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Is the CO2 accumulation entirely due to human (or I suppose animal) respiration? So it will typically be worse in small houses with lots of people (holding other factors, like ventilation, constant)?
In a modern house, with no open fires, lead paint etc, what "household air pollution" might there be?
Thanks - this is useful and I will explore some of the suggestions.
Is there much research comparing immediate vs extended release melatonin? E.g.:
- Is IR better for speeding sleep onset, as one might expect?
- Does XR actually improve sleep maintenance/duration more than IR?
- Do they have the same effect on sleep efficiency?
- Is the optimal dose the same for each?
- Dose aside, do combined IR/XR supplements, or taking a bit of each, give you the 'best of both worlds'?
[Edited on 19 Nov 2021: I removed links to my models and report, as I was asked to do so.]
Just to clarify, our (Derek Foster's/Rethink Priorities') estimated Effect Size of ~0.01–0.02 DALYs averted per paying user assumes a counterfactual of no treatment for anxiety. It is misleading to estimate total DALYs averted without taking into account the proportion of users who would have sought other treatment, such as a different app, and the relative effectiveness of that treatment.
In our Main Model, these inputs are named "Relative impact of Alternative App" and "Proportion of users who would have used Alternative App". The former is by default set at 1, because the other leading apps seem(ed) likely to be at least as effective as Mind Ease, though we didn't look at them in depth independently of Hauke. The second defaults to 0; I suppose this was to get an upper bound of effectiveness, and because of the absence of relevant data, though I don't recall my thought process at the time. (If it's set to 1, the counterfactual impact is of course 0.)
Our summary, copied in a previous comment, also stresses that the estimate is per paying user. I don't remember exactly why, but our report says:
Other elements of the MindEase evaluation (i.e. parts not done by Rethink Priorities) consider a “user” to be a paying user, i.e. someone who has downloaded the app and purchased a monthly or annual plan. For consistency, we will adopt the same definition. (Note that this is a very important assumption, as the average effect size and retention is likely to be many times smaller for those who merely download or install the app.)
As far as I can tell (correct me if I'm wrong), your "Robust, uncertainty-adjusted DALYs averted per user" figure is essentially my theoretical upper-bound estimate with no adjustments for realistic counterfactuals. It seems likely (though I have no evidence as such) that:
- Many users would otherwise use a different app.
- Those apps are roughly as effective as MindEase.
- The users who are least likely to use another app, such as people in developing countries who were given free access, are unlikely to be paying (and therefore perhaps less likely to regularly use/benefit from it) – not to mention issues with translation to different cultures/languages.
So 0.02 DALYs averted per user seems to me like an extremely optimistic average effect size, based on the information we had around the middle of last year.
[Edited on 19 Nov 2021: I was asked to remove the links.]
For those who are interested, here is the write-up of my per-user impact estimate (which was based in part on statistical analyses by David Moss): [removed]
The Main Model in Guesstimate is here: [removed]
The Effect Size model, which feeds into the Main Model, is here: [removed]
I was asked to compare it to GiveDirectly donations, so results are expressed as such. Here is the top-level summary:
Our analysis suggests that, compared to doing nothing to relieve anxiety, MindEase causes about as much benefit per paying user as donating $40 (90% confidence interval: $10 to $140) to GiveDirectly. We suspect that other leading apps are similarly effective (perhaps more so), in which case most of the value of MindEase will come from reaching people who would not have accessed alternative treatment.
Due to time constraints and lack of high-quality information, the analysis involved a lot of guesswork and simplifying assumptions. Of the parameters included in our Main Model, the results are most sensitive to the effect sizes of both MindEase and GiveDirectly, the retention of those effects over time, and the choice of outcome metric (DALYs vs WELLBYs). One large, independent study could eliminate much of this uncertainty. Additional factors worth considering include indirect effects (e.g. economic productivity, meat consumption, evidence generation), opportunity costs of team members’ time, and robustness to non-utilitarian worldviews.
Note that this was done around June 2020 so there may be better information on MindEase's effectiveness by now. Also, I think the Happier Lives Institute has since done a more thorough analysis of the wellbeing impact of GiveDirectly, which could potentially be used to update the estimate.
Hi Sam,
Thanks for the comments.
1. Have you done much stakeholder engagement? No. I discuss this a little bit in this section of Part 2, but I basically just suggest that people look into this and come up with a strategy before spending a huge amount of time on the research. I do know of academics who would may be able to advise on this, e.g. people who have developed previous metrics in consultation with NICE etc, but they’re busy and I suspect they wouldn’t want to invest a lot of time into efforts outside academia.
I think they’d reject the assumption that they are “not improving these metrics” and would point to considerable quantities of research in this area. The main issue, I think, is that they want a different kind of metric that what I’m proposing, e.g. they think it’s important that they are based on public preferences and are focused on health rather than wellbeing. A lot of resources are going into what I see (perhaps unfairly) as “tinkering around the edges,” e.g. testing variations of the time tradeoff/DCE and different versions of the EQ-5D, rather than addressing the fundamental problems.
As I say in Part 3 with respect to the sHALY (SWB-based HALY):
In my view, the strongest reason not to do this project is the apparent lack of interest among key stakeholders. Clinicians, patients, and major HALY “consumers” such as NICE and IHME seem strongly opposed to a pure SWB measure, even if focused on dimensions of health, and to the use of patient-reported values more broadly. As discussed in previous posts, this is due to a combination of normative concerns, such as the belief that those who pay for healthcare have the right to determine its distribution or that disability has disvalue beyond its effect on wellbeing, and doubts about the practicality of SWB measures in these domains.
So this project may only be worth considering if the sHALY would be useful for non-governmental purposes (e.g., within effective altruism), or in “supplementary” analyses alongside more standard methods (e.g., to highlight how QALYs neglect mental health). Either that, or changing the minds of large numbers of influential stakeholders will have to be a major part of the project—which may not be entirely unrealistic, given the increasing prominence of wellbeing in the public sector. We should also consider the possibility that projects such as this, which offer a viable alternative to the status quo, would themselves help to shift opinion.
That said, there is increasing increasing interest in hybrid health/wellbeing measures like the E-QALY, and scope for incremental improvement of current HALYs (see Part 2), and in the use of wellbeing for cross-sector prioritisation. In at least the latter case, you are likely to know more than me about how to effect policy change within governments.
2. Problem 4 - neglect of spillover affects – probably cannot be solved by changing the metric. I discuss spillovers a little in Part 2 and plan to have a separate post on it in Part 6 (but it might be a while before that’s out, and it’s likely to focus on raising questions rather than providing solutions). I’m still unsure what to do about them and would like to see more research on this. I agree changing the metric alone won’t solve the issue, but it may help—knowing the extent to which the metric captures spillovers seems like an important starting point.
3. Who would you recommend to fund if I want to see more work like this? It probably depends what your aims are. If it’s to influence NICE, IHME, etc, it probably has to go via academia or those institutions. If you want to develop a metric for use in EA, funding individual EAs or EA orgs may work—but even then, it’s probably wise to work closely with relevant academics to avoid reinventing the wheel. So I guess if you have a lot of money to throw at this, funding academics or PhD students may be a good bet; there is already some funding available (I’m applying for PhD scholarships in this area at the moment), but it may be hard to get funding for ideas that depart radically from existing approaches. I list some relevant institutions and individuals in Part 2.
4. How is the E-QALY project going? It got very delayed due to COVID-19. I’m not sure what the new timeline is.
Thanks Bob! I will probably do this after publishing the next post.
I've made a few edits to address some of these issues, e.g.:
Clearly, there are many possible “wellbeing approaches” to economic evaluation and population health summary, defined both by the unit of value (hedonic states, preferences, objective lists, SWB) and by how they aggregate those units when calculating total value. Indeed, welfarism can be understood as a specific form of desire theory combined with a maximising principle (i.e., simple additive aggregation); and extra-welfarism, in some forms, is just an objective list theory plus equity (i.e., non-additive aggregation).
However, it seems that most advocates for the use of wellbeing in healthcare reject the narrow welfarist conception of utility, while retaining fairly standard, utility-maximising CEA methods—perhaps with some post-hoc adjustments to address particularly pressing distributional issues. So it seems reasonable to consider it a distinct (albeit heterogenous) perspective.
For the purpose of exposition, I will assume that the objective is to maximise total SWB (remaining agnostic between affect, evaluations, or some combination). This is not because I am confident it’s the right goal; in fact, I think healthcare decision-making should probably, at least in public institutions, give some weight to other conceptions of wellbeing, and perhaps to distributional concerns such as fairness. One reason to do so is normative uncertainty—we can’t be sure that the quasi-utilitarianism implied by that approach is correct—but it’s also a pragmatic response to the diversity of opinions among stakeholders and the challenges of obtaining good SWB measurements, as discussed in later posts.
However, I am fairly confident that SWB-maximization—or indeed any sensible wellbeing-focused strategy—would be an improvement over current practice, so it seems like a reasonable foundation on which to build. Moreover, most of these criticisms should hold considerable force from a welfarist, extra-welfarist, or simply “common sense” perspective. One certainly does not have to be a die-hard utilitarian to appreciate that reform is needed.
Changed the first two problem headings to avoid ambiguity and, in the first case, to focus on the result of the problem rather than the cause, which helps distinguish it from 5.
There is much to be admired in this report, and I don't find it intuitively implausible that mental health interventions are several times more cost-effective than cash transfers in terms of wellbeing (which I also agree is probably what matters most). That said, I have several concerns/questions about certain aspects of the methodology, most of which have already been raised by others. Here are just a few of them, in roughly ascending order of importance:
My out-of-date notes:
Topic 2.2: (Re-)prioritising causes and interventions
[…]
GiveWell
[…]
Spillover effects
Secondly, there are also potential issues with ‘spillover effects’ of increased consumption, i.e. the impact on people other than the beneficiaries. This is particularly relevant to GiveDirectly, which provides unconditional cash transfers; but consumption is also, according to GiveWell’s model, the key outcome of deworming (Deworm the World, Sightsavers, the END Fund) and vitamin A supplementation (Hellen Keller International). Evidence from multiple contexts suggests that, to some extent, the psychological benefits of wealth are relative: increasing one person’s income improves their SWB, but this is at least partly offset by decreases in the SWB of others in the community, particularly on measures of life satisfaction (e.g. Clark, 2017). If increasing overall wellbeing is the ultimate aim, it seems important to factor these ‘side-effects’ into the cost-effectiveness analysis.
As usual, GiveWell provides a sensible discussion of the relevant evidence. However, it is somewhat out of date and does not fully report the findings most relevant to SWB, so I’ve provided a summary of wellbeing outcomes from the four most relevant papers in Appendix 2.1. In brief:
As GiveWell notes, it is hard to aggregate the evidence on spillovers (psychological and otherwise) because of:
Like GiveWell, I suspect the adverse happiness spillovers from GiveDirectly’s current program are fairly small. In order of importance, these are the three main reasons:
In addition, any psychological harm seems to be primarily to life satisfaction rather than hedonic states. As noted in Haushofer, Reisinger, & Shapiro (2019): “This result is intuitive: the wealth of one’s neighbors may plausibly affect one’s overall assessment of life, but have little effect on how many positive emotional experiences one encounters in everyday life. This result complements existing distinctions between these different facets of well-being, e.g. the finding that hedonic well-being has a “satiation point” in income, whereas evaluative well-being may not (Kahneman and Deaton, 2010).” This is reassuring for those of us who tend to think feelings ultimately matter more than cognitive evaluations.
Nevertheless, I’m not extremely confident in the net wellbeing impact of GiveDirectly.
A few more notes on interpreting the wellbeing effects of GiveDirectly:
In addition, I would note that the other income-boosting charities reviewed by GiveWell could potentially cause negative psychological spillovers. According to GiveWell’s model, the primary benefit of deworming and vitamin A supplementation is increased earnings later in life, yet no adjustment is made for any adverse effects this could have on other members of the community. As far as I can tell, the issue has not been discussed at all. Perhaps this is because these more ‘natural’ boosts to consumption are considered less likely to impinge on neighbours’ wellbeing than windfalls such as large cash transfers. But I’d like to see this justified using the available evidence.
I make some brief suggestions for improving assessment of psychological spillover effects in the “potential solutions” subsection below.
Appendix 2.1
Four studies investigated psychological impacts of GiveDirectly transfers. Two of these found wellbeing gains for cash recipients (“treatment effects”) and only null or positive psychological spillovers:
However, two studies are more concerning:
Note: GiveWell’s review of an earlier version of the paper reports a “statistically significant negative effect on an index of psychological well-being that is larger than the short-term positive effect that the study finds for receiving a transfer, but the negative effect becomes smaller and non-statistically significant when including data from the full 15 months of follow-up… The authors interpret these results as implying that cash transfers have a negative effect on well-being that fades over time.” I’m not sure why the authors removed those analyses from the final version.