Evidence map›Paper›PMID 40955351›Full record

ArticleJournal of multidisciplinary healthcare2025

Development and Preliminary Evaluation of a Structured Narrative Nursing Log for Conscious Patients in the Intensive Care Unit.

Hong-Mei Liu, Jing-Yi Jin, Jian-Hong Ji, Yun Zhang, Zhi-Ming Cui

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hong-Mei Liu *School of Nursing and Rehabilitation, Nantong University, Nantong, Jiangsu Province, 226001, People's Republic of China.
Jing-Yi Jin *School of Nursing and Rehabilitation, Nantong University, Nantong, Jiangsu Province, 226001, People's Republic of China.
Jian-Hong JiDepartment of Critical Care Medicine, Nantong First People's Hospital, Nantong, Jiangsu Province, 226006, People's Republic of China.
Yun ZhangSchool of Nursing and Rehabilitation, Nantong University, Nantong, Jiangsu Province, 226001, People's Republic of China.
Zhi-Ming CuiDepartment of Critical Care Medicine, Nantong First People's Hospital, Nantong, Jiangsu Province, 226006, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to develop a structured narrative nursing log, grounded in narrative nursing theory, for use with conscious patients in the intensive care unit (ICU), and to conduct a preliminary clinical evaluation of its effectiveness. Methods: A structured narrative nursing log was developed through literature review, group brainstorming, and expert consultation. A quasi-experimental design was adopted. The study included 90 conscious ICU patients from a Class III Grade A hospital in Nantong, Jiangsu Province, selected via convenience sampling. Participants were assigned to either the control group (n = 46), in which nurses documented care using a blank nursing log, or the intervention group (n = 44), in which nurses utilized the structured narrative nursing log developed in this study. Primary outcome measures included patient-reported anxiety levels, perceived caring, time spent by ICU nurses on narrative nursing, and nurses' sense of professional fulfillment. Results: Patients in the intervention group exhibited significantly lower anxiety levels and significantly higher perceived caring compared to those in the control group ( Conclusion: The structured narrative nursing log shows promise in reducing anxiety-related symptoms, improving patients' perception of care, and enhancing nurses' sense of professional accomplishment. These findings suggest its potential value in refining nursing practices for conscious patients in intensive care settings.

Indexed as

conscious patientsDelphi methodICUnarrative nursingnursing efficiencynursing logs

Identifiers

PMID40955351
PMCPMC12433643

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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.