Global Assessment of Functioning (GAF): properties and frontier of current knowledge

Global Assessment of Functioning (GAF) is well known internationally and widely used for scoring the severity of illness in psychiatry. Problems with GAF show a need for its further development (for example validity and reliability problems). The aim of the present study was to identify gaps in current knowledge about properties of GAF that are of interest for further development. Properties of GAF are defined as characteristic traits or attributes that serve to define GAF (or may have a role to define a future updated GAF). A thorough literature search was conducted. A number of gaps in knowledge about the properties of GAF were identified: for example, the current GAF has a continuous scale, but is a continuous or categorical scale better? Scoring is not performed by setting a mark directly on a visual scale, but could this improve scoring? Would new anchor points, including key words and examples, improve GAF (anchor points for symptoms, functioning, positive mental health, prognosis, improvement of generic properties, exclusion criteria for scoring in 10-point intervals, and anchor points at the endpoints of the scale)? Is a change in the number of anchor points and their distribution over the total scale important? Could better instructions for scoring within 10-point intervals improve scoring? Internationally, both single and dual scales for GAF are used, but what is the advantage of having separate symptom and functioning scales? Symptom (GAF-S) and functioning (GAF-F) scales should score different dimensions and still be correlated, but what is the best combination of definitions for GAF-S and GAF-F? For GAF with more than two scales there is limited empirical testing, but what is gained or lost by using more than two scales? In the history of GAF, its basic properties have undergone limited changes. Problems with GAF may, in part, be due to lack of a research programme testing the effects of different changes in basic properties. Given the widespread use, research-based development of GAF has not been especially strong. Further research could improve GAF.