Evidence map›Paper›PMID 39403913›Full record

ArticleActas espanolas de psiquiatria2024

Mood State in Patients with Post-traumatic Stress Disorder due to Lung Cancer: A Clinical Application Study of Intensive Cognitive Management.

Kai Zhang, Rongze Zhang

Abstract read
In one paragraph

Article in Actas espanolas de psiquiatria, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Randomized controlled trial: Synergistic effect of three-ball mindfulness breathing rehabilitation training following pulmonary lobectomy for lung cancer.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Trial
4 · The record

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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.

Kai ZhangDepartment of Respiratory and Critical Care Medicine, Zibo First Hospital, 255200 Zibo, Shandong, China.
Rongze ZhangDepartment of Oncology and Immunology, The Fourth Hospital of Hebei Medical University, 050011 Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPost-traumatic stress disorder (PTSD) due to lung cancer seriously affects the mood state of patients. Intensive cognitive management is a structured management method based on cognitive behavioral therapy, which can correct cognitive distortions and regulate adverse emotions. This study mainly explored the effect of intensive cognitive management on the mood state of patients with PTSD due to lung cancer.

methodsA retrospective analysis was conducted on the clinical data of 169 patients with PTSD due to lung cancer admitted to our hospital from June 2020 to June 2021. Based on different clinical management schemes, these patients were divided into the reference group (RG, n = 87, routine management) and the study group (SG, n = 82, routine management+intensive cognitive management). The sleep status and degree of depression and anxiety were evaluated using the Pittsburgh Sleep Quality Index (PSQI), Self-rating Anxiety Scale (SAS), Depression Scale (D), and Post-traumatic Stress Disorder Check List (PCL).

resultsAfter 2 weeks (T1) and 4 weeks (T2) of nursing, the scores on the PSQI (p < 0.001), SAS (T0-T1: p < 0.001; T0-T2: p < 0.001) and D (T0-T1: p = 0.026, p < 0.001; T0-T2: p < 0.001), as well as three PCL factors (p < 0.001) of the two groups were significantly lower than those before nursing (T0). At the T1 and T2 stages, difference scores for the PSQI (difference score 1: p = 0.003; difference score 2: p = 0.006), SAS (difference score 1: p = 0.002; difference score 2: p = 0.007), and D (difference score 1: p < 0.001; difference score 2: p = 0.002) were higher in the SG compared with the RG. At the T1 stage, the difference score of the PCL high-alert factor (p = 0.008) was higher in the SG compared with the RG, with no significant difference in difference scores of other two factors (p > 0.05). At the T2 stage, the SG had higher difference scores for the three PCL factors compared with the RG (p < 0.001, p = 0.011, p < 0.001).

conclusionIntensive cognitive management can effectively improve sleep quality and adverse emotions and has potential for clinical management of PTSD in patients with lung cancer.

Indexed as

AffectAnxietyCognitive Behavioral TherapyLung NeoplasmsStress Disorders, Post-TraumaticAgedDepressionFemaleHumansMaleMiddle AgedRetrospective StudiesSleep Quality

Identifiers

PMID39403913
PMCPMC11474963

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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.