| Literature DB >> 32787919 |
Muhammad Raihan Jumat1, Pierce Kah-Hoe Chow1,2, John Carson Allen1, Siang Hui Lai1,2, Nian-Chih Hwang1,2, Jabed Iqbal1,2, May Un Sam Mok2, Attilio Rapisarda1, John Matthew Velkey3, Deborah Lynn Engle3, Scott Compton4.
Abstract
BACKGROUND: Burnout is a serious issue plaguing the medical profession with potential negative consequences on patient care. Burnout symptoms are observed as early as medical school. Based on a Job Demands-Resources model, this study aims to assess associations between specific job resources measured at the beginning of the first year of medical school with burnout symptoms occurring later in the first year.Entities:
Keywords: Burnout; Engagement; Grit; Medical education; Medical school; Tolerance for ambiguity
Mesh:
Year: 2020 PMID: 32787919 PMCID: PMC7425562 DOI: 10.1186/s12909-020-02187-1
Source DB: PubMed Journal: BMC Med Educ ISSN: 1472-6920 Impact factor: 2.463
Summary of survey instrument results (mean ± standard deviation) at the 4 study sampling times (N = 59)
| Survey Instrument | T | T | T | T |
|---|---|---|---|---|
| Emotional Exhaustion | 13.2 ± 5.2 | 13.2 ± 4.9 | 11.6 ± 5.4 | 11.8 ± 4.6 |
| Professional Efficacy | 25.6 ± 5.9 | 23.8 ± 6.0 | 24.8 ± 4.9 | 24.8 ± 5.5 |
| Cynicism | 6.4 ± 4.7 | 7.7 ± 5.7 | 8.1 ± 6.1 | 7.6 ± 5.6 |
| 20.6 ± 5.5 | – | – | – | |
| Organizational Religious Activity (ORA) | 2.8 ± 1.8 | – | – | – |
| Non-Organizational Religious Activity (NORA) | 2.5 ± 1.8 | – | – | – |
| Intrinsic Activity (IR) | 8.6 ± 4.0 | – | – | – |
| 3.6 ± 0.5 | – | – | – | |
| Significant Other | 5.6 ± 1.3 | – | – | – |
| Family | 5.7 ± 1.0 | – | – | – |
| Friends | 5.7 ± 0.8 | – | – | – |
| Overall | 5.7 ± 0.8 | – | – | – |
T1: 22nd August – 5th September 2017, T2: 1st November – 10th November 2017, T3: 1st February 2018- 10th February 2018, T4: 1st May – 10th May 2018
Analysis of study variables as predictors of NO BURNOUT
| Parameter | CHI SQUARE | ODDS RATIO ESTIMATES | ||||
|---|---|---|---|---|---|---|
| Wald Chi-Square | B-Value | Point Estimate | 95% Wald Confidence Limits | |||
| 0.48 | 0.49 | 0.45 | 1.56 | 0.44 | 0.45 | |
| 0.06 | 0.81 | 0.02 | 1.02 | 0.90 | 0.02 | |
| 0.31 | 0.58 | −0.05 | 0.95 | 0.81 | −0.05 | |
| 6.77 | < 0.01 | 0.17 | 1.19 | 1.04 | 0.17 | |
| 0.77 | 0.38 | 0.03 | 1.03 | 0.96 | 0.03 | |
Fig. 1Receiver Operating Characteristic (ROC) Curve for grit score as a predictor of NO BURNOUT’. Area under curve (AUC; (95% Confidence Interval): 0.76 (0.63, 0.89))
ROC Curve cut-points with positive and negative predictive values (NPV and PPV) for predicted outcome of NO BURNOUT
| GRIT Score* | PPV | NPV | Youden J |
|---|---|---|---|
| 32 | 0.68 | . | 0.00 |
| 34 | 0.68 | 0.33 | 0.00 |
| 35 | 0.70 | 0.60 | 0.11 |
| 36 | 0.72 | 0.67 | 0.16 |
| 37 | 0.73 | 0.71 | 0.21 |
| 38 | 0.75 | 0.75 | 0.27 |
| 39 | 0.74 | 0.67 | 0.24 |
| 40 | 0.76 | 0.70 | 0.29 |
| 41 | 0.76 | 0.57 | 0.27 |
| 42 | 0.80 | 0.58 | 0.38 |
| 43 | 0.82 | 0.52 | 0.38 |
| 45 | 0.91 | 0.46 | 0.39 |
| 47 | 0.88 | 0.40 | 0.24 |
| 48 | 0.86 | 0.38 | 0.19 |
| 50 | 0.83 | 0.36 | 0.14 |
| 51 | 0.75 | 0.33 | 0.04 |
| 55 | 1.00 | 0.35 | 0.10 |
| 56 | 1.00 | 0.34 | 0.08 |
| 57 | 1.00 | 0.33 | 0.05 |
| 59 | 1.00 | 0.33 | 0.03 |
*Uncorrected grit score values (Grit Score × 12)
An uncorrected grit cut-off score of 44 was indicated as the statistically optimal threshold for discrimination of NO BURNOUT (in bold)
Fig. 2Distribution of students according to their uncorrected grit score (x-axis). Y axis shows student count. Upper panel: students experiencing burnout at least once in the year: lower panel: students experiencing NO BURNOUT