Associations between demographic factors and the academic trajectories of medical students in Japan

Association between maternal dissatisfaction with oneself at birth and shaking and smothering toward the offspring up to 18 months old

BACKGROUND

A mother who feels dissatisfaction with herself may resort to abusive behavior such as shaking or smothering toward their offspring. Understanding this association can inform effective prevention strategies.

OBJECTIVE

This study aimed to investigate the associations between maternal feelings of dissatisfaction with oneself and infant physical abuse.

PARTICIPANTS AND SETTING

The study included 434 mothers who had recently given birth in two obstetric wards in a relatively wealthy area in Tokyo, Japan.

METHODS

Adopting a longitudinal design, the study used questionnaires post-childbirth to measure mothers' dissatisfaction with themselves. This involved evaluating perceptions of failing to meet personal standards or self-image. Physical abuse (specifically shaking or smothering) in infants was tracked at 3, 6, 12, and 18 months. Data analysis comprised multilevel analysis, group-based trajectory modeling, and multivariable logistic regression to explore the association between maternal dissatisfaction and child physical abuse.

RESULTS

Multilevel analysis showed that mothers with middle or high dissatisfaction with themselves were more likely to abuse their infant compared to mothers with low dissatisfaction with themselves (adjusted odds ratios [aOR] 5.71, 95 % confidence interval [CI], 1.06-30.78 and aOR 12.47, 95 % CI: 2.11-73.69, respectively). Trajectory analyses indicated that mothers with middle or high dissatisfaction with themselves were consistently more likely to abuse their infants up to 18 months (aOR 8.08, 95 % CI 1.61-40.53 and aOR 6.42, 95 % CI 1.27-32.43, respectively).

CONCLUSIONS

Our findings highlight a robust association between mother's dissatisfaction with themselves and a higher risk of infant physical abuse. These insights call for a comprehensive review of preventive measures for childhood physical abuse.

Association between the social network of medical students and their academic performance on the anatomy written examination

Although medical students learn human anatomy within a social network of friends/classmates, limited research has examined how social network structure is related to student's performance in human anatomy examinations. This study aimed to examine the association between centrality (i.e., the degree to which a student is connected to other students in class) before the start of the anatomy laboratory and changes in centrality owing to the start of the laboratory and failing the written examination taken on the last day of the course. Data included all 211 medical students at Tokyo Medical and Dental University who took anatomy classes in 2018 and 2019. The in-class social network before the laboratory was defined as "connected" if the student had more than one connection to the same individual in terms of the type of club activity, high school, and affiliation with an extracurricular program. The laboratory group adds the connection to the prelaboratory network, resulting in a postlaboratory network. Logistic regression models were used to estimate the association of degree and eigenvector centrality and changes in centrality after the laboratory with failing the written examination. Of the 211 students, 38 failed the examination. A one standard deviation increase in eigenvector centrality before the laboratory was significantly associated with a 44% decrease in odds of failing the examination (OR: 0.56, 95% CI: 0.34, 0.92). Changes in centrality measures were not associated with the performance of students in the examination. Higher in-class network centrality was associated with lower odds of failing the written examination.

Still want to be a doctor? Medical student dropout in the era of COVID-19

This research examines the intention of undergraduate medical students to withdraw from the medical profession and pursue a career in a different field upon graduation during COVID-19. We leverage the first and most comprehensive nationwide survey for medical education in China, which covered 98,668 enrolled undergraduate students from 90 out of 181 Chinese medical schools in 2020. We focus on these students' self-reported intention to leave the healthcare industry (the "dropout intention") before and after the outbreak of the epidemic. We also designed a randomized experiment to test whether and to what extent medical students dropout intention responded to an information nudge that highlighted the prosociality of health professionals in the fight against the virus. Results from a difference-in-differences model and a student fixed effect model suggest that after the onset of COVID-19, the proportion of Chinese undergraduate medical students with a dropout intention declined from 13.7% to 6.8%. Furthermore, the nudge information reduced the intent-to-drop-out probability by 0.8 additional percentage points for students in their early college years. There was large heterogeneity underneath the treatment effect. Specifically, we find that prior dropout intention and exposures to COVID-19-related information tended to mitigate the nudge effects. Data on students' actual dropout outcomes support our findings.

Exploring College Adjustment in First-Year Gen Z Medical Students and Its Contributing Factors

Background

First-year medical students need to adjust to university life to achieve optimal education. Notably, generation Z (Gen Z) students recently admitted to medical school possess unique characteristics that may affect their adjustment. However, limited studies have evaluated the adjustment of Gen Z medical students. In line with this, the present study explores the adjustment process of Gen Z medical students in their first year of study.

Methods

A qualitative phenomenological study was held from January 2020 to October 2020. The respondents comprised first-year students from two medical institutions. Maximum variation sampling was applied to select the respondents. Moreover, 11 focus group discussions (FGDs) with students and 10 in-depth interviews with lecturers were conducted. Curriculum documents were examined, and then the data were analysed thematically.

Results

Three themes were identified: i) domain; ii) process and iii) contributing factors to college adjustment. Academic, social and personal-emotional components of adjustment were included in the domain theme. The process theme consisted of transition, transition-transformation and transformation phases. Meanwhile, the contributing factors consisted of existing and supportive factors. Student characteristics, including demographics, mentality, prior educational experiences and social support, were considered the existing factors, while technology, learning system and well-being constituted the supporting factors.

Conclusion

College adjustment involves various domains, processes and contributing factors that are unique to Gen Z characteristics, technology dependence and culture. Therefore, well-prepared faculties are needed to support the adjustment of Gen Z students.

Identifying and supporting students at risk of failing the National Medical Licensure Examination in Japan using a predictive pass rate

BACKGROUND

Students who fail to pass the National Medical Licensure Examination (NMLE) pose a huge problem from the educational standpoint of healthcare professionals. In the present study, we developed a formula of predictive pass rate (PPR)" which reliably predicts medical students who will fail the NMLE in Japan, and provides an adequate academic support for them.

METHODS

Six consecutive cohorts of 531 medical students between 2012 and 2017, Gifu University Graduate School of Medicine, were investigated. Using 7 variables before the admission to medical school and 10 variables after admission, we developed a prediction formula to obtain the PPR for the NMLE using logistic regression analysis. In a new cohort of 106 medical students in 2018, we applied the formula for PPR to them to confirm the capability of the PPR and predicted students who will have a strong likelihood of failing the NMLE.

RESULTS

Medical students who passed the NMLE had the following characteristics: younger age at admission, graduates of high schools located in the surrounding area, high scores in the graduation examination and in the comprehensive computer-based test provided by the Common Achievement Test Organization in Japan. However, total score of examination in pre-clinical medical sciences and Pre-CC OSCE score in the 4th year were not correlated with the PPR. Ninety-one out of 531 students had a strong likelihood of failing the NMLE between 2012 and 2017 and 33 of these 91 students failed NMLE. Using the PPR, we predicted 12 out of 106 students will have a strong likelihood of failing the NMLE. Actually, five of these 12 students failed NMLE.

CONCLUSIONS

The PPR can be used to predict medical students who have a higher probability of failing the NMLE. This prediction would enable focused support and guidance by faculty members. Prospective and longitudinal studies for larger and different cohorts would be necessary.