A systematic review of questionnaires to assess patient satisfaction with limb orthoses
Bibliographic record
Abstract
BACKGROUND: Assessment of patient satisfaction with orthosis is a key point for clinical practice and research, requiring questionnaires with robust psychometric properties. OBJECTIVES: To identify which validated questionnaires are used to investigate patient satisfaction with orthosis in limb orthotics and to analyse (1) their main fields of clinical application, (2) the orthosis-related features analysed by the questionnaires and (3) the strength of their psychometric properties. STUDY DESIGN: Systematic review. METHODS: A literature search using MEDLINE (PubMed), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Scopus databases for original articles published within the last 20 years was performed. RESULTS: A total of 106 papers pertaining to various clinical fields were selected. The main features of patient satisfaction with orthosis analysed were as follows: aesthetic, ease in donning and doffing the device, time of orthotic use and comfort. CONCLUSION: Of the questionnaires used to investigate patient satisfaction with orthosis, only four are adequately validated for this purpose: two for generic orthotic use (Quebec User Evaluation of Satisfaction with assistive Technology 2.0 and Client Satisfaction with Device of Orthotics and Prosthetic Users' Survey) and two for specific application with orthopaedic shoes (Questionnaire for the Usability Evaluation of orthopaedic shoes and Monitor Orthopaedic Shoes). Further development, refinement and validation of outcome measures in this field are warranted. CLINICAL RELEVANCE: Given the importance of analysing patient satisfaction with orthosis (PSwO), appropriate instruments to assess outcome are needed. This article reviews the currently available instruments and reflects on how future studies could be focused on the development, refinement and validation of outcome measures in this field.
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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 | 0.029 | 0.124 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".