While the present study employed the Youden Index to assess for the best balance between sensitivity and specificity, decisions on whether cutoff scores should place a higher priority on including true positives or on excluding false positives can be highly dependent on the intended purpose of the diagnostic grouping. In a clinical setting, one may wish to prioritize sensitivity, ensuring that the maximum number of potential patients is identified, with less concern placed on limiting over-inclusivity and false positives. When using the SF-36 to determine substantial reduction in young adults for clinical purposes, the recommendations outlined in this article may be loosened by increasing one or more cutoff values or by reducing the number of scales required to meet the substantial reduction criterion. However, in research settings, high levels of specificity may be more important to ensure that studies minimize the number of false positives. Including unacceptably high levels of non-patients in patient samples would result in skewed findings. Indeed, Jason, McManimen, Sunnquist, Newton, and Strand [32] have recommended that the field move towards developing a research case definition that would be less inclusive than most of the currently available clinical case definitions. Retaining strict cut-point standards for research purposes, thus prioritizing specificity, would ensure greater homogeneity among patient samples by excluding more false positives. Homogeneous or "pure" samples, containing a minimum of falsely identified individuals as "patients," would reduce bias and aid in overall efforts to specify the etiology and effectiveness of treatment for this illness.
