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Goal attainment scaling (GAS) in rehabilitation: a practical guide

Turner-Stokes, Lynne·2009·Clinical Rehabilitation

Abstract

Goal attainment scaling is a mathematical technique for quantifying the achievement (or otherwise) of goals set, and it can be used in rehabilitation. Because several different approaches are described in the literature, this article presents a simple practical approach to encourage uniformity in its application. It outlines the process of setting goals appropriately, so that the achievement of each goal can be measured on a 5-point scale ranging from -2 to +2, and then explains a method for quantifying the outcome in a single aggregated goal attainment score. This method gives a numerical T-score which is normally distributed about a mean of 50 (if the goals are achieved precisely) with a standard deviation of around this mean of 10 (if the goals are overachieved or underachieved). If desired, the approach encompasses weighting of goals to reflect the opinion of the patient on the personal importance of the goal and the opinion of the therapist or team on the difficulty of achieving the goal. Some practical tips are offered, as well as a simple spreadsheet (in Microsoft Excel) allowing easy calculation of the T-scores.

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Metadata

Authors
Turner-Stokes, L.
Venue
Clinical Rehabilitation
Published
2009-01-29
Volume
23
Issue
4
Pages
362-370
ISSN
  • 0269-2155 (ISSN-L)
  • 1477-0873
OpenAlex
W2131027601
Cited by
841
References
2
FWCI
41.73
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Goal attainment scaling (GAS) in rehabilitation: a practical guide. https://app.cochat.ai/papers/10.1177/0269215508101742
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Turner-Stokes, L. (2009). Goal attainment scaling (GAS) in rehabilitation: a practical guide. Clinical Rehabilitation. https://doi.org/10.1177/0269215508101742

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.