Contextualizing the Conscientiousness Index Tool and Correlating Burnout with Conscientiousness Index as a measure of...

To contextualize the Conscientiousness Index and determine the relationship between burnout and the Conscientiousness Index as a measure of professionalism in postgraduate students.

This mixed-method study was done in two phases in Lahore from September 2023 to July 2024. The first phase involved contextualization of the Conscientiousness Index (CI) tool. A literature review, feedback from consultants and staff, identification of data sources, expert validation, and cognitive pretesting were conducted to contextualize the CI tool. In the second phase, a correlational study was done by collecting data using a purposive sampling technique (n=134). The CI scores were calculated from administrative records and clinical staff input. Burnout levels were assessed using the Maslach Burnout Inventory, which has three main constructs: Emotional exhaustion (EE), depersonalization (DP), and personal accomplishment (PA). Burnout and CI scores were compiled and analyzed using SPSS v26.0. The t-test, one-way ANOVA, Chi-square test, and Pearson's correlation were used for data analysis.

A six-item CI scale was contextualized with S-CVI (0.89) and CVR >0.62. Mild burnout was found in 63 (47%) participants, while 71 (53%) exhibited moderate-to-severe burnout. The overall mean CI score was 42.1 ± 5.96 (total score: 50). No significant association was found between burnout and CI scores. However, a moderate negative correlation was observed between EE and CI scores (r=-0.69), and a weak positive correlation (0.19) was found between PA and CI scores, which was statistically significant (p = 0.02).

The CI tool had good validity in the local context. There was a high prevalence of burnout among postgraduate students. No statistically significant association was found between burnout severity and CI scores. However, a weak correlation was found between burnout domains and CI scores. Further research is required to understand this weak correlation and validation of CI tool in different settings.