Using behavior change techniques to identify components for adapting a vaccination in pregnancy communication intervention in Canada
Bibliographic record
Abstract
BACKGROUND: Vaccine communication is critical to improve pregnancy and childhood vaccination uptake. However, communication about vaccination in pregnancy between health care providers and patients is suboptimal. The Sharing Knowledge About Immunization (SKAI) is an Australian multicomponent intervention aimed at improving vaccine communication to increase vaccine uptake in pregnancy and childhood. However, it is unclear whether and how effective the intervention would be in the Canadian context. OBJECTIVES: The objectives of this study were to (1) determine what components of SKAI addressed vaccine communication and barriers identified by providers and parents in Canada, and (2) if necessary, identify additional intervention components that could improve vaccine communication during pregnancy in Canada. METHODS: This multi-method study used the Behaviour Change Wheel and the Theory and Techniques Tool to (1) identify behavior change techniques (BCTs) in the SKAI intervention; (2) map the identified BCTs to the barriers and enablers of vaccination in pregnancy communication, as reported by providers and parents in Canada, using the Theoretical Domains Framework; and (3) if the BCTs identified did not address reported barriers, develop a shortlist of possible BCTs to target barriers reported in Canada but not identified in SKAI. RESULTS: A total of 22/93 BCTs were identified in the SKAI intervention materials for providers and 8/93 BCTs in the materials for patients. The majority of BCTs from both the providers' and the patients' materials targeted the barrier domains, Knowledge and Environmental Context and Resources, focusing on providing information. The domains with the fewest BCTs identified were Intention and Behavior Regulation. BCTs that targeted barriers in Skills, Belief About Capabilities , and Behavior Regulation for providers and Reinforcement, Social Influences , and Emotions for parents and not identified in SKAI were shortlisted (n = 26) for the Canadian intervention. CONCLUSION: A tailored Canadian intervention aimed at improving vaccine communication during pregnancy should move beyond simply providing information, and should include BCTs that target Skills , Belief About Capabilities , and Behavior Regulation for providers. For parents, BCTs should target Reinforcement, Social Influences , and Emotions . Including BCTs that target these barriers that are unique to the Canadian context will increase the likelihood of changing patients' and providers' communication behavior and improving vaccine acceptance during pregnancy. SPANISH ABSTRACT: http://links.lww.com/IJEBH/A427.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".