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Enregistrement W2175280707 · doi:10.5339/jlghs.2015.itma.72

Innovative strategies to reduce traffic related injuries and deaths in youth

2015· article· en· W2175280707 sur OpenAlexaff
Joanne Banfield

Notice bibliographique

RevueJournal of Local and Global Health Science · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueInjury Epidemiology and Prevention
Établissements canadiensHealth Sciences CentreSunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésCommitCognitive dissonanceIntervention (counseling)Injury preventionSuicide preventionHuman factors and ergonomicsPsychologyOccupational safety and healthPoison controlApplied psychologyMedicineMedical emergencyComputer securitySocial psychologyPsychiatryComputer science

Résumé

récupéré en direct d'OpenAlex

Introduction: Road traffic injuries are the leading cause of death among young people, aged 15-29 years (1). It is generally accepted that the high rate of adolescent injuries may be due to a variety of factors. Studies have shown young drivers are more likely to underestimate the probability of specific risks caused by traffic situations, as well as to overestimate their own driving skills making them more vulnerable to trauma. It has also been hypothesized that adolescents are more prone to motor vehicle collisions due to their risk-taking attitudes (2). There is consensus among experts in the field of road safety that the best road safety strategies and programs are based on research-driven and psycho-social theories of behavior (3). The P.A.R.T.Y. (Prevent Alcohol and Risk-Related Trauma in Youth) Program is one of those programs. Developed in 1986, P.A.R.T.Y. is a one day, in hospital injury awareness and prevention program for youth aged 15 and older. The goal is to provide young people with information about trauma that will enable them to recognize their injury risks, make prevention-oriented choices and adopt behaviours that minimize unnecessary risks through vivid clinical reality. Attitudes towards risk taking in traffic have been correlated with aggressive driving behavior, speeding, and intention to commit traffic law violations. Thus, an effective intervention to increase road safety may be to change the attitudes that influence the driving behavior of adolescents. This is consistent with the cognitive dissonance theory, which states that changing the beliefs that underlie certain behaviors can cause a behavioral change (2). From these theories, one can expect that changing the risk taking attitudes of adolescents can lead to a decrease in the probability of collisions. A recent meta-analysis suggested interventions aimed at influencing attitudes might be the most effective measure to improve safety on the roads (2). Methods: Several research studies have been undertaken to determine effectiveness and changes in attitudinal risk behavior from youth attending the P.A.R.T.Y. A ten-year longitudinal study was conducted to determine whether students who attended P.A.R.T.Y. had a reduction in injuries compared with a matched control group of students based on age, gender and geographic area who did not attend the program. Students follow the course of injury from occurrence through transport, treatment, rehabilitation and community re-integration phases. Additionally by augmenting a didactic format through a technologically innovative approach including but not limited to vivid clinical reality, social media, interactive websites and simulators we see attitudinal and behavioural changes. Results: The 10 year longitudinal study showed P.A.R.T.Y. participants had a lower incidence of traumatic injuries than a control group of non-P.A.R.T.Y. participants of the same age, gender, residential area, and initial year in database, during the 10-year study (4). Conclusion: Research-driven, psycho-social theories of behavior and technologically innovative approaches have proven it is possible to influence behavior through the delivery of well-designed and well-executed road safety strategies, programs and campaigns. Providing students with real-life education to depict the vivid clinical reality of injuries was shown to be a compelling and effective method of education. References 1. Road safety basic facts. World Health Organization. 2013 [cited July 28, 2015]. Available from:http://www.who.int/violence_injury_prevention/publications/road_traffic/Road_safety_media_brief_full_document.pdf 2. Pal Ulleberg, T.R., Risk-taking attitudes among young drivers: The psychometric qualities and imensionality of an instrument to measure young drivers' risk-taking attitudes. Scandinavian Journal of Psychology, 2002. 43(3): p. 227-237. 3. Road Safety Campaigns: What the research tells us. Traffic Injury Research Foundation.2015 [cited July 7, 2015]. Available from: http://www.tirf.ca/publications/PDF_publications/2015_RoadSafetyCampaigns_Report_2.pdf 4. Banfield JM, Gomez M, Kiss A, Redelmeier DA, Brenneman F. Effectiveness of the P.A.R.T.Y. (prevent alcohol and risk-related trauma in youth) program in preventing traumatic injuries: A 10-year analysis. J Trauma. 2011 Mar;70(3):732-5.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,619
Score d'incertitude au seuil0,269

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,051
Tête enseignante GPT0,419
Écart entre enseignants0,368 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2015
Routes d'admission1
Résumé présentoui

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