Great post!
Nitpick:
For instance, the worst possible health state would be represented by “11111”.
I think “11111” usually refers to full health. (cf. the “EQ-5D Value Sets: Inventory, Comparative Review and User Guide” by Szende, Oppe & Devlin, 2007).
As part of a bigger project on descriptive (population) ethics, I’ve been working on a literature review of health economics. It also contains a section on the EQ-5D and its weaknesses. Here some excerpts:
Problem II: Impossible health states Another problem is that many health states, such as e.g. 22123 are psychologically impossible or at least very implausible. E.g. if you have “no problems with performing your usual activities (work, study, housework, family or leisure activities, etc.) ”, you can’t, simultaneously, suffer from “extreme depression”. This is immediately obvious to anyone who ever suffered from severe depression.
I’d guess that almost as much as 20% of all EQ-5D health states are psychologically impossible. This indicates that the whole system is suboptimal.
Problem III: Using “immediate death” Another problem is that subjects are often asked to choose between “immediate death” vs. the alternative scenario. However, this means that the subject is unable to say goodbye to their loved ones, or get their affairs in order. Arguably, the difference between dying immediately and dying in e.g. 3 months can make an enormous difference.”
(Incorporating the TTO lead-time approach can easily overcome this problem.)
Anway, you write:
First, DALYs are biased towards physical health. The instruments used for eliciting them and affective forecasting errors cause mental health to be underrepresented.
I couldn’t agree more.
IMHO, another big problem is the evaluation of states worse than death (SWD) (and states of severe mental illness such as depression arguably belong in this category). For example, most studies don’t even allow for SWD assessments. Furthermore, most researchers transform negative evaluations, limiting them to a lower bound of −1. Assuming that people with a history of mental illness more often evaluate health states indicating severe mental illness as highly negative (i.e. give utilities as lower than −1), then this ex-post transformation causes their judgments to have less influence than the judgments of uninformed people who underestimate the severity of mental illness.
I discuss this problem, as well as other problems, in much greater detail in my doc.
I plan on publishing the doc within the next months, but if you’re interested I’m happy to send you a link to the current version.
Otoh, a few decades later handwashing did become mainstream. So I’d think that correct and clearly useful models have a great advantage in becoming adopted eventually. Good strategy/movement building is more relevant for hastening the rate of adoption.
To take another example: Communism profited from extremely good strategy/movement building at the beginning (Engels being one of the first EtGlers ever). But it ultimately failed to become widely accepted because it brought about bad consequences. Admittedly, it’s still pretty popular, probably because it appeals to human intuitions (such as anti-market bias, etc.)