ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2018
Of mice and mental health: facilitating dialogue and seeing further.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 16 citations in OpenAlex.
- Introduction to Special Issue on Affective Science in Animals: Toward a Greater Understanding of Affective Processes in Non-Human Animals.Affective science · 2022Article
- Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science.The lancet. Psychiatry · 2020Review
- Fear not: recent advances in understanding the neural basis of fear memories and implications for treatment development.F1000Research · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
The science of mental life is critical for understanding both how we function, and impairments in our functioning. However, understanding the causal mechanisms underlying mental health disorders and developing new treatments are challenges too great to be solved by any individual approach. There is a growing awareness that translational research-from laboratory to patient and back again to animal models-will be critical for the improved understanding and treatment of mental health disorders. The motivation and intention to pursue translational approaches is therefore strong in mental health research, but critically, opportunities for interaction between basic scientists and clinicians are relatively limited, and vary depending on the institution in which researchers are working. This has promoted the development of a 'culture gap' between basic and clinical scientists that limits interaction and sharing of knowledge. Here, we provide 14 examples of contemporary translational research and call for an increased collaborative approach to mental health research that spans clinical diagnoses, levels of analysis and bridges between basic to clinical mental health sciences, including, but not limited to, psychology and neuroscience. What is needed is an inclusive and integrated approach, bringing together scientists working at all levels of enquiry with clinicians providing insights on what works (and what does not). To stimulate the much-needed innovation in therapeutic techniques, an analysis of component parts is critical. Our approach suggests simplifying complex behaviours into distinct psychological components. Asking collaboratively driven scientific questions about dysfunction will also benefit our fundamental understanding of mental life.This article is part of a discussion meeting issue 'Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists'.
Indexed as
Identifiers
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.