I offer these comments about the short screening scale for posttraumatic stress disorder (PTSD) described by Naomi Breslau, Ph.D., and colleagues +(1), both to help those who will use this instrument and to promote better understanding of the roles of sensitivity, specificity, and prevalence in test interpretation +(2).

From the authors’ Table 3, one sees that when four or more items on the seven-symptom scale are endorsed, sensitivity equals 0.803 and specificity equals 0.973. In the population evaluated, the proportion of individuals with PTSD, or disorder prevalence, was 142/1,830=0.078. Using this prevalence, Dr. Breslau and colleagues correctly calculated the positive predictive value as (sensitivity × prevalence) / (sensitivity × prevalence + [1 – prevalence] × [1 – specificity]) = 0.713 and the negative predictive value as (specificity × [1 – prevalence]) / (specificity × [1 – prevalence] + prevalence × [1 – sensitivity]) = 0.983. The authors should have pointed out, however, that these values are correct only for the prevalence in their group. The prevalence of PTSD has been reported to range from 1% in community-based samples to 75% among rape victims +(3). If the cutoff of four or more symptoms is used in a population where the prevalence is 2%, the positive predictive value is 0.378 and the negative predictive value is 0.996; if the same cutoff is used in a population in which the prevalence is 50%, the positive predictive value is 0.967 and the negative predictive value is 0.832.

The authors say that with the cutoff of four or more symptoms, "less than 2% of ‘true’ cases of PTSD were missed, whereas 29% of subjects without PTSD were falsely identified as having PTSD" (p. 910). This is incorrect. A positive predictive value of 0.713 means that about 29% of the subjects identified as having PTSD do not actually have it, and a negative predictive value of 0.983 means that about 2% of the subjects identified as not having PTSD actually have the disorder. The scale’s sensitivity is the probability that it will detect PTSD if a subject has the disorder; the scale’s specificity is the probability that a subject without PTSD will be deemed not to have the disorder. So if sensitivity is 0.803, the fraction of "true" cases missed is (1 – sensitivity) = (1 – 0.803) = 0.197, or about 20% of the subjects. If specificity is 0.973, the chance of falsely identifying someone without PTSD as having the disorder is (1 – specificity) = (1 – 0.973) = 0.027, or about 3%.

Dr. Breslau and colleagues say that the cutoff of four or more symptoms is well suited "to maximize the number of true cases of PTSD" detected initially when a subsequent evaluation will be used "to reclassify those who were wrongly classified as having the disorder" (p. 911). However, better cutoffs for such a purpose might be two or more symptoms (sensitivity=0.993) or three or more symptoms (sensitivity=0.951); these cutoffs would miss only 1% or 5% of the actual cases of PTSD, respectively.