
Instead of asking “What’s the best fitness tracker?”, maybe the question should be “Is a fitness tracker the best tool for you?”
There’s no doubt that tracking data can be useful. People looking to improve their health and fitness want to see if the changes they are making are working. Someone who wants to lose weight will look at the number on the scale. Runners wanting to get faster will measure their mile pace. These are objective outcomes; the numbers are what they are.
Are you a numbers person? Do you love technology, spreadsheets, analyzing data? Are you motivated by those external goals? Most important, do you see that data as just information – not a reflection of you as person? Then fitness data trackers are probably a good tool for you.
However, fitness trackers can be demotivating: if collecting the data feels like a chore, or if you end up feeling guilty for not hitting your targets. This is especially true of trackers that come with preset goals, such as sleeping a certain number of hours or walking a certain number of steps a day.(1) Some people have a hard time separating themselves from the numbers; if their sleep analysis is suboptimal, for example, then they’ve “failed” in some way, or there must be something wrong with them.
Dr. Kayla Nuss focused much of her graduate research on the relationship between data trackers and motivation to exercise. According to Dr. Nuss, when someone continually falls short of the goals the tracker sets, they can feel discouraged. Not only do they stop using the tracker, but they may also give up trying to improve the activity they were tracking.(2)
Even worse, consumer fitness trackers aren’t completely accurate. Research shows that the reliability of trackers depend on a number of factors, including the part of the body monitored (finger, wrist or chest, or example) and the activity being monitored. (3,4) The least accurate progress indicators include distance, sleep quality, calories consumed, and calories burned.
Think about those last two for a minute. Calorie count is hard to measure in the first place. The calories listed on food labels and restaurant menus can be off as much as 20%.(5) Consumer fitness trackers’ estimates of daily calorie expenditure can be off by about 30%. Using your tracker as a guide, you may actually be consuming more, and expending fewer, calories than you thought. And if your goal is weight loss, you may be confused and discouraged by the numbers you see on your scale.
Bottom line: Different types of people thrive on different types of data. Fitness data trackers work best for people who are numbers-oriented; who tend to have more advanced fitness goals, like competitive athletes or bodybuilders (whose income depend on their performance); and who see the data as information-only, not as a reflection of their worth or identity as a person.
Some people can actually be harmed by an overemphasis on data: by becoming over-competitive to beat their last “personal best”, they may over-train and become injured; people engaging in “all-or-nothing” thinking or perfectionism may feel they never can live up to their ideal “numbers” (which may turn out to be a continually moving target). Some people can become overly anxious about the activity they’re tracking – putting on that sleep tracker triggers a night of tossing and turning.(6)
People like this could benefit from other data and progress-tracking methods, such as consistency with a behavior (adding a serving of veggies to a meal, for example), or more subjective outcomes (such as how adding a meditation practice affects stress levels).
If fitness data trackers work for you – great! If not, there are many other ways to track progress that may work better for you.
References:
1. Kerner C, Goodyear VA. The Motivational Impact of Wearable Healthy Lifestyle Technologies: A Self-determination Perspective on Fitbits With Adolescents. Am J Health Educ. 2017 Sep 3;48(5):287–97.16.
2. Nuss K, Moore K, Nelson T, Li K. Effects of Motivational Interviewing and Wearable Fitness Trackers on Motivation and Physical Activity: A Systematic Review. Am J Health Promot. 2020 Jul 14;890117120939030.
3. Shin G, Jarrahi MH, Fei Y, Karami A, Gafinowitz N, Byun A, et al. Wearable activity trackers, accuracy, adoption, acceptance and health impact: A systematic literature review. J Biomed Inform. 2019 May;93:103153.
4. Mahloko L, Adebesin F. A Systematic Literature Review of the Factors that Influence the Accuracy of Consumer Wearable Health Device Data. In: Responsible Design, Implementation and Use of Information and Communication Technology. Springer International Publishing; 2020. p. 96–107.
5. Center for Food Safety, Nutrition A. Guidance on Developing and Using Databases for Nutrition Labeling.
6. Baron KG, Abbott S, Jao N, Manalo N, Mullen R. Orthosomnia: Are Some Patients Taking the Quantified Self Too Far? J Clin Sleep Med. 2017 Feb 15;13(2):351–4
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