Comparing the Experiences of Participants With Mild Cognitive Impairment and Mild Dementia During an Oral Health Intervention
Bibliographic record
Abstract
Background and Objectives: Cognitive impairment is associated with poor oral health outcomes. Oral hygiene tasks are an essential target of interventions aiming to improve oral health for older adults with cognitive impairment. We aimed to examine whether experiences in an oral health intervention based on the Adaptive Leadership Framework for Chronic Illness differed between individuals with mild cognitive impairment (MCI) or mild dementia (MD) and their respective care partners. Research Design and Methods: = 16) in the treatment arm of the intervention. For each participant, we analyzed audio recordings of 4 intervention coaching sessions, each ranging between 30 and 45 min. We managed the data and coding using ATLAS.TI software. Results: Participants in both the MCI and MD groups experienced similar challenges in adapting to changes in oral hygiene techniques, and both groups worked on learning new oral hygiene techniques taught by the dental hygienist and meeting individualized goals developed with their care partner, interventionist, and hygienist. On the other hand, there were subtle differences in technical challenges between participants in MCI and MD groups; participants in the MCI group reacted more actively to dental hygienist suggestions than the MD group. Discussion and Implications: Study findings provide information about how researchers and clinicians might tailor interventions to meet the learning needs of individuals and care partners in each group.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| 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".