Barriers and facilitators in providing oral health care to nursing home residents, from the perspective of care aides—a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Unregulated care aides provide up to 80 % of direct resident care in nursing homes. They have little formal training, manage high workloads, frequently experience responsive behaviours from residents, and are at high risk for burnout. This affects quality of resident care, including quality of oral health care. Poor quality of oral health care in nursing homes has severe consequences for residents and the health care system. Improving quality of oral health care requires tailoring interventions to identified barriers and facilitators if these interventions are to be effective. Identifying barriers and facilitators from the care aide's perspective is crucial. METHODS: We will systematically search the databases MEDLINE, Embase, Evidence Based Reviews-Cochrane Central Register of Controlled Trials, CINAHL, and Web of Science. We will include qualitative and quantitative research studies and systematic reviews published in English that assess barriers and facilitators, as perceived by care aides, to providing oral health care to nursing home residents. Two reviewers will independently screen studies for eligibility. We will also search by hand the contents of key journals, publications of key authors, and reference lists of all the studies included. Two reviewers will independently assess the methodological quality of the studies included using four validated checklists appropriate for different research designs. Discrepancies at any stage of review will be resolved by consensus. We will conduct a thematic analysis of barriers and facilitators using all studies included. If quantitative studies are sufficiently homogeneous, we will conduct random-effects meta-analyses of the associations of barriers and facilitators with each other, with care aide practices in resident oral health care, and with residents' oral health. If quantitative study results cannot be pooled, we will present a narrative synthesis of the results. Finally, we will compare quantitative findings to qualitative studies to identify hypothesized associations or effects not yet tested quantitatively. DISCUSSION: This review will advance the development of effective strategies for improving quality of oral health care and highlight gaps in research on barriers and facilitators to providing oral health care to nursing home residents, as perceived by care aides. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015032454.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".