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Enregistrement W3095893026 · doi:10.70010/afzy8167

Assessment of various critical incident management and support protocols for railway employees after a serious incident

2019· article· en· W3095893026 sur OpenAlexaboutno aff
Cécile Bardon

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueRisk and Safety Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIncident managementCritical Incident TechniqueIncident reportComputer scienceRisk analysis (engineering)Computer securityBusiness

Résumé

récupéré en direct d'OpenAlex

The Canadian railway industry must regularly deal with critical incidents (CI) involving collisions with people or vehicles. Such incidents may result in serious injuries or even fatalities, in addition to causing mental health problems for the locomotive engineers and conductors involved. Every year, approximately one hundred people in Canada, including some 20 in Québec, lose their lives in collisions with trains. In addition to fatal events, an unknown number of incidents also occur in which people are injured or property is damaged. Most locomotive engineers and train conductors will be exposed to this type of event at least once in their careers. When a critical incident of this nature occurs, they are witnesses, victims, participants and often first responders, all at the same time. A significant proportion of locomotive engineers and train conductors soon return to satisfactory personal and occupational functioning levels and have very few psychological, social or functional after-effects. However, the recovery time after a CI can be quite long, and employees require support during this period. In addition, between 4% and 17% of these employees will experience more serious problems, including depression, acute stress disorder, posttraumatic stress disorder or anxiety. Several clinical approaches are effective in mitigating posttraumatic symptoms, and a great deal of the research has focused on them. In contrast, needs are less well known and there are fewer resources for those who do not suffer posttraumatic stress, but who struggle with major undiagnosed adverse effects. Some studies have examined the critical incident management and support protocols (CIMSPs) implemented by employers, and they often recommend the adoption of practices to reduce the potential impact of critical incidents on employees and to shorten their recovery period. However, although these protocols are based on studies of CI after-effects and employees’ needs, they have not yet undergone empirical evaluation. Assessments of this kind are necessary to determine the key elements of these protocols that have a positive impact on employee recovery and to promote recommendations based on scientific findings. The aim of this project was to assess the CIMSPs that have been implemented in the Canadian rail industry and their impact on the recovery of employees who have been involved in critical incidents and to propose key practices to reduce the adverse effects. Seventy-four locomotive engineers and train conductors who had experienced a CI were recruited to take part in the study. They were interviewed four times over a six-month period. As well, nine managers of train operations (MTOs) who met the same inclusion criteria were interviewed twice over a three-month period. A mixed-method approach was used to analyse the data collected, combining statistical and qualitative analyses to fully understand the relationships between critical incidents, CIMSPs and post-CI recovery. The perceptions, needs and recommendations of MTOs who are responsible for applying protocols and providing support are also presented. The results indicate that existing CIMSPs are implemented partially or unevenly, depending on employer, province and CI type. In CIs without fatalities, for instance, management and support protocols are not completely followed, even when employee health is affected. Iv Assessment of Various CIMSPs for Railway Employees After a Serious Incident IRSST CIs affect employees in a wide variety of ways. The research team was able to establish five distinct recovery trajectories: no adverse effects, adverse effects that disappear within the month following the CI, adverse effects that gradually decline and disappear within the three months following the CI, adverse effects that reach a plateau between one and three months afterwards and then disappear, and adverse effects that are still present after six months. Overall, among two thirds of employees, the adverse effects of a CI dissipate more or less rapidly in the month following the CI, 20% still feel significant effects after three months (course of the plateau and effects that persist after six months), while that proportion falls to 13% after six months. These effects are not negligible and affect employees’ cognition (concentration, rumination, distraction), energy (fatigue, trouble sleeping) and emotions (guilt, grief). They may also interfere with employees’ ability to perform their jobs effectively. Differences in the application of CIMSPs provide opportunities for assessing their role in the post-CI recovery process. The study results show that management protocols can have an effect on the recovery process. The following factors tend to foster an acceleration of the process: the presence of a manager on site; a manager taking charge at the scene of the CI; the various stakeholders showing respect and empathy toward those affected; no pressure on employees to continue working or to return to work before they are ready; demobilization (automatically removing employees from the scene of the CI and taking them home) and granting them recovery leave; a proactive offer of support by the employee assistance program (EAP); a clear procedure for return to work and assessment of the employee’s readiness to resume occupational duties; deferred offer of support if needed; follow-up after return to work and a positive work environment. The study shows that CI management and the support provided by employers are key factors in promoting employee recovery. These are attitudes and actions that employers can act on and that can be applied fairly easily, without entailing prohibitive costs for companies. Employers have less control over other factors, such as social support or the complexity of the CI. Railway companies have protocols that already include most of the actions deemed to be effective. Following those protocols assiduously is a first step toward improving current practices and mitigating the adverse effects of CIs.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,017
score de la tête « metaresearch » (Gemma)0,070
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,025
Score d'incertitude au seuil0,092

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0170,070
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0040,001
Études des sciences et des technologies0,0030,001
Communication savante0,0020,001
Science ouverte0,0030,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,041
Tête enseignante GPT0,417
Écart entre enseignants0,377 · 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 source (Gemma direct ou Codex distillé), 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

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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