No meaningful relationship! (see code below.) However, big caveat here that we had to guess on some of the samples because many studies do not report how many subjects or meals were treated (e.g. they report how many restaurants or days were assigned to treatment and control but didn't count how many people participated)

> summary(lm(d ~ total_sample, data = dat))

Call:
lm(formula = d ~ total_sample, data = dat)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.59897 -0.13702 -0.01868  0.12322  0.75767 

Coefficients:
                Estimate  Std. Error t value Pr(>|t|)  
(Intercept)   0.06330835  0.02664964   2.376   0.0193 *
total_sample -0.00002876  0.00004690  -0.613   0.5410  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.2474 on 110 degrees of freedom
Multiple R-squared:  0.003407,	Adjusted R-squared:  -0.005653 
F-statistic: 0.376 on 1 and 110 DF,  p-value: 0.541

Delay indicates the number of days that have elapsed between the beginning of treatment and the final outcome measure. How outcomes are measured varies from study to study, so in some cases it's a 24 hour food recall X number of days after treatment is administered (the last part of it), in others it's a continuous outcome measurement in a cafeteria (the entire period of delay). 

I don't know this, sorry, and not every study reports enough location data to begin to estimate this (e.g. studies that recruit an online sample from multiple countries)

This I can say more about!

The median delay, in days, is 14, and the mean is 52 (we have a few studies with long delays, the longest is 3 years (Jalil et al. 2023). 

So I'd say, think "about 2 weeks on average with some lengthy outliers". Also there's basically no relationship between delay and effect size.

to replicate in R (from the root directory of our project):

> source('./scripts/libraries.R')
> source('./scripts/load-data.R')
> summary(dat$delay)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   4.00   11.50   14.00   52.05   60.00 1095.00 
   
> source('./functions/sum-lm.R') # this is a little function we wrote that puts summary(lm()) into a dplyr-friendly pipe
> dat |> sum_lm(y = d, x = delay)
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.05312    0.02552 2.08181  0.03968
delay        0.00005    0.00019 0.23166  0.81723

Hi Vasco, I'm afraid not, sorry. The diversity of outcome measures makes this all but impossible, e..g one study measures "servings of meat per week", others measure actually measure it by the gram, others count how many meals are served in a given time period, etc. 

Thank you David! We will post any updates to https://doi.org/10.31219/osf.io/q6xyr

The paper is currently under submission at a journal and we likely won’t modify it until we get some feedback.

$3500 to Animal Charity Evaluators

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$500 to Direct Action Everywhere

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Definitely! When I went vegan, I prompted someone I know to look up how dairy cows are treated (not well), and they changed their diet quite a bit in light of that. So I have seen downstream effects personally.  Caveat that I am annoying and prone to evangelize.

And if i were going to promote one definitely-not-scalable intervention to one very-hard-to-reach-population, I would take a bunch of die-hard meat eaters to Han Dynasty on the upper west side of Manhattan and order 1) DanDan noodles without pork 2) pea leaves with garlic 3) cumin tofu 4) kung pao tofu and 5) eggplant in garlic sauce for the table,  and then just be "like hello is this not delicious??" every 30 seconds 😃

I don’t know, sorry. There would be a lot of additional assumptions needed to extrapolate from the RCTs we analyze to this.

That sounds very interesting!

Making things more pleasant for vegetarians and vegans is a good thing to do, even if it does not change other people's behavior too much. 

In the long-run, we want to make vegetarianism seem just as "nice, natural, and normal" (https://www.sciencedirect.com/science/article/abs/pii/S0195666315001518) as eating meat. 

I think things like a Meatless Monday Lunch are very helpful for that.