Goal attainment scaling for patients with low back pain in rehabilitation: A systematic review
Bibliographic record
Abstract
BACKGROUND AND AIMS: Goal attainment scaling (GAS) has been widely applied to chronic conditions; however, only recently has it been used for patients with low back pain (LBP). The objectives of this systematic review were to (a) examine the characteristics and rigor of published studies of GAS in the rehabilitation of patients with LBP, (b) describe how GAS has been applied in patients with LBP, and (c) evaluate the responsiveness and validity of GAS as an outcome measure in patients with LBP. METHODS: A systematic search of the CINAHL, PubMed, and MEDLINE databases was performed (1968 and 1 September 2020) in addition to hand searching. Studies including GAS procedures in patients with LBP during rehabilitation were included in the review. Two authors independently selected studies for inclusion and determined levels of evidence using the Oxford Levels of Evidence and rated each study for quality using the Newcastle-Ottawa scale and reporting transparency using the STROBE statement checklist. RESULTS: Six Level IV and one Level III/IV study were included in this review (search produced 248 studies for review). These studies assessed GAS feasibility, validity, sensitivity, and association with other outcome measures in patients with LBP. Findings suggest that patients with LBP are able to identify and set individualized goals during GAS, while GAS may be more sensitive to change and may measure different aspects of the patient experience as compared with fixed-item patient-reported measures. Additionally, GAS may have a therapeutic effect while improving patient outcomes and may be associated with patient satisfaction. CONCLUSION: Based on this review, GAS shows promise as a feasible patient-centered measure that may be more responsive to change than traditional outcome measures. However, GAS has been inadequately developed and validated for use during rehabilitation in patients with LBP.
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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 | 0.015 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".