Assessing the Mental Health Crisis Among New York's Postdoctoral Researchers
Martinelli, S.; Uddin, J.; Alonso, E. B.; Doreste, R.; Jalal, S.
Show abstract
Grave concerns have been raised in recent years regarding the graduate student mental health crisis in academia; however, similar attention has not been focused on the subsequent and more challenging career stage in science, that of the postdoctoral researchers. We conducted a pilot survey among postdoctoral associates (N =160) at Weill Cornell Medicine, Cornell Universitys medical school in New York City, to understand the unique challenges faced by the postdoctoral community. Our survey found that respondents mental health and wellness were primarily affected by challenges intrinsic to the demands of academic life, with additional factors related to living in a major metropolitan city. Additionally, the survey identified unique challenges of postdoctoral researchers based on their gender, ethnicity, or citizenship/immigration status. Finally, our analyses also found that respondents had a negative outlook on career progression and ability to transition into an independent position within academia. These results are in line with similar surveys conducted in the past among students and postdoctoral researchers, and highlight the fact that, despite critical evidence, the situation has not changed overtime. Further studies should be conducted across various institutions and cities to gather more comprehensive data on the mental health and wellbeing of early-stage academic researchers. The findings from this study can be utilized by institutional Postdoctoral Offices or Associations to provide updated policies and resources aimed at alleviating some of the professional stresses faced by postdoctoral researchers.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Mental health in higher-education students and non-students: evidence from a nationally representative panel study 93%
- Mental Health of Clinical Staff Working in High-Risk Epidemic and Pandemic Health Emergencies: A Rapid Review of the Evidence and Meta-Analysis 92%
- The association between experience of COVID-19-related discrimination and psychological distress among healthcare workers for six national medical research centers in Japan 91%
Similar papers in this journal
- Citizenship status and career self-efficacy: An intersectional study of biomedical trainees in the United States 93%
- Gender-affirming care, mental health, and economic stability in the time of COVID-19: a global cross-sectional study of transgender and non-binary people 93%
- Characteristics of mental health stability during COVID-19: An online survey with people residing in the Liverpool City Region 93%
Similar papers in this journal
- Mental Health Impact of COVID-19: A global study of risk and resilience factors 91%
- Mental and social health of children and adolescents with pre-existing mental or somatic problems during the COVID-19 pandemic lockdown 91%
- Longitudinal trends and risk factors for depressed mood among Canadian adults during the first wave of COVID-19 90%
Similar papers in this journal
- The influence of repeated mild lockdown on mental and physical health during the COVID-19 pandemic: a large-scale longitudinal study in Japan 93%
- Prevalence and Predictors of Depression among Training Physicians in China: A Comparison to the United States 91%
- Loneliness and diurnal cortisol levels during COVID-19 lockdown: the roles of living situation, relationship status and relationship quality 91%
Similar papers in this journal
- The impact of working during the Covid-19 pandemic on health care workers and first responders: mental health, function, and professional retention 93%
- Black women in medical education publishing: Bibliometric and testimonio accounts using intersectionality methodology 91%
- An Evaluation of the Vulnerable Physician Workforce in the United States During the Coronavirus Disease-19 Pandemic 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.