R function to change value after a condition has been fulfilled - r

Question

Participants in an experiment took a test that has a rule that says "once a participant has gotten 6 items wrong in a window of 8 items, you stop running the test". However, some experimenters kept testing past this point. I now need to find a way in which I can automatically see where the test should have been stopped, and change all values following the end to 0 (= item wrong). I am not even sure if this is something that can be done in R.
To be clear, I would like to go row by row (which are the participants) and once there are six 0s in a given window of 8 columns (items), I would need all values after the sixth 0 to be 0 too.
While the reproducible data is below, here is a visualization of what I would need, where the blue cells are the ones that should change to 0:
Pre-changes
Post-changes
Reproducible data:
structure(list(Participant_ID = c("E01P01", "E01P02", "E01P03",
"E01P04", "E01P05", "E01P06", "E01P07", "E01P08", "E02P01", "E02P02"
), A2 = c(1, 1, 1, 0, 0, 1, 1, 1, 1, 1), A3 = c(1, 1, 0, 0, 0,
1, 0, 0, 0, 0), B1 = c(1, 1, 1, 0, 0, 1, 0, 0, 1, 1), B2 = c(1,
1, 1, 1, 1, 1, 0, 0, 0, 1), C3 = c(1, 0, 0, 1, 0, 1, 0, 0, 0,
1), C4 = c(1, 0, 0, 0, 0, 1, 0, 0, 1, 1), D1 = c(1, 0, 0, 0,
0, 1, 0, 0, 0, 0), D3 = c(1, 1, 1, 1, 0, 0, 1, 0, 0, 1), E1 = c(1,
0, 0, 0, 0, 1, 0, 0, 0, 1), E3 = c(1, 1, 0, 1, 0, 1, 0, 0, 0,
0), F1 = c(1, 0, 0, 0, 1, 0, 0, 1, 0, 0), F4 = c(1, 1, 1, 1,
0, 1, 0, 1, 1, 0), G1 = c(1, 0, 0, 0, 0, 1, 0, 0, 0, 1), G2 = c(0,
0, 0, 0, 1, 1, 1, 0, 1, 1)), row.names = c(NA, -10L), class = c("tbl_df",
"tbl", "data.frame"))
Any help is highly appreciated!

Answer 1

Here is a solution that involves some pivoting, rollsum, cumsum, if_else logic, then pivoting back. Let me know if it works.
library(tidyverse)
library(zoo)
structure(list(Participant_ID = c("E01P01", "E01P02", "E01P03",
"E01P04", "E01P05", "E01P06", "E01P07", "E01P08", "E02P01", "E02P02"
), A2 = c(1, 1, 1, 0, 0, 1, 1, 1, 1, 1), A3 = c(1, 1, 0, 0, 0,
1, 0, 0, 0, 0), B1 = c(1, 1, 1, 0, 0, 1, 0, 0, 1, 1), B2 = c(1,
1, 1, 1, 1, 1, 0, 0, 0, 1), C3 = c(1, 0, 0, 1, 0, 1, 0, 0, 0,
1), C4 = c(1, 0, 0, 0, 0, 1, 0, 0, 1, 1), D1 = c(1, 0, 0, 0,
0, 1, 0, 0, 0, 0), D3 = c(1, 1, 1, 1, 0, 0, 1, 0, 0, 1), E1 = c(1,
0, 0, 0, 0, 1, 0, 0, 0, 1), E3 = c(1, 1, 0, 1, 0, 1, 0, 0, 0,
0), F1 = c(1, 0, 0, 0, 1, 0, 0, 1, 0, 0), F4 = c(1, 1, 1, 1,
0, 1, 0, 1, 1, 0), G1 = c(1, 0, 0, 0, 0, 1, 0, 0, 0, 1), G2 = c(0,
0, 0, 0, 1, 1, 1, 0, 1, 1)), row.names = c(NA, -10L), class = c("tbl_df",
"tbl", "data.frame")) %>%
as_tibble() %>%
pivot_longer(-1) %>%
group_by(Participant_ID) %>%
mutate(running_total = zoo::rollsumr(value==0, k = 8, fill = 0),
should_terminate = cumsum(running_total >= 6),
value = if_else(should_terminate > 0, 0, value)) %>%
ungroup() %>%
select(Participant_ID, name, value) %>%
pivot_wider(names_from = name, values_from = value)