Development of a Caregivers’ Support Platform (Connected Health Sustaining Home Stay in Dementia): Protocol for a Longitudinal Observational Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Dementia disease is a chronic condition that leads a person with dementia (PwD) into a state of progressive deterioration and a greater dependence in performing their activities of daily living (ADL). It is believed nowadays that PwDs and their informal caregivers can have a better life when provided with the appropriate services and support. Connected Health (CH) is a new technology-enabled model of chronic care delivery where the stakeholders are connected through a health portal, ensuring continuity and efficient flow of information. CH has demonstrated promising results regarding supporting informal home care and Aging in Place, and it has been increasingly considered by researchers and health care providers as a method for dementia home care management. OBJECTIVE: This study aims to describe the development and implementation protocol of a CH platform system to support informal caregivers of PwDs at home. METHODS: This is a longitudinal observational mixed methods study where quantitative and qualitative data will be combined for determining the utility of the CH platform for dementia home care. Dyads, consisting of a PwD and their informal caregiver living in the community, will be divided into 2 groups: the intervention group, which will receive the CH technology package at home, and the usual care group, which will not have any CH technology at all. Dyads will be followed up for 12 months during which they will continue with their traditional care plan, but in addition, the intervention group will receive the CH package for their use at home during 6 months (months 3 to 9 of the yearly follow-up). Further comprehensive assessments related to the caregiver's and PwD's emotional and physical well-being will be performed at the initial assessment and at 3, 6, 9, and 12 months using international and standardized validated questionnaires and semistructured individual interviews. RESULTS: This 3-year funded study (2016-2019) is currently in its implementation phase and is expected to finish by December 2019. We believe that CH can potentially change the PwD current care model, facilitating a proactive and preventive model, utilizing self-management-based strategies, and enhancing caregivers' involvement in the management of health care at home for PwDs. CONCLUSIONS: We foresee that our CH platform will provide knowledge and promote autonomy for the caregivers, which may empower them into greater control of the care for PwDs, and with it, improve the quality of life and well-being for the person they are caring for and for themselves through a physical and cognitive decline predictive model. We also believe that facilitating information sharing between all the PwDs' care stakeholders may enable a stronger relationship between them, facilitate a more coordinated care plan, and increase the feelings of empowerment in the informal caregivers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13280.
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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 | 0.075 | 0.049 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.039 | 0.010 |
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".