Expectations of stakeholders regarding technology in home care to optimise the functional autonomy of clients
Bibliographic record
Abstract
Purpose : In Quebec, administrators of home care are more and more open to offering smart environments as part of services to maintain at home individuals facing an important loss of autonomy. Nonetheless, the implementation of technology in the context of home care requires the involvement of other stakeholders including care providers, clients and their families. The influence of care providers on the implementation of technology within the healthcare system is documented (Cf. Reviews1 2). However, little information is available about the implementation of technology in the community as well as the perspective of the clients and their families. Consequently, stakeholders in home care may not have the same expectations as those working in an institutional setting. Acceptance of technology is not the only barrier to the implementation, other factors such as social, technical, and organizational context can play a role. \n \nMethod : Prior to implementing technology within home care services of an Integrated University Health and Social Services Centre in Montreal (Quebec), the purpose of this qualitative study was to evaluate the perspectives of multiple stakeholders in regards to: (1) facilitators and barriers to maintaining individuals at risk of self-neglect at home; and (2) expectations toward technology to optimise the functional autonomy of this clientele. lndividuals and group interviews were conducted with administrators (n = 2), head of services (n=S), care providers (n = 8), as well as clients at risk of \nself-neglect (n = 5) and their caregivers (n = 3). Data was analyzed using the approach of Miles, Huberman and \nSaldana. \n \nResults & Discussion : Perspectives of stakeholders were sometimes complementary but also divergent. On the one hand, the concept of perceived risk for the client was central to the decision-making process regarding the type of support needed to maintain the persan at home including technology. On the \nother hand, some of the clients expressed relatively no needs for services as they perceived themselves as functioning well at home while other stakeholders identified important problems. Overall, technology was \nexpected to fulfill two main functions: (1) obtaining additional data to support the decision-making process \nrelated to the type and frequency of support needed to maintain the client at home; and (2) supporting the \nautonomy of the client. In conclusion, these results suggest that the implementation of technology within home \ncare requires merging perspectives from multiple stakeholders to have a common understanding of the needs of the client and identify common objectives regarding the role of technology.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".