The general factor of psychopathology: a comparison with the general factor of intelligence with respect to magnitude and predictive validity.

In recent years, there has been a surge of interest in the general factor of psychopathology ("p"), which is intended to summarize broad psychiat-ric comorbidity into a single index. In this study, rather than attempting to validate this model using statistical techniques, we compared the magnitude (as indicated by the variance explained in the respective indicators) and the predictive validity of the "p" factor with those of the gen-eral factor of intelligence ("g"). To compare the magnitude, for "g", we analyzed fifteen Wechsler Adult Intelligence Scale subtests (N=1,200). For "p", we analyzed fourteen psychiatric diagnoses in Swedish adults (N=909,699), eight self- and parent-rated psychopathology scales in Swedish adolescents (N=2,069), and sixteen parent-rated psychopathology scales in Swedish children (N=14,589). To compare the predictive validity, we analyzed Swedish male military conscripts (N=414,595, mean age: 18.3 years) with measures on both "g" and "p" (derived from eight psychiatric diagnoses). We then examined their unique associations with three intelligence-related outcomes (annual income, highest education, and university entrance exam scores), and sixteen adverse outcomes (e.g., suicidal behavior, psychotropic medication prescription, and criminality) retrieved from registers (mean age at follow-up = 29.2 years). Results indicated that the magnitudes of "g" and "p" were very similar. Controlling for "p", "g" significantly predicted later education (standardized beta, β=0.38, SE=0.01) and university entrance exam scores (β=0.48, SE=0.01). Controlling for "g", "p" significantly predicted all adverse outcomes (mean β=0.32; range: 0.15 to 0.47). These findings support the notion that psychopathology indicators can be combined into a single score, similar to how intelligence subtests are combined into a general intelligence score. This "p" score might supplement specific diagnoses when formulating a management plan and predicting prognosis.