Evidence map›Paper›PMID 39624515›Full record

ArticleFrontiers in psychiatry2024

Exploring factors influencing the quality of life in diabetes: a network analysis-based study.

Lu Chen, Ling Li, Kexin Qiao, Zhengxue Qiao, Ying Xiang, Jiawei Zhou, Tianyi Bu, Xiaomeng Hu, Siyuan Ke, Yuecui Kan and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in psychiatry, 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

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

1 citing paper in PubMed.

  1. Article
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

14 authors.

Lu Chen *Department of Health Prevention and Care, Beijing Hospital, Beijing, China.
Ling Li *Psychology and Health Management Center, Harbin Medical University, Harbin, China.
Kexin Qiao *Psychology and Health Management Center, Harbin Medical University, Harbin, China.
Zhengxue QiaoPsychology and Health Management Center, Harbin Medical University, Harbin, China.
Ying XiangDepartment of Endocrinology, Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Jiawei ZhouPsychology and Health Management Center, Harbin Medical University, Harbin, China.
Tianyi BuPsychology and Health Management Center, Harbin Medical University, Harbin, China.
Xiaomeng HuPsychology and Health Management Center, Harbin Medical University, Harbin, China.
Siyuan KePsychology and Health Management Center, Harbin Medical University, Harbin, China.
Yuecui KanPsychology and Health Management Center, Harbin Medical University, Harbin, China.
Xuan LiuPsychology and Health Management Center, Harbin Medical University, Harbin, China.
Yanping Ji1 Department of Infectious Disease, the Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Xiaohui QiuPsychology and Health Management Center, Harbin Medical University, Harbin, China.
Yanjie YangPsychology and Health Management Center, Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The purpose of this study was to explore the key pathways leading to low quality of life in type 2 diabetes patients by means of network analysis, so as to provide the possibility of effective interventions. Methods: The study involved 1,011 adult type 2 diabetes patients from a tertiary hospital in Harbin. Data was collected through questionnaires, and network analysis was performed using R software to assess the centrality and predictability of each node. Results: "Depression" and "Submission" (weight = 0.26), "Depression" and "Physiological field" (weight = -0.16), exhibit the strongest associations. Overall, "Depression" has the highest weight in the association with diabetes symptom, regarding betweenness, "Depression" and "Submission" exhibit the highest scores, Furthermore, the analysis of closeness centrality reveals that "Depression" and "Submission" share the highest level of proximity, it suggests that they have the shortest distances to other network factors in our research network. Conclusion: Depression and Submission are likely to be key factors affecting the quality of life of people with diabetes. Providing psychological support and scientific coping strategies for diabetes patients may be an effective way to help them live a better life.

Indexed as

depressiondiabetesmedical copingmental healthnetwork analysisquality of life

Identifiers

PMID39624515
PMCPMC11609220

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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.