Use of three-dimensional printing as a rehabilitation tool for individuals with deafblindness or vision impairment: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: This scoping review aims to synthesize evidence on the practices involving additive manufacturing, also known as three-dimensional printing, as a rehabilitation tool to assist individuals with deafblindness or vision impairment, and to identify which International Classification of Functioning, Disability and Health domains of functioning can be improved by its use. The goal is to inform health care professionals and family caregivers on how additive manufacturing may enhance the quality of life of people with deafblindness or vision impairment. INTRODUCTION: Deafblindness and vision impairment impact many life domains, such as access to information, communication, and mobility. The sense of touch is the main gateway for communication for individuals living with these impairments. Additive manufacturing is a promising technology for producing customized, tactile-based, low-cost tangible objects and devices that could improve the functioning of those with sensory impairment. Emerging studies explore the benefits of additive manufacturing in rehabilitation, education, and inclusion of people living with vision impairment, but very little is known about its use for the deafblind. INCLUSION CRITERIA: This review will consider studies that focus on the most widespread additive manufacturing technologies for the use of individuals living with deafblindness or vision impairment, their family caregivers, or professionals who provide their rehabilitation care. METHODS: A comprehensive search of 10 databases (PsycINFO, MEDLINE, Global Health, PubMed, CINAHL, Embase, ERIC, Web of Science, Engineering Village, and Scopus) will be conducted. Screening of records will be done at the title/abstract level and at the full-text level by independent reviewers of the team.
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 | 0.073 | 0.066 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.026 | 0.017 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.047 | 0.010 |
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".