It’s 11:00 pm and cold outside. Mary taps her wrist and sees she is 1,000 steps short of her daily goal. For the last month she has been diligent about hitting her daily activity target. Even though her knee hurts and her body feels drained, she puts on warm clothes and goes for a late-night stroll around her neighborhood.
A thousand dreary steps later Mary returns home, freezing and uncomfortable. Figuring she deserves a small treat for those steps she just took, she heads to the kitchen. Although her snack more than compensates calorically for her brief walk, at least her wristband is flashing with a dazzling array of lights—she has made it to her daily step goal.
The next morning Mary walks into the gym and I ask her how she is feeling and whether she has stayed active. With a sigh, she tells me she’s made her step goal every day and has the logs to prove it. I applaud her accomplishment, but when I look closely at her tired face, I see that she is not doing as well as her steps might indicate.
What’s going on? Mary tells me that hitting her daily step count is often a burden and usually leads to more snacking throughout the day. Not only that, but work is stressing her out and she spends most of her walk ruminating over criticisms from her boss.
I pause for a second, since I was the one who recommended she wear an activity monitor. I’ve found that the Fitbit and similar devices can keep clients accountable when we are not together. I also thought that being able to chart her every move, seamlessly and effortlessly, and display her data in cool graphs and charts would keep Mary motivated.
I now see that what was supposed to be a benign and beneficial nudge to get her moving has caused more harm than good. It’s clear that many of Mary’s steps were taken in a state of resentment, obligation, discomfort or stress.
Her experience highlights how a technology-driven pursuit of fitness, with its numerical goals and statistical solutions, can sometimes be counterproductive to health. Getting caught up in Mary’s activity data while neglecting other dimensions of her well-being has brought me face to face with a simple truth: No matter what an activity tracker says, not all steps are created equal.
How Do These Bits Fit Into Personal Training
For personal trainers and couch potatoes alike, the ability to quantify our lives is powerful. However, when we become so engrossed in hitting our daily or monthly numerical targets, we can easily overlook the quality of our activities. It feels good when my Moves app says I’ve accumulated over 10,000 steps, but what was my experience while making those steps? Was I running around in a stressed-out frenzy, or was I laughing with a friend while walking through a park? Was I taking strenuous steps up a steep hill, or taking a slow downhill saunter?
Wearable fitness technology is constantly improving in its ability to distinguish between languishing steps and vigorous ones. New devices like the Microsoft Band and Samsung Simband incorporate more advanced sensors to tease out the subjective nuances of our daily activities: electrocardiogram to measure pulse and estimate blood pressure; bioimpedance to monitor blood flow to body fat; and galvanic skin response to measure stress levels (Samsung 2014). While these advances give us a fuller picture of the quality of our activities, for now the strength of wearables lies in their objectivity. What they do best is keep us honest about our habitual patterns of activity (or lack thereof).
The question is not whether activity monitors and daily step goals can help us establish new healthy behaviors; evidence says they can. A systemic review of over 26 studies found that pedometer users increased their physical activity walking by nearly 1 mile per day while also lowering their body mass index and blood pressure. This result, however, was seen only when people were given a daily step goal to hit, suggesting that data from activity monitors is not sufficient in and of itself to change people’s behavior (Bravata et al. 2007).
The question therefore remains: For our clients, and ourselves, how do we incorporate the data from these devices into a holistic framework of well-being that doesn’t promote fitness at the expense of health?
Appreciating the Complexity of Mind, Body and Lifestyle
Today we are using wearable monitors to quantify our activity in the same way we quantified nutrition in past decades. We used to ascribe to a reductionism that assumed 100 calories from food A was the same as 100 calories from food B, regardless of the larger nutritional context. This was true, but only part of the picture. We now know that total calories are one important factor in weight management, but the quality of our calories (i.e., how the food is grown, how much it is processed, whether it contains harmful additives, etc.) and their interaction with our genetics and lifestyle are equally important to our weight and health (Cooney 2013; Flier & Mekalanos 2009; Waterland 2014). Not all calories are created equal, and in the same way, not all steps have the same effect on our health and fitness.
With exercise, understanding the contextual lifestyle factors of sleep, stress, nutrition and attitude is important because they influence the dosage of activity (frequency, intensity, time and type, or F.I.T.T.) that will produce the desired effects. Too much exercise without adequate recovery can tip the hormonal cascade in favor of adrenal fatigue and catabolic processes that will eventually run people into the ground (Brooks & Carter 2013). Too little exercise and there’s not enough stimulus to elicit desired adaptations.
Every smart coach and trainer knows this, but what is often overlooked is how the same exercise can produce different effects depending on the person’s affect (emotional state) while exercising. Our emotions can drive our physiology by influencing our autonomic nervous system, shifting us into sympathetic or parasympathetic states based on our level of arousal and stress. In turn, our experience of being stressed or relaxed can influence production of glucocorticoids like cortisol much in the same way exercises can (Sauro, Jorgensen & Pedlow 2003).
These hormones impact our metabolism through insulin-mediated effects on adipose tissue, ultimately affecting body composition (Tsigos & Chrousos 2002; Egecioglu et al. 2011). It therefore makes sense to consider how feelings and emotions are affecting our hormonal balance, and how this relationship interfaces with our exercise activities in producing physical changes.
For example, a leisurely walk in a calm, natural setting with good company is likely to elicit the relaxation response in the body, producing a different neurochemical and hormonal response than a stressful walk would. A study done in Japan documented this reaction when people were asked to take walks in a forest (a calming environment) and a city (a stressful one). Researchers measured various biomarkers of stress before and after the jaunts. They found that when people walked in the forest, they tended to have lower cortisol levels, lower blood pressure and greater parasympathetic nerve activity than when they walked in the chaotic city environment, even though the level of physical exertion remained the same (Park et al. 2010).
This is not to say we’d be better off living in the woods, nor should we over-extrapolate that the effects of exercise are all in our heads. Rather, we need to acknowledge that the emotional and environmental context of our activities can profoundly influence how our body responds to the exercise stimulus.
In the quantified age it is easy to neglect this. But when that happens, the negative effects of emotional stress may begin to outweigh the positive effects of extra physical effort. Therefore, when technology promises to help us move more so we can live better, we must not
assume that taking “x” number of steps per day is going to benefit our health until we’ve considered the F.I.T.T. aspects and the subjective experience (e.g., attitude, emotions, mindset) of those steps.
The Pitfalls of Data-Driven Exercise
Data tracking can be a useful first step in behavior change; clients can’t change a current pattern until they become aware of it, and an activity monitor lets them see what they are doing. But an overquantified approach to fitness has pitfalls. As a fitness and wellness professional, you can teach your clients to recognize and address them:
The “more-is-always-better” attitude is flawed. As the adage goes, “More isn’t better. Better is better.” Clients need to understand how their effort to “go the extra mile” and log more steps may be counterproductive if it leads to compensatory eating, mental distress or physical burnout.
Data loses its allure. In the beginning, the razzle-dazzle of tracking steps or activities can be motivating. But as people become more accustomed to having this data on hand, expectations shift, and it is common to stop caring. According to a white paper released by Endeavour Partners, “More than half of U.S. consumers who have owned a modern activity tracker no longer use it. A third of U.S. consumers who have owned one stopped using the device within six months of receiving it” (Endeavour Partners 2014). Ways of counteracting this loss of interest include improving the quality of the exercise experience and increasing clients’ engagement with their data.
Tracking data is not sufficient by itself to accomplish lasting change. Data tracking raises awareness of behavior patterns and can prompt clients to begin the process of change, but on its own, is not enough to establish new, positive behaviors. If clients are to develop sustainable health habits, the mental and emotional aspects of behavior change must also be addressed.
Helping Clients Get the Most From Their Steps and Devices
Consider these recommendations to help clients use their wearable activity monitors for maximum overall well-being:
Highlight progress and build self-efficacy. Use wearable devices to highlight progress toward defined goals, and build clients’ confidence by shifting their attitude from seeing exercise as “a chore” to embracing it as part of who they are. A study found that the most important factor in helping previously sedentary adults maintain their walking habits was “making walking part of [their] lifestyle” (Coleman et al. 1999). Setting and hitting daily activity goals
can enable clients to build self-efficacy through small regular achievements. Moreover, clients can leverage the success from achieving several smaller goals into the momentum necessary for achieving bigger goals.
Encourage journaling during and after activities. If clients enjoy journaling (and don’t find it stressful), recommend that they write down one or two good things they experienced, noticed or accomplished while exercising (or suggest they record their observations during the activity). Also ask people to consider one way they could have made their activity better. This leverages the technology as an additional tool for introspection that can build a positive attitude around exercise.
Help clients interpret data and develop appropriate progressions/ regressions. Look at subjective recovery measures like appetite, sleep quality, tiredness and willingness to train. Help clients correlate these measures with the objective data from their activity monitors so they understand how their activities affect their energy and mood. Recommend ways to increase or decrease daily step goals depending on how the activity makes them feel.
Make steps meaningful. Encourage clients to walk in places, with people and in ways that bring them joy. Have them identify their favorite places to take a stroll and make a commitment to visit that place regularly. Inspire them to skip, hop, jump or dance the next time they are out walking. If they can complete an errand on foot, encourage them to walk. You can even challenge them to look for things along the way that they haven’t noticed before.
Next Step to Well-Being
We need to honor the beautifully complex interactions between body and mind if we want to fully reap the benefits of our activity. This means using the data from wearable activity monitors to deepen our understanding and appreciation of our bodies; it also means listening to our bodies, attending to our emotional well-being and recruiting our minds in the service of positive change.
Moving our way to more optimal living needs to be about more than just hitting an arbitrary number of steps; it needs to be a celebration of being alive. After all, our upright, bipedal nature is one of our defining human characteristics. Now, if we could design a device that tracks the number of times we laugh and smile while we walk, I’ll be the first in line to buy.
Bravata, D.M., et al. 2007. Using pedometers to increase physical activity and improve health: A systematic review. Journal of the American Medical Association, 298 (19), 2296-2304.
Brooks, K. A., & Carter, J. G. 2013. Overtraining, exercise, and adrenal insufficiency. Journal of novel physiotherapies, 3 (125).
Coleman, K.J., et al. 1999. Providing sedentary adults with choices for meeting their walking goals. Preventive Medicine, 28 (5), 510-19.
Cooney, C. A. 2013. Dietary effects on epigenetics with aging. In Watson & Preedy (Eds.), Bioactive Food as Dietary Interventions for the Aging Population (pp. 21-45). Waltham MA: Academic Press.
Egecioglu, E., et al. 2011. Hedonic and incentive signals for body weight control. Reviews in Endocrine & Metabolic Disorders, 12 (3), 141-51.
Endeavour Partners. 2014. Inside wearables: How the science of human behavior change offers the secret to long-term engagement. Accessed Jan. 9, 2015. (http://endeavourpartners.net/assets/Endeavour-Partners-Wearables-White-Paper-2014.pdf.
Flier, J.S., & Mekalanos J.J. 2009. Gut check: Testing a role for the intestinal microbiome in human obesity. Science Translational Medicine, 1 (6), 6-7.
Park, B.J., et al. 2010. The physiological effects ofShinrin-yoku (taking in the forest atmosphere or forest bathing): Evidence from field experiments in 24 forests across Japan. Environmental Health and Preventive Medicine, 15 (1), 18-26.
Samsung (Samsung Strategy & Innovation Center). 2014. Samsung’s Simband open reference design backgrounder [Press release]. Accessed Jan. 9, 2015. www.samsung.com/us/globalinnovation/pdf/Sa,simg_Simband_Backgrounder.pdf.
Sauro, M.D., Jorgensen, R.S., & Pedlow, C. 2003. Stress, glucocorticoids, and memory: A meta-analytic review. Stress, 6 (4), 235-45.
Siegel, M.A., & Beck, J. 2014. Slow change interaction design. Interactions, 21 (1), 28-35.
Tsigos, C., & Chrousos, G. P. 2002. Hypothalamic-pituitary-adrenal axis, neuroendocrine factors and stress. Journal of Psychosomatic Research, 53 (4), 865-71.
Waterland, R.A. 2014. Epigenetic mechanisms affecting regulation of energy balance: Many questions, few answers. Annual Review of Nutrition, 34 337-55.
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