The six‐domain well‐being framework in oral health sciences: A pathway from theory to practice
Bibliographic record
Abstract
OBJECTIVES: Well-being is a complex and multifaceted construct that has gained popularity in oral health sciences education. Maintaining students' well-being is essential for their academic performance and quality of life. While many definitions and frameworks of well-being exist, their applicability to oral health sciences education remains unknown. This study aimed to evaluate the applicability of the Feeney and Collins's framework of well-being to oral health sciences education by exploring students' perceptions and experiences in the University of British Columbia METHODS: An Interpretive Description approach was used to conduct semi-structured interviews with dental and dental hygiene students. Interviews were transcribed, and transcripts were coded and analyzed with guidance from Feeney and Collins's well-being and thriving framework using content analysis. Domains were inductively developed within and beyond the organizing categories of the chosen framework. RESULTS: Thirty-one oral health sciences students participated in the study. Study data can largely be explained by the five well-being domains suggested by Feeney and Collins: physical, psychological, eudaimonic, subjective, and social. Spirituality and gratitude emerged as an additional domain that contributes to students' well-being. Interdomain relationships were observed. The social domain seemed to contribute to all other well-being domains; while the subjective domain seemed to be shaped by all other domains CONCLUSIONS: Feeney and Collins's framework seemed to be useful to understand and conceptualize well-being in oral health sciences education but needed to be expanded to include spirituality and gratitude. Further evidence is needed to explore the applicability of this framework in other health professional education disciplines.
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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 | 0.041 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.007 |
| 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".