This episode explores how statistics for n-of-1 designs can help practitioners make day-to-day decisions in applied behavior analysis (ABA). Mark Ramos describes how a personal concern about his daughter’s early intervention led him to ask a simple but important question: when does observed performance (for example, 4 of 5 vs. 8 of 10 correct trials) justify concluding a child has truly mastered a skill?

Using Bayesian ideas, he shows how increasing trial counts changes the posterior probability that latent mastery meets a chosen threshold, and how that can be integrated into routine ABA records. He also describes a prototype app to give practitioners updated, individualized probabilities and emphasizes choosing statistical tools to fit the context.

In this episode of N of 5 Minutes, we talk with Dr Nita Jain about why health care needs to look past lab numbers and averages to understand individual patients. She explains how treating a “low” result with a supplement can miss the deeper causes, and why single-patient studies are especially valuable for complex illnesses like long COVID. Dr Jain highlights how sex differences, personal baselines, and genomics could make care safer and more precise. She also shares an ecological view of microbes, showing how context shapes whether organisms are partners in health or sources of disease.

In this episode, we chat with Garrett Hall, a Florida State University school psychology professor, about individualized education intervention models. Garrett explains how single-case designs are crucial for addressing academic challenges, especially in math and reading. He highlights the importance of early intervention and its long-term benefits for students and schools. We explore how these tailored approaches can effectively measure and improve individual student outcomes.

Dr. Harezlak, a biostatistician from Indiana University, delves into the nuanced world of human walking. Dr. Harezlak highlights how walking patterns can reveal significant insights into individual health, such as aging and physical performance. The discussion extends to the realm of competitive sports, exploring how analyzing head impacts in American college football players can lead to more personalized concussion research. This episode invites listeners to rethink how individualized data can revolutionize scientific understanding and health interventions.

This episode features Dr. Lutz Kraushaar, a longevity researcher dedicated to personalizing health recommendations through N-of-1 methods.

He explains how individualized trials can guide people in navigating their personal journeys toward successful aging, focusing on vascular function as a key biomarker.

By using simple tools and data-driven approaches, anyone has the potential to test lifestyle interventions—such as dietary changes or exercises—to determine what truly works for them.

Dr. Kraushaar’s vision is to empower individuals to adopt only those habits that match their genetic predisposition, ultimately creating a “minimum viable health” plan for lasting well-being.

How can we bring people with mental health conditions closer to their doctors and improve their care?

Linda Valeri is an expert biostatistician specializing in causal inference with a focus on biostatistical methodology and statistical learning. She received her doctorate degree in biostatistics from Harvard University and is currently an assistant professor of Biostatistics at Columbia University's Mailman School of Public Health.

Her research encompasses causal mediation analysis, measurement error, missing data, and the integration of data from multiple sources such as smartphones and wearable devices, life course cohort studies, and electronic medical records, all in diverse populations.

How can we monitor your health in a way that is personally meaningful?

Diogo Branco is a PhD student in Computer Science at the University of Lisbon. His research focuses on human computer interaction, particularly in pervasive health care. Over the past five years, he has dedicated his research to designing, developing, and evaluating applications and platforms in various health care fields including Parkinson's disease.

Throughout his PhD, Diogo's primary objective is to utilize personalized tracking mechanisms to improve treatment adherence among individuals with Parkinson's and increased data availability for clinicians. In this episode, he talks to us about some of his work with patients with Parkinson's disease, with a focus on how we can make health monitoring easy and engaging so patients and clinicians can both benefit.

How can we support people that have an intense reaction to certain sounds?

⁠Dr. Kibby McMahon⁠ is a clinical psychologist, yoga teacher, and the co-host of ‘A Little Help for our Friends’⁠ podcast. Kibby completed her undergraduate degree at Columbia University, her PhD at Duke University in the Clinical Psychology program and her pre-doctoral internship at Cornell and New York Presbyterian Hospital.

She recently completed a postdoctoral fellowship at Duke University Medical Center, where she investigated novel treatments for misophonia in which people are intensely bothered by specific sounds (for more description of condition check out this website). Having been trained in several forms of evidence-based psychotherapies, Kibby treats adults with a range of mental health struggles, particularly depression, anxiety, personality disorders, trauma, and general relationship problems. Her passion lies in helping people connect more deeply to themselves and to others.

Ali Boolani is a multidisciplinary scientist whose work is focused on identifying feelings of mental and physical energy and fatigue and prescribing inter and intra individual interventions. His work is trying to identify intra individual differences in interventions to modify fatigue led to his interest in learning more about stats of one. He's currently the PI of the Mental Performance Lab at the Gatorade Sports Science Institute, and is interested in using these methods to improve his work.

How can we create personalized support for people with Diabetes using mobile devices?

In this episode, Dr Simon Harper talks about his work creating computer algorithms that monitor and adapt to people's behavior to provide them with personalized support to manage their Type I Diabetes. Dr Harper is a Professor in Computer Science at the University of Manchester. His work is centered on understanding, predicting and influencing a user's behavior in the real-world and through interfaces and information, while taking into account cognitive, behavioral, perceptual and technological factors. His contributions lie in the development of adaptive user models of extreme users and/or extreme environments.