Track it to change it: why the act of measuring works

The moment you start counting

There is a particular moment most of us know. You decide to walk more, so you put your phone in your pocket and start counting steps. For the first week the number is a quiet thrill. Then one evening you notice you have taken the long way home, not because you wanted the air, but because you were three hundred steps short of a figure that a machine decided mattered. Something has shifted. The walk used to be the point. Now the number is.

That small shift is the whole story of this post. Measuring your progress towards a goal genuinely makes you more likely to reach it, and the effect is stronger when you write the progress down rather than just clock it in your head. But measurement is not free, and the people selling you trackers rarely mention the bill.‍ ‍

Why measuring changes what you do

The clearest explanation comes from control theory, set out by Charles Carver and Michael Scheier in 1982. Their idea is almost mechanical, and better for it. Whenever you are trying to reach a goal, your mind runs a feedback loop. It compares where you are now against a reference point, the standard you are aiming for, and if it detects a gap it nudges your behaviour to close it. Set a goal to walk more and every glance at the step count is a comparison. Behind is a signal to move. On track is a signal to keep going.

The important part is that the comparison only works if you actually take the reading. A goal with no monitoring is a thermostat with no thermometer. It knows the temperature it wants and has no idea what the room is doing. This is why simply wanting something changes so little, a theme running through this whole series. Wanting sets the standard. Monitoring is what turns the standard into action. ‍

What the research actually found

‍The strongest evidence here is a meta-analysis led by Benjamin Harkin at the University of Sheffield, published in 2016. His team pulled together 138 studies covering 19,951 people, and crucially they only used experiments that randomly assigned people either to monitor their progress or not, which is what lets you talk about cause rather than coincidence.‍ ‍

Two findings stand out. First, prompting people to monitor really did increase how often they checked their progress, and the size of that change was large. Second, that increased monitoring fed through into hitting the goal itself, and here the benefit was consistent but moderate rather than dramatic. Reassuringly, when the authors tested whether the result was inflated by the usual tendency to publish only flattering findings, the adjusted estimate barely moved, which suggests the effect is real rather than an artefact. whiterose

This lines up with older work on what actually makes health programmes tick. A meta-regression by Susan Michie and colleagues in 2009 pooled 122 evaluations covering 44,747 people and found that self-monitoring was the single technique that explained the most difference between what worked and what did not. Programmes that paired self-monitoring with at least one other self-regulation technique clearly outperformed those that did not. Tracking is not a nice-to-have bolted onto behaviour change. It is closer to the engine.

The part most trackers get wrong

Harkin's team also tested what made monitoring work better, and one finding matters more than the rest. Monitoring had a bigger effect on goal attainment when the progress was physically recorded, and bigger again when it was reported to other people, rather than just noticed privately. A number you write down is harder to fudge, harder to forget, and harder to gloss over when the news is bad. ResearchGateWhite Rose Research Online

Interestingly, it made little difference whether people tracked the behaviour or the outcome. What mattered was that the reading was captured somewhere real. That single detail is the difference between a tracker that works and a mental note that quietly evaporates. White Rose Research OnlineAPA

What this looks like in real life

The weight-loss literature makes it concrete. In a two-year trial of 210 people led by Lora Burke, those who kept up their food records at least sixty per cent of the time lost significantly more weight than those who recorded less than thirty per cent of the time. Later work found the same pattern with electronic logging, where people who logged more often were more likely to lose a meaningful amount of weight. The recording itself, not just the intention behind it, tracked the result.

On the question of paper versus phone, the honest answer is that the recording matters more than the format. Some trials find app users stick with logging for longer than people using paper diaries, which can translate into better results over several months, but the effect is about sticking with it rather than any magic in the technology. A diary you keep beats an app you abandon. PubMed

The costs nobody prints on the box

Here is the part the wellness industry tends to skip. In 2016 Jordan Etkin published six experiments in the Journal of Consumer Research showing that measuring an activity can quietly spoil it. When people counted their steps, or the shapes they coloured, or the pages they read, they did more of the activity. They also enjoyed it less, felt it had become more like work, and afterwards reported lower wellbeing. In one telling experiment, once the counter was taken away, people who had been tracking did less than those who never tracked at all. The measurement had eaten into the very motivation that made the activity worth doing. upenn + 3

This is not a fringe result. It sits on decades of work on what psychologists call the overjustification effect, the finding that dangling an external reason for an enjoyable activity can crowd out the internal one. A large meta-analysis by Edward Deci and colleagues in 1999 confirmed that tangible rewards reliably undermine intrinsic motivation. Etkin's contribution was to show that a bare number, with no reward attached, can do something similar. The honest caveat is that the effect showed up for activities people already enjoyed, and did not appear every single time, so this is a real risk rather than an iron law. upenn + 2

There is a more serious version of this, and a wellness brand has no business tiptoeing around it. Several studies have linked calorie and food tracking to disordered eating. In one study of 493 college students, those who used calorie trackers reported higher levels of eating concern and dietary restraint even after accounting for body mass, and fitness tracking was independently linked to eating disorder symptoms. In another, among 105 people already diagnosed with an eating disorder, around three quarters had used the calorie-counting app MyFitnessPal, and of those, nearly three quarters felt it had contributed to their condition. These studies are correlational and cannot prove that tracking causes eating disorders, since people already prone to disordered eating may simply be drawn to these tools. But the association is strong enough that the caution stands. If tracking food or weight starts to feel compulsive, or to sharpen anxiety rather than settle it, that is a signal to stop, not to try harder. Break Binge Eating

The streak deserves a word too. Streaks work by borrowing the sting of loss aversion, the well-established fact that losing something hurts more than gaining the same thing feels good. That sting is exactly what makes a broken streak land so hard, and it can turn one missed day into a reason to abandon the whole effort. It is worth remembering from earlier in this series that missing a single day does not meaningfully harm habit formation. A tool that tells you otherwise is measuring your guilt, not your progress. It is also worth knowing that around a third of people abandon their trackers within the first several months, so building a routine that can survive without the device is the real goal. Thebrink

What to track, and what to leave alone‍ ‍

The practical line falls in a sensible place. Track the things you are trying to change and do not naturally love, such as a savings target, a medication schedule, a couch-to-something plan. For those, the number is doing useful work, and writing it down does more than noticing it. Be far more careful with things you do for pleasure. If you love your morning run, counting every split may slowly turn it into a chore. And be most careful of all with food and weight, where the costs can be real. Track for a season to learn something, then let the number go once the behaviour holds on its own.‍ ‍

A short note on Rise Habits

We should be straight about the obvious tension. Rise Habits is a tracker, and this post has just spent several hundred words on the evidence that tracking can cost you something. We think both things are true at once. The measuring genuinely helps, and it can quietly take the joy out of things if you let it run your life. That is why Rise Habits counts your consistency over weeks rather than lighting up a fire alarm the moment you miss a day, because the science says one missed day barely matters and the guilt does more harm than the gap. Use it while it earns its place, and put it down when the habit no longer needs it.

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References

Burke, L.E., Wang, J. and Sevick, M.A. (2011) 'Self-monitoring in weight loss: a systematic review of the literature', Journal of the American Dietetic Association, 111(1), pp. 92-102. doi: 10.1016/j.jada.2010.10.008.

Carver, C.S. and Scheier, M.F. (1982) 'Control theory: a useful conceptual framework for personality-social, clinical, and health psychology', Psychological Bulletin, 92(1), pp. 111-135. doi: 10.1037/0033-2909.92.1.111.

Deci, E.L., Koestner, R. and Ryan, R.M. (1999) 'A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation', Psychological Bulletin, 125(6), pp. 627-668. doi: 10.1037/0033-2909.125.6.627.

Etkin, J. (2016) 'The hidden cost of personal quantification', Journal of Consumer Research, 42(6), pp. 967-984. doi: 10.1093/jcr/ucv095.

Harkin, B., Webb, T.L., Chang, B.P.I., Prestwich, A., Conner, M., Kellar, I., Benn, Y. and Sheeran, P. (2016) 'Does monitoring goal progress promote goal attainment? A meta-analysis of the experimental evidence', Psychological Bulletin, 142(2), pp. 198-229. doi: 10.1037/bul0000025. [Frequency of monitoring d+ = 1.98, 95% CI 1.71 to 2.24; goal attainment d+ = 0.40, 95% CI 0.32 to 0.48.]

Levinson, C.A., Fewell, L. and Brosof, L.C. (2017) 'My Fitness Pal calorie tracker usage in the eating disorders', Eating Behaviors, 27, pp. 14-16. doi: 10.1016/j.eatbeh.2017.08.003.

Michie, S., Abraham, C., Whittington, C., McAteer, J. and Gupta, S. (2009) 'Effective techniques in healthy eating and physical activity interventions: a meta-regression', Health Psychology, 28(6), pp. 690-701. doi: 10.1037/a0016136. [122 evaluations, N = 44,747; pooled effect 0.31, 95% CI 0.26 to 0.36; self-monitoring plus another control-theory technique 0.42 vs 0.26.]

‍Simpson, C.C. and Mazzeo, S.E. (2017) 'Calorie counting and fitness tracking technology: associations with eating disorder symptomatology', Eating Behaviors, 26, pp. 89-92. doi: 10.1016/j.eatbeh.2017.02.002.