Job Burnout Is Associated With Prehospital Decision Delay: An Internet-Based Survey in China

A network analysis bridging the gap between the big five personality traits and burnout among medical staff

BACKGROUND

Burnout is a common issue among medical professionals, and one of the well-studied predisposing factors is the Big Five personality traits. However, no studies have explored the relationships between these traits and burnout from a trait-to-component perspective. To understand the specific connections between each Big Five trait and burnout components, as well as the bridging effects of each trait on burnout, we employed network analysis.

METHODS

A cluster sampling method was used to select a total of 420 Chinese medical personnel. The 15-item Chinese Big Five Personality Inventory-15 (CBF-PI-15) assessed the Big Five personality traits, while the 15-item Maslach Burnout Inventory-General Survey (MBI-GS) assessed burnout components. Network analysis was used to estimate network structure of Big Five personality traits and burnout components and calculate the bridge expected influence.

RESULTS

The study revealed distinct and clear relationships between the Big Five personality traits and burnout components. For instance, Neuroticism was positively related to Doubt significance and Worthwhile, while Conscientiousness was negatively related to Accomplish all tasks. Among the Big Five traits, Neuroticism displayed the highest positive bridge expected influence, while Conscientiousness displayed the highest negative bridge expected influence.

CONCLUSIONS

The network model provides a means to investigate the connections between the Big Five personality traits and burnout components among medical professionals. This study offers new avenues for thought and potential targets for burnout prevention and treatment in medical personnel, which can be further explored and tested in clinical settings.

Psychosocial markers of pre-hospital delay in patients with diabetic foot: A cross-sectional survey

AIM

This study aimed to determine the psychosocial markers associated with pre-hospital delay among patients with diabetic foot (DF).

DESIGN

This study has a cross-sectional design.

METHODS

The participants completed a questionnaire including pre-hospital time, demographic characteristics, Social Support Rate Scale, Brief Illness Perception Questionnaire and Type D Personality Scale-14. Bivariate and multivariate analyses were conducted to explore independent associations with pre-hospital delay.

RESULTS

Only 1.8% (3/164) of participants arrived at the hospital for medical care in 24 h of symptom onset. Patients with low utilization of social support (p = 0.029), low negative illness perceptions (p = 0.014) and high levels of negative affectivity (p = 0.009) are likely to arrive late at the clinic. Medical staff should pay attention to identifying diabetic patients' Type D personalities and take actions to improve their social support as well as illness perception, so as to reduce the occurrence of hospital delay.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Psychosocial factors play a vital role in the delay in seeking medical treatment for patients with DF. Medical staff need to improve patients' illness perception as well as self-management ability through health education. Importantly, key family members provide an emotional and psychological support system for diabetic patients. Therefore, nurses need to work with family members together to give information and psychological support during family visits. Additionally, building and maintaining trust with patients is crucial to encouraging individuals to express their concerns and worries. In this case, nurses may identify patients' negative emotions and conduct timely intervention, so as to achieve favourable outcomes.

PATIENT OR PUBLIC CONTRIBUTION

This study used a convenience sample of 164 participants with DF recruited from the wound clinic of Northern Jiangsu People's Hospital and Yangzhou Hospital of TCM in China.

Underestimated prognostic value of depression in patients with obstructive coronary artery disease

OBJECTIVE

The aim of this study was to explore the different predictive values of depression among patients with different cardiac systolic function levels.

METHODS

Four hundred eighty-three consecutive patients with obstructive coronary artery disease (CAD) were included the depressive state was assessed using the Chinese version of the Patient Health Questionnaire 9 (PHQ-9). Depression was defined as have depressive symptoms with a PHQ-9 score ≥5. The level of cardiac systolic function was classified as left ventricular ejection fraction (LVEF) ≥50 and <50%.

RESULTS

Over a median of 26.2 months, 421 patients completed the follow-up and experienced 101 major adverse cardiovascular events (MACEs), 45 non-cardiac rehospitalizations, and 17 deaths. Predictors for clinical outcomes in patients with different cardiac systolic function levels were not the same. For participants with preserved LVEF, depression was associated with increased risks for cardiovascular events and composite outcomes. However, when focusing the whole population, predictive values of depression for MACEs, non-cardiac rehospitalizations, and composite endpoints all dropped. Receiver operating characteristic (ROC) analyses further confirmed that depression was the one of the main predictors for all clinical outcomes. With the combination of other simple features, area under curve (AUC) could reach 0.64-0.67.

CONCLUSIONS

Inconsistent with the general impression, depression is found to have a closer linkage with clinical outcomes in CAD patients with preserved LVEF rather than in those with decreased LVEF. These findings appeal for more attention on CAD patients with depressive symptoms and comparatively normal LVEF. Including psychological factors may be a good attempt when constructing risk prediction models.