Edwin Shneidman captured what is perhaps the most ­significant challenge confronting clinicians in suicide prevention today in his claim: "Currently, the major ­bottleneck in suicide prevention is not remediation […]; rather it is in diagnosis and identification (cited in Shea, 2011, p. xii). Predicting Suicide: Science, Art, or Chance? A landmark study by Pokorny (1983) demonstrated the difficulties associated with predicting suicide. He tried to predict suicide in a sample of 4,800 consecutive Veteran patients, all assessed against 21 known risk factors for suicide risk. More than 800 of these patients were assessed as being at high risk for suicide; however, only 3.75% (n = 30) of these individuals actually died by suicide within a 5-year follow-up period. Unexpectedly, 37 suicides occurred (out of 67) among those that were not previously identified as being at increased suicide risk (more false negatives than true positives). Pokorny's findings revealed an over-identification of persons at risk who never went on to suicide, and a high number of false negatives, constituted by individuals whose high suicide risk was missed or not identified. The overall predictive validity of his assessment was 2.8% (Pokorny, 1983).