Single subject experiments

Instrumentation and analytics for body and soul; Quantified self; precision medicine.

2022-01-11 — 2025-10-11

Wherein single‑subject experiments are described, and the practice of N‑of‑1 trials is set forth with mention of self‑blind methods, biomarker tracking and Apple Health data exports.

causality
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economics
faster pussycat
fit
gene
graphical models
how do science
machine learning
mind
probability
statistics
Figure 1

Other people have written much more about principled single-subject experimentation, especially self-experimentation. Here are some links we’ve found, though.

1 Folk history of the quantified self movement

Obligatory: The tragic morality fable, Seth Roberts’ Final Column: Butter Makes Me Smarter.

2 Experiment design

3 Data collection

3.1 Activity

I mention some activity-monitoring strategies under time management.

3.2 Subjective things

Measuring moods? See the Experience Sampling Method (Verhagen et al. 2016; Hektner, Schmidt, and Csikszentmihalyi 2007) or Swan (2013).

3.3 Biomarkers

See biomarkers.

4 Tools

  • Flaredown - Decode your chronic illness

    See also Chronic illness: symptoms, treatments and triggers

  • StudyU - Personalized Health Interventions

  • n1.tools: Conduct simple N-of-1 Experiments

    A simple tool that encourages randomisation to uncover the causal link between your actions and desired outcomes; whether testing a supplement, meditation, cold showers, or any other intervention.

    Easily add your data and use the mean and p-value to establish confidence in your result. This tool works for simple experiments where the effects of what you’re testing show up and wear off within a day. It doesn’t take into account things like lag times between your action and the outcome, autocorrelation (when data points influence each other), the buildup of substances in your body over time etc.

    This can be useful as a first order approximation, and is still more rigourous than many other methods. However, if you’re looking at something more complex, you likely need to consider other factors and use a more sophisticated methodology.

  • Bearable — mood and symptoms tracker app

  • Exist — a hip quantified-self tracker.

  • Symple — symptom journal and health diary

  • Cronometer — track nutrition and count calories

  • Gyroscope — your personal health coach

  • ActivityWatch

    • A set of watchers that record relevant information about what you do and what happens on your computer (such as if you are AFK or not, or which window is currently active).
    • A way of storing data collected by the watchers.
    • A data format accommodating most logging needs due to its flexibility.
    • An ecosystem of tools to help users extend the software to fit their needs.

  • Burn Notice - kieranhealy.org

Yesterday I decided I wanted to take a look specifically at the health data on my iPhone. I’m not a huge user of the iPhone’s or the Apple Watch’s health features. I don’t use or subscribe to Apple Fitness+, for example.

5 Incoming

Figure 2

6 References

Backman, and Harris. 1999. “Case studies, single-subject research, and N of 1 randomized trials: comparisons and contrasts.” American Journal of Physical Medicine & Rehabilitation.
Barlow, Nock, and Hersen. 2009. Single Case Experimental Designs: Strategies for Studying Behavior for Change.
Brien, and Demétrio. 2009. “Formulating Mixed Models for Experiments, Including Longitudinal Experiments.” Journal of Agricultural, Biological, and Environmental Statistics.
Chapple, and Blackston. 2019. “Finding Benefit in n-of-1 Trials.” JAMA Internal Medicine.
Chrisinger. 2020. “The Quantified Self-in-Place: Opportunities and Challenges for Place-Based N-of-1 Datasets.” Frontiers in Computer Science.
Corti, Reddy, Choi, et al. 2015. “The Researcher as Experimental Subject: Using Self-Experimentation to Access Experiences, Understand Social Phenomena, and Stimulate Reflexivity.” Integrative Psychological and Behavioral Science.
Daskalova, Desingh, Papoutsaki, et al. 2017. “Lessons Learned from Two Cohorts of Personal Informatics Self-Experiments.” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
Daza, Eric J. 2018. “Causal Analysis of Self-Tracked Time Series Data Using a Counterfactual Framework for N-of-1 Trials*.” Methods of Information in Medicine.
Daza, Eric Jay. 2019. “Person as Population: A Longitudinal View of Single-Subject Causal Inference for Analyzing Self-Tracked Health Data.”
Dugard, File, and Todman. 2012. Single-Case and Small-n Experimental Designs: A Practical Guide To Randomization Tests, Second Edition.
Dulaud, Di Loreto, and Mottet. 2020. “Self-Quantification Systems to Support Physical Activity: From Theory to Implementation Principles.” International Journal of Environmental Research and Public Health.
Feng, Mäntymäki, Dhir, et al. 2021. “How Self-Tracking and the Quantified Self Promote Health and Well-Being: Systematic Review.” Journal of Medical Internet Research.
Fitzmaurice, and Ravichandran. 2008. “A Primer in Longitudinal Data Analysis.” Circulation.
Ganz, and Ayres. 2018. “Methodological Standards in Single-Case Experimental Design: Raising the Bar.” Research in Developmental Disabilities.
Hektner, Schmidt, and Csikszentmihalyi. 2007. Experience Sampling Method: Measuring the Quality of Everyday Life. Experience Sampling Method: Measuring the Quality of Everyday Life.
Heyen. 2020. “From Self-Tracking to Self-Expertise: The Production of Self-Related Knowledge by Doing Personal Science.” Public Understanding of Science.
Janosky, Leininger, Hoerger, et al. 2009. Single Subject Designs in Biomedicine.
Johnston, and Mills. 2004. “N-of-1 Randomized Controlled Trials: An Opportunity for Complementary and Alternative Medicine Evaluation.” The Journal of Alternative and Complementary Medicine.
Karkar, Zia, Vilardaga, et al. 2016. “A Framework for Self-Experimentation in Personalized Health.” Journal of the American Medical Informatics Association.
Kazdin. 2020. Single-Case Research Designs: Methods for Clinical and Applied Settings.
McDonald, Vieira, and Johnston. 2020. “Analysing N-of-1 Observational Data in Health Psychology and Behavioural Medicine: A 10-Step SPSS Tutorial for Beginners.” Health Psychology and Behavioral Medicine.
Moeyaert, Manolov, and Rodabaugh. 2020. “Meta-Analysis of Single-Case Research via Multilevel Models: Fundamental Concepts and Methodological Considerations.” Behavior Modification.
Ordovas, Ferguson, Tai, et al. 2018. “Personalised Nutrition and Health.” BMJ.
Pelayo. 2015. “Design and Application of Quantified Self Approaches for Reflective Learning in the Workplace.”
Percha, Baskerville, Johnson, et al. 2019. “Designing Robust N-of-1 Studies for Precision Medicine: Simulation Study and Design Recommendations.”
Piccininni, Stensrud, Shahn, et al. 2024. “Causal Inference for N-of-1 Trials.”
Roberts. 2004. “Self-Experimentation as a Source of New Ideas: Ten Examples about Sleep, Mood, Health, and Weight.” Behavioral and Brain Sciences.
Senn. 2018. “Statistical Pitfalls of Personalized Medicine.” Nature.
Simons, Harrison, O’Brien, et al. 2019. “Graded Exposure Treatment for Adolescents with Chronic Pain (GET Living): Protocol for a Randomized Controlled Trial Enhanced with Single Case Experimental Design.” Contemporary Clinical Trials Communications.
Swan. 2013. “The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery.” Big Data.
Taylor, Sano, Ferguson, et al. 2018. “QuantifyMe: An Open-Source Automated Single-Case Experimental Design Platform.” Sensors (Basel, Switzerland).
Verhagen, Hasmi, Drukker, et al. 2016. “Use of the Experience Sampling Method in the Context of Clinical Trials.” Evidence-Based Mental Health.
Vieira, McDonald, Araújo-Soares, et al. 2017. “Dynamic Modelling of n-of-1 Data: Powerful and Flexible Data Analytics Applied to Individualised Studies.” Health Psychology Review.
Wicks. 2018. “Patient, Study Thyself.” BMC Medicine.
Zarbin, and Novack. 2021. “N-of-1 Clinical Trials: A Scientific Approach to Personalized Medicine for Patients with Rare Retinal Diseases Such as Retinitis Pigmentosa.” Journal of Ocular Pharmacology and Therapeutics.
Zenner, Böttinger, and Konigorski. 2022. “StudyMe: A New Mobile App for User-Centric N-of-1 Trials.” Trials.
Zuidersma, Riese, Snippe, et al. 2020. “Single-Subject Research in Psychiatry: Facts and Fictions.” Frontiers in Psychiatry.