The impact of staffing structures in long-term care homes on the quality of work-life and work outcomes of care-workers: A narrative scoping review
Notice bibliographique
Résumé
BACKGROUND: Chronic underfunding of the long-term care sector, coupled with increased complexity of care, has deteriorated working conditions and contributed to severe staffing shortages of healthcare workers globally. While previous reviews have examined the association between long-term care staffing and care outcomes for residents, none have examined specifically how staffing structures affect the care-workers themselves. OBJECTIVE: The aim of this review is to investigate how staffing structures impact the quality of work-life, work-related outcomes of care-workers and the context that affects staffing decisions. METHODS: A narrative scoping review of primary empirical peer-reviewed literature was conducted to examine how long-term care staffing structures impact quality of work-life and work outcomes of care-workers in OECD countries. PubMed, CINAHL, and Scopus databases were searched for relevant articles published within the past 10 years. Searches yielded 4561 unique articles, which were independently screened by pairs of reviewers, of which 76 articles were included. Data were extracted and synthesized to examine the ways in which staffing structures impact the workforce, what structures existed, and how they came to be. RESULTS: Contextual factors shaped staffing decisions in long-term care, including both organizational/regulatory practices and external issues. These included market-based ideologies, increased care complexity, regulatory requirements, COVID-19, and organizational fiscal austerity, which affected the quality of work-life and work outcomes for care-workers. These factors contributed to chronic understaffing, restructuring of skill mix, and greater reliance on agency workers. Consequences for care-workers included work intensification, unpaid labour, and strained team dynamics, particularly where registered nurse oversight was limited. While some homes developed adaptive strategies to buffer these effects, inadequate staffing often eroded job quality, undermined teamwork, and contributed to job dissatisfaction, turnover, presenteeism, and adverse physical and psychological health outcomes. CONCLUSIONS: This review shows that staffing structures have consequences for quality of work-life and work outcomes. A reliance on lean staffing eventually destabilizes the workforce, perpetuating recruitment and retention issues. This review suggests that to create and maintain a strong long-term care workforce, sufficient staffing with the right skills and competencies need to be a priority in improvement initiatives. REGISTRATION: Not registered.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,008 | 0,012 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».