Decentralized Management of Home Care Services for Seniors: Protocol for a Participatory Action Research
Bibliographic record
Abstract
BACKGROUND: The centralization of decision-making power in the public health care system has a negative impact on the practice of professionals and the quality of home care services (HCS) for seniors. To improve HCS, decentralized management could be a particularly promising approach. To be effective, strategies designed to incorporate this management approach require attention to 3 elements: autonomy of local stakeholders, individual and organizational capacities, and accountability for actions and decisions. Not many studies have focused on strategies for integrating decentralized and collaborative management at the local level in HCS. OBJECTIVE: The overall aim of this study is to coconstruct HCS management strategies and explore decentralized practices in the day-to-day work of low-level managers and professionals. The specific objectives, in collaboration with local HCS stakeholders, are to (1) identify concrete and achievable strategies for decentralized management, and (2) describe factors (facilitators and obstacles) that could potentially influence their integration. METHODS: This participatory action research involves a cyclical process. Before initiating the cycles, a preliminary stage consists of forming a steering committee composed of managers (n=3), professionals (n=3), seniors (n=3), informal caregivers (n=3), and the research team (n=3). This committee will facilitate multistakeholder consultation to coconstruct local management strategies based on a real-life problem identified by the committee. The steering committee will also guide the research process. The first cycle will consist of establishing an initial plan of decentralized management strategies. During the observation phase, meetings of 4 homogeneous focus groups, including managers, professionals, seniors, and informal caregivers, will be held. During the reflection phase, a thematic analysis will be carried out, and data will be interpreted and validated by the steering committee. Then, in the action phase, results will be presented to managers and professionals so that they can coconstruct a plan of decentralized management strategies to prioritize. The second cycle will explore the factors involved. The observation, reflection, and action phases will be repeated. Ultimately, the results of the 2 cycles will be integrated in a model coconstructed by the steering committee. RESULTS: Data collection is in progress; the partnership officially began on February 1, 2024, and the plan is to continue data collection through 2025. The steering committee will validate the data to ensure that they are accurate and that the results reflect the reality of local stakeholders. CONCLUSIONS: By identifying decentralized and collaborative management strategies at the local level as well as factors to facilitate their integration in HCS, this approach can be used for other decentralized management projects in different areas of the health care system. This study will give decision makers insight into strategies aimed at improving the management of their institution, which will enhance seniors' well-being and the quality of their health care services. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58271.
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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 | 0.185 | 0.136 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.063 | 0.013 |
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".