Implementation of Goal Attainment Scaling in Community Intellectual Disability Services
Bibliographic record
Abstract
Abstract The authors describe the evaluation of the implementation of an outcome measurement system (Goal Attainment Scaling – GAS) within the context of an interdisciplinary and interagency intellectual disability services setting. The GAS database allowed analysis of follow‐up goals and indicated the extent of implementation, while a rater study evaluated the quality of goals. While staff were able to produce adequate goals and scales, fewer goals were set than anticipated, and the overall quality was not high. Although implementation resulted in a number of perceived benefits, various barriers to implementation were experienced. These hinged on staff perceptions of the value, ease of use, appropriateness, and soundness of the method. Widespread adoption of GAS in community intellectual disability teams is not supported by the findings of this study. The authors suggest that staff perceptions, ease of use, and the implementation process play a key role in the successful adoption of an outcome measurement system. They conclude that alternative ways of measuring individually oriented outcomes may be more useful.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.091 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".