Re: numbers vs categories: I largely agree with you. Numerical scales such as the one we used for suffering can be used intuitively to represent intensity, and the numbers can be stand-ins for categories. But problems can arise when the numbers are misinterpreted as being points on a linear scale (which it is not), or that they represent (even non-linearly) quantities of a defined unit that can simply be aggregated in various ways to yield a single value. Having separate categories of severe and extreme suffering is a way of avoiding these problems. I very much agree with the qualitative distinctness of suffering so extreme that giving up one’s life is seen as preferable in that moment. For prioritisation purposes, there doesn’t seem to be any need to try to distinguish between levels of unbearable suffering (as you imply) - they all deserve very high prioritisation. In principle one would never want such experiences to occur.
Re: correlating suffering and EQ-5D-5L: Yes, I agree it would be good to compare existing measures with the suffering score. EQ-5D-5L has scores for pain/discomfort and for anxiety/depression, so we would expect moderate-to-strong correlations of suffering with both, if data were collected in the same way. But for health economics, EQ-5D-5L is used especially to quantify overall utility, whereas we are arguing for separate one-dimensional suffering metrics that directly measure the key ethical parameter: experiencing an unpleasant state and wanting to be free of it. Our approach is also to try to capture extreme suffering that wouldn’t necessarily be captured using momentary measures of wellbeing, such as with EQ-5D-5L. So there’s a distinction not just in the scales themselves, but how they are potentially used.
Re: how they bear this suffering: We did, in fact, include such a question: “Is there anything that worked well to alleviate your suffering from this condition or situation, that you think other people should know about?” But I didn’t include responses in this post, as it would have made it too long.
Re: the comparative approach: Agreed, it wouldn’t be equivalent to the DALY for the reason you gave (no tradeoff exercise), just allow rankings.
Re: bearing: I’m glad you did include something like this. Another angle would have been protective non-action factors, but your wording seems more solution-oriented.
Re: EQ-5D-5L (or something similar): I agree that the suffering and health-related quality of life or health utilities only partially overlap and that some dimensions will have more predictive power than others. What I would be interested to know is how big the discrepancy is between reported suffering and a generic instrument. Are people who suffer greatly reporting middling problems on other commonly used instruments? or How much does conventional QALY tools under-report extreme suffering? It could be another argument for why and how existing tools and metrics are inadequate.
One thing I struggle with in this area is how to think about temporal aggregation. Is one hour of suffering on two days worse than two hours of suffering one day? I am nonetheless glad to see OPIS trying to map out a ‘global burden of suffering’.
Thanks, Marius. Some responses:
Re: numbers vs categories: I largely agree with you. Numerical scales such as the one we used for suffering can be used intuitively to represent intensity, and the numbers can be stand-ins for categories. But problems can arise when the numbers are misinterpreted as being points on a linear scale (which it is not), or that they represent (even non-linearly) quantities of a defined unit that can simply be aggregated in various ways to yield a single value. Having separate categories of severe and extreme suffering is a way of avoiding these problems. I very much agree with the qualitative distinctness of suffering so extreme that giving up one’s life is seen as preferable in that moment. For prioritisation purposes, there doesn’t seem to be any need to try to distinguish between levels of unbearable suffering (as you imply) - they all deserve very high prioritisation. In principle one would never want such experiences to occur.
Re: correlating suffering and EQ-5D-5L: Yes, I agree it would be good to compare existing measures with the suffering score. EQ-5D-5L has scores for pain/discomfort and for anxiety/depression, so we would expect moderate-to-strong correlations of suffering with both, if data were collected in the same way. But for health economics, EQ-5D-5L is used especially to quantify overall utility, whereas we are arguing for separate one-dimensional suffering metrics that directly measure the key ethical parameter: experiencing an unpleasant state and wanting to be free of it. Our approach is also to try to capture extreme suffering that wouldn’t necessarily be captured using momentary measures of wellbeing, such as with EQ-5D-5L. So there’s a distinction not just in the scales themselves, but how they are potentially used.
Re: how they bear this suffering: We did, in fact, include such a question: “Is there anything that worked well to alleviate your suffering from this condition or situation, that you think other people should know about?” But I didn’t include responses in this post, as it would have made it too long.
Re: the comparative approach: Agreed, it wouldn’t be equivalent to the DALY for the reason you gave (no tradeoff exercise), just allow rankings.
Good points! Some follow-ups:
Re: bearing: I’m glad you did include something like this. Another angle would have been protective non-action factors, but your wording seems more solution-oriented.
Re: EQ-5D-5L (or something similar): I agree that the suffering and health-related quality of life or health utilities only partially overlap and that some dimensions will have more predictive power than others. What I would be interested to know is how big the discrepancy is between reported suffering and a generic instrument. Are people who suffer greatly reporting middling problems on other commonly used instruments? or How much does conventional QALY tools under-report extreme suffering? It could be another argument for why and how existing tools and metrics are inadequate.
One thing I struggle with in this area is how to think about temporal aggregation. Is one hour of suffering on two days worse than two hours of suffering one day? I am nonetheless glad to see OPIS trying to map out a ‘global burden of suffering’.