Bibliographic record
Abstract
BACKGROUND: The liner is an integral part of a transtibial prosthesis designed to protect the residual limb, enhance comfort and provide suspension. Literature is difficult to interpret and use given the variety of interventions, outcome measures and method designs. Critical appraisal and synthesis of the evidence is needed to help inform decisions about liner prescription based on the user experience. OBJECTIVES: To critically appraise and synthesise research describing the user experience of transtibial prosthetic liners. STUDY DESIGN: Systematic review. METHODS: A comprehensive suite of databases were searched using terms related to amputation level, liner type and user experience. Included studies were in English and measured the first-person experience of using a transtibial liner. Studies were appraised using the McMaster University Critical Review Forms. RESULTS: A total of 18 articles met the inclusion criteria. While the quality of the evidence has improved over time, a number of common issues (e.g. sampling bias, validity of outcome measures, incorrect inferential analysis) reduce our ability to differentiate between the user experience of different transtibial liners. CONCLUSION: There is insufficient research to differentiate between the user experience of different transtibial liners. High-quality research is needed to inform decisions about liner prescription based on the user experience. Clinical relevance The available evidence suggests that the user experience of commonly reported problems (e.g. sweating) may be very similar between different liners. Aspects of the user experience that differ most between liners (e.g. unwanted noises, rotation within the socket) can help focus attention on what matters most when discussing prescription.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".