Healthcare providers' perspectives on the Canadian Caries Risk Assessment Tool implementation in Indigenous pediatric primary care: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Early childhood caries remains a significant public health concern among Indigenous children in Canada. Integrating caries risk assessment (CRA) into primary care settings could improve early detection and intervention. OBJECTIVES: This qualitative study explored the barriers to implementing and integrating the Canadian CRA tool into the primary care of First Nations and Métis children in Manitoba, based on the perspectives of non-dental primary care providers (NDPCPs). METHODS: Fifty NDPCPs providing care to Indigenous children under six years of age were purposefully selected from ten Indigenous communities in Manitoba, including Winnipeg, Selkirk, St. Laurent, Swan River, Pine Creek, Camperville, and Pine Falls. The study employed an exploratory design, with data collected through eight focus groups and twelve in-depth key informant interviews conducted between April 2023 and September 2024. All interviews were audio-recorded, transcribed verbatim, and analyzed using inductive thematic analysis with NVivo software. RESULTS: Participants included pediatricians, family physicians, public health nurses, nurse practitioners, physician assistants, dietitians, and child development workers, with an average age of 41 years (range: 24-61) and 13 years of practice experience (range: 1-40). Thematic analysis identified four major barriers to integrating the CRA tool: (1) Service provider level - time constraint, scope of practice, documentation/referral pathways, and funding; (2) Community level - oral care not priority, separation of dental and general health, lack of transportation, and healthcare distrust; (3) Caregiver and child level - lack of dental insurance, parental willingness, substituting CRA for dental visit; and (4) Provider training and skills - lack of training on fluoride varnish application and dental screening. Despite these challenges, participants expressed a positive attitude toward receiving training on early childhood caries prevention, fluoride application, and the use of the Canadian CRA tool. CONCLUSION: This study highlights that NDPCPs in Manitoba recognize the Canadian CRA tool as a valuable resource for improving access to early preventive dental care for First Nations and Métis children. The identified barriers provide critical insights for dental, medical, and allied healthcare providers, offering a foundation for developing strategies, guidelines, and policies to enhance preventive oral health services for Indigenous children in Manitoba.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".