| Literature DB >> 34284770 |
Yayoi Shikama1, Yasuko Chiba2, Megumi Yasuda2, Maham Stanyon2, Koji Otani2.
Abstract
BACKGROUND: Professional identity formation is nurtured through socialization, driven by interaction with role models, and supported through early clinical exposure (ECE) programmes. Non-healthcare professionals form part of the hospital community but are external to the culture of medicine, with their potential as role models unexplored. We employed text mining of student reflective assignments to explore the impact of socialization with non-healthcare professionals during ECE.Entities:
Keywords: Altruism; Professional identity formation; Role modelling; Socialization; Text mining
Mesh:
Year: 2021 PMID: 34284770 PMCID: PMC8293517 DOI: 10.1186/s12909-021-02818-1
Source DB: PubMed Journal: BMC Med Educ ISSN: 1472-6920 Impact factor: 2.463
Fig. 2A breakdown of how the 50 most-commonly-occurring words extracted from the reflective essays distribute across the three emergent networks leading to the extracted themes
A breakdown of the job categories listed by students after orientation
| Job categories | Percentage of students listing the profession | |
|---|---|---|
| Healthcare professionals | Nurse | 98,0 |
| Medical doctor | 96.8 | |
| Allied healthcare professionalsa | 64.0 | |
| Pharmacist | 46.2 | |
| Non-healthcare professionals | Office workers | 71.5 |
| Cleaner | 65.2 | |
| Cook | 23.7 | |
| Security officer | 21.7 | |
| Maintenance technicians | 5.5 | |
| Management consultant | 2.8 | |
| Medical supply manager | 2.8 | |
| Medical records keeper | 0.8 | |
| Lawyer | 0.8 | |
| Helicopter pilot | 0.8 |
aAllied health professionals consisted of physiotherapists, occupational therapists, speech and language therapists, dieticians, counsellors, healthcare assistants, radiographers and laboratory technicians
Fig. 1A comparison of the frequencies of the four most-commonly-used words describing professional characteristics across all three time points. The numbers in the brackets are chi-square values. **p < 0.01
Fig. 3a Comparison of the frequencies of the seven extracted themes across the reflective essays, categorised by student self-reported impact. The black and white bars represent group A (most influenced by non-healthcare professionals) and group B (most influenced by clinical or allied health professionals), respectively. A chi- squared test was used to explore differences between the expression of themes depending on which department had the greatest self-reported impact on students. *p < 0.05. b Diagrammatic representation of the significant interrelationships among the themes based on the results of Fisher’s exact test. *p < 0.05, **p < 0.01, ***p < 0.001