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To identify and quantify public preferences for attributes of newborn screening conditions.

We conducted an online national survey of the public (n = 502) to evaluate preferences for attributes of candidate newborn screening conditions. Respondents were presented with hypothetical condition profiles that were defined using 10 attributes with 2-6 levels per attribute. Participants indicated whether they would recommend screening for a condition and which condition attributes were most and least important when making this decision (best–worst scaling). Difference scores were calculated and stratified by condition recommendation (recommend or not recommend for screening). Regression analyses were used to evaluate the effect of attributes on choice to screen or not screen.

The number of babies diagnosed was important to those who would recommend newborn screening for a …