Transitioning: A Synergy Care Practicum for Senior Nursing Students
Notice bibliographique
Résumé
References: AACN. (2010). The AACN synergy model for patient care. http://www.aacn.org/wd/certifications/content/synmodel.pcms?menu=certification;Albsmeyer, D. (2013). Individualized Capstone Experience Proposal Based on Quality and Safety Education for Nurses (QSEN) Competencies. Retrieved from http://qsen.org/individualized-capstone-experience-proposal-based-on-quality-and-safety-education-for-nurses-qsen-competencies/;Alspach, G. (2006). Extending the synergy model to preceptorship: A preliminary proposal. Critical Care Nurse, 26(2), 10-13.;Assessment Technologies Institute. (2013). ATI Product Solutions. Retrieved from https://www.atitesting.com/Solutions.asp;Bourbonnais, F., & Kerr, E. (2007). Preceptoring a student in the final clinical placement: reflections from nurses in a Canadian Hospital. Journal of Clinical Nursing, 16(8), 1543-1549.;Charleston, R., & Happell, B. (2005). Coping with uncertainty within the preceptorship experience: the perceptions of nursing students. Journal of Psychiatric & Mental Health Nursing, 12(3), 303-309. doi:10.1111/j 1365-2850.2005.00837.x;Curley, M.A.Q. (1998). Patient-nurse synergy: Optimizing patients' outcomes. American Journal of Critical Care, 7(1): 64-72.;Diefenbeck, C., Plowfield, L., & Herrman, J. (2006). Clinical immersion: a residency model for nursing education. Nursing Education Perspectives, 27(2), 72-79.;Fahy, A., Tuohy, D., McNamara, M. C., Butler, M., Cassidy, I., & Bradshaw, C. (2011). Evaluating clinical competence assessment. Nursing Standard, 25(50), 42-48.;Ford, K., Fitzgerald, M., & Courtney-Pratt, H. (2013). The development and evaluation of a preceptorship program using a practice development approach. Australian Journal Of Advanced Nursing, 30(3), 5-13.;Harrison-White, K., & Simons, J. (2013). Preceptorship: ensuring the best possible start for new nurses. Nursing Children And Young People, 25(1), 24-27.;Jackman, D., Myrick, F. & Yonge, O. (2012). Putting the (R)ural in preceptorship. Nursing Research and Practice, 1-7. doi:10.1155/2012/528580;Josephsen, J. M. (2013). Evidence-Based Reflective Teaching Practice: A Preceptorship Course Example. Nursing Education Perspectives, 34(1), 8-11.;Kaplow, R. (2002). The synergy model in practice: Applying the synergy model to nursing education. Critical Care Nurse, 22(3), 77-81.;Kilstoff, K. & Rochester, S.F. (2004). Hitting the floor running: Transitional experiences of graduates previously trained. Australian Journal of Advanced Nursing, 22(1), 13-17.;Kolb, A. (2005). The Kolb Learning Style Inventory—Version 3.1 2005 technical specifications. Case Western University.;Kuiper, R. (2005). Self-regulated learning during a clinical preceptorship: the reflections of senior baccalaureate nursing students. Nursing Education Perspectives, 26(6), 351-356.;McCarthy, B., & Murphy, S. (2010). Preceptors' experiences of clinically educating and assessing undergraduate nursing students: an Irish context. Journal of Nursing Management, 18, 234–244. DOI: 10.1111/j.1365-2834.2010.01050.x;Monterosso, L. & Zilembo, M. (2008). Towards a conceptual framework for preceptorship in the clinical education of undergraduate nursing students. Contemporary Nurse, 30(1), 89-94.;Mullen, J.E. (2002). The synergy model in practice: The synergy model as a framework for nursing rounds. Critical Care Nurse, 22(6), 66-68.;Mulready-Shick, J. (2012). Integrating QSEN into clinical evaluation tools. QSEN Institute. Retrieved from http://qsen.org/integrating-qsen-into-clinical-evaluation-tools/.;NCBON (North Carolina Board of Nursing). (2013). Focused client care experience guidelines. Retrieved from http://www.ncbon.com/myfiles/downloads/focused-client-care-experience-guidelines.pdf;NCSBN. (2013a). Transition to practice: Outline of NCSBN’s Transition to Practice (TTP) Modules. Retrieved from https://www.ncsbn.org/2013_TransitiontoPractice_Modules.pdf;NCSBN (2013b). Transition to practice: Toolkit. Retrieved from https://transitiontopractice.org/ toolkit.php#preceptortools.; Newhouse, R., Dearholt, S., Poe, S, Pugh, L.C., White, K. (2005). The Johns Hopkins Nursing Evidence-based Practice Rating Scale. Baltimore, MD,The Johns Hopkins Hospital; Johns Hopkins University School of Nursing. Newton, J., Cross, W., White, K., Ockerby, C., & Billett, S. (2011). Outcomes of a clinical partnership model for undergraduate nursing students. Contemporary Nurse, 39(1), 119-128. doi:10.5172/conu 2011.39.1.119.;Sullivan-Callopy, K. (1999). The synergy model in practice: Advanced practice nurses guiding families through systems. Critical Care Nurse, 19(5), 80-85.;Tuning. (2005). Approaches to teaching, learning and assessment and the subject area competencies. Retrieved from http://www.unideusto.org/tuningeu/images/stories/teaching/TLA___NURSING.pdf;Udlis, K. (2008). Preceptorship in undergraduate nursing education: an integrative review. Journal of Nursing Education, 47(1), 20-29.;Wieland, D., Altmiller, G., Dorr, M., & Wolf, Z. (2007). Clinical transition of baccalaureate nursing students during preceptored, pregraduation practicums. Nursing Education Perspectives, 28(6), 315-32.;Wolkowitz, A., & Kelley, J. (2010). Academic Predictors of Success in a Nursing Program. Journal Of Nursing Education, 49(9), 498-503. doi:10.3928/01484834-20100524-09.;Zilembo, M., & Monterosso, L. (2008). Nursing students' perceptions of desirable leadership qualities in nurse preceptors: a descriptive survey. Contemporary Nurse: A Journal For The Australian Nursing Profession, 27(2), 194-206. doi:10.5172/conu.2008.27.2.194. Acknowledgments Thanks to Dr.Sandra Lewenson, PhD for her support and enthusiasm. Dr.Kyong Hyatt, PhD, many thanks for your kind words. Dr. Shelley Barry, DNP thank you for taking me under your wing. The nursing students at MU, you are one step above the rest. My current colleagues and supervisors without you I would not be able to attend congress, thanks for adjusting the schedule. To my fiance Derek, you are the wind beneath my wings. ! Contact Information: The author can be contacted at sabrenawells@gmail.com. Table 2. The AACN Synergy Model characteristics and competencies.
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 | 0,006 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,016 |
| Intégrité de la recherche | 0,003 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,045 | 0,027 |
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 ».