Evidence map›Paper›PMID 29652523›Full record

ArticleTraffic injury prevention2018

Attitudes on technological, social, and behavioral economic strategies to reduce cellphone use among teens while driving.

M Kit Delgado, Catherine C McDonald, Flaura K Winston, Scott D Halpern, Alison M Buttenheim, Claudia Setubal, Yanlan Huang, Kathryn A Saulsgiver, Yi-Ching Lee

Abstract read
In one paragraph

Article in Traffic injury prevention, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Trial
  2. Novel Smartphone-Based Measures of Cell Phone Use While Driving in a Sample of Newly Licensed Adolescent Drivers.Health education & behavior : the official publication of the Society for Public Health Education · 2019
    Trial
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  12. Texting/Emailing While Driving Among High School Students in 35 States, United States, 2015.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

M Kit Delgadoa Behavioral Science and Analytics for Injury Reduction (BeSAFIR) Lab, Department of Emergency Medicine, Perelman School of Medicine , University of Pennsylvania , Philadelphia , Pennsylvania.ORCID 0000-0002-2248-8401
Catherine C McDonaldd Penn Injury Science Center, University of Pennsylvania , Philadelphia , Pennsylvania.
Flaura K Winstone Center for Injury Research and Prevention, The Children's Hospital of Philadelphia , Philadelphia , Pennsylvania.
Scott D Halpernb Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine , University of Pennsylvania , Philadelphia , Pennsylvania.
Alison M Buttenheimc Center for Health Incentives and Behavioral Economics , University of Pennsylvania , Philadelphia , Pennsylvania.
Claudia Setubala Behavioral Science and Analytics for Injury Reduction (BeSAFIR) Lab, Department of Emergency Medicine, Perelman School of Medicine , University of Pennsylvania , Philadelphia , Pennsylvania.
Yanlan Huanga Behavioral Science and Analytics for Injury Reduction (BeSAFIR) Lab, Department of Emergency Medicine, Perelman School of Medicine , University of Pennsylvania , Philadelphia , Pennsylvania.
Kathryn A Saulsgivera Behavioral Science and Analytics for Injury Reduction (BeSAFIR) Lab, Department of Emergency Medicine, Perelman School of Medicine , University of Pennsylvania , Philadelphia , Pennsylvania.
Yi-Ching Leej Department of Psychology , George Mason University , Fairfax , Virginia.

Funding

Institutional Clinical and Translational Science AwardUL1TR000003 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2012 to 2015
$38.9M
The Penn Roybal Center on Behavioral Economics and Health: Solving for Scale and Impact with Design Thinking, Digital Platforms, and Dynamic AdaptationP30AG034546 · NIA · UNIVERSITY OF PENNSYLVANIA · PI KEVIN G VOLPP · 2009 to 2026
$10.6M
Enabling Medical Research Growth in Emergency MedicineK12HL109009 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI KIMMEL, STEPHEN E. · 2011 to 2015
$3.4M
Reducing Risky Teen Cellphone Use While Driving Using Behavioral Economics, Technology, and EpidemiologyK23HD090272 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI DELGADO, MUCIO · 2017 to 2020
$675k
NCATS NIH HHS UL1 TR000003NHLBI NIH HHS K12 HL109009NIA NIH HHS P30 AG034546NICHD NIH HHS K23 HD090272
6 · The paper itself

Abstract

objectiveThe majority of U.S. teens admit to handheld cellphone use while driving, an increasingly common cause of crashes. Attitudes toward novel cellphone applications and settings that block use while driving are poorly understood, potentially limiting uptake. We examined teens' willingness to reduce cellphone use while driving and perceptions of potential strategies to limit this behavior.

methodsTeen drivers (n = 153) aged 16-17 who owned smartphones and admitted to texting while driving completed an online survey. Survey instruments measured willingness to give up cellphone use and perceptions of technological and behavioral economic strategies to reduce cellphone use while driving. We used chi-square tests to test the hypothesis that willingness to give up certain types of cellphone use while driving and the perceptions of strategies to reduce cellphone use while driving would differ by self-reported frequency of texting while driving in the past 30 days (low [1-5 days] vs. high [6 or more days]).

resultsMost teens were willing or somewhat willing to give up reading texts (90%), sending texts (95%), and social media (99%) while driving. However, they were not willing to give up navigation (59%) and music applications (43%). Those who engaged in high-frequency texting while driving were more likely to say that they were not willing to give up navigation applications (73 vs. 44%, P <.001), music applications (54 vs. 32%, P <.001), and reading texts (15 vs. 4%, P =.029). Overall, the following strategies where rated as likely to be very effective for reducing texting while driving: gain-framed financial incentives (75%), loss-framed financial incentives (63%), group-based financial incentives (58%), insurance discounts (53%), automatic phone locking while driving (54%), e-mail notifications to parents (47%), automated responses to incoming texts (42%), peer concern (18%), and parental concern (15%). Those who engaged in high-frequency texting while driving were less likely to say that following strategies would be very effective: automated responses to incoming texts (33 vs. 53%, P =.016), peer concern (9 vs. 29%, P =.002), and parental concern (9 vs. 22%, P =.025). The strongest perceived benefit of cellphone blocking apps was decreasing distraction (86%). The predominant reason for not wanting to use this technology was not wanting parents to monitor their behavior (60%).

conclusionsPromising strategies for increasing acceptance of cellphone blocking technology among teen drivers include automated screen locking and permitting hands-free navigation and music combined with behavioral economic incentives to sustain engagement.

Indexed as

Automobile DrivingEconomics, BehavioralSmartphoneText MessagingAdolescentDistracted DrivingFemaleHumansMalePerceptionRisk-TakingSelf Reportauto insurancebehavioral economicsCellphone usedistracted drivingtechnological interventionsteen drivers

Identifiers

PMID29652523
PMCPMC6215497

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.