric Green
  • ออกอากาศปี
    พ.ศ. 2569
  • ตอน
    2
  • การจัดระดับ
    เหมาะสม
  • ลิขสิทธิ์
    © Eric Green
  • เว็บไซต์รายการ
    Research Notes