THE PRELIMINARY ANALYSIS OF YOGA THERAPY ON BURNOUT AMONG MEDICAL STAFF: A SINGLE-ARM PRE-POST INTERVENTION
Notice bibliographique
Résumé
Abstract Background Burnout, encompassing emotional exhaustion, disrupts the balance between the mind and body, emphasizing the need for concise and practical interventions to mitigate risk in medical settings. Yoga therapy has been shown to alleviate anxiety and depression in both healthy adults and patients with severe mental illnesses. However, there is a paucity of research investigating the effects of short- term yoga therapy on burnout among medical staff. Aims & Objectives This study aims to evaluate the effect of a two-week yoga therapy on burnout among medical staff. Methods We conducted a two-week single-arm pre-post intervention study involving medical and co- medical staff working at the general hospital of Tokyo Dental College, Chiba, Japan. This study protocol received approval from the Institutional Review Board (IRB) of the general hospital of Tokyo Dental College (UMIN:000044465). The intervention comprised in-person and online yoga sessions held twice weekly for four sessions, each lasting 60 minutes. The primary outcome measures included the number of participants, completion rate, and the Client Satisfaction Questionnaire 8 (CSQ-8). The secondary outcomes encompassed the assessment of burnout levels using the Maslach Burnout Inventory General Survey (MBI-GS), blood pressure, heart rate variability, alpha-amylase activities, the Patient Health Questionnaire-9 (PHQ-9), the General Anxiety Disorders-7 (GAD-7), the Pittsburgh Sleep Quality Index (PSQI), the EuroQol-5 dimensions classification system (EQ-5D), the Sheehan Disability Scale (SDS), and the Resilience Scale (RS). These assessments were conducted at registration, the end of the first session, the end of the fourth session, and one-week and four-week follow-up. This study is currently ongoing and aims to recruit fifty participants. A preliminary statistical analysis was performed using R, employing analysis of covariance and repeated-measures analysis of variance. Results Preliminary analysis results were reported herein. Between July 2021 and the present, 21 participants (mean age: 42.2±9.5 years old, 9.5% male) were enrolled in this intervention, with 19 participants (90.4%) completing all sessions. The mean CSQ-8 was 27.7±3.7. Although the total score of MBI-GS did not show significant improvement, the score of GAD-7 decreased from 5.2±3.2 to 2.8±2.8 (p<0.05), the score of PHQ-9 decreased from 6.7±4.0 to 3.2±4.0 (p<0.05), and EQ-5D increased from 67.1±15.5 to 75.2±16.4 (p<0.05). These improvements were sustained at the 4-week follow-up assessments. However, other measurements did not show significant improvement during the short-term period. Discussion & Conclusion This pre-post study, based on a preliminary analysis of 21 participants, highlights the positive effects of a 2-week Hatha yoga intervention on anxiety, depression, and quality of life (QoL) among medical staff in a general hospital. Our findings demonstrate the potential clinical utility of hybrid yoga sessions in mitigating the risk of burnout among medical staff. However, the transient nature of the observed clinical gains underscores the need for further investigations into potential strategies for enhancing these acute effects. This pre-post study has limitations, including a small sample size (n=21) and a shorter session module. Future investigations exploring the optimal intervention are necessary to achieve sustained therapeutic effects of hybrid yoga intervention on burnout.
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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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».