Hello everyone!

Daylivia brings everyday self-care into one place: build or break habits, check in with your mood, and keep a journal, with support for guided journaling prompts when you’d like a little help getting started.

Who is it for?

Anyone looking to build better routines, break unwanted habits, improve their mental well-being through journaling and healthier habits, and understand themselves better over time through the power of their own data.

As you use the app, you can explore patterns in your data, like how your habits, sleep, and everyday activities tend to relate to your mood, how your mood changes over time, and what often shows up on better or harder days.

Privacy

Daylivia works offline, requires no account, and your personal data stays fully private on your device. Your habits, mood logs, and journal entries are stored locally, and you can export your data whenever you like.

🎁 Giveaway

I’m giving away Lifetime access ($59.99 → Free) for the next 72 hours to find early adopters and gather feedback to help improve the app and ship features users actually want.

Spots are limited. First come, first served.

How to claim:

1. Upvote the post and leave a comment to help more people find the giveaway.
2. Download Daylivia here: https://apps.apple.com/app/apple-store/id6794620176?pt=129197952&ct=Freebie&mt=8
3. Redeem the offer here: https://apps.apple.com/redeem?ctx=offercodes&id=6794620176&code=LIFETIME

Alternatively, you can redeem your free Lifetime offer by opening the paywall, tapping “Redeem Code” at the bottom, and entering the code 'LIFETIME'.

Your feedback is super valuable and will help improve and shape the app.

To send feedback, you can DM me or send a message through Settings → Feedback in the app. I’d love to hear your thoughts :)

Thank you all for the support!

I’ve been looking into the relationship between sleep and mood because it’s also one of the relationships I’m interested in measuring through Daylivia.

The intuitive assumption is simple: sleep better, feel better tomorrow.

But I wanted to see how well that actually holds up when the same people are measured repeatedly in their everyday lives.

A 2026 meta-analysis combined 118 intensive longitudinal studies using daily diaries, ecological momentary assessments, and both subjective and objective sleep measurements.

The overall result was that better subjective sleep quality and longer sleep duration were associated with better next-day affect. The reverse relationship existed for subjective sleep quality, but was weaker. More positive affect and less negative affect during the day were modestly associated with better subjective sleep quality, but not with subsequent total sleep time.

Sleep and mood: what the studies actually found

Research	Participants / data	Finding
Bourke et al. (2026)	118 studies	Better subjective sleep quality and longer sleep predicted better next-day affect. More positive affect and less negative affect during the day were modestly associated with better subjective sleep quality, but not with subsequent total sleep time.
Triantafillou et al. (2019)	208 recruited adults; 206 analyzed; planned 6-week ecological momentary assessment study	Within-person normalized mixed-effects model coefficient for sleep quality → next-day mood: 0.344. Mood → subsequent sleep quality: 0.132. Both p<.001.
Barber et al. (2023)	Two MIDUS subsamples: 2,022 + 782 adults × 8 days	Shorter sleep predicted greater next-day negative affect in both samples. Negative affect did not significantly predict subsequent sleep duration.
Sin et al. (2020)	1,982 adults × 8 days	Within-person sleep duration correlated −0.08 with negative affect and +0.06 with positive affect. Sleep duration correlated −0.06 with whether a daily stressor occurred that day. All p<.001.

That Triantafillou result caught my attention.

When they looked at differences within the same individual, rather than comparing one person’s absolute ratings against another’s, the sleep → mood relationship was substantially larger. These coefficients came from within-person normalized mixed-effects models:

Direction	Within-person coefficient	p
Sleep quality → next-day mood	0.344	<.001
Mood → subsequent sleep quality	0.132	<.001

The researchers also tested possible confounders including previous mood and sleep, stress, energy, focus, physical activity, weather, work/day type, and day of the week. Accounting for those measured variables did not significantly change the average relationship.

More sleep wasn’t simply better

The Barber study gives another interesting result.

They analyzed two MIDUS subsamples of 2,022 and 782 adults and found the relationship between sleep duration and next-day negative affect wasn’t linear:

Previous night’s sleep	Next-day negative affect
<7.5 hours	Higher
7.5–10.5 hours	Lower
&gt;10.5 hours	Higher

So their data didn’t support a simple “more sleep = better mood” relationship. Both the shorter and very long sleep ranges were associated with greater next-day negative affect compared with the middle range.

That doesn’t mean 7.5–10.5 hours is some universal optimal range - the authors were analyzing associations within these particular samples - but it shows why reducing sleep to “hours = good” can hide useful information.

Sleep may also change how you react to your day

Sin et al. followed 1,982 adults for eight consecutive days.

Their within-person correlations were:

Same-person daily relationship	r
Sleep duration ↔ negative affect	−0.08*
Sleep duration ↔ positive affect	+0.06*
Sleep duration ↔ whether a daily stressor occurred	−0.06*

* p≤.001

The daily-stressor measure referred to whether a stressor occurred that day, coded 0/1, rather than to a continuous measure of stress intensity.

Those are small correlations, but their more interesting finding was about affective reactivity.

When people slept less than usual, stressful events the following day were associated with a greater loss of positive affect. Positive events also produced a smaller increase in positive affect.

So sleep might not only relate to whether tomorrow’s mood is higher or lower. It may also relate to how your mood responds to what actually happens tomorrow.

This is where personal tracking gets interesting to me

These studies can tell us what tends to happen across thousands of people.

They can’t necessarily tell me:

• Is my mood more closely related to sleep quality or sleep duration?
• Is 6.5 vs 8 hours meaningful for me?
• Does going to bed late matter even when I sleep the same number of hours?
• Does my apparent sleep/mood correlation disappear when stress, exercise, symptoms, or another factor is considered?
• Is the relationship linear at all?

And a correlation in personal data obviously doesn’t establish causation. Reverse relationships, common causes, delayed effects, and variables you aren’t tracking can all produce patterns.

But that’s also what makes longitudinal self-tracking interesting to me: you’re asking what repeatedly happens within your own baseline, rather than assuming a population average describes you.

One of our internal beta testers agreed to let me share two anonymized screenshots from his August tracking. The clearest pattern in this month was that his mood was highest after 7-8 hours of sleep, with 8-9 hours very close behind. Nights below 6 hours were noticeably worse.

Across the month, the correlation between last night’s sleep duration and the following day’s mood was modest (r = 0.268). The sleep window itself was less clear - there wasn’t one bedtime that consistently produced a better mood. In this case, getting enough sleep seemed more important than going to bed at one exact time.

This is part of why We've built Daylivia

Daylivia is a private life-tracking app we’ve been working on that was recently released on the App Store. It lets you track sleep, mood, habits, activities, and factors such as symptoms, emotions, stress, weather, or anything else relevant to you.

Rather than keeping these as isolated logs, Daylivia aggregates and correlates what you track so you can investigate relationships within your own day to day data.

So instead of only seeing “I slept 7 hours,” you can look at how your sleep duration and perceived sleep quality relate to your mood and how other factors you track relate to those patterns.

Everything is stored locally using SQLite. Daylivia works fully offline, requires no account, and your data stays on your device unless you choose to export it. Data can be exported as CSV or JSON, with PDF export also available for mood entries.

We sincerely hope you find Daylivia useful in your day to day life. We’re also happy to give promotional access to early adopters from this community who would like to try all of the app’s premium features at no cost. Just DM me and I’ll be happy to help you with that.

We’d love to hear your feedback as well. We want to keep iterating on Daylivia and make it genuinely more useful for people who care about understanding their own data.

For people here who already track both:

Do you see a noticeable sleep → next-day mood relationship in your own data? And is sleep duration or perceived sleep quality more strongly related for you?

Daylivia App

Download on the App Store | Website | Privacy

Research

Bourke et al. (2026) — Sleep well, feel well and vice versa? A meta-analysis of daily bidirectional within-person associations between sleep and affect
https://www.sciencedirect.com/science/article/pii/S1087079226000043
https://pubmed.ncbi.nlm.nih.gov/41570755/

Triantafillou et al. (2019) — Relationship Between Sleep Quality and Mood: Ecological Momentary Assessment Study
https://mental.jmir.org/2019/3/e12613
https://pubmed.ncbi.nlm.nih.gov/30916663/

Barber, Rackoff & Newman (2023) — Day-to-Day Directional Relationships Between Sleep Duration and Negative Affect
https://pmc.ncbi.nlm.nih.gov/articles/PMC10529882/
https://pubmed.ncbi.nlm.nih.gov/37478504/

Sin et al. (2020) — Sleep Duration and Affective Reactivity to Stressors and Positive Events in Daily Life
https://pmc.ncbi.nlm.nih.gov/articles/PMC7704897/
https://pubmed.ncbi.nlm.nih.gov/32897097/

 Hello everyone!

I’m the founder of Daylivia, and we’re very excited to launch our new iOS app for tracking your everyday life and understanding yourself better.

With Daylivia, you can:

• Track habits you want to build or break 
• Check in with how you feel throughout the day 
• Log the activities you do and daily factors such as energy levels or symptoms 
• Record your sleep 
• Journal your thoughts and cherish your memories 
• Discover what helps you feel better and understand your patterns

 

Most habit trackers and mood trackers track data in isolation. They do not tell you what tends to move the needle for you, what tends to make you happier or help you sleep better, or which habits, activities, and factors tend to be correlated with each other.

Daylivia brings these different parts of your day together to help you understand yourself better, while supporting you in building the routines you’d like to have, journaling your thoughts and memories, and understanding your mood and sleep patterns over time.

Privacy is super important to us. Daylivia requires no account, works offline, and your personal tracking data stays on your device unless you choose to export it. All of the analysis happens on-device, and we don’t use any AI.

Links: Appstore | Website | Privacy

We’d also love to hear your feedback as we continue making Daylivia as useful as possible for understanding your days and building better routines.

Thank you for taking the time to check out Daylivia! If you have any questions, feel free to leave them in the comments or send me a DM - I’ll be happy to answer.

Hello everyone!

I’m the founder of Daylivia, and we’re very excited to launch our new iOS app for tracking your everyday life and understanding yourself better.

With Daylivia, you can:

• Track habits you want to build or break
• Check in with how you feel throughout the day
• Log the activities you do and daily factors such as energy levels or symptoms
• Record your sleep
• Journal your thoughts and cherish your memories
• Discover what helps you feel better and understand your patterns

Most habit trackers and mood trackers track data in isolation. They do not tell you what tends to move the needle for you, what tends to make you happier or help you sleep better, or which habits, activities, and factors tend to be correlated with each other.

Daylivia brings these different parts of your day together to help you understand yourself better, while supporting you in building the routines you’d like to have, journaling your thoughts and memories, and understanding your mood and sleep patterns over time.

Privacy is super important to us. Daylivia requires no account, works offline, and your personal tracking data stays on your device unless you choose to export it. All of the analysis happens on-device, and we don’t use any AI. You can learn more about Daylivia here.

We’d love for you to give it a try! Daylivia is free to download from the App Store

We’d also love to hear your feedback as we continue making Daylivia as useful as possible for understanding your days and building better routines.

Thank you for taking the time to check out Daylivia! If you have any questions, feel free to leave them in the comments or send me a DM - I’ll be happy to answer.