Machine says go, doctor says no: an ecological momentary assessment analysis examining clinicians' perceptions of, and their antibiotic prescribing behaviour when using rapid molecular diagnostic tests in intensive care.
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| Title: | Machine says go, doctor says no: an ecological momentary assessment analysis examining clinicians' perceptions of, and their antibiotic prescribing behaviour when using rapid molecular diagnostic tests in intensive care. |
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| Authors: | Stewart SF; UCL School of Pharmacy, University College London, London, UK.; School of Psychology, University of Surrey, Guildford, UK., Enne VI; Division of Infection and Immunity, Faculty of Medical Sciences, University College London, London, UK., Pandolfo AM; UCL School of Pharmacy, University College London, London, UK., Jani YH; UCL School of Pharmacy, University College London, London, UK.; Centre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, UK., Brealey D; Division of Critical Care, University College London Hospitals NHS Foundation Trust, London, UK., Brett SJ; Department of Surgery and Cancer, Imperial College London, London, UK., Livermore DM; Norwich Medical School, University of East Anglia, Norwich, UK., Gant V; Department of Medical Microbiology, University College London Hospitals NHS Foundation Trust, London, UK., Horne R; UCL School of Pharmacy, University College London, London, UK. r.horne@ucl.ac.uk. |
| Corporate Authors: | INHALE WP Study Group |
| Source: | Antimicrobial resistance and infection control [Antimicrob Resist Infect Control] 2026 Mar 24; Vol. 15 (1). Date of Electronic Publication: 2026 Mar 24. |
| Publication Type: | Journal Article; Randomized Controlled Trial |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 101585411 Publication Model: Electronic Cited Medium: Internet ISSN: 2047-2994 (Electronic) Linking ISSN: 20472994 NLM ISO Abbreviation: Antimicrob Resist Infect Control Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2047-2994 |
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| DOI: | 10.1186/s13756-025-01690-8 |
