Exploring Professionals’ Experiences in the Rehabilitation of Older Clients with Dual-Sensory Impairment
Bibliographic record
Abstract
En vue de mieux comprendre et d'améliorer le processus de réadaptation des personnes âgées présentant à la fois une déficience auditive et visuelle, soit une double déficience sensorielle (DDS), cette étude s'est penchée sur les perspectives des professionnels de la santé qui œuvrent chez cette population. Treize professionnels aux parcours variés ont été interviewés en lien avec leur expérience de travail auprès de personnes âgées avec DDS. Les entrevues ont été transcrites et codées, et une analyse de contenu a été effectuée. Les participants des diverses professions ont perçu qu'ils devaient assumer les rôles additionnels suivants : (1) conseiller, (2) guide, (3) formateur ou rééducateur. Ces rôles consistaient à aider les personnes avec DDS et leurs familles présentant une dépression, des problèmes d'acceptation, des consultations répétées et des parcours complexes dans le système de santé. Selon les professionnels interviewés, ces rôles supplémentaires accroissent leur charge de travail et les confrontent à des problématiques pour lesquelles ils n'ont pas reçu de formation. Ils suggèrent l'implantation d'une formation sur les DDS pour les professionnels et les membres de la famille concernés, ainsi qu'une approche de réadaptation en équipe multidisciplinaire. To better understand and improve the rehabilitation process of older adults with sensory losses in both hearing and vision or dual sensory impairment (DSI), this study explored the perspectives of health care professionals who work with this population. Thirteen individuals, with varied professional backgrounds, were interviewed about their experiences in working with older adults with DSI. We transcribed and coded the interviews, then conducted content analysis. Regardless of their professional backgrounds, the participants reported additional roles that they perceived they fulfilled: (a) counsellor, (b) navigator, and (c) trainer and re-trainer. These roles involved helping individuals with DSI, and their family, with depression, acceptance, repeat consultations, and way-finding through the health system. From the professionals’ perspective, these additional roles increase workload and place them in situations they were not trained for. They suggest education for all professionals and for family members working with people with DSI; moreover, they suggest a multidisciplinary team rehabilitation approach.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".