Using the Behaviour Change Wheel to develop an oral hygiene self-care intervention for Punjabi immigrant adults: an illustrative example.
Bibliographic record
Abstract
Background: This article describes the development of an oral hygiene self-care behaviour change intervention (Safeguard Your Smile [SYS]) for Punjabi immigrant adults, using the Behaviour Change Wheel (BCW) theoretical framework. Methods: The 3 stages and 8 steps of the BCW were followed to develop the face-to-face SYS intervention. Identification of the problem in behavioural terms was enabled by referring to the results of a qualitative focus group (FG) previously conducted by the research team. Following the BCW method, the sources of behaviour were defined in terms of capability, opportunity, and motivation. Appropriate intervention functions, policy categories, behaviour change techniques (BCTs), and modes of delivery were then identified, selected, and mapped. Concrete strategies were chosen to bring about the desired oral hygiene self-care behavioural change. Results: Two main barriers to oral hygiene self-care faced by Punjabi immigrant adults were identified from the original FG: 1) inadequate knowledge and 2) inconsistent daily routine. Oral hygiene self-care behaviour was designated as a target behaviour, detailing frequency, duration, and technique. Five intervention functions (education, training, modelling, environmental restructuring, and enablement) and 2 policy categories (communication and service provision) were identified to influence the capability, opportunity, and motivation related to oral hygiene self-care behaviour. Nine BCTs were selected to influence desired oral hygiene self-care behaviour among adults. Conclusion: The development process for this SYS intervention may be employed by researchers to design a behaviour change intervention for other populations. However, additional strategies tailored to each specific context and population must be incorporated.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".