A qualitative study on stakeholder perceptions of digital prosthetic socket fabrication for transtibial amputations
Bibliographic record
Abstract
BACKGROUND: Digital residual limb shape capture (three-dimensional [3D] scanning), computer-assisted design (CAD), and computer-assisted manufacturing with 3D printing technology show promise for a completely digital process of fabricating prosthetic sockets for patients with limb loss. The effectiveness and quality of digitally designed 3D-printed lower extremity prosthetic sockets is understudied, and there is lack of data on the patient and prosthetist experiences with this digital workflow. OBJECTIVE: To obtain stakeholder feedback on the feasibility and acceptability of using a completely digital prosthetic fabrication process consisting of 3D scanning, CAD, and 3D printing in a rehabilitation setting for adults with transtibial limb amputations. STUDY DESIGN: Qualitative design. METHODS: Study participants with a transtibial-level amputation were fit with a prosthetic socket fabricated using digital shape capture with a 3D scanner, CAD, and 3D printing in addition to a traditionally handcasted manually fabricated socket. Participants tried on and evaluated both sockets. Semistructured interviews took place after the fitting appointments. A focus group was conducted with prosthetists to obtain their feedback. Audio data were transcribed verbatim, and an inductive content analysis was undertaken. RESULTS: Eleven patient participants and 3 prosthetists identified 4 main themes: 1) openness and enthusiasm for digital prosthetic fabrication; 2) relative advantages of digital fabrication vs. traditional socket fabrication; 3) readiness of the technology used for adoption in practice; and 4) digital prosthetic workflow and 3D printing implementation considerations. CONCLUSIONS: Patients and prosthetists were enthusiastic about digital prosthetic socket fabrication and saw potential advantages over traditional methods. Both patients and prosthetists had concerns about the durability, safety, and aesthetics of the 3D printed sockets in this study. Further studies are needed to optimize digital prosthetic fabrication with 3D printing in prosthetic practice.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".