Whoops-- definitely meant my comment as a response to "what content can be cut?" And the section about activities was meant to show how some of the activities in the current fellowship are insufficient (in my view) & offer some suggestions for other kinds of activities.

Regardless of whether we shift to a radically new model, or we try to revamp the existing structure, I think it'll be useful to dissect the current fellowship to see what content we most want to keep/remove.

Will try to respond to the rest at some point soon, but just wanted to clarify!

TLDR: I agree that content is important, but I don't think the current version of the fellowship does a good job emphasizing the right kind of content. I would like to see more on epistemics/principles and less on specific cause areas. Also the activities can be more relevant.

Longer version: I share some of your worries, Mauricio. I think the fellowship (at least, the version that Penn EA does) currently has three kinds of content:

• Readings about principles and ways of seeing the world (e.g., counterfactualism, effectiveness mindset, expanding one's moral circle)
• Readings about content and specific information about cause areas (e.g., arguments for global health and development, animal welfare, longtermism, etc.)
• Exercises in which people reflect on reading topics (e.g., estimating your future income and the impact you could make with it, sending a letter to a version of yourself from the 1840s and trying to convince them to expand their moral circle)

I think we could cut several of the readings about content and cause areas and replace them with more readings/activities about epistemics and "ways of seeing the world." Based on my experience as a facilitator, I think the readings on principles/epistemics are usually much more valuable than the readings on cause areas. Also, if you get people fired up about the underlying ideas/principles, I think they're inclined to read a bit about specific cause areas on their own. And I also worry a bit about the perception that EA is defined by a core set of cause areas (as opposed to being defined by a core set of principles, which then leads people to some cause areas but there is a lot of disagreement here and we should be open to changing cause areas over time etc etc.)

 I also think the exercises in the fellowship could be revamped to be a bit more relevant and applied (e.g., more focus on career planning, independent research skills, redteaming EA research reports or project proposals, developing agency, and converting beliefs into actions). 

Examples of new exercises: "take 1 hour to research a topic you're interested in and write a 5-min summary" or "spend 15 minutes brainstorming people who you could talk to in order to address key uncertainties. Then, spend 15 minutes reaching out to them." (Note: Brainstormed these in 5 mins. These are meant to be illustrative rather than polished).

Thank you, Brendon and jh! A few more thoughts/questions below. Feel free to ignore any that are not super relevant or that would take a very long time to address.

• My understanding is that most popular apps (e.g., Headspace, Calm) offer free versions to people [including people in low- and middle-income countries]. I suppose MindEase would have an edge if it offers the full (premium) version for free, but it still seems quite difficult to compete with highly popular apps like Headspace/Calm. What do you think? And has this model of offering an app for free in low- and middle-income countries worked for any apps in the past?
• The Pacifica study that Hauke cites compares counseling alone to counseling + Pacifica. This seems like a comparison that would underestimate the effect of Pacifica. (It seems rather impressive that an app is able to have any effect above and beyond therapy, and I would imagine its standalone effect to be larger). Furthermore, I don't think Pacifica will be Mind Ease's main competitor-- Headspace and Calm appear to be much more popular than Pacifica (here and here), and they also focus on mindfulness/relaxation. Are there any estimates of Mind Ease's counterfactual impact relative to Headspace or Calm?
• Is the business analysis by Lionheart publicly available? (Apologies if you said this somewhere in your post).
• Thank you for the info about startups! I'm still a bit skeptical about the mental health app space in particular; are there any statistics about the percentage of funded health/mental health app startups that succeed?

It seems to me like the case for MindEase (whether from an impact perspective or from a return-on-investment perspective) rests on MindEase's ability to attract users. 

Can you say more where the estimate of 1,000,000 active users came from, as well as the 25% chance of success? At first glance, this strikes me as overly optimistic, given that a) many other well-designed apps have failed to acquire users and b) it seems really hard to compete with the existing mindfulness apps. (See here, here, and here for papers that go into these points in greater detail).

Great work, Ben! I appreciate the actionable suggestions & the structure of the post (i.e., summaries at the top and details in the main body). Excited to see the other posts in this series!

One suggestion: I think it would be helpful to distinguish between interventions that are helpful for people with poor sleep quality (e.g., people with insomnia) and those that are helpful for people with "average" sleep quality (e.g., people who don't have any huge problems with their sleep quality but are trying to optimize their sleep quality). 

In other words: let's assume person A has diagnosable insomnia, and person B has "average" sleep quality but is trying to optimize (i.e., by going from 50th percentile sleep quality to 80th percentile). Would you suggest the same intervention for person A and person B?

My understanding  is that many of the top recommendations are typically studied for insomnia, but there is much less research supporting their effectiveness for "people with ordinary sleep habits who are trying to optimize" (epistemic status pretty uncertain: I'm not a sleep researcher but have talked with a few about this topic).

A few questions:

• In general, would you say the evidence for these interventions is strongest for people with insomnia/poor sleep quality?
• Which intervention(s) would you recommend most strongly to someone with insomnia/poor sleep quality?
• Which intervention(s) would you recommend most strongly to someone with average/good sleep quality?

I think this content is well-written, so I am praising it publicly! (See what I did there?) 

Some thoughts/questions:

1. Do you recommend any books/guides on writing [besides Copyblogger]? (e.g., Sense of Style or  On Writing)
2. I wonder if it would be useful to have a section that describes under what circumstances this advice is most likely to be helpful. In my view, this advice is most important for writing that is intended for wide audiences. (Examples: Rationality skills that nearly everyone could benefit from; blogs that offer thought-provoking insights). I agree that engaging writing would make all writing better, but given that there are costs, it might be useful to emphasize situations/contexts in which this advice would be especially valuable.
3. What do you think are the biggest reasons why (some) EA writing is dry? 
4. What advice would you give to people who think that they're bad writers? Or people who are worried that their writing not being "good enough" for the forum?

Some strategies that I've heard about or found helpful:

1. Omit needless words! Go back & delete all of the words you don't truly, really, fully, actually need! (See what I did there?)
2. Find good writing, try to break it down into elements, and then copy those elements.
3. Ask people for feedback! 
4. Read writing out loud. (I agree that many people, myself included, are generally more engaging speakers than writers).
5. Remove hedges (unless they are intentional).
6. Remove nominalizations (instances in which you use nouns when you could have used verbs) unless they are intentional.

Terrific overview! I'll offer some feedback with the hope that some of it may be helpful:

Big Picture Thoughts

1. In general, I thought the report did a great job summarizing some of the major themes/ideas that are fairly well-established in global mental health. I wonder if it could be useful to include a section on more experimental/novel/unestablished/speculative ideas. Sort of like a "higher risk, higher potential reward" section.
2. Relatedly, I'd be interested in seeing bolder and more specific recommendations for future work. As an example, Box 2 ("Promising Research Directions") lists important goals, but they're too broad to really know how to act on (e.g., "improve treatments and expand access to care."). I'd be more curious to see HLI's subjective opinions on the most impactful next steps (more similar to the list of project ideas that you have, rather than the goals in Box 2).
3. I'd love to see more analysis on key issues/controversies (see last section for examples).

Potentially useful points that I didn't see in the report:

1. A lot of suffering is caused by subclinical/subsyndromal mental health problems. In the case of mood disorders, "subsyndromal symptoms are impairing, predict syndrome
   onset and relapse, and account for more doctor’s visits and suicide attempts
   than the full syndromes." (Ruscio, 2019). This point is especially important because there are debates about how funding should be allocated (e.g., how much should we spending on treatments that target people with diagnosable disorders vs. mental health promotion strategies and prevention programs that reach broader audiences?)
2. Recent work has suggested that the "latent disease" view of depression (and other mental disorders) may be flawed (e.g., Borsboom, 2017). A related body of work has suggested that some depressive symptoms may be more impairing than others (e.g., Fried & Nesse, 2014). This could have important implications for measuring the effectiveness of interventions-- e.g., estimating SWB weights for each symptom, rather than using sum-scores.
3. The evidence on task-sharing/task-shifting is strong, so I understand why you spent a lot of space covering it. At the same time, it could be useful to spend more time discussing some of the more novel approaches. Some examples include unguided self-help interventions and single-session interventions (Schleider & Weisz, 2017). Although the evidence for guided interventions and longer interventions is stronger, unguided interventions are substantially cheaper. This might make them more cost-effective, even if longer/guided interventions are more effective (discussed further in this preprint).
4.  The digital interventions studied in meta-analyses and reviews are very different than those that have been disseminated widely. We know a lot about the effectiveness of digital interventions developed by professors, but much less about the effectiveness of Headspace, Calm, and other popular apps (Wasil et al., 2019).
5.  There's are some important gaps in the digital mental health space: popular interventions tend to focus on relaxation/mindfulness and rarely include other empirically supported treatment elements (Wasil et al., 2020). This reminds me that I really should write up a digital mental health forum post at some point :) 

Examples of questions/controversies that HLI could address:

1. Broadly, what does HLI see as some of the most important open questions in the mental health space? 
2. What content should be included in interventions? Does HLI believe that specific elements should be the focus of interventions? Or are common factors driving effects?
3. Which delivery formats be used? Is HLI optimistic or pessimistic about unguided self-help interventions? Are they likely to be more cost-effective than task-sharing interventions?
4. Does HLI see mental disorders as diseases, networks of symptoms, or something else? Do you think this matters, or not really?
5. Broadly, what does HLI think that a lot of people interested in mental health "get wrong" or "don't yet know" about the most cost-effective ways to make an impact?
6. How long do the effects of interventions last? How should the uncertainty around this estimate affect our cost-effectiveness calculations? (assuming that the effects of an intervention will last <1 year seems like it would yield radically different conclusions than assuming it would 1-3 years, 3+ years, 10+ years 30+ years, etc.)

I hope that some of this was helpful & I'm looking forward to seeing future reports!

I think the steelman of the neglectedness argument would be something like: "The less neglected something is, the less likely it is that we would be able to make them do it slightly better."

This is both because (a) it is harder to change the direction of the movement and (b) it is harder to genuinely find meaningful ways to improve the movement.

In (b), I wonder if there are some specific limitations of the current War-on-Drugs movement that would match the skills/interests of (some) EAs. 

I'd be curious to learn more about the "types" of EAs that might be best-suited for this work, or how the "EA perspective" could enhance ongoing efforts.

As it stands, the case for scale (i.e., the magnitude of the problem) is very clear. However, I think scale is usually the strongest part of most cause area analyses (i.e., there are a lot of really big problems and it's usually not too difficult to articulate the bigness of those problems, especially using words rather than models). I think the role that EAs would play is less clear (as has been reflected in other comments relating to neglectedness). So, I wonder:

Are there some clear gaps or limitations in the current anti-War-on-drugs movement that could be filled by EA perspectives/skills? (As an example, one of the commentators emphasized that global efforts to legalize drugs may be neglected, and EAs who have skills/interests related to global advocacy might be especially helpful).

What a great opportunity! I wonder if people at SparkWave (e.g., Spencer Greenberg), Effective Thesis, or the Happier Lives Institute would have some ideas. All three organizations are aligned with EA and seem to be in the business of improving/applying/conducting social science research.

Also, I have no idea who your advisor is, but I think a lot of advisors would be open to having this kind of conversation (i.e., "Hey, there's this funding opportunity. We're not eligible for it, but I'm wondering if you have any advice..."). [Context: I'm a PhD student in psychology at UPenn.]

If that's not a good option, you could consider asking your advisor (and other academics you respect) if they know about any metascience/open science organizations that are highly effective [without mentioning anything about your relative and their interest in donating].

Finally, it's not clear to me if the donor is only interested in metascience or if they would also be open to funding "basic science" projects. "Basic science" is broad enough that I imagine it could open up a lot of alternative paths (many of which might be more explicitly EA-aligned than metascience). Examples include basic scientific research on effective giving, animal advocacy, mental health, AI safety, etc. Do you have a sense of how open to "basic science" your relative is, or was basic science just meant as a synonym for metascience?

Finally, good luck on this! :)