Goal attainment scaling in evaluating a multidisciplinary pain management programme
Bibliographic record
Abstract
OBJECTIVE: To examine the value of Goal Attainment Scaling (GAS) as a therapeutic tool and an outcome measure in a rehabilitation programme in the management of chronic pain. DESIGN: A prospective observational study. SETTING: A 15-day pain management programme, day case or residential, in an NHS Regional rehabilitation centre. SUBJECTS: One hundred and forty-nine consecutive patients enrolled during a 15-month period. INTERVENTIONS: Multidisciplinary structured educational programme of physiotherapy, occupational therapy and clinical psychology. MAIN OUTCOME MEASURES: GAS; timed tests of physical mobility measures; McGill Pain Questionnaire (MPQ); Pain Intensity Numerical Rating Scale (NRS); Oswestry low back pain Disability Questionnaire (ODQ); General Health Questionnaire (GHQ); Pain and Impairment Relationship Scale (PAIRS). GAS and physiotherapy measures were compared with baseline data at enrollment and at discharge 15 days later. At six-month follow-up all measures were repeated. RESULTS: Significant improvements at discharge were found for GAS, and physiotherapy measures. One hundred and twelve patients returned for review at six months, when improvements were maintained for GAS, sit/stand, Pain, ODQ and GHQ. GAS was shown to be a valid measure of ability, correlating significantly with walking improvement and somewhat less with a therapist-defined measure, suggesting some ability to discriminate. CONCLUSIONS: The improvement measured by GAS showed that patients were enabled by the programme to achieve personally valued goals over a six-month period and to improve on these more than on other more conventional outcome measures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".