What Frames of Reference Underlie Self‐Ratings of Oral Health?*
Bibliographic record
Abstract
OBJECTIVES: This study aimed to investigate the referents and meanings that underlie self-ratings of oral health and to determine whether they vary by participants' characteristics. METHODS: Semistructured interviews were conducted with a convenience sample of 80 adults who were asked to rate their oral health and explain the reasons for their ratings. The interviews were tape-recorded, transcribed in full, and subject to a content analysis that involved identification and coding of their frames of reference. These codes were collapsed to create a smaller number of categories to allow for comparisons of the proportions invoking each frame of reference. RESULTS: There was considerable variation in the accounts offered to support the self-ratings of oral health. The most common referents used were biomedical, involving current oral problems, treatment needs and treatment histories, and behavioral, which included oral self-care practices, other health behaviors, and dental visiting patterns. Pain and tooth loss were also common. Most notable was the absence of functional and psychosocial referents that are prominent in contemporary definitions and measures of "oral-health-related quality of life." There was some variation in the referents used according to sociodemographic characteristics, with age being the main source of variation. There was also variation according to the category of the self-rating used; those with favorable ratings tended to use different frames of reference than those with unfavorable ratings. CONCLUSIONS: The biomedical model and professional ideologies and values provide the main frames of reference that give meaning to self-ratings of oral health. Variations in the meanings of the self-ratings have some implications for the use of this item in quantitative studies, which warrants further investigation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".