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Enregistrement W1908843739 · doi:10.55633/s3me/e088.2022

Education and training for preventing and minimizing workplace aggression directed toward healthcare workers

2024· article· en· W1908843739 sur OpenAlexaff
Steve Geoffrion, Danny Hills, Heather Ross, Jacqueline Pich, April T. Hill, Therese Kristine Dalsbø, Sanaz Riahi, Begoña Martínez‐Jarreta, Stéphane Guay

Notice bibliographique

RevueEmergencias · 2024
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueWorkplace Violence and Bullying
Établissements canadiensOntario Shores Centre for Mental Health SciencesUniversity of TorontoUniversité de Montréal
Organismes subventionnairesnon disponible
Mots-clésPsychological interventionAbsenteeismAggressionHealth careMedicineRandomized controlled trialNursingOccupational safety and healthMEDLINEPoison controlFamily medicinePsychologyPsychiatryMedical emergencySocial psychology

Résumé

récupéré en direct d'OpenAlex

<h4>Background</h4>Workplace aggression constitutes a serious issue for healthcare workers and organizations. Aggression is tied to physical and mental health issues at an individual level, as well as to absenteeism, decreased productivity or quality of work, and high employee turnover rates at an organizational level. To counteract these negative impacts, organizations have used a variety of interventions, including education and training, to provide workers with the knowledge and skills needed to prevent aggression. OBJECTIVES: To assess the effectiveness of education and training interventions that aim to prevent and minimize workplace aggression directed toward healthcare workers by patients and patient advocates.<h4>Search methods</h4>CENTRAL, MEDLINE, Embase, six other databases and five trial registers were searched from their inception to June 2020 together with reference checking, citation searching and contact with study authors to identify additional studies.<h4>Selection criteria</h4>Randomized controlled trials (RCTs), cluster-randomized controlled trials (CRCTs), and controlled before and after studies (CBAs) that investigated the effectiveness of education and training interventions targeting aggression prevention for healthcare workers.<h4>Data collection and analysis</h4>Four review authors evaluated and selected the studies resulting from the search. We used standard methodological procedures expected by Cochrane. We assessed the certainty of evidence using the GRADE approach.<h4>Main results</h4>We included nine studies-four CRCTs, three RCTs, and two CBAs-with a total of 1688 participants. Five studies reported episodes of aggression, and six studies reported secondary outcomes. Seven studies were conducted among nurses or nurse aides, and two studies among healthcare workers in general. Three studies took place in long-term care, two in the psychiatric ward, and four in hospitals or health centers. Studies were reported from the United States, Switzerland, the United Kingdom, Taiwan, and Sweden. All included studies reported on education combined with training interventions. Four studies evaluated online programs, and five evaluated face-to-face programs. Five studies were of long duration (up to 52 weeks), and four studies were of short duration. Eight studies had short-term follow-up (< 3 months), and one study long-term follow-up (> 1 year). Seven studies were rated as being at "high" risk of bias in multiple domains, and all had "unclear" risk of bias in a single domain or in multiple domains. Effects on aggression Short-term follow-up The evidence is very uncertain about effects of education and training on aggression at short-term follow-up compared to no intervention (standardized mean difference [SMD] -0.33, 95% confidence interval [CI] -1.27 to 0.61, 2 CRCTs; risk ratio [RR] 2.30, 95% CI 0.97 to 5.42, 1 CBA; SMD -1.24, 95% CI -2.16 to -0.33, 1 CBA; very low-certainty evidence). Long-term follow-up Education may not reduce aggression compared to no intervention in the long term (RR 1.14, 95% CI 0.95 to 1.37, 1 CRCT; low-certainty evidence). Effects on knowledge, attitudes, skills, and adverse outcomes Education may increase personal knowledge about workplace aggression at short-term follow-up (SMD 0.86, 95% CI 0.34 to 1.38, 1 RCT; low-certainty evidence). The evidence is very uncertain about effects of education on personal knowledge in the long term (RR 1.26, 95% CI 0.90 to 1.75, 1 RCT; very low-certainty evidence). Education may improve attitudes among healthcare workers at short-term follow-up, but the evidence is very uncertain (SMD 0.59, 95% CI 0.24 to 0.94, 2 CRCTs and 3 RCTs; very low-certainty evidence). The type and duration of interventions resulted in different sizes of effects. Education may not have an effect on skills related to workplace aggression (SMD 0.21, 95% CI -0.07 to 0.49, 1 RCT and 1 CRCT; very low-certainty evidence) nor on adverse personal outcomes, but the evidence is very uncertain (SMD -0.31, 95% CI -1.02 to 0.40, 1 RCT; very low-certainty evidence). Measurements of these concepts showed high heterogeneity.<h4>Authors' conclusions</h4>Education combined with training may not have an effect on workplace aggression directed toward healthcare workers, even though education and training may increase personal knowledge and positive attitudes. Better quality studies that focus on specific settings of healthcare work where exposure to patient aggression is high are needed. Moreover, as most studies have assessed episodes of aggression toward nurses, future studies should include other types of healthcare workers who are also victims of aggression in the same settings, such as orderlies (healthcare assistants). Studies should especially use reports of aggression at an institutional level and should rely on multi-source data while relying on validated measures. Studies should also include days lost to sick leave and employee turnover and should measure outcomes at one-year follow-up. Studies should specify the duration and type of delivery of education and should use an active comparison to prevent raising awareness and reporting in the intervention group only.

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)0,001
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: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,878
Score d'incertitude au seuil0,485

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
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 Opus0,060
Tête enseignante GPT0,375
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'étudeAutre devis
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

Citations73
Publié2024
Routes d'admission1
Résumé présentoui

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