Evidence map›Paper›PMID 35932024›Full record

ArticleBMC nursing2022

Effects of comprehensive nursing intervention based on self-disclosure on improving alexithymia in elder patients with coronary heart disease.

Weixin Zhang, Haili Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC nursing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Alexithymia and asthma: a systematic review.Frontiers in psychology · 2023
    Review
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

2 authors at 1 institution in 1 country.

Weixin ZhangNursing School of Qiqihar Medical University, No 333, BuKui North Street, Jianhua District, Heilongjiang Province, 161006, Qiqihar City, China.
Haili ZhangNursing School of Qiqihar Medical University, No 333, BuKui North Street, Jianhua District, Heilongjiang Province, 161006, Qiqihar City, China. haili_zhang@yeah.net.
Qiqihar Medical University · CN

Funding

Self-exposure palliative care for alexithymia in patients with CHD QMSI2019M-28
6 · The paper itself

Abstract

objectivesPatients with coronary heart disease (CHD) experience stress and suffer from the risk of recurrence and death. Comprehensive nursing intervention based on self-disclosure (CNISD) is an interdisciplinary service and an effective approach to care that improves quality of life and alleviates suffering for patients with CHD. The purpose of this study was to analyze the effects of CNISD on alexithymia in patients with CHD.

methodsA total of 1088 patients with CHD were recruited and received CNISD (n = 540) and usual care (n = 548). The quality of life, alexithymia, four statutory health insurance funds, recurrence, mortality, and satisfaction was compared in patients with CHD between CNISD and usual care group.

resultsOutcomes showed that CNISD improved sleep quality and quality of life, increased physical activity, reduced the hospital anxiety and depression scale in patients with CHD compared to usual care. Recurrence and mortality of patients with CHD were markedly improved by CNISD compared to patients with CHD in usual care group.

conclusionsIn conclusion, data in this study indicate that CNISD presents benefits in improving quality of life, physical activity, anxiety, depression, recurrence, and mortality for patients with CHD.

Indexed as

AlexithymiaComprehensive nursing interventionCoronary heart diseasePhysical activityRecurrence

Identifiers

PMID35932024
PMCPMC9354330
OpenAlexW4289874620

What OpenQuestion holds

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LicenceCC BY
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.