Community health assessment of needs and continuous empowerment (CHANCE): a quantitative cross-sectional survey targeting primary health care nurses in Lebanon
Notice bibliographique
Résumé
BACKGROUND: Primary Health Care (PHC) is the cornerstone of any healthcare system, with nurses forming the largest workforce involved in care. This study aimed to assess the current use of core competencies among community-based nurses, identify their learning needs, and assess factors associated with training needs within PHC centers. METHODS: A quantitative cross-sectional survey design was used, targeting community health nurses working within primary healthcare centers. Data were collected using a survey instrument adapted from the Canadian Community Health Nurses' Standards of Practice and informed by a validated tool, then piloted for clarity in the Lebanese context. Data were collected between September and November 2018. Mean, standard deviation (SD), frequency, and percentage data were computed for descriptive purposes. The generalized estimating equation (GEE) was used to identify the factors associated with nurses' training needs clustered within centers. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic GEE regression models that accounted for cluster effects. RESULTS: The total number of PHCs that agreed to participate was 206, of which 173 returned completed surveys. Given that we do not have an accurate number of the population of nurses working in those centers, we assumed that there would be two nurses in each PHC. Thus, for a total of 251 surveys completed by nurses, the response rate is estimated to be 61%. Of the 173 surveys, 139 were included in the final analysis after deleting those that were incomplete. Descriptive results showed that nurses were competent in providing continuous care (60.0%), electronic technology use (55.08%), and clinical nursing assessment (54.01%). They reported a need for more training on community health promotion (65.12%), patient-centered care (PCC) (58.30%), and patient self-management of chronic diseases (52.0%). In comparison to nurses working in accredited centers, nurses working in centers in the process of becoming accredited required three times more training to become competent in PCC (OR = 3.39, 95% CI: 1.26-9.31, p = 0.016). Registered nurses required three times less training in PCC than senior/head nurses (OR = 0.30, 95% CI: 0.11-0.80, p = 0.016). Education level was statistically significantly associated with most training needs. Nurses with Baccalaureate and Technique Superior degrees needed six times more training (OR = 6.07, 95% CI: 1.81-31.16, p = 0.031) than those with a bachelor's or master's degree in nursing. CONCLUSION: This study provided a baseline assessment for the competencies that nurses reported implementing and those that they requested more training on. Future steps would be to develop interventions to empower nurses with the competencies they requested as priorities and to conduct a post intervention assessment to test the effect of the training on nursing adoption of those skills.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».