Trial reportBMC anesthesiology2025
Effect of nurse's verbal communication on the level of consciousness, pain, and agitation in anesthetized patients admitted to the intensive care unit: a double-blind clinical trial.
Trial report in BMC anesthesiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Research progress on occupational therapy for disorders of consciousness in the context of neurorehabilitation: visual analysis based on CiteSpace.Frontiers in neurologyPooled it
- Analysis of factors influencing innovative behaviors of intensive care unit nurses using a random forest model-a multicentre cross-sectional study.BMC nursing · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVarious sensory stimuli, including verbal communication, can influence patients' consciousness level, pain perception, and agitation in intensive care units (ICU). This study aimed to explore the impact of verbal communication on the consciousness level, pain, and agitation of anesthetized patients admitted to ICU.
methodsIn this randomized controlled clinical trial (RCT), participants were randomly assigned to two groups: an intervention group (n = 35) and a control group (n = 35). Patients in the intervention group received verbal communication twice a day for 10 days, while the control group received routine care. The level of consciousness, pain, and agitation of patients in both groups were assessed before and 15 min after verbal communication. Demographic questionnaires and Glasgow Coma Scale (GCS), Behavior Pain Scale and Richmond Agitation-Sedation Scale were used to collect data. Data were analyzed by SPSS 25 using t-test, Chi-square and repeated measures ANCOVA test.
resultsNo significant differences were found between the two groups (verbal communication and control) concerning demographic variables (p > 0.05). Before the intervention, no significant difference was observed between the groups in terms of pain (P = 0.17). However, significant differences were noted in agitation and the level of consciousness (P < 0.05). Comparing the 10-day intervention period, a significant difference in the variables of level of consciousness, pain, and agitation was observed between the verbal communication and control groups (P < 0.001).
conclusionThe findings of this study indicate that verbal communication had a positive impact on the level of consciousness, pain, and agitation of anesthetized patients in ICUs. Implementing verbal communication as an intervention by nurses can be an effective approach in medical centers. ETHICAL CODE: IR.RUMS.REC.1398.189. CLINICAL TRIAL REGISTRATION CODE: IRCT20150519022320N22; 8/05/2020.
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.