Partnering with periodontal patients and care providers to establish research priorities for patient engagement in specialized periodontal care: A study protocol
Bibliographic record
Abstract
INTRODUCTION: Periodontitis is highly prevalent and disproportionately affects vulnerable populations, including older adults, racial and ethnic minorities, and low-income individuals. While periodontal therapies are largely effective, patient engagement in periodontal care is problematic. The study describes in this protocol aims to identify the top ten research priorities or uncertainties for specialized periodontal care (SPC) that are most important to periodontal patients and care providers. METHODS: The James Lind Alliance approach will guide the priority-setting partnership (PSP), which involves several steps: forming a PSP steering committee, gathering potential research uncertainties, summarizing the research uncertainties, verifying unanswered uncertainties, completing an interim priority setting survey, and facilitating a priority setting workshop. Study participants will be periodontal patients (n ~ 150) and care providers (n ~ 120), including general dentists, periodontists, and dental hygienists in Alberta, Canada. A steering committee representing the four stakeholder groups will oversee the study. Data on uncertainties from these groups will be gathered through two online surveys and focus groups. Demographic data (e.g., age, sex) will be collected to describe participants and ensure representation of all stakeholder groups. Uncertainties submitted by participants will be evaluated against the existing evidence gathered through a scoping review to determine if they have already been addressed. Unanswered uncertainties will be taken to a workshop where participants (n ~ 20) representing all the stakeholder groups will set the top ten research priorities. Data analysis will include descriptive statistics and content analysis. The study is expected to conclude in August 2026. CONCLUSION: Study findings will be disseminated to raise awareness among researchers and funders on research priorities that matter most to patients and dental care providers regarding patient engagement in SPC.
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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 | 0.131 | 0.086 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.059 | 0.017 |
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".