Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.


45th Annual Convention; Chicago, IL; 2019

Event Details

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Symposium #523
Self-Experimentation and the Quantified-Self: Research, Theory, and Application
Monday, May 27, 2019
3:00 PM–4:50 PM
Swissôtel, Concourse Level, Zurich BC
Area: EAB/CBM; Domain: Applied Research
Chair: Clodagh Mary Murray (National University of Ireland Galway)
Discussant: April M. Becker (University of North Texas and University of Texas Southwestern Medical Center)
Abstract: This symposium discusses two research areas in which experimenter (or observer) and subject are one and the same. Self-Experimenters (S-E) employ n-of-1 methods common in behavioral studies. Self-experimental research has led to animal-model studies, to research with human populations, and, importantly, to successful applications. Sometimes the stimulus for research flows in the opposite direction: self-experiments have followed from medical and behavioral “real world” problems and from research on others. Quantified-Self (Q-S) researchers use contemporary technologies for automatic recording and analyses of behaviors, emotions and physiological changes. They share and compare self-generated data on the internet, in small-group meetings, and in international conventions. The interests and goals of S-E and Q-S researchers are often similar, and our symposium shows some of the ways in which the two areas can interact. The symposium offers two general discussion papers (Gary Wolf on Q-S and Allen Neuringer on S-E), and two sets of data-based and experimental studies (Valerie Lanard’s Q-S study and Robert Stromer’s S-E). We hope to demonstrate why a combination of S-E and Q-S can be more powerful than either alone.
Instruction Level: Basic
Keyword(s): behavior change, health psychology, self-control, self-monitoring

The Everyday Science of "Quantified Self”

GARY WOLF (QuantifiedSelf)
Abstract: The Quantified Self is a loosely organized collaboration among makers and users of self-tracking tools who share what they are learning about themselves from their own data. The first Quantified Self meeting was held in the San Francisco Bay Area in 2007. Since that time similar groups have been organized in over 30 countries. My presentation will outline the history of the Quantified Self, characterize the types of self-tracking projects participants undertake, and show examples. I’ll show projects designed to explore causal models, projects testing medical interventions, retrospective n-of-1 studies, projects focused on self-expression, diaristic reflection, interpersonal communication, and artistic creation. The effects of behavioral feedback using self-collected data will also be described. Gary Wolf is the co-founder of the Quantified Self.

Learning From Excuses, and Other Unexpected Lessons From Self-Tracking

VALERIE LANARD ( Engineering)

Valerie Lanard will present what she has learned from years of self-tracking: how she has used it to form healthy habits, how self-tracking has helped with physical therapy compliance, and what she has learned about behavioral and physiological patterns that may be unique to herself. Some of her studies involve self experiments. She will provide details of her exercise journey from weekly chore to daily habit as well as the inadvertent lessons she has learned along the way about how to get sick less often and, ironically, injured more. She will review her basic tracking tools and methods as well as supplementary data sources she uses, including wearables and electronic health records. Finally, she will discuss tensions between the current healthcare system (designed for an N of many) and her own data-driven self-advocacy (informed by an N of 1). By day, Valerie is Director of Engineering at arts-funding startup Patreon.


Technology-Assisted Self-Experimentation in a Septuagenarian: Use of a Brain Sensing Device During Mindfulness Meditation Practices

ROBERT STROMER (George Brown College)

Technology-assisted self-experimentation is a natural fit for data-oriented practitioners who want improved self-regulation skills. To illustrate, years ago I began practicing mindfulness-based self-care. Then, to explore private events from a biologic perspective, I began meditating with a Muse™ Brain Sensing Headband, a clinical grade device that distributes brain signals into “Calm,” “Neutral,” and “Active” zones. As a training aid, Muse™ provides auditory feedback to differentiate among brain signals. Initially, therefore, I examined distributions of “Calm” brain signals under auditory feedback versus no-feedback conditions; and results clearly favored auditory feedback. In addition, I examined “Calm” brain signals under sitting versus walking meditations. (Walking possesses both contemplative and muscle strengthening aspects.) Here, results were comparable, and similar to those observed initially for no-feedback. Interestingly, “Calm” walking meditations increased as the experiment ended. To date, I have used the Muse™ for 390 consecutive days, often, hour or longer each day. Throughout, almost 75% of my brain signals appear in the “Calm” zone; most all other brain signals in the “Neutral” zone. Overall, what I have learned benefits my personal practice immensely – with and without technology – and lessons learned inform my teaching of others in mindfulness-based stress reduction.

Self-Experimentation and its Impact on “Normal” Research and Application
Abstract: The history of experimenting on one’s own behavior and physiology goes back to the 17th century and continues to this day. In an encyclopedic work, A. Finks (2003) describes more than 500 self-experiments by physicians, biologists, physiologists, experimental psychologists and behavior analysts, among others (e.g., Isaac Newton and Arthur Conan Doyle). Many experiments led to discoveries that were later validated by “normal research.” Examples span the range from Hermann Ebbinghaus’s impactful self-studies on human memory to James Marshall’s revolutionary self-experiment on ulcers, the latter of which led to the Nobel Prize in physiology. Many of the self-experiments done by my students at Reed College employ classic A-B-A designs to study such things as effects of exercise. Some students did exploratory (non-hypothesis based) research: e.g., of complete silence for 3 days; or of sleeping in two bouts (3 and 4 hrs.) rather than a single 7-8 hr. period. My own self-experiments on random-like responding led to more than 30 years of research (with non-human animals as well as human participants) on “operant variability.” I will describe some of these self-experiments and critically evaluate the intersection between self-experimentation and more common “other-based” research.



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