Beautifully broken: Implementing a peer support program to help healthcare providers heal
Notice bibliographique
Résumé
Introduction: This evidence-based project aimed to determine the feasibility of implementing a peer support program to minimize trauma in healthcare professionals (HCP)s following unanticipated adverse events. Based on the forYOU Program designed by Sue Scott at the University of Missouri Health System, this program trained peers to offer real-time caring and support to other clinicians coping with such events. Most healthcare professionals are involved in at least one adverse event in their careers. Albert Wu, MD (2000) coined the term second victim to capture the essence of the trauma experienced by healthcare professionals when an unanticipated event negatively impacts a patient. When left unchecked, this trauma can result in moral distress, stress disorders, and burnout as the clinician ruminates over the event. Providing emotional support has improved second victims' emotional well-being and recovery. Therefore, healthcare leaders are encouraged to develop comprehensive programs to provide easy access to peer and social support when they experience an adverse event.Methods: Designed for implementation in the Women's Service Department of a 350-bed southwestern hospital, this project employed a pre-/post-evaluation of subjective outcomes using an online survey for nurses. A core group of trainers attended a two-day peer support train-the-trainer event hosted by the forYOU Program at the University of Missouri Health Care System. This group trained 26 peer supporters representing the four departments in Women's Services and both shifts. Baseline data was collected (n = 44) to assess the frequency and impact of unanticipated adverse events, the perceived support, and the type of support received. Following the four-month implementation in the Summer/Fall of 2020, post-data was obtained, including a program awareness assessment (n = 17).Results: Pre- and post-implementation of the Peer Support Program, nurses in Women's Services reported adverse events impacting their emotional well-being. Post-program, more nurses reported receiving support (86% post-program versus 43% pre-program). Before employment, 79% of nurses who received support received peer support, versus 86% receiving peer support post-implementation. The implementation occurred during the COVID pandemic, which may have resulted in a decreased post-assessment sample size. However, the peer supporters reported hesitancy in completing encounter forms feeling that providing support was “too personal”. The participants said that they found the peer support program worthwhile.Conclusions: Nurses on the implementation units indicated receiving more support after the peer support program was implemented and felt the program was beneficial. Since unanticipated events are inevitable in health care, the steering committee recommended sustaining and spreading the program to all the nursing departments. More data is needed to determine the full impact of the program.
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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 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».