Ever feel like you want to throw your phone across the room? No? Just us? 😳

If you’re like us (constantly fighting distraction), this might explain why. 🧵
People receive an average of 60-80 daily notifications on their phones.

While notifications have become a standard part of our lives, a constant barrage of information is also linked to ⬆️ anxiety, depression, and attention disorders.
Too many notifications make us feel tired, alter our perception of time, and harm our decision-making abilities! Why?

Notifications increase our #CognitiveOverload (the amount of information processed by the working memory).
In a recent study, 188 undergraduates did a survey while getting texts.

Students who got more texts interrupting their task experienced ⬆️ levels of impulsivity, inattention, and stress than those who got fewer texts. The science suggests notifications ruin your concentration.
Can we do better? Enter #Neuroergonomics, a collection of tactics and systems intended to relieve cognitive burden.

Some are behavioral (like spreading chores out through the week); some are designed (like batching notifications).
Batching smartphone notifications is especially helpful.

In a 2019 study, participants in three conditions received their notifications three times a day, hourly, or none at all. One group experienced more benefits than the other two.
The group that received normal notifications felt distracted.

The notification-free subjects experienced more anxiety and #FOMO.

The participants that received three daily 'batches' felt more productive, attentive, in a better mood, and in greater control of their phones.
Many UX researchers believe that more holistic #design is possible. We agree.

Developers should pay attention to how people interact with their devices—and align their products with actual user values and sustainable #engagement.
We think tech designers AND users have agency here. The key is good #BehavioralDesign.

Want to learn more? We analyzed the problem, and proposed a few solutions. 👇
irrationallabs.com/blog/dont-hate…

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with IrrationalLabs

IrrationalLabs Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @IrrationalLabs

Dec 9, 2021
Knowing these top 16 critical behavioral ideas could change your work—and your life. 🚨

We cover all of these in our bootcamps. And we wrote an essential primer. Read on! (THREAD 👇)
There are a lot of behavioral hacks, but we think these 16 are essential. They cover a few major categories:

+ Perceived Costs and Benefits
+ Attention and Effort
+ Cognitive Heuristics
+ Risk and Uncertainty
+ Choice Architecture
+ Norms and Influence

Learn all 16 below 👇
1. PRESENT BIAS: We live in the here and now, placing more value on the present than the future. It’s hard to delay gratification, even when we know it’s good for us. Think: hitting the snooze button even when it will make you late.
Read 20 tweets
Dec 7, 2021
How do you know if someone will pay you back?

Behavioral Scientist Allison White summarizes a recent paper from Wang, Drabeck and Wang that tries to discern the best predictor of loan repayment using "hard" and "soft" information about borrowers. (THREAD)
"Hard Information" describes financial metrics like assets, mortgages, and income.

"Soft Information" includes demographic characteristics like age, education, gender + race, as well as social networks, video interviews, profile pictures, and prior borrowing stories. /2
In a study on an online Chinese peer-based lending platform, RenrenDai.com, the researchers explored the role of soft information.

They created and tested the predictive power of three different models to predict default rates. /3 Image
Read 10 tweets
Feb 3, 2021
We designed an intervention that reduced shares of flagged content on TikTok by 24% via a large scale RCT, thread 👇1/7
We put a short prompt on videos that reminded people to think about the accuracy of the content they were watching. And then - when people went to share the video - we reminded them again that the video was flagged & asked them if they were sure they wanted to share. 3/7
Read 7 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us on Twitter!

:(