Alternative and Augmentative Communication Technologies for Supporting Adults With Mild Intellectual Disabilities During Clinical Consultations: Scoping Review
Bibliographic record
Abstract
BACKGROUND: People with intellectual disabilities (IDs) face significant communication barriers when accessing health care services; they find it difficult to identify and describe conditions clearly enough to support practitioners in making an accurate diagnosis. In addition, medical professionals generally have little knowledge and understanding of the needs of people with ID, which may result in the use of consultation techniques that do not cater to their patients' skills. OBJECTIVE: This review aims to identify and synthesize the literature on alternative and augmentative communication technologies that are used to support adults with mild ID during the exchange of information with medical practitioners. METHODS: We performed a scoping review of studies published in English that describe the technologies that are used to promote communication with patients with mild ID during medical consultations. The databases searched were PubMed, ACM Digital Library, and Google Scholar. A qualitative framework-based approach was used to synthesize the data and discern key recurring themes across the identified literature. RESULTS: Of the 1557 articles screened, 15 (0.96%) met our inclusion criteria. The bulk of the communication aids used focused on low-tech solutions, including patient passports, note-based prompts, Talking Mats, health diaries, and easy-read information sheets. Their influence on current practice ranged from advancing medical professionals' knowledge of the health and communication needs of people with ID to increasing interagency collaboration, patient advocacy skills, and health promotion activities. The major barriers to the implementation of low-tech aids were a lack of portability and increased maintenance efforts. Only 3 studies explored the use of mobile apps to promote communication. Their findings indicated that high-tech solutions offer greater customization with regard to the accessibility and health care needs of people with ID. CONCLUSIONS: Alternative and augmentative communication technologies have the potential to increase the quality of care provided to patients with mild ID; however, little work has been carried out in this area. Greater emphasis must be placed on (high-tech) two-way communication aids that empower patients to become involved in decisions regarding their care. Quantitative evaluation methods should be used to discern the true benefits of such aids, and researchers should describe their study protocols in depth to promote replication and generalizability.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".