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Global Assessment of Functioning (GAF): properties and frontier of current knowledge
Open accessAbstract
BACKGROUND: 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). METHODS: A thorough literature search was conducted. RESULTS: 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? CONCLUSIONS: 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.
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“The GAF is broadly acknowledged and has been applied worldwide in hundreds of studies (Aas 2010).”
From The process-outcome mindfulness effects in trainees (PrOMET) study: Protocol of a pragmatic randomized controlled trial (2015) · cites this paper as Aas 2010
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“Although there are validity and reliability issues with the psychologist's’ overall judgement of the patient's level of functioning and GAF [17], this does seems a large effect.”
From Healthcare utilization in general practice before and after psychological treatment: A follow-up data linkage study in primary care (2014) · cites this paper as [17]
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Metadata
- Authors
- Aas, I. M.
- Venue
- Annals of General Psychiatry
- Published
- 2010-05-07
- Volume
- 9
- Issue
- 1
- Pages
- 20-20
- ISSN
- 1744-859X (ISSN-L)
- PMC
- PMC2880316
- OpenAlex
- W2157799751
- Cited by
- 341
- References
- 98
- Citations by year
- 2026: 18 · 2025: 32 · 2024: 35 · 2023: 23 · 2022: 31 · 2021: 50 · 2020: 18 · 2019: 18 · 2018: 22 · 2017: 11 · 2016: 14 · 2015: 17 · 2014: 17 · 2013: 16 · 2012: 9
- FWCI
- 15.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Annals of General Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Arts and Humanities › Philosophy › Mental Health and Psychiatry
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Keywords
- Global Assessment of Functioning, disease severity, psychiatric rating scales, scale development, anchor points, scale reliability and validity, positive mental health, prognosis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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