ReviewJournal of graduate medical education2022
Resting and Recharging: A Narrative Review of Strategies to Improve Sleep During Residency Training.
Review in Journal of graduate medical education, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 7 citations in OpenAlex.
- Medical Students on Their Internal Medicine Clerkship Experience Short Sleep Duration.ATS scholar · 2025Article
- Relationship between shift scheduling, sleep knowledge and sleep quality in medical trainees: protocol for a global cross-sectional survey.Journal of thoracic disease · 2025Article
- Evaluating the Impact of Training Duration on Resident Sleep Patterns and Well-Being in Family Medicine.Family medicine · 2024Article
- Examining Anxiety and Insomnia in Internship Students and Their Association with Internet Gaming Disorder.Journal of clinical medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Residency involves demanding training with long hours that may cause fatigue and sleep deprivation and adversely impact residents and patients under their care. Objective: To identify, using a narrative review, evidence-based interventions to reduce the physiologic effects of fatigue and sleep deprivation from overnight and night shift work. Methods: A PubMed literature search was conducted through August 30, 2021, using the terms "resident" and "sleep" in the title or abstract and further narrowed using a third search term. Observational studies, randomized controlled trials, systematic reviews, and meta-analyses of human subjects written and published in English were included. Studies that were not specific to residents or medical interns or did not investigate an intervention were excluded. Additional studies were identified by bibliography review. Due to the heterogeneity of study design and intervention, a narrative review approach was chosen with results categorized into non-pharmacological and pharmacological interventions. Results: Initially, 271 articles were identified, which were narrowed to 28 articles with the use of a third search term related to sleep. Bibliography review yielded 4 additional articles. Data on interventions are limited by the heterogeneity of medical specialty, sample size, length of follow-up, and reliance on self-report. Non-pharmacological interventions including strategic scheduling and sleep hygiene may improve sleep and well-being. The available evidence, including randomized controlled trials, to support pharmacological interventions is limited. Conclusions: Non-pharmacological approaches to mitigating fatigue and sleep deprivation have varying effectiveness to improve sleep for residents; however, data for pharmacological interventions is limited.
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.