What’s in a name: Dual sensory impairment or deafblindness?
Bibliographic record
Abstract
Communications about deafblindness within the clinical and research literature are littered with several terms that have not yet been well established or defined, such as deafblindness, dual sensory loss, or combined vision and hearing impairment. Depending on the context (e.g. service delivery for children, adults, or seniors) or the user (e.g. educators, clinicians, researchers, or clients), these terms are sometimes used interchangeably; such practice, however, can be misleading and does not assist the scientific goal of precise communication. The goal of this study was to review the existing definitions of these terms and their use through a systematic review of the literature and by conducting a qualitative survey to solicit the opinions of clinicians and researchers in the field of deafblindness. A systematic review of five databases resulted in 809 references containing terms relevant to deafblindness, which were then searched using the terms, such as deafblind, deaf-blind, deaf AND blind, dual, vision AND hearing, and combined, as they appeared in the titles and/or abstracts. In addition, a survey of researchers and rehabilitation professionals in this domain was conducted. The large majority of articles using deafblind-related terminology were published in clinician-oriented journals, whereas authors of high-impact research journal articles (many outside the domain of sensory rehabilitation) were more likely to utilize terms such as dual sensory or combined impairment. This segregation was similar in the 68 responses obtained through the survey. There is a need to harmonize the interpretation of terminology, specifically across professionals and interest groups relevant to deafblindness. Through the development of comparable terminology and clarity in communication, rehabilitation professionals will find it easier to access (and translate) research findings in their respective fields. In addition, the exchange of ideas between practitioners and researchers will be easier, resulting in more practically relevant research projects.
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 | 0.016 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.006 | 0.019 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".