I suspect the synthesis here is that unguided is very effective when adhered to, but the main challenge is adherence. The reason to believe this is that there is usually a strong dosage effect in psychotherapy studies, and that the Furukawa study I posted in the first comment found that the only value humans provided was for adherence, not effect size.
Unfortunately, this would then cause big problems, because there is likely a trial bias affecting adherence, potentially inflating estimates by 4× against real-world data. I’m surprised that this isn’t covered in the literature, and my surprise is probably good evidence that I have something wrong here. This is one of the reasons I’m keen to study our intervention’s real-world data in a comparative RCT.
You make a strong point about the for-profit space and relative incentives, which is partly why, when I had to make a decision between founding a for-profit unguided app and joining Kaya Guides, I chose the guided option. As you note, the way the incentives seem to work is that large for-profits can serve LMICs only when profit margins are competitive with expanding further in HICs. This is the case for unguided apps, because translation and adaptation is a cheap fixed cost. But as soon as you have marginal costs, like hiring humans (or buying books, or possibly, paying for AI compute), it stops making sense. This is why BetterHelp have only now begun to expand beyond the U.S. to other rich countries.
But I think you implicitly note—if one intervention has zero marginal cost, then surely it’s going to be more cost-effective and therefore more attractive to funders? One model I’ve wondered about for an unguided for-profit is essentially licensing its core technology and brand to a non-profit at cost, which would then receive donations, do translations, and distribute in other markets.
I suspect the synthesis here is that unguided is very effective when adhered to, but the main challenge is adherence. The reason to believe this is that there is usually a strong dosage effect in psychotherapy studies, and that the Furukawa study I posted in the first comment found that the only value humans provided was for adherence, not effect size.
Unfortunately, this would then cause big problems, because there is likely a trial bias affecting adherence, potentially inflating estimates by 4× against real-world data. I’m surprised that this isn’t covered in the literature, and my surprise is probably good evidence that I have something wrong here. This is one of the reasons I’m keen to study our intervention’s real-world data in a comparative RCT.
You make a strong point about the for-profit space and relative incentives, which is partly why, when I had to make a decision between founding a for-profit unguided app and joining Kaya Guides, I chose the guided option. As you note, the way the incentives seem to work is that large for-profits can serve LMICs only when profit margins are competitive with expanding further in HICs. This is the case for unguided apps, because translation and adaptation is a cheap fixed cost. But as soon as you have marginal costs, like hiring humans (or buying books, or possibly, paying for AI compute), it stops making sense. This is why BetterHelp have only now begun to expand beyond the U.S. to other rich countries.
But I think you implicitly note—if one intervention has zero marginal cost, then surely it’s going to be more cost-effective and therefore more attractive to funders? One model I’ve wondered about for an unguided for-profit is essentially licensing its core technology and brand to a non-profit at cost, which would then receive donations, do translations, and distribute in other markets.