Participation experiences of people with deafblindness or dual sensory loss: A scoping review of global deafblind literature
Bibliographic record
Abstract
BACKGROUND: Deafblindness, also known as dual sensory loss, is a varying combination of visual and hearing impairment in the same individual. Interest in this topic has increased recently due to evidence suggesting an increase in prevalence of this condition among older adults. Persons with deafblindness frequently experience participation barriers and social isolation. Developing an understanding of their experiences can inform the design of programs and policies to enhance participation of people with deafblindness in society. OBJECTIVE: To identify and summarize available research literature on participation experiences of people with deafblindness or dual sensory loss. METHODS: A comprehensive literature search of eight databases (CINAHL/EBSCO, Embase, ERIC, Global Health, MEDLINE, ProQuest, PsycINFO, PubMed) was performed in accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) during January 2017 and last updated in June 2017. In addition, non-peer reviewed (grey) literature was also retrieved in the form of online published reports of research projects by 16 deafblind-specific organizations across the globe. To be included, sources had to be published after 1990, had persons with deafblindness as the focal population, and focused on their participation experiences. RESULTS: A total 1172 sources were identified of which 54 studies were included. The findings reveal that persons with deafblindness, regardless of origin of their impairment, experience difficulty in communication, mobility, daily living functioning, and social interactions. While these experiences may vary between individuals with congenital versus acquired conditions, they generally feel socially isolated, insecure and uncertain about their future. CONCLUSION: Participation experiences of persons with deafblindness are shaped by dynamic interactions between personal factors (such as onset and type of impairments) and environmental influences (such as attitude, technology, and supports). A better understanding of participation experiences may help professionals in placing emphasis on affected participation domains to design services to enhance participation of people with deafblindness.
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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 | 0.013 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.025 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".