Assessing Technology Needs for Residential Autonomy: Considering Individual and Environmental Context
Bibliographic record
Abstract
Residential autonomy poses a challenge for individuals with intellectual disability (ID; Carey et al., 2022), autism spectrum disorder (ASD; Longuépée et al., 2019) or physical disability (PD; Kingsnorth et al., 2015). However, living in autonomous housing would enhance the well-being of individuals with disabilities and their relatives (INESSS, 2019). The aim of this qualitative study is to identify barriers, strategies and needs related to residential autonomy, as well as collected suggestions for assistive technology tools. For this qualitative research, five individuals with disability, three relatives and 19 care providers and managers were asked about the main challenges, strategies, and needs observed in the activities of daily living (ADLs), and instrumental activities of daily living (IADLs), including transportation, emotional management, safety, and environmental control. The results of this first phase allow the co-development of technological tools that will support individual autonomy, in addition to increasing their social involvement in partnership with field experts. L'autonomie résidentielle représente un défi pour les personnes atteintes d'une déficience intellectuelle (Carey et al., 2022), d'un trouble du spectre de l'autisme (Longuépée et al., 2019) ou d'une déficience physique (Kingsnorth et al., 2015). Cependant, résider dans des habitations autonomes pourrait augmenter le bien-être des individus et de leurs proches (INESSS, 2019). Cette étude qualitative a pour objectif de décrire les obstacles, les stratégies et les besoins relatifs à l'autonomie résidentielle, ainsi que d'obtenir des suggestions concernant les outils d'assistance technologique à développer pour promouvoir l'autonomie. Cinq individus en situation de handicap, trois proches aidants et 19 intervenants et gestionnaires ont été consultés pour fournir des informations sur les obstacles, les stratégies et les besoins observés dans les activités de la vie quotidienne, dont l'utilisation des transports, la gestion émotionnelle, la sécurité et le contrôle de l'environnement. Les résultats de cette première phase permettent le co-développement d'outils technologiques soutenant l'autonomie et la participation sociale en partenariat des experts.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".