In-Home Respite Care Services Available to Families With Palliative Care Needs in Quebec: Novel Digital Environmental Scan
Bibliographic record
Abstract
BACKGROUND: Caregiving dyads in palliative care are confronted with complex care needs. Respite care services can be highly beneficial in alleviating the caregiving burden, supporting survivorship and dying at home. Yet, respite care services are difficult to locate and access in the province of Quebec, Canada, particularly when navigating ubiquitous sources of online health information of varying quality. OBJECTIVE: This project aimed to (1) compile a list of at-home palliative respite care services in Quebec, Canada; (2) describe key accessibility features for each respite care service; (3) identify accessibility gaps and opportunities; and (4) describe a novel method for conducting environmental scans using internet search engines, internet-based community health databases, and member checking. METHODS: A novel environmental scan methodology using 2 internet-based targeted databases and 1 internet search engine was conducted. Results were screened and data were extracted, descriptively analyzed, and geographically schematized. RESULTS: A total of 401 services were screened, and 52 at-home respite care services specific to palliative populations were identified, compiled, and analyzed. These respite care services were characterized by various types of assistance, providers, fees, and serviced geographical regions. Accessibility was explored through the lens of service amenability, availability, eligibility, and compatibility. The data revealed important barriers to accessing respite care services, such as a lack of readily available information on service characteristics, limited availability, and a time-consuming, technical search process for potential respite care users and clinicians to identify appropriate services. CONCLUSIONS: Both methodological and contextual knowledge have been gained through this environmental scan. Few methodologies for conducting internet-based environmental scans have been clearly articulated, so we applied several learnings from other scans and devised a methodology for conducting an environmental scan using the mixed methods of internet search engines, internet-based community health databases, and member checking. We have carefully reported our methods, so that others conducting community health environmental scans may replicate our process. Furthermore, through this scan, we identified assorted respite care services and pinpointed needs in the provision of these services. The findings highlighted that more easily accessible and centralized information about respite care services is needed in Quebec. The data will enable the creation of a user-friendly tool to share with community support services across Quebec and ultimately help alleviate the added burden caregivers and clinicians face when looking for respite care services in fragmented and complex digital spaces.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".