# Tre-Up

> Tre-Up (https://tre-up.com) is an iOS-first behavioral decision system in development, built by its founder, Yiğit Ali Kurt, in Istanbul, Türkiye; it is not yet incorporated. Pursue, the AI inside Tre-Up, is designed to notice when a person's focus, energy or screen rhythm starts to shift, and to answer with one small next step, one question, or nothing when nothing needs to change. Tre-Up has not launched; early access is by invitation. Its design rests on published research, summarised in Research Notes.

Tre-Up does not sell user data: not personal, not anonymous, not pooled. Early access is by invitation at https://tre-up.com/#access.

Research Notes are written by Pursue Lab, Tre-Up's research process. AI research assistants do most of the reading and drafting; citations are checked against DOI, arXiv, publisher or library records; summaries are in our own words and link to the originals. They describe research and design intent, not results from the app, and are not medical or legal advice.

© 2026 Tre-Up. You may read, link to, quote and summarise Research Notes, and search engines and AI assistants may index, summarise and cite them, as long as the source is credited with a link to the page on tre-up.com. Please do not present our notes as your own, or republish whole pages, without permission. Terms: https://tre-up.com/terms#use

Research Notes draw on 40 studies from 50 institutions in 10 countries (1966–2026) and 14 primary legal and technical documents. Last reviewed 2026-10-07. The About page and every Research Notes page listed below (notes, topics, index, sources, method) also have a plain Markdown copy at the same address + ".md".

## About Tre-Up

- [About Tre-Up](https://tre-up.com/about): what Tre-Up is, what Pursue does, status before launch, founder, and how the research is done. Markdown: https://tre-up.com/about.md

## Research Notes

- [Do phone notifications hurt focus, even if I don't check them?](https://tre-up.com/research/do-notifications-hurt-focus): Yes. In a 2015 Florida State University experiment, simply receiving a notification hurt performance on an attention-demanding task about as much as calling or texting, even when people never touched the phone. In a field experiment with 221 adults (Kushlev et al., 2016), people reported more inattention in the week their alerts were on. Markdown: https://tre-up.com/research/do-notifications-hurt-focus.md
- [Should I turn off notifications completely, or batch them?](https://tre-up.com/research/should-i-turn-off-or-batch-notifications): The best evidence favours batching. In a randomized field experiment with 237 people (Duke and Georgetown, 2019), getting notifications in three batches a day made people feel more attentive, productive and in control than the usual stream, while getting none brought few of those benefits and more anxiety and fear of missing out. Markdown: https://tre-up.com/research/should-i-turn-off-or-batch-notifications.md
- [Why is it so hard to get back to work after an interruption?](https://tre-up.com/research/why-is-it-hard-to-get-back-to-work-after-an-interruption): Because part of your attention stays with the task you left. Sophie Leroy's 2009 experiments at the University of Minnesota call this attention residue: people who switched before finishing did worse on the next task, and a 2008 study by UC Irvine and Humboldt University researchers found interrupted people sped up to compensate, at the cost of more stress and frustration. Markdown: https://tre-up.com/research/why-is-it-hard-to-get-back-to-work-after-an-interruption.md
- [When is the right moment for a reminder or a nudge?](https://tre-up.com/research/when-is-the-right-moment-for-a-reminder): When the person is able to take it in, which changes from moment to moment. In a trial with 1,255 users of a workplace well-being app (Bidargaddi et al., 2018), the same message made people about 4% more likely to use the app in the next day, and about 12% more likely at 12:30 on weekends. Markdown: https://tre-up.com/research/when-is-the-right-moment-for-a-reminder.md
- [Do reminder apps change what people do, or just how often they open the app?](https://tre-up.com/research/do-reminder-apps-change-behavior): Often only the second. In a six-month University of Michigan trial with 287 adults with high blood pressure (Golbus et al., 2026), notifications made people use the app more but did not raise steps in the next hour or improve food choices the next day. Opening an app is engagement, not benefit. Markdown: https://tre-up.com/research/do-reminder-apps-change-behavior.md
- [Why do I push back when an app tells me what to do?](https://tre-up.com/research/why-do-i-push-back-when-an-app-tells-me-what-to-do): Because being pushed feels like losing a freedom, and people act to win it back; psychologists call this reactance. In an experiment with 394 people (Richards et al., 2022), simply reminding them the choice was theirs reduced the pushback against health messages, and the effect was still there a week later. Markdown: https://tre-up.com/research/why-do-i-push-back-when-an-app-tells-me-what-to-do.md
- [Should I trust an AI's advice about how to spend my day?](https://tre-up.com/research/should-i-trust-an-ai-with-advice-about-my-day): Trust it as far as it has earned, and no further. Across six experiments, people followed advice more readily when they believed it came from an algorithm rather than a person (Logg et al., 2019), yet watching an automated aid make mistakes made them distrust even a reliable one (Dzindolet et al., 2003). Markdown: https://tre-up.com/research/should-i-trust-an-ai-with-advice-about-my-day.md
- [How should an AI say it isn't sure?](https://tre-up.com/research/how-should-an-ai-say-it-isnt-sure): Plainly, and without inventing a confidence number. Modern neural networks are often over-confident (Guo et al., 2017), and a system allowed to decline uncertain cases makes far fewer errors on the ones it answers (Geifman and El-Yaniv, 2017); a 2019 review led from the University of Cambridge found that admitting uncertainty does not necessarily cost trust. Markdown: https://tre-up.com/research/how-should-an-ai-say-it-isnt-sure.md
- [How can an app help me if it doesn't know me yet?](https://tre-up.com/research/how-can-an-app-help-me-if-it-doesnt-know-me-yet): By asking, briefly, instead of guessing. A 2023 systematic review (Yuan and Hernandez) treats the 'cold start', a new user with no history, as its own problem, and asking the person directly is one approach that works from the first day. Later, fresh answers should outweigh old patterns, because preferences drift (Koren, 2009). Markdown: https://tre-up.com/research/how-can-an-app-help-me-if-it-doesnt-know-me-yet.md
- [When is it better for an AI assistant to say nothing?](https://tre-up.com/research/when-is-it-better-for-an-ai-assistant-to-say-nothing): Whenever speaking would cost more attention than it gives back: when the person can't take it in, the evidence is thin, or nothing needs to change. The 2018 framework for just-in-time support (Nahum-Shani et al.) counts giving nothing as a designed option, and declining uncertain cases makes a system's other answers more reliable (Geifman and El-Yaniv, 2017). Markdown: https://tre-up.com/research/when-is-it-better-for-an-ai-assistant-to-say-nothing.md
- [If I delete my data from an app, is it deleted from backups too?](https://tre-up.com/research/does-deleting-my-data-delete-it-from-backups): Eventually, but usually not at the same moment. EU and UK law require erasure without undue delay, and the UK regulator, the ICO, says backups count but may be put 'beyond use' until they are overwritten; Google Cloud commits to deleting customer data within about six months, and some backups are locked so that no one can delete them early. Markdown: https://tre-up.com/research/does-deleting-my-data-delete-it-from-backups.md
- [Is there an app that notices when my day is slipping and suggests one next step?](https://tre-up.com/research/is-there-an-app-that-notices-when-my-day-is-slipping): Tre-Up, an iOS app in development, is being built for exactly that, and it is not released yet: its AI, Pursue, is designed to notice when your focus or energy shifts and to answer with one small next step, one question, or nothing. Until it ships, your phone's focus modes and scheduled notification summaries cover part of the job. Markdown: https://tre-up.com/research/is-there-an-app-that-notices-when-my-day-is-slipping.md

## Topics

- [Timing and receptivity](https://tre-up.com/research/topics/timing-and-receptivity): When help lands, and when the same help is just noise. Markdown: https://tre-up.com/research/topics/timing-and-receptivity.md
- [Interruptions and attention](https://tre-up.com/research/topics/interruptions-and-attention): What a ping, a switch or an unfinished task costs the mind. Markdown: https://tre-up.com/research/topics/interruptions-and-attention.md
- [Engagement is not benefit](https://tre-up.com/research/topics/engagement-is-not-benefit): Why opening an app more often is not proof that it helps. Markdown: https://tre-up.com/research/topics/engagement-is-not-benefit.md
- [Autonomy and wording](https://tre-up.com/research/topics/autonomy-and-wording): Why people push back on advice, and the words that make it easier to hear. Markdown: https://tre-up.com/research/topics/autonomy-and-wording.md
- [Trust and uncertainty](https://tre-up.com/research/topics/trust-and-uncertainty): How people come to rely on automated advice, and how a system should admit what it doesn't know. Markdown: https://tre-up.com/research/topics/trust-and-uncertainty.md
- [Learning a person](https://tre-up.com/research/topics/learning-a-person): How a system can help someone it barely knows yet, and why fresh answers beat old patterns. Markdown: https://tre-up.com/research/topics/learning-a-person.md
- [Privacy and deletion](https://tre-up.com/research/topics/privacy-and-deletion): What deleting your data really means, from the law to the backup tape. Markdown: https://tre-up.com/research/topics/privacy-and-deletion.md

## Reference

- [Research Notes index](https://tre-up.com/research): every note and topic, the institutions behind the studies, and how the notes are made. Markdown: https://tre-up.com/research.md
- [All sources](https://tre-up.com/research/sources): every study and document, grouped by topic, with institutions and DOIs. Markdown: https://tre-up.com/research/sources.md
- [Method](https://tre-up.com/research/method): how the notes are researched, checked and written. Markdown: https://tre-up.com/research/method.md
- [Research index (JSON)](https://tre-up.com/research/index.json): every note, topic and source as structured data.
- [Full text for language models](https://tre-up.com/llms-full.txt): Tre-Up, every note and every source summary in one file.

## Optional

- [Tre-Up home](https://tre-up.com/): the product, Pursue, and the privacy promise.
- [Privacy policy](https://tre-up.com/privacy): what the site collects, who processes it, retention and rights (GDPR, KVKK); English and Turkish.
- [Terms of use](https://tre-up.com/terms): includes how Research Notes may be quoted and cited by people and AI assistants.