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Enregistrement W4385898077 · doi:10.1111/jan.15831

Empowering understanding and mitigating workplace violence: The role of sense of coherence and the global approach to violence toward emergency nurses framework

2023· letter· en· W4385898077 sur OpenAlexaboutno aff
Nicola Ramacciati

Notice bibliographique

RevueJournal of Advanced Nursing · 2023
Typeletter
Langueen
DomaineSocial Sciences
ThématiqueWorkplace Violence and Bullying
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsychological interventionHealth carePsychologyPhenomenonWorkplace violenceMedicineSociologyNursingSuicide preventionPolitical sciencePoison controlEpistemologyMedical emergencyLaw

Résumé

récupéré en direct d'OpenAlex

Dear Editor, I was greatly impressed by the recent study published in the Journal of Advanced Nursing (JAN) by Amit-Aharon, Warshawski and Itzhaki, which delves into the role of sense of coherence (SOC) in workplace violence directed at nurses (Amit-Aharon et al., 2023). Workplace violence (WPV) against healthcare professionals is a pervasive and far-reaching global phenomenon, the resolution of which remains elusive despite the efforts of major international health and workplace safety organizations spanning over two decades. The article authored by Amit-Aharon and colleagues is truly captivating and thought-provoking. It aptly emphasizes the significance of protective factors such as SOC (Amit-Aharon et al., 2023, p. 8), while concurrently shedding light on the inclusion of data from individuals not employed in the health system, thus enriching the study (Amit-Aharon et al., 2023, p. 8). The examination of SOC from the patients' perspective provides substantial value to the research. Over the course of several years, I have been deeply engrossed in the study of WPV, with a particular focus on emergency nurses (Ramacciati et al., 2021). My endeavours as both a practising nurse and a researcher have led me to develop a comprehensive theoretical model elucidating the dynamics of WPV within emergency departments. The model not only identifies the key variables at play, including precipitating factors, risk factors and antecedents, but also takes into account various interventions and strategies for its mitigation. The outcome of these efforts culminated in the creation of the GAVEN (Global Approach to Violence toward Emergency Nurses) model, which draws upon a synthesis of experiential knowledge and a comprehensive analysis of scholarly literature on the subject matter. A meticulous review of the global literature convincingly underscores the complexity and multi-layered causality of WPV, thereby necessitating an all-encompassing and comprehensive approach to address the issue. At the core of the theoretical model lies the fundamental postulate that only through a truly comprehensive and concerted approach can the risks of violence be effectively minimized, thereby thwarting episodes of violence against healthcare workers, especially emergency nurses. The model's robustness is reinforced by its alignment with the findings from international literature, which revealed 24 frameworks elucidating violence against healthcare workers in emergency departments, further substantiating the complex nature of this urgent challenge. As a result, the GAVEN model, currently garnering the attention of esteemed researchers (Timmins et al., 2023; Yıldız & Tok Yıldız, 2022; Yin et al., 2023), seamlessly encompasses four distinctive domains. The first domain, titled the internal domain, diligently considers essential factors associated with emergency nurses, encompassing gender, age, work experience, professional titles, roles within the ED and specific shift types. A profound understanding of the composition and dynamics of the ED team, coupled with an appreciation of employment nature (full-time or part-time), further enriches the model's insights. The second domain, titled the external domain, delves into the intricacies surrounding patients and visitors in the ED. Factors such as gender, age, socio-cultural conditions and prevalent health issues (ranging from alcohol or illicit drug abuse to mental illness, brain injuries, Alzheimer's or senile dementia and various neurological and biochemical conditions) constitute integral components of the analysis. Moreover, patient and visitor behaviour, encompassing ED presentation in terms of triage code, waiting times and length of stay, assumes critical significance. Significantly, the article by Amit-Aharon et al. brings to light the association of SOC with the characteristics of ED users (patients, accompanying individuals or visitors), warranting its inclusion as a novel variable within the external domain. The third domain, titled the organizational domain, meticulously captures the organizational characteristics of the services (Emergency Departments and Hospitals) where episodes of violence transpire. Organizational factors occupy a central role in the model's design, with a keen focus on regulatory measures and security protocols to address violence within the ED. Measures ranging from multi-language information displays and access restrictions to explicit condemnation of violence through ‘Zero Tolerance’ signs and the utilization of pass or identification cards for visitors and accompanying individuals are thoughtfully highlighted. Emphasizing safety, the framework incorporates robust security measures such as closed-circuit surveillance, direct access to hospital security or police services through alarm bells and the presence of bulletproof or shatterproof glass. The incorporation of a violence-reporting system and a rapid response team further fortifies the ED against potential violent incidents. Additionally, comprehensive procedures for effectively managing aggressive patients or violent acts are central to the framework's preparedness. Another important aspect concerns the training of personnel in communication and the management of aggressive individuals. Moreover, equally crucial is the support and attention from various levels of company management towards frontline workers facing violence. Also, the support and assistance provided to workers after an episode of violence. Lastly, the fourth domain, aptly titled the situational/environmental domain, devotes its attention to factors characterizing the contextual backdrop of violence. Beyond human factors, the framework extends its scope to encompass organizational climate and environmental elements, including architectural considerations. For example, the integration of architectural measures such as emergency unit entrance checks devoid of automatic door opening, enclosed nursing stations, well-lit ED spaces, examination rooms equipped with internal locks and alternative exits and various comfort amenities such as automatic food and drink dispensers, informative televisions or monitors, access to reading materials and background music ensures an all-encompassing approach to violence mitigation. The GAVEN framework could take into consideration the sense of coherence studied by Amit-Aharon and colleagues. As stated by these authors, the SOC comprises three pivotal dimensions: (1) comprehensible, wherein individuals hold the belief that they can comprehend the challenges they encounter; (2) manageable, wherein individuals perceive having diverse internal and external resources at their disposal, which they can utilize to meet their needs; (3) meaningful, wherein individuals derive a sense of purpose and interest in life, motivating them to confront challenges (Amit-Aharon et al., 2023, p. 2). However, it is crucial to understand how emergency nurses can effectively recognize and promote SOC in patients and/or accompanying individuals/visitors during the care process in the emergency department. If feasible, SOC could be incorporated as a new dependent variable in the second domain (external domain). I would be grateful if the authors could share their insights on this question, as their research has the potential to significantly advance our understanding of how to mitigate violence in healthcare settings, including the patient perspective. This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. The authors have no conflict of interest to declare.

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)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,453
Score d'incertitude au seuil0,873

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
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 Opus0,027
Tête enseignante GPT0,342
Écart entre enseignants0,315 · 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'étudeQualitatif
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

Citations2
Publié2023
Routes d'admission1
Résumé présentoui

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