Evidence map›Paper›PMID 33841710›Full record

ArticleAmerican journal of translational research2021

The application effect analysis of personalized health education in acute leukemia nursing.

Cuiping Zhang, Yanqin Mao, Fang Tang, Xiang Xu

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
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

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 7 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Cuiping ZhangDepartment of Hematology, The First Affiliated Hospital of Soochow University Suzhou, Jiangsu Province, China.
Yanqin MaoDepartment of Hematology, The First Affiliated Hospital of Soochow University Suzhou, Jiangsu Province, China.
Fang TangDepartment of Hematology, The First Affiliated Hospital of Soochow University Suzhou, Jiangsu Province, China.
Xiang XuDepartment of Hematology, The First Affiliated Hospital of Soochow University Suzhou, Jiangsu Province, China.
First Affiliated Hospital of Soochow University · CNSoochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo analyze the effectiveness of personalized health education care in the nursing of patients with acute leukemia.

methodsA total of 108 patients with leukemia who were admitted to our hospital were randomly selected as research subjects. A random number table was used to allocate the patients into the observation group and the control group, with 54 patients in each group. The control group had routine health education care and the observation group received personalized health education care in addition to treatment given to the control group. The knowledge of leukemia, bad moods, adverse reaction and nursing satisfaction were compared between the two groups.

resultsThe observation group had better knowledge of leukemia and nursing satisfaction than the control group, and the incidence of bad moods (anxiety, depression) and adverse reactions were lower than that in the control group (all P<0.05).

conclusionThe application of personalized health education in the nursing of acute leukemia patients was significant, which improved the knowledge of acute leukemia, reduced the incidence of bad moods and adverse reactions, and improved nursing satisfaction.

Indexed as

Acute leukemiabad moodnursingnursing satisfactionpersonalized health education

Identifiers

PMID33841710
PMCPMC8014421
OpenAlexW3155699101

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.