The Big-Mad Behavioral Study
Most people who feel worn down by apps, dashboards and timelines assume they are the problem. We think it is worth checking whether the work changed instead. This is a study of where that frustration goes, and it is not open yet.
01 · The question
Where does it go?
When your day runs on someone else’s software, what happens inside you, and where does it go next?
Sometimes it lands on the tool. Sometimes it lands on the people around you, a coworker, a customer, someone at home. Sometimes it lands back on you. And sometimes it just goes. The usual advice is better habits, better boundaries, a better attitude, all of which assume the problem is you. That may be true. It is also the explanation that costs the people who built the software nothing, which is a good reason to test it rather than take it on trust.
So the study asks one thing of each frustrating moment: where did most of it go? And it compares each person with themselves, moments with an app or a metric in them against moments without, so that who you are, what you do and how your week is going all cancel out.
02 · Taking part
Built for people who are already tired
A short screener, about a week of check-ins by text or voice note, and two tiny surveys. No essays, no login, no homework.
It is for anyone whose day is shaped by apps, dashboards, tickets, routes or metrics, in any job and at any comfort with technology: support, healthcare, delivery and the trades, office and remote roles, and jobs that barely touch a computer but still run on other people’s schedules. You do not need to know anything about AI. We want people with a lot of automation in their day, a little, and almost none.
You can skip a day, skip a question, or stop, without telling us why. It is unpaid, and we would rather say so here than let you find out later. What you get back is what everyone gets: the findings in plain language, the methods, and the limits. We never contact employers.
03 · What we expect
And what would prove us wrong
Before anyone takes part, we write down what we expect to find and how big a difference has to be to count. If we turn out to be wrong, we publish that too. Read the plan.
- H1
The main question
For the same person, a frustrating moment that involved an app, a dashboard, a metric or some automated system is more likely to land on people, someone else or themselves, than one that did not.
It counts only if the odds are at least one and a half times higher. Anything smaller, we report as no meaningful difference, however the statistics come out.
- H2
Second
For the same person, those moments also feel stronger.
At least half a point higher on the 0 to 10 scale people use to rate each moment.
- Ex
Exploratory, labelled so
Whether the difference is bigger for people whose work runs more on automation.
Too few people to test properly, so it is reported as a lead, never as a finding.
04 · The fine print
What it can’t tell you
No study is neutral. These are its limits, written down before there is any data to explain away.
- 01
People who sign up already feel something
An unpaid, public study draws people who have opinions about work and technology. That is why the main question compares each person with themselves, and why nothing we publish will claim how common anything is.
- 02
People report what they notice
If frustration with software is more memorable rather than more common, the moments people choose to tell us about will carry that. No design of this kind can remove it, so we say it first.
- 03
Association, not cause
A moment with an app in it may also be a busier moment. Comparing people with themselves removes what stays the same about them, not what changes from hour to hour.
- 04
People will drop out, and not at random
Unpaid daily check-ins lose people, and in a study about frustration, the frustrated may be the first to go. We will report who finished against who started, and we will not fill in the gaps.
- 05
Keeping track changes things
A week of noticing your frustration may change your frustration a little.
- 06
The result gets published either way
If the pattern is not there, that is the result, and it goes up in the same place, at the same length.
05 · Not open yet
What has to happen first
1 of 7 done. Nobody can take part until all of them are, and nothing has been collected.
A study about people living inside systems they did not design should not ask them to trust one either. So the order is fixed: the plan first, then the people who check our work, then you.
- 01
Done
Write the plan down
The question, the hypotheses, what would count as no effect, the analysis and its limits, all fixed before any data. Reviewed once against the experience-sampling literature by an AI reviewer, and disclosed as such.
- 02
Not yet
Try the questions on a few people
Ten to fifteen people we know, two or three days each, on the real text-message flow, to check that the four places frustration can go cover what people actually say. Their answers are never analysed, and none of them can join the study.
- 03
Not yet
File the plan with an independent registry
OSF Registries timestamps it and gives it a DOI, so anyone can check that we did not move the goalposts after seeing the answers.
- 04
Not yet
Independent ethics review
An outside review board reads the protocol, the consent and the plan for anyone who is upset by taking part, and approves them or sends them back.
- 05
Not yet
Consent and privacy, checked by a lawyer
Including what we would have to report, a separate permission for voice recordings, and how long anything is kept.
- 06
Not yet
A named person for anyone in distress
Someone who reads difficult entries and knows what to do, with crisis lines in every reply.
- 07
Not yet
Somewhere safe to keep answers
Contact details kept apart from what people tell us, names removed before analysis, and a deletion that actually deletes.
Read the plan, every hypothesis, rule and limit, in the words we will register. Or read the consent you would be asked to agree to, as it stands today.
Questions, objections and methodologists especially welcome: bob@goodcitizens.us.