Exploring the Behaviour Change Wheel and Theoretical Domains Framework in Interventions for Mobile Phone Use While Driving: a Scoping Review Protocol
Bibliographic record
Abstract
Background: Specific distracted driver behaviors such as using a mobile phone while driving is a major contributor to motor vehicle collisions. Macro level mitigation efforts such as legislation and legal penalties fall short in facilitating desired behaviour change. Thus, behavioural interventions are required to reduce mobile phone use while driving. This scoping review aims i) to identify behavioural constructs that have been targeted in intervention efforts to reduce mobile phone use while driving, ii) to map existing intervention attempts using the Behaviour Change Wheel and the Theoretical Domains Framework, iii) to identify target groups in intervention attempts and whether the success of the intervention vary by target groups’ demographic information (e.g. age, gender, driving experience).The findings will be discussed and used to develop a new intervention to reduce mobile phone use while driving in Ontario. Methods and Analysis: The review is being conducted in line with the Joanna Briggs Institute (JBI) manual for scoping review, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews for reporting. The following databases are being searched: MEDLINE, Embase, APA PsycINFO, TRID, Applied Social Sciences Index & Abstracts (ASSIA), and Scopus. Two researchers will independently screen search results to identify relevant studies. Two other researchers will extract data using a standardized data collection tool that is being developed. Ethics and Dissemination: This review is exempt from ethics approval. Authors aim to disseminate results through meetings with the Ministry of Transportation Ontario (MTO), report for MTO, conference presentations and publication in a leading peer reviewed journal.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".