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Enregistrement W7062672681

Workplace violence and intentions to quit: results from a survey of London nurses

2008· other· en· W7062672681 sur OpenAlexfundno aff

Notice bibliographique

RevueGreenwich Academic Literature Archive (University of Greenwich) · 2008
Typeother
Langueen
DomainePhysics and Astronomy
ThématiqueMagnetic confinement fusion research
Établissements canadiensnon disponible
Organismes subventionnairesMedical Research CouncilSouth African Medical Research CouncilSigma Theta Tau InternationalMcGill University
Mots-clésHarassmentVerbal abuseWorkplace violenceAffect (linguistics)Logistic regressionOccupational safety and healthJob satisfactionDescriptive statisticsTest (biology)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Study Objective: 
\nWork-place violence, harassment and abuse is an increasing feature of nurses’ experience of work in many countries. There is some evidence that the experience of workplace violence affects levels of job satisfaction (Hesketh et al 2003) and career decisions (e.g. Mayer et al 1999, Fernandes
\net al 1999). This paper reports on verbal and physical abuse by patients, relatives and carers, as well as racial and sexual harassment in Acute Hospitals in London and investigates whether workplace violence affects nurses’ intentions to leave either their current job or the nursing
\nprofession, controlling for a number of other factors that are known to affect career decisions, such as workload, pay and own health.
\nMethod:
\nA questionnaire designed by two of the authors (Reeves and West) to assess many different aspects of nurses work life was used in a postal survey of nurses grades A to I practising in twenty London acute trusts in 2002. A total of 6,160 clinical nurses were mailed the questionnaires and 2,880 returned completed questionnaires, resulting in an overall response rate of 47%, discounting undelivered questionnaires. Respondents worked in a wide variety of clinical settings but mainly in acute medical and surgical wards. In addition to descriptive statistics, results were analysed using logistic regression with robust standard errors: the appropriate test when the dependent variable is dichotomous and the individual respondents clustered within units (nurses working within hospitals are not statistically independent).
\nResults: 
\nOur results show high levels of racial (%), sexual (%) and other, unspecified forms of harassment (%), as well as verbal and physical abuse (14% had been physically assaulted with 5% being assaulted more than once), over the previous 6 months. A very small number (1%) reported
\nexperiencing all three forms of harassment; 12% two forms and 29% one form. Only 45% of this sample intended to stay in nursing for at least 3 years; 40% were undecided and 15% intended to leave. Logistic regression estimates showed that reported levels of abuse and harassment had a significant impact on respondents’ career intentions, even in models that controlled for known factors affecting career decisions. About 70% of our respondents reported that they had had too little training in dealing with aggressive behaviour—or none at all—but there was no statistical relationship between lack of training and reported assaults.
\nConclusions:
\nThe international shortage of health care workers is due at least in part to low retention rates. It is crucial to investigate nurses’ experiences of work to identify the factors that shape their career decisions. Workplace violence is increasingly acknowledged as an international, service-wide, health care problem. This paper adds to the literature that shows that workplace violence has an
\nimpact on nurses’ career decisions. The implications for managers and policy makers are that strengthening systems of security and providing nurses with training in interpersonal relationships including dealing with aggressive patients could slow nurse turnover.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,331
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0100,000

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 Opus0,012
Tête enseignante GPT0,235
Écart entre enseignants0,222 · 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.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

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
Publié2008
Routes d'admission1
Résumé présentoui

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