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Enregistrement W3217685305 · doi:10.1097/nur.0000000000000652

Using Our Voice

2021· article· en· W3217685305 sur OpenAlexaboutno aff

Notice bibliographique

RevueClinical Nurse Specialist · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueGlobal Health and Surgery
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFeelingAcute carePandemicMEDLINEHealth careCoronavirus disease 2019 (COVID-19)Nursing careMental health

Résumé

récupéré en direct d'OpenAlex

The data are in – a lot of data and it keeps coming! We have COVID related data on cases, deaths, and vaccines organized by categories – state, county, age group, political affiliation, to name a few, all neatly available on any number of websites. For nurses, some additional data should be considered. In Spring and Winter of 2020, the American Nurses Foundation conducted national surveys on the Mental Health and Wellness of the nursing workforce. A repeat study in Winter 2021 added COVID impact questions. The reports are all available at https://www.nursingworld.org/practice-policy/work-environment/health-safety/disaster-preparedness/coronavirus/what-you-need-to-know/survey-series-results/. In brief, the most recent results show that high percentages of nurses working in intensive/critical care (52%), emergency departments (46%), medical-surgical units (44%); acute care hospitals (40%), and nurse managers (36%) reported feeling not or not at all emotionally healthy. Correspondingly, nurses working in intensive/critical care (68%), emergency departments (62%), acute care hospitals (45%), medical-surgical units (44%), and nurse managers (42%) reported experiencing an extremely stressful, disturbing, or traumatic event. By age, a greater percentage of younger nurses reported feeling not or not at all emotionally healthy and reported having experienced a stressful, disturbing, or traumatic event when compared to older nurses. These findings are alarming. Among nurses under 35 years, 31% reported intent to leave the profession. Considering that one-third of nurses are 55 years old or older, the profession is facing some daunting challenges.1 The image of nurses and nursing matters now more than ever. On her website, The Truth About Nursing, Sandy Summers has been calling out the harmful effects of negative images of nurses in the media (https://www.truthaboutnursing.org/#gsc.tab=0). In a recent opinion, Buerhaus2 suggested that current negative media images of overworked and emotionally exhausted nurses are not supportive to continued growth of the profession. Both Summers and Buerhaus are correct. Negative images of nurses are not helpful, whether as brainless bimbos in movies or emotionally distraught COVID caregivers on the evening news. Negative images at a time of severe COVID related stressors are converging to magnify impending challenges. Images are symbols, and as such they convey values and mirror perceptions of nurses by the public and the profession itself. Negative images suggest limited value, smallness, and weakness. A lack of power. Yet we know hospitals operate on nurse power, as the pandemic has made clear. For the last 18 or so months, hospital administrators have been in the news reminding us that it’s not the lack of beds, it’s the lack of nurses that limit hospital care. Yet too often “beds” and “nurses” are interchangeable words denoting hospital capacity managed by others. Words matter as much as images, and hospital administrators talking about nurses as commodities that are managed also contributes to a negative image. Meeting the impending challenge of maintaining a nursing workforce is more than finding positive images and words; it means nurses using the power of voice. The power of voice was demonstrated in the results of a study conducted by The Canadian Centre for Advanced Practice Nursing Research at McMaster University, in collaboration with Ryerson University and the Canadian Health Workforce Network, which examined advanced practice nurses’ worldwide response to health needs during the COVID pandemic. In a herculean show of ingenuity, imagination, knowledge, skill, emotional fortitude, and leadership, advanced practice nurses – clinical nurse specialists and nurse practitioners, reported redeploying to critical need areas, expanding use of technology, setting up isolation units, establishing screening and vaccination clinics, designing team-based care delivery models, addressing mental health needs of fellow healthcare providers, providing education, training, and coaching for team members, and generally “filled the gap.” These accomplishments frequently were facilitated by emergency legislation increasing the scope of practice.3 Yes, the data are in! Nurses, particularly advanced practice nurses, can and will make a difference given the opportunity to manage rather than be managed. It’s voice that we need. The Canadian study group identified the imbalance of power and decision making as a significant barrier to nursing practice. Voice is power. Voice in the legislature. Voice on hospital boards. Voice in the university. Voice for mental health services and voice for well-being. Decision-making voice. Voice to shout out movie images of nurse as plotting shrew or scantily clad tart. Be gone the days of nurse recognition by trinket – tote bags, key chains, water bottles, and free ice cream for nurse’s week. Only powerful voice will meet the challenges going forward. We may be wobbly at first with limited experience in unfamiliar, decision-making areas. It’s okay, we will improve, we will strengthen our voice. As always, clinical nurse specialists should study the data. Strengthen those voice muscles. We led with courage during the pandemic, and this is no time to slow down. Bring your voice to the table! Shirley Chisholm famously said, “If they don’t give you a seat at the table, bring in a folding chair.” Voice is the way forward.

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)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,254
Score d'incertitude au seuil0,851

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,001

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 Opus0,165
Tête enseignante GPT0,492
Écart entre enseignants0,327 · 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'étudeSans objet
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

Citations3
Publié2021
Routes d'admission1
Résumé présentoui

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