Rehabilitation at Home With the Development of a Sustainable Model Placing the Person’s Needs and Environment at Heart: Protocol for a Multimethod Project
Bibliographic record
Abstract
BACKGROUND: Each year, more than 1.5 million people in Europe have a stroke, and many experience disabilities leading to activity and participation restrictions. Home-based rehabilitation is the recommended approach for stroke rehabilitation, in line with the international shift to integrated care. Despite this, rehabilitation often focuses on the person's physical functions, not the whole life situation and opportunities to live an active life. Given that rehabilitation today is often provided in the person's home, there is a need to develop new models that consider the rehabilitation process as situated in the everyday living environment of persons with stroke. This project is grounded in experiences from our ongoing research, where we study the importance of the home environment for health and participation among persons with stroke, rehabilitated at home. This research has shown unmet needs, which lead to suboptimal rehabilitation outcomes. There is a need for studies on how to use environmental resources to optimize stroke rehabilitation in the home setting. OBJECTIVE: The overarching objective of the project is to develop a new practice model for rehabilitation where the needs of the person are the starting point and where the environment is considered. METHODS: The project will be conducted in partnership with persons with stroke, significant others, health care professionals, and care managers. Results from a literature review will form the base for interviews with the stakeholders, followed by co-designing workshops aiming to create a new practice model. Focus groups will be held to refine the outcome of the workshops to a practice model. RESULTS: This 4-year project commenced in January 2023 and will continue until December 2026. The results of the literature review are, as of April 2024, currently being analyzed. The ethics application for the interviews and co-design phase was approved in October 2023 and data collection is ongoing during spring 2024. We aim to develop a practice model with stakeholders and refine it together with care managers and decision makers. The outcome is a new practice model and implementation plan, which will be achieved in autumn 2026. CONCLUSIONS: The project contributes with a prominent missing puzzle to optimize the rehabilitation process by adding a strong focus on user engagement combined with integrating different aspects of the environment. The goal is to improve quality of life and increase reintegration in society for the large group of people living with the aftermath of a stroke. By co-designing with multiple stakeholders, we expect the model to be feasible and sustainable. The knowledge from the project will also contribute to an increased awareness of the importance of the physical environment for sustainable health care. The findings will lay the foundation for future upscaling initiatives. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56996.
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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 | 0.093 | 0.081 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.078 | 0.014 |
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".