Experiences and Perceptions of Nurses Participating in an Interprofessional, Videoconference-Based Educational Programme on Concurrent Mental Health and Substance Use Disorders: A Qualitative Study
Notice bibliographique
Résumé
Abstract Background Individuals with co-occurring mental health and substance use disorders (i.e., concurrent disorders) remain a challenge for the nurses attempting to care for them. They require nurses to constantly adapt themselves and develop high-level competencies despite the limited resources they have and the isolated settings in which many of them work. The Extension for Healthcare Community Outcomes (ECHO®) is a promising collaborative learning and capacity building model that uses videoconference technology to support and train healthcare professionals in the management of complex and chronic health conditions. The aim of this study was to explore the experiences and perceptions of nurses participating in a Canadian ECHO programme on concurrent disorders about the competencies they developed and mobilized in their clinical practice, and which factors have influenced this process. Methods The study was qualitative, guided by an interpretive descriptive approach. Individual semi-structured interviews were held with ten nurses who had participated in the programme for the 2018–2019 and 2019–2020 curricula. A thematic analysis was conducted iteratively using an inductive approach to progressive data coding and organization. Results Four themes and eighteen sub-themes emerged. During their participation in ECHO, the nurses perceived as having further developed and mobilized eight clinical nursing competencies. Nurses viewed ECHO as a unique opportunity to open themselves to their peers’ experiences and reflect on their own knowledge. Learning from experts in the field of concurrent disorders helped them to build their confidence in managing complex clinical situations. The nurses’ sense of belonging to a community further enhanced their engagement in the programme, and learning was facilitated through the programme’s interprofessional environment. Nevertheless, the lack of contextualized educative content linked to local realities, the limited resources in concurrent disorders and time constraints were experienced as factors limiting competency development. Conclusions ECHO is a promising alternative to conventional, in-person continuing education programmes to improve the development of advanced competencies and clinical practice among nurses providing care to individuals with chronic and complex health conditions. These findings can inform clinicians, educators, researchers, and decision makers who are developing, implementing, evaluating and escalating future educational interventions in the field of CDs.
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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 | 0,012 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,009 | 0,008 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,003 |
| 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 ».