These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

167 related articles for article (PubMed ID: 34781172)

  • 21. Young drivers and smartphone use: The impact of legal and non-legal deterrents.
    Ogden J; Brown PM; George AM
    J Safety Res; 2022 Dec; 83():329-338. PubMed ID: 36481024
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Application of the theory of planned behaviour to the prediction of objectively assessed breaking of posted speed limits.
    Conner M; Lawton R; Parker D; Chorlton K; Manstead AS; Stradling S
    Br J Psychol; 2007 Aug; 98(Pt 3):429-53. PubMed ID: 17705940
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Gender differences in the effectiveness of public education messages aimed at smartphone use among young drivers.
    Gauld CS; Lewis IM; White KM; Watson BC; Rose CT; Fleiter JJ
    Traffic Inj Prev; 2020; 21(2):127-132. PubMed ID: 32154732
    [No Abstract]   [Full Text] [Related]  

  • 24. Cross-cultural differences in drivers' speed choice.
    Wallén Warner H; Ozkan T; Lajunen T
    Accid Anal Prev; 2009 Jul; 41(4):816-9. PubMed ID: 19540971
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Predicting Australian adults' sun-safe behaviour: examining the role of personal and social norms.
    White KM; Starfelt LC; Young RM; Hawkes AL; Leske S; Hamilton K
    Br J Health Psychol; 2015 May; 20(2):396-412. PubMed ID: 24917299
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Promoting drivers' compliance with speed limits: testing an intervention based on the theory of planned behaviour.
    Elliott MA; Armitage CJ
    Br J Psychol; 2009 Feb; 100(Pt 1):111-32. PubMed ID: 18662491
    [TBL] [Abstract][Full Text] [Related]  

  • 27. The use of risk homeostasis theory to reduce smartphone use during low-speed driving.
    Kita E; Luria G; Pindek S; Albert G; Lotan T
    Accid Anal Prev; 2022 Apr; 168():106596. PubMed ID: 35180466
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Using the theory of planned behaviour to predict observed driving behaviour.
    Elliott MA; Armitage CJ; Baughan CJ
    Br J Soc Psychol; 2007 Mar; 46(Pt 1):69-90. PubMed ID: 17355719
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Theory of planned behaviour, psychological stressors and intention to avoid violating traffic rules: A Multi-Level modelling analysis.
    Shukri M; Jones F; Conner M
    Accid Anal Prev; 2022 May; 169():106624. PubMed ID: 35272222
    [TBL] [Abstract][Full Text] [Related]  

  • 30. "I Snapchat and Drive!" A mixed methods approach examining snapchat use while driving and deterrent perceptions among young adults.
    Truelove V; Freeman J; Davey J
    Accid Anal Prev; 2019 Oct; 131():146-156. PubMed ID: 31255800
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Underestimated Risk Perception Characteristics of Drivers Based on Extended Theory of Planned Behavior.
    Chen Y; Liu X; Xu J; Liu H
    Int J Environ Res Public Health; 2022 Feb; 19(5):. PubMed ID: 35270437
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Testing an extended theory of planned behaviour to predict young people's sun safety in a high risk area.
    White KM; Robinson NG; Young RM; Anderson PJ; Hyde MK; Greenbank S; Rolfe T; Keane J; Vardon P; Baskerville D
    Br J Health Psychol; 2008 Sep; 13(Pt 3):435-48. PubMed ID: 17535506
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Speeding by young novice drivers: What can personal characteristics and psychosocial theory add to our understanding?
    Scott-Parker B; Hyde MK; Watson B; King MJ
    Accid Anal Prev; 2013 Jan; 50():242-50. PubMed ID: 22608268
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A priori acceptance of highly automated cars in Australia, France, and Sweden: A theoretically-informed investigation guided by the TPB and UTAUT.
    Kaye SA; Lewis I; Forward S; Delhomme P
    Accid Anal Prev; 2020 Mar; 137():105441. PubMed ID: 32007779
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Perceived enjoyment, concentration, intention, and speed violation behavior: Using flow theory and theory of planned behavior.
    Atombo C; Wu C; Zhang H; Wemegah TD
    Traffic Inj Prev; 2017 Oct; 18(7):694-702. PubMed ID: 28332869
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Mobile phone use among truck drivers: The application and extension of the theory of planned behavior.
    Baikejuli M; Shi J; Qian Q
    Accid Anal Prev; 2023 Jan; 179():106894. PubMed ID: 36370511
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Why do older drivers self-regulate: Psychological factors influencing self-regulation in a Chinese sample.
    Chen B; Zhao X; Ding Z; Li Y; Wan M; He Q; Liu X
    J Safety Res; 2022 Feb; 80():330-340. PubMed ID: 35249613
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Y TXT N DRIVE? Predictors of texting while driving among a sample of Ontario youth and young adults.
    Berenbaum E; Harrington D; Keller-Olaman S; Manson H
    Accid Anal Prev; 2019 Jan; 122():301-307. PubMed ID: 30408754
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Assessing driver acceptance of technology that reduces mobile phone use while driving: The case of mobile phone applications.
    Oviedo-Trespalacios O; Briant O; Kaye SA; King M
    Accid Anal Prev; 2020 Feb; 135():105348. PubMed ID: 31790969
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Predicting healthy eating intention and adherence to dietary recommendations during pregnancy in Australia using the Theory of Planned Behaviour.
    Malek L; Umberger WJ; Makrides M; ShaoJia Z
    Appetite; 2017 Sep; 116():431-441. PubMed ID: 28536056
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.