mHealth Gratitude Exercise Mindfulness App for Resiliency Among Neonatal Intensive Care Unit Staff: Three-Arm Pretest-Posttest Interventional Study
Notice bibliographique
Résumé
Background Health care is highly complex and can be both emotionally and physically challenging. This can lead health care workers to develop compassion fatigue and burnout (BO), which can negatively affect their well-being and patient care. Higher levels of resilience can potentially prevent compassion fatigue and BO. Strategies that enhance resilience include gratitude, exercise, and mindfulness. Objective The purpose of this study was to determine if a 3-week daily resiliency practice, prompted via a gratitude, exercise, and mindfulness smartphone app, impacted the professional quality of life, physical activity, and happiness level of health care workers in a newborn intensive care unit setting. Methods In total, 65 participants from a level III newborn intensive care unit at a regional hospital in the western United States completed this study. The Professional Quality of Life Scale, Physical Activity Vital Sign, and Subjective Happiness Score instruments were used to evaluate the effects of the mobile health (mHealth) intervention. Further, 2-tailed dependent paired t tests were used to evaluate participant pre- and postintervention instrument scores. Multiple imputation was used to predict scores of participants who practiced an intervention but did not complete the 3 instruments post intervention. Results Dependent t tests using the original data showed that participants, as a whole, significantly improved in BO (t35=2.30, P=.03), secondary trauma stress (STS; t35=2.11, P=.04), and happiness (t35=–3.72, P<.001) scores. Compassion satisfaction (CS; t35=–1.94, P=.06) and exercise (t35=–1.71, P=.10) were trending toward, but did not reach, significance. Using the original data, only the gratitude intervention group experienced significant improvements (CS, BO, and happiness), likely due to the higher number of participants in this group. Analysis using imputed data showed that participants, as a whole, had significant improvements in all areas: CS (t64=–4.08, P<.001), BO (t64=3.39, P=.001), STS (t64=4.08, P<.001), exercise (t64=–3.19, P=.002), and happiness (t64=–3.99, P<.001). Looking at the intervention groups separately using imputed data, the gratitude group had significant improvements in CS, BO, STS, and happiness; the exercise group had significant improvements in STS and exercise; and the mindfulness group had significant improvements in CS and happiness. Conclusions Phone app delivery of resilience-enhancing interventions is a potentially effective intervention model for health care workers. Potential barriers to mHealth strategies are the technical issues that can occur with this type of intervention. Additional longitudinal and experimental studies with larger sample sizes need to be completed to better evaluate this modality.
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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 | 0,000 | 0,000 |
| 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 | 0,000 | 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) | 0,004 | 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 ».