ArticlePloS one2023
Experience of irreproducibility as a risk factor for poor mental health in biomedical science doctoral students: A survey and interview-based study.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Prevalence and severity of mental health problems in early-career researchers: a systematic review and meta-analysis.Nature human behaviour · 2026Pooled it
- Support systems impacting the mental health of diverse women in biomedical science programs: An ecological approach.SSM. Mental health · 2025Article
- Mental Health Among Spanish Doctoral Students: Relationship Between Anxiety, Depression, Life Satisfaction, and Mentoring.European journal of investigation in health, psychology and education · 2025Article
- Assessing the well-being of PhD scholars: a scoping review.BMC psychology · 2025Article
- A Model for Emotional Intelligence in Biology Education Research.CBE life sciences education · 2024Article
- Behind the graduate mental health crisis in science.Nature biotechnology · 2024Article
- Women's mental health in the doctoral context: Protective function of the psychological capital and academic motivation.Women's health (London, England)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High rates of irreproducibility and of poor mental health in graduate students have been reported in the biomedical sciences in the past ten years, but to date, little research has investigated whether these two trends interact. In this study, we ask whether the experience of failing to replicate an expected finding impacts graduate students' mental health. Using an online survey paired with semi-structured qualitative interviews, we examined how often biomedical science doctoral students at a large American public university experienced events that could be interpreted as failures to replicate and how they responded to these experiences. We found that almost all participants had experience with irreproducibility: 84% had failed to replicate their own results, 70% had failed to replicate a colleague's finding, and 58% had failed to replicate a result from the published literature. Participants reported feelings of self-doubt, frustration, and depression while experiencing irreproducibility, and in 24% of cases, these emotional responses were strong enough to interfere with participants' eating, sleeping, or ability to work. A majority (82%) of participants initially believed that the anomalous results could be attributed to their own error. However, after further experimentation, most participants concluded that the original result was wrong (38%), that there was a key difference between the original experiment and their own (17%), or that there was a problem with the protocol (17%). These results suggest that biomedical science graduate students may be biased towards initially interpreting failures to replicate as indicative of a lack of skill, which may trigger or perpetuate feelings of anxiety, depression, or impostorism.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.