The Role of an Intraorganizational Digital Community in Shaping Nurses’ Professional Identities and Practice: Qualitative Interview Study
Notice bibliographique
Résumé
Background: In 2017, Israel's health organizations established intraorganizational social media communities, believing that they would serve as a tool that would enable people to share experiences across regional boundaries. However, conducting preliminary studies and analyzing the findings to determine how they affected employees' experience was never part of this effort. Objective: This study examined the impact of an intraorganizational digital community on nurses' professional identities and practices within a large health care organization. Methods: Using a qualitative descriptive approach, semistructured interviews were conducted with 20 nurses from various specialties and regions participating in an intraorganizational nurses' community on Facebook. Results: The findings showed that the intraorganizational community fostered a strong sense of belonging, emotional support, and professional development among its members. Participants talked about having a sense of community, much like being a member of a family, where they could confide in one another, ask for help and advice, and receive support. Enriched professional knowledge, self-efficacy, and pride in the nursing profession were all associated with active involvement in the community. The complex interactions of social media use in a hierarchical health care system were emphatically acknowledged by addressing challenges, including information overflow and concerns about sustaining a professional persona in a public digital domain. Conclusions: Overall, the study illustrated how crucial it is for health care organizations to actively manage potential negative consequences while using the benefits of intraorganizational digital networks, such as improving supportive relationships and ongoing shared learning. This study contributes to the growing body of knowledge regarding the crossroad between social media and health care, offering insights into developing strategies to promote a supportive and connected nursing workforce. The implications are particularly relevant for organizations seeking to strengthen nurse well-being and professional development through innovative digital tools. Future research should include quantitative studies to assess an intraorganizational platform's influence on outcomes such as nurses' sense of community, professional identity, self-efficacy retention, and job satisfaction.
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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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| 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 ».