Tag Archives: Research
We’ve been holding Quantified Self Conferences since 2011. Every year since then we’ve been approached by scientists and researchers in the academic community to help them find a way to incorporate their work and their ideas into our structure. After a few years of holding back, listening, and watching the research community become engaged with other scientists and the real-world QS practitioners we’re ready to take that next step.
We are excited to announce today that we are inviting scientists and non-scientists to join a research oriented poster session at our upcoming Quantified Self European Conference on May 10th and 11th.
These sessions are a way for us to support interesting work that doesn’t fit into our established show&tell format, including research results from academic and scientific studies relevant to QS practitioners. Possible topics include (but are not limited to):
- Validity, reliability, usability, and effectiveness of self-tracking devices
- Experiment design
- Statistical and/or visualization methods
- Social and psychological investigation into self-tracking practices
- Social science research on the QS community
Our hope is that these posters and the conversations around them will help us (scientists and non-scientists) learn from each other, stimulate new ideas/projects, and to uncover new applications for the research findings.
How to submit a poster
The process is very simple. Simply send us a draft of your poster submission via email. We will be accepting submissions until April 14, 2014. For format and other info, please read the instructions below. The posters will be reviewed for content and relevance; if you would like to be involved with the review process, or have any questions, please contact us.
Posters should contain the following elements:
- Authors and affiliations
- QS Relevance
- Contact information. We recommend including a picture of yourself so others at the conference can find you, and, if applicable, your twitter account.
- You must use the A0 size (841 × 1189mm or 33.11 × 46.81 inches)
- A PowerPoint template is provided for you to use.
Remember to Keep It Short and Simple (KISS). We want to stimulate creativity and strongly recommend the use of tables, figures, and visualizations. For examples and design tips we recommend the following articles:
- Creating Effective Poster Presentations
- Advice on designing scientific posters
- Poster Presentation
- Designing Effective Posters
Dates & Deadlines
Deadline for submission is April 14, 2014. We will conducting reviews and informing submitters of acceptance on a continual basis. All submitters will be notified by April 21, 2014. We look forward to seeing your inspiriting projects and findings.
(Co-written with Gary Wolf)
In January we started asking ourselves, “How many people self-track?” It was an interesting question that stemmed from our discussion with Susannah Fox about the recent Pew report on Tracking for Health. Here’s a quick recap of the discussion so far.
The astute Brian Dolan of MobiHealthNews suggested that the Pew data on self-tracking for health seems to show constant – not growing – participation. According to Pew, in 2012 only 11% of adults track their health using mobile apps, up from 9% in 2011.
All this in the context of a massive increase in smartphone use. Pew data shows smartphone ownership rising 20% just in the last year, and this shows no signs of slowing down. Those smartphones are not just super-connected tweeting machines. They pack a variety of powerful sensors and technologies that can be used for self-tracking apps. We notice a lot of people using these, but our sample is skewed toward techies and scientists.
What is really going on in the bigger world? How many people are actually tracking?
A few weeks ago ABI, a market research firm, released a report on Wearable Computing Devices. According to the report there will be an estimated 485 million wearable computing devices shipped by 2018. Josh Flood, the analyst behind this report indicated that they estimated that 61% of all devices in wearable market are fitness or activity trackers. “Sports and fitness will continue to be the largest in shipments,” he mentioned “but we’ll start to see growth in other areas such as watches, cameras, and glasses.”
One just needs to venture into their local electronics retailer to see that self-tracking devices are becoming more widespread. So why are our observations out of synch with the Pew numbers?
The answer may lie in the framing of the Pew questions as “self-tracking for health?” For instance:
On your cell phone, do you happen to have any software applications or “apps” that help you track or manage your health, or not?
Thinking about the health indicator you pay the most attention to, either for yourself or someone else (an adult you provide unpaid care for), how do you keep track of changes? Do you use paper, like a notebook or journal, a computer program, like a spreadsheet, a website or other online tool, an app or other tool on your phone or mobile device, a medical device, like a glucose meter, or do you keep track just in your head?
We think it is likely that many practices we include in our definition of Quantified Self are not being captured by the Pew Research. A person who tracks a daily run with a Garmin GPS watch might show up in the wearables data that ABI looks at, and might look to us as a self-tracker for health, but might be invisible to Pew. There may be even self-tracking practices that fall outside health or wearables. We’ve seen a large number of people who track time and productivity using computer applications such as RescueTime, apps that support well-being such as meditation trackers, mood trackers, and diet trackers; and apps that support general self-reflection and journaling, such as a life-logging app. Many self-tracking practices do not fit neatly into “health.” (Though they may influence health!)
In a way, there is a parallel here to what we found when we compared Fitbit with Fuelband data. Both of them produced different numbers for “steps.” When we got into the details, we ended up thinking that this was not a matter of one being closer to the “ground truth,” but of intentionally different interpretations of messy accelerometer data. Fitbit gives more step credit for general movement, because it is a lifestyle/activity tracker; Nike might prefer to credit intentional exercise, since the Nike brand sits closer to sports. Context matters.
This confusion about what is health tracking, what fits in the frame, is closely analogous to many other confusions in the conversation about health generally. It is common now in the healthcare world to talk about how the larger determinants of public health are outside the control of the healthcare industry; for instance, diet, exercise, stress, and exposure to environmental toxins. Sometimes people who make these observations follow them with a call for the healthcare industry to begin addressing these larger concerns; for instance, to “medicalize” tracking apps by making them prescribable and reimbursable by health insurers.
But maybe this isn’t the only approach. If the “healthcare” frame isn’t adequate to capture the most important determinants of health, we could try switching frames. What our journey through the self-tracking data suggests is that the opposite approach might be useful to consider: start with the bigger world of self-care practices, and enhance these. Why? Because that’s where we trackers already are. That is, how are we deriving meaning from self-tracking? That’s the mental framework that we typically use, and that we like to use. That’s where the growth – in terms both of us, and of cultural understanding, engagement, and knowledge-making – might really be happening.
We don’t know this for sure. We take the Pew data as evidence that this approach is worth trying.
The report is called The Social Life of Health Information, and has several interesting findings. Here is an excerpt:
Carol Torgan, a health science strategist, points out that anyone who makes note of their blood pressure, weight, or menstrual cycle could be categorized as a “self-tracker.”10 Add an online component, and you have the ingredients for a social health application or an electronic health record. Our survey finds that 15% of internet users have tracked their weight, diet, or exercise routine online. In addition, 17% of internet users have tracked any other health indicators or symptoms online. Fully 27% of adult internet users say yes to either question.
Wireless users are more likely than other internet users to track health data online. Eighteen percent of wireless users have tracked their weight, diet, or exercise routine online, compared with 9% of internet users who do not have a wireless-enabled laptop or other device. Nineteen percent of wireless users have tracked any other health indicators or symptoms online, compared with 11% of non-wireless internet users.
Separately, looking just at the 85% of adults who own a cell phone, 9% say they have software applications or “apps” on their phones that help them track or manage their health.
By popular request, we have just launched a global QS forum at: http://forum.quantifiedself.com/
Gary, Dan Dascalescu, and I took some exciting topics from the conference and turned them into forum discussions, with expert moderators to help explore ideas and answer questions. You’ll find discussions on:
Please join in the conversations, ask questions, share what you’ve learned, and come play with us!
As far as I know, Adam Butterfield is the first person doing his Master’s thesis on the subject of the Quantified Self. He wrote in with this request:
Calling all self-trackers! My name is Adam Butterfield, and I am a graduate student in the department of Anthropology at San Jose State University conducting research on Quantified Self and self-tracking practices. I am looking to recruit people that are willing to be interviewed about Quantified Self and self-tracking/self-experimenting from their perspective.
The interviews will be about one hour in length and I expect that we will need two sessions to cover all the questions. There is no compensation offered for participating other than knowing that you have helped contribute to this research project and added to the body of knowledge around health management and self-tracking. Interviews can take place in person, over the telephone, or via Skype.
If you are interested in participating in the project, please contact me for more information at the following email address: email@example.com.
This is a guest post by Beck Tench:
This Friday begins a month-long participatory blogging project at the Museum of Life and Science, where I work, called Experimonth – and QS’rs are invited to participate.
Experimonth, which started as a personal project for me in 2008, has morphed into an effort to bring scientists and citizens together through data collection and blogging. For our first experimonth as a museum, we’ll be focusing on Mood and working with Frances Ulman, Ph.D., a clinical psychologist doing her post-doctoral research at the University of North Carolina at Chapel Hill.
Here’s how it’ll work:
Last week, I wrote a post recruiting self-quantifiers who live in Pittsburgh for face-to-face interviews at Carnegie Mellon University, but not many responded. Thankfully, a QS reader informed me of Skype’s ‘Share Screen’ feature.
Now, I am writing again to recruit participants, but this time the interviews will be remote using Skype’s ‘Share Screen’ feature. The study consists of two interviews (a few weeks apart). In the first interview, I will observe how you explore your data using your personal informatics tool and ask you questions about what you learn from your data.
In the second interview, I will show you different designs of graphs and visualizations and ask you about your thoughts on the designs. Participants will receive a $10 Amazon gift certificate per hour of interview.
If you are interested in participating, please complete the pre-questionnaire (http://ianli.com/pi/2010pre/qs), which has a few questions about the types of information that you keep track. We will select interview participants from those who complete the pre-questionnaire.
If you have questions, please email me at firstname.lastname@example.org.
Hello, everyone! Last summer, we conducted a study about people’s experiences using personal informatics tools to collect and reflect on data about themselves.
This summer, we are running a more focused study to explore how people reflect on their personal informatics data. The study consists of two one-hour interviews (a few weeks apart) at Carnegie Mellon University.
In the first interview we will observe how you explore your data using your personal informatics tool and ask you questions about what you learn from your data.
In the second interview, we will show you different designs of graphs and visualizations and ask you about your thoughts on the designs. Participants will be paid $10 per hour of interview.
You are eligible to participate in the study if:
- you live near Carnegie Mellon University in Pittsburgh, Pennsylvania
- you use personal informatics tools to keep track of personal information (e.g.,physical activity, blood glucose level, spending habits, energy usage, weight, etc.).
If you are interested in participating, please complete the pre-questionnaire (http://ianli.com/pi/2010pre/qs), which has a few questions about the types of information that you keep track of. We will select interview participants from among those who complete the pre-questionnaire.
If you have questions, please email me at email@example.com.
Many people participated describing their experiences using existing tools to track and reflect on personal information. The survey helped us develop a model to describe personal informatics systems (Figure 1).
The model is a series of five stages: Preparation, Collection, Integration, Reflection, and Action, with four properties: problems in earlier stages cascade to later stages; stages are iterative; they are user-driven and/or system-driven; and they are uni-faceted and/or multi-faceted.
From these properties, we suggest that personal informatics systems should:
1) be designed in a holistic manner across the stages;
2) support iteration between stages;
3) apply an appropriate balance of automated technology and user control within each stage to facilitate the user experience; and
4) provide support for associating multiple facets of people’s lives to enrich the value of systems.
In the rest of this post, I will talk about our findings in further detail and discuss how the model can guide the evaluation and design of personal informatics systems.
Figure 1. The stage-based model of personal informatics systems and its four properties.
(Full report after the jump.)
A common question people ask me is, “Why do you track yourself?” The primary answer, for anyone living with chronic pain, is simple — to help reduce the pain. Migraine, for example, is a chronic condition where self-tracking can have a positive effect.
According to the National Headache Foundation, migraine affects 13% of the US population, with women 3 times more susceptible than men. A study of tracking migraine using an electronic diary showed that tracking helped sufferers accurately predict incidents of migraine. Headache diaries have also been shown to be comparable to clinical interviews for diagnosing migraine.
This greater self-knowledge that tracking brings is invaluable. Like predicting earthquakes and volcano eruptions, predicting a migraine can help a sufferer either take action to prevent it or prepare for the worst. In order to better understand how to predict and alleviate migraine pain, a live, crowdsourced research study on migraine is being conducted.
The call for participants is below, but first, the story of a self-tracking migraineur.
Mercedes (her online name) has had migraines for 30 years. That’s almost as long as I’ve been alive. She tracks her migraines in order to minimize how often they occur. Here is her story, in her own words:
“This is what I track:
- Amount of bedrest (since I do not sleep well, I find that bedrest is a better indicator)
- Foods I eat
- Stress levels
- Computer work
- Lunar calendar
What I have found is that incidents of migraines can be minimized if:
- I get to bed between 9 and 10 p.m.
- I restrict certain foods such as chocolate, sugar, red meats and salt
- I meditate and exercise to avoid high stress levels. By exercise I mean largely tai chi and dancing
- Since most of my headaches begin early in the morning before I get up, drinking coffee and applying heat to my neck first thing in the morning is beneficial more often than not
- I have started to track the lunar calendar and the length of time I spend on the computer and, while not conclusive yet, find that on occasion the full moon and/or too much time at the computer coincide with my headache
Essentially to manage my headache, I have to eat right, rest enough, cope with stress, drink caffeine and apply heat (the hot tub is great for this too). And maybe avoid too much time at the computer. But how to avoid the full moon?
But even with that, there are still unexplained times when I get headaches. I am also trying to gauge if the severity of the headaches can be identified in advance but so far I have come to no conclusions.“
Mercedes’ story shows the dedication of chronic pain trackers and the complexity of the conditions they face. If enough people living with pain came together to track themselves and compare notes, we would be a lot closer to understanding these conditions.
And stopping the pain.*
Participants Needed for Online Migraine Research Study
CureTogether is conducting a study on Migraine. People who experience migraine are invited to self-report data on their symptoms, treatments, and triggers. The goal is to discover associations in this data to help characterize which migraine treatments work best for patients with different groups of symptoms.
Participation is entirely voluntary, anonymous, and completely confidential. It should take 15-20 minutes to complete. Statistics for the study are posted live, so you will be able to see aggregate results of other participants’ data after completing your entry.
* If you don’t have migraines but know someone who does, be a friend and forward this post to them. Self-tracking can help!
Photo by Auntie P.