Writing
The link between sleep and mood, and how to test it on yourself
That sleep affects mood is well established. What that means for you specifically — how much, at what threshold — is not, and is testable.
What is well established
The relationship between sleep and next-day mood is one of the sturdier findings in this area. It shows up in experimental sleep restriction studies, in daily-diary studies where people report both over weeks, and in the clinical literature, where sleep disturbance is entangled with mood disorders closely enough that it appears as both a symptom and a risk factor.
It also appears to run in both directions. Poor sleep degrades next-day mood; low mood degrades that night's sleep. This matters for interpretation, because a correlation you find in your own data will not tell you which way the arrow points — and in this particular case there is good reason to think it points both ways.
What is not established, for you
Population averages describe populations. They are a poor guide to an individual, and the size of the individual differences here is large.
Your threshold is a specific example. "Adults need seven to nine hours" is a population range, not a personal prescription — some people are genuinely fine at six and a half, some are impaired at seven and a half, and the average tells you which is more common, not which you are. The same applies to whether duration or consistency matters more for you, and to how long the effect lasts.
None of that is knowable from an article. It is knowable from a few weeks of your own paired records.
How to actually test it on yourself
Record both sides daily, at a fixed time. Mood is best captured at a consistent point — evening works for most people — because a score taken at 8am and one taken at 11pm are not measuring the same thing, and mixing them adds noise you will later mistake for signal.
Pair the right days. Last night's sleep against today's mood is the comparison you want if you are asking whether sleep drives mood. Getting the offset wrong is the most common way a personal analysis of this ends up meaningless.
Collect at least 20 paired days before drawing anything. Below that a correlation coefficient swings wildly on single observations, and you will find a strong-looking relationship in ten days of data that evaporates in thirty.
Decide in advance what you are testing. If you compute every possible comparison and report whichever looks strongest, you will find something — that is guaranteed by the number of comparisons, not by your data. Deciding the question first is what makes the answer mean anything.
Expect nothing, often. A null result after a month is a real and common outcome. It is more informative than a spurious finding, because acting on a spurious finding costs you weeks.
Reading the number you get
A correlation coefficient runs from -1 to 1. For self-tracked daily data, anything above about 0.25 in absolute value is worth attention and anything above 0.4 is strong for this kind of noisy, single-subject measurement. Do not expect 0.8; that is not what human behavioural data looks like.
And the coefficient alone is not enough. You need the sample size beside it and a p-value corrected for how many comparisons you ran. A coefficient of 0.5 over 12 days and one of 0.3 over 90 days are very different claims, and only one of them survives contact with more data.
This is the work Crescendo does automatically — pairing the days, applying the offset, holding the hypotheses fixed in advance, correcting for the number of tests, and showing the coefficient and sample size on every card whether or not it cleared the threshold. But none of it requires the app. A spreadsheet and a month of honest recording will answer the question too.