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Record 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 on OpenAlexaboutno aff
Nicola Ramacciati

Bibliographic record

VenueJournal of Advanced Nursing · 2023
Typeletter
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionHealth carePsychologyPhenomenonWorkplace violenceMedicineSociologyNursingSuicide preventionPolitical sciencePoison controlEpistemologyMedical emergencyLaw

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.342
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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