ArticleFrontiers in psychiatry2026
Network analysis of distress, symptom burden, social support, and digital health literacy in older postoperative patients with gastric cancer.
Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: To use network analysis to explore the relationships among distress, symptom burden, social support, and digital health literacy in older patients with gastric cancer following surgery. Background: Digital healthcare is gaining increasing prominence and represents a promising approach to improving long-term care and psychological support for older postoperative patients with gastric cancer. However, this population frequently experiences high distress, heavy symptom burden, limited social support, and low DHL, which together constitute major barriers to the effective use of digital health resources. To date, the mechanisms underlying the interactions among these factors remain poorly understood. Therefore, this study seeks to clarify these relationships and provide empirical evidence to support the integration of digital health into geriatric oncology care. Methods: A cross-sectional study was conducted involving 767 older postoperative patients with gastric cancer at a teaching hospital between August 2024 and June 2025. Participants completed validated questionnaires, including the Brief Symptom Inventory-18 (BSI-18), the M. D. Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI), the Multidimensional Scale of Perceived Social Support (MSPSS), and the eHealth Literacy Scale (e-HEALS). R software version 4.2.1 was used. Network analysis assessed the structure, centrality, stability, and accuracy of these factors. Results: Network analysis revealed that "Blue" and "Tense" of the BSI-18, and "Evaluate" of the e-HEALS were the most central nodes. "Friends" and "Sleep" acted as key bridge nodes, linking distress, symptom burden, and social support domains. The network proved stable and accurate. Conclusions: This study highlighted the item "Blue" as a central node and "Sleep" as a key bridge node. These findings suggest the potential utility of network analysis in precision nursing. Furthermore, measures such as emotional counseling for low mood, sleep optimization, and peer-navigated digital empowerment may help address the interconnected symptom pattern observed in this population.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.