Tracking Gaps Are Data Too

The days you don't log tell a story. Often a more important one than the days you do.

I’ve tracked my mood daily for months. My adherence rate? About 52%.

That means I logged roughly half the days and missed the other half. By most app standards, that’s a failure. My streak is terrible. If there was a leaderboard, I’d be near the bottom.

But here’s what I’ve realized: the days I didn’t log are some of the most informative data I have.

Why people stop logging

There’s a pattern to when I miss entries, and I don’t think it’s unique to me.

When I’m stable and doing well, I log consistently. It’s easy. I feel on top of things. The act of logging is mildly satisfying — a small ritual that confirms things are okay.

When I’m struggling — sleep disrupted, mood dropping, energy gone — logging is the first thing I skip. Not consciously. I don’t think “I’m too depressed to track my mood.” I just… don’t do it. The app notification comes and I swipe it away. Or I don’t even notice it. The routine breaks down because routine is the first casualty of an episode.

Which means my tracking data has a built-in bias. The logged days skew toward stability. The gaps skew toward difficulty. And if I only look at the logged data, I’m seeing a misleadingly stable picture of my mental health.

What gaps look like in the data

When I generate reports from my tracking data, gaps show up as discontinuities. The chart might show mood going from 6 to 5 smoothly, but if there are three unlogged days in between, the real trajectory might have dipped to 3 and come back up. I’ll never know because those days are invisible.

But the gaps themselves form a pattern. I went back and mapped when my tracking gaps occurred, and they clustered in predictable ways:

Around periods of high work stress
During depressive dips
When my sleep schedule was disrupted (late nights, shifted rhythms)
During transitions and upheaval

The gaps are the signal. A two-week stretch of consistent daily logging followed by five days of silence followed by a log entry with a low mood score — that tells a clear story even without the missing data. Something happened. It was bad enough to disrupt the routine. And by the time logging resumed, the damage was already visible.

Streak counters make this worse

Most tracking apps reward consistency with streak counters. Log every day for 7 days, get a badge. 30 days, get a bigger badge. Miss a day, streak resets.

For general habit building, fine. For mental health tracking, this is actively counterproductive.

Here’s why: when you break a streak because you were too depressed or destabilized to log, the app punishes you by resetting your counter. So now on top of feeling terrible, you also feel like you “failed” at tracking. Which makes you less likely to open the app the next day. Which makes the gap longer. Which means you lose even more data during the period where data matters most.

I don’t have streak counters in Steadyline. Deliberately. I don’t want anyone to feel like they failed because they missed a day during a hard stretch. Missing days is normal. It’s expected. And the app should handle it gracefully instead of making you feel guilty about it.

Using gaps productively

Instead of ignoring gaps, I’ve started using them as their own kind of data point.

When I look at a week where I missed three days of logging, I ask myself: what was happening? I might not have logged, but I usually remember the general picture. Was work stressful? Was I sleeping badly? Was there a specific trigger?

Sometimes I’ll retroactively add a rough entry for a missed day — not with precise numbers (I can’t remember my exact mood three days ago) but with a general note: “rough few days, sleep bad, skipped logging.” Even that is better than nothing. It preserves the signal that those days existed and weren’t good, rather than leaving a hole in the record.

More importantly, when I see a fresh gap forming in my tracking — two or three days without logging — I now treat that as a soft alarm. Not “oh no, I need to log right away” but “huh, I’ve stopped logging. Why? Is something going on that I should pay attention to?” The gap itself becomes a prompt for self-awareness.

What this means for design

If you’re building a mental health app, here’s my take: design for imperfect tracking.

Don’t assume daily logging. Don’t punish gaps. Don’t make the user feel bad about inconsistency. Instead, build systems that handle missing data gracefully. Interpolate where you can. Flag gaps as potential signals. Make it easy to do a quick retroactive entry.

And for the love of god, don’t use streak counters for anything related to serious mental health. The person who breaks a 30-day streak because they had a depressive episode doesn’t need a reset counter. They need the app to say “welcome back, we’re glad you’re here.”

The goal isn’t perfect data. The goal is enough data, captured honestly, including the honest acknowledgment that some days were too hard to capture at all.

52% is enough

My 52% tracking adherence gave me enough data to see real patterns, generate useful clinician reports, and make genuinely better decisions about my mental health. It wasn’t perfect. It was enough.

If you’re tracking your mental health and you miss days — that’s normal. You’re not failing. You’re being human. And if you’re smart about it, the days you missed can tell you just as much as the days you didn’t.

Steadyline is built for real tracking patterns — including the imperfect ones. No streak counters. No guilt. Just data that’s useful whether you log every day or every other day.