As pointed out in an earlier comment, raising the compensation for challenge trials and/or seeking out participants with lower ‘willing participation price’ seems promising as a way to get enough participants.
I would be interested to see an analysis on the “donation equivalent” of participation.
E.G. if it would cost 10k to pay a willing participant, and an EA were willing to do it for free for social good, is this the “equivalent” of a 10k donation to an effective health cause? If not, approximately how much would it be worth? Putting a number on this would be interesting, and could help individuals decide whether to participate (comparing to their opportunity costs, etc).
Heck, maybe if we had a number, individuals who track donations could even log challenge participation as a number amount towards their donation goal (e.g. for those who donate 10% of their incomes), though that’s probably a whole different conversation.
The donation equivalent aspect is pretty interesting. A study probably would not allow a participant not to take a donation, so in practice it might just be however much money from the study one chooses to donate to effective causes (minus taxes; trial income is usually treated as taxable income, which is probably bad policy). I might be misunderstanding your point, though.
I’ll reiterate (this probably should’ve been worded clearer in the post), one of the arguments we make here is that assuming all participants who make it into the study are about equally useful, we think EAs are more likely to be effective as pre-participants as well. This is because the study is still under consideration: there are decisions about the study’s design that may make it go faster, and informed advocacy from earnest pre-participants could be very persuasive for regulators and ethicists who might otherwise reject certain study design decisions on paternalistic grounds. The community and shared worldview of EA makes us think EAs will, on average, be more engaged when it comes to voicing their views on study design.
This interactive model app based on the paper we mention in footnote 4 lets you tinker with a bunch of variables related to challenge model development and vaccine deployment. Based on that, and after a conversation with the lead author, we get about 200 years of life saved for every day sooner the model is developed. (The app isn’t that granular/to the day yet but it is supposed to be updated soon.) So pushing for stud decisions that condense things even by a month or two could be huge.
Very interesting write-up, thank you for it.
As pointed out in an earlier comment, raising the compensation for challenge trials and/or seeking out participants with lower ‘willing participation price’ seems promising as a way to get enough participants.
I would be interested to see an analysis on the “donation equivalent” of participation.
E.G. if it would cost 10k to pay a willing participant, and an EA were willing to do it for free for social good, is this the “equivalent” of a 10k donation to an effective health cause? If not, approximately how much would it be worth? Putting a number on this would be interesting, and could help individuals decide whether to participate (comparing to their opportunity costs, etc).
Heck, maybe if we had a number, individuals who track donations could even log challenge participation as a number amount towards their donation goal (e.g. for those who donate 10% of their incomes), though that’s probably a whole different conversation.
Thanks for reading!
The donation equivalent aspect is pretty interesting. A study probably would not allow a participant not to take a donation, so in practice it might just be however much money from the study one chooses to donate to effective causes (minus taxes; trial income is usually treated as taxable income, which is probably bad policy). I might be misunderstanding your point, though.
I’ll reiterate (this probably should’ve been worded clearer in the post), one of the arguments we make here is that assuming all participants who make it into the study are about equally useful, we think EAs are more likely to be effective as pre-participants as well. This is because the study is still under consideration: there are decisions about the study’s design that may make it go faster, and informed advocacy from earnest pre-participants could be very persuasive for regulators and ethicists who might otherwise reject certain study design decisions on paternalistic grounds. The community and shared worldview of EA makes us think EAs will, on average, be more engaged when it comes to voicing their views on study design.
This interactive model app based on the paper we mention in footnote 4 lets you tinker with a bunch of variables related to challenge model development and vaccine deployment. Based on that, and after a conversation with the lead author, we get about 200 years of life saved for every day sooner the model is developed. (The app isn’t that granular/to the day yet but it is supposed to be updated soon.) So pushing for stud decisions that condense things even by a month or two could be huge.