Perspectives on Oral Health After Stroke: A Mixed Methods Study Involving Health Care Professionals, Stroke Survivors and Primary Caregivers
Bibliographic record
Abstract
Maintaining good oral health after a stroke can be challenging, requiring stroke survivors (StS) to rely on healthcare professionals (HCPs) and caregivers for mouth/denture cleaning. This study aimed to understand the oral/denture care practices of HCPs and explore StS’ experiences in acute stroke care and rehabilitation settings. A mixed methods approach was used, involving quantitative data from a retrospective review (RCR) of 168 charts and an oral health and care survey (OHCS) with 32 HCPs. The multiple case study (MCS) included six StS and caregivers with data from care observations, oral examinations, interviews, and chart reviews. RCR and OHCS revealed that while HCPs had good knowledge about oral health, they lacked confidence in providing oral/denture care due to insufficient education, leading to a shortfall in adherence to Canadian stroke guidelines. Sociostructural factors such as the absence of an oral/denture care protocol presented barriers to care provision. From the MCS, the rehabilitation center showed more support for regaining self-care skills compared to the acute care hospital, with caregivers playing a crucial role in supporting oral/denture care activities. The study highlights the need for an evidence-based oral/denture care protocol in both hospitals, tailored to specific needs, outlining care processes, defining stakeholder roles, and promoting education. The recommended protocol should include an oral screening tool, toothbrushing twice daily, and continuing education for HCPs, StS, and caregivers. These findings contribute to future protocol development and oral/denture care initiatives in Canadian hospitals and institutions, emphasizing a feasible patient-centered approach to enhance stroke recovery.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".