Caregivers' knowledge, attitudes and behaviour towards the daily oral care of bedridden patients in Chiang Rai, Thailand
Bibliographic record
Abstract
OBJECTIVES: The objectives of this study are to explore caregivers' knowledge, attitudes and behaviours towards oral care for bedridden patients and to examine the relationship among those three variables. METHODS: Participants were 24 caregivers from Muang District, Chiang Rai Province, Thailand, who agreed to be part of the study. Data were collected in January 2020 via a 24-item questionnaire covering knowledge such as understanding what can cause and prevent oral problems, attitudes such as feelings towards providing oral care and behaviours such as actions taken to clean the patient's mouth. Caregivers were also interviewed using a semi-structured guide to further explore their oral health care knowledge, attitudes and behaviours. Descriptive analysis and Chi-square correlation were used to analyse quantitative data. Thematic analysis was used to explore the interview data. RESULTS: The caregivers' roles were all informal, with an average age of 54.2 years and almost all were female (91.7%). They cared for bedridden patients who were on average 14 years older, comprised mostly of their parents (54.1%) and were partially dentate (79.2%); half were males. Although most caregivers (87.5%) did consider sugar as likely causing tooth decay, one in three did not think that fluoride toothpaste could help to prevent dental decay. None of the edentulous patients and 42.1% of the partially dentate patients had their mouths cleaned by their caregivers daily. Knowledge was not associated with the oral health care behaviour of the caregiver (P = .43). Financial constraints, limited knowledge and personal beliefs contributed to caregivers' behaviour towards oral health care for their bedridden patients. CONCLUSIONS: Knowledge remains unassociated with behaviour. Caregiver education and support are needed to maintain good oral health care practices for bedridden patients.
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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 | 0.000 |
| 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".