FEEDBACK trial - A randomised control trial to investigate the effect of personalised feedback and financial incentives on reducing the incidence of road crashes
DOI: 10.1186/s12889-023-16886-z
archive: archived pipeline: cataloged verified
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Summary
The FEEDBACK trial is a study protocol for a multi-centre, two-arm parallel-group individually randomised controlled trial designed to evaluate whether personalised driver feedback combined with financial incentives reduces road crash incidence among young drivers. The study addresses the significant public health burden of road injuries, particularly among drivers aged 18–25, who are over-represented in crash statistics, especially during their first year of provisional licensing. While previous research suggests that feedback and incentives can improve driving behaviours, this trial is the first to specifically evaluate the impact of these interventions on actual crash outcomes in this vulnerable population. The trial will recruit 3,610 young drivers (aged 18–20) holding a first-year provisional (P1) licence in Queensland, New South Wales, or Western Australia. Participants will engage in a 28-week study comprising a 4-week baseline, a 20-week intervention, and a 4-week post-intervention period. Driving data, including speed, harsh braking, and acceleration, will be collected via mobile telematics through a smartphone application. After the baseline, participants will be randomised into an intervention group or a control group. The intervention group will receive personalised feedback in the form of a “DrivePoints” score and financial incentives structured as loss-framed penalties. Specifically, participants receive an upfront payment of AU$120, from which AU$24 is deducted monthly if they fail to meet personalised, progressively stricter safe driving targets. The control group receives no feedback or incentives but is entered into weekly prize draws to maintain engagement. The primary outcome is the incidence of police-reported crashes during the 24-week intervention and post-intervention periods. Secondary outcomes include self-reported crashes, changes in DrivePoints scores, and specific risky driving behaviours such as speeding, harsh braking, and hard acceleration, measured via telematics. Statistical analysis will employ Poisson regression for police-reported crashes, log-binomial regression for self-reported crashes, and constrained longitudinal data analysis for DrivePoints scores. The study aims to detect a reduction in police-reported crashes from 3% in the control group to 1.5% in the intervention group. The significance of this trial lies in its potential to provide robust evidence for policymakers regarding the efficacy of population-scale interventions linking insurance premiums or financial penalties to safer driving behaviours. By utilising “smart incentives” that leverage loss aversion and personalised thresholds, the study seeks to determine if such strategies can effectively mitigate the high risk of injury associated with young, inexperienced drivers. Positive findings could support the implementation of similar feedback and incentive programs to help Australia achieve its national road safety targets.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-17 |
| archive | success | unpaywall | — | — | 2 | 2026-06-25 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-18 |
| chunk | success | chunk | — | — | 1 | 2026-06-18 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-18 |
| promote | success | — | — | — | 1 | 2026-06-17 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-18 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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Information type
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- Applied Guidance: countermeasure evaluation
- Empirical Findings: crash risk outcomes
- Methodological Resource: dataset resource