Journal of psychosomatic research · 2026
Semantic network analysis of cognitive-affective patterns related to suicide risk and end-of-life attitudes in cancer.
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Noh Hae-Lim, Hahm Bong-Jin, Lee Young-Jin, Lee Jong Won, Youn Hyun Jo, Park Seun Ja, Park Sieun, Shim Eun-Jung
Аннотация
PURPOSE: Suicide, euthanasia, and physician-assisted suicide (PAS) represent significant clinical challenges in oncology and palliative care. Although these topics are conceptually related, they are often studied separately. Previous studies have relied on structured, close-ended measures, but none have applied semantic network analysis (SNA) to patient-generated language in this context.
AIMS: The study seeks to explore patterns of lexical association related to suicide risk and attitudes toward end-of-life interventions, applying SNA to Sentence Completion Test (SCT) responses. Networks were compared by suicide risk status, approval or disapproval of active euthanasia, and PAS.
METHODS: A total of 298 patients with cancer completed a seven-item SCT covering five domains: self, relationships, future, distress, and cancer appraisal. Group-specific undirected semantic networks were constructed. Global network metrics and node-level centrality were computed. Group differences were tested via permutation procedures and conceptual similarity was assessed using Jaccard similarity coefficients of top-ranking central terms.
RESULTS: The suicide risk networks were more narrowly illness-related terms, with words such as cancer, suffering, and death occupying more central positions. Similarly, networks of participants approving euthanasia and PAS were organized around illness and mortality-related terms, whereas disapproving groups showed more diverse and distributed patterns, including positively valenced terms such as appreciation and hope. Although there was moderate-to-high overlap in key terms across groups, each group showed distinct patterns in how these terms were organized.
CONCLUSIONS: Attending to emotionally salient language may provide insights into patients' experiences and could help inform psychosocial support and suicide prevention efforts.
AIMS: The study seeks to explore patterns of lexical association related to suicide risk and attitudes toward end-of-life interventions, applying SNA to Sentence Completion Test (SCT) responses. Networks were compared by suicide risk status, approval or disapproval of active euthanasia, and PAS.
METHODS: A total of 298 patients with cancer completed a seven-item SCT covering five domains: self, relationships, future, distress, and cancer appraisal. Group-specific undirected semantic networks were constructed. Global network metrics and node-level centrality were computed. Group differences were tested via permutation procedures and conceptual similarity was assessed using Jaccard similarity coefficients of top-ranking central terms.
RESULTS: The suicide risk networks were more narrowly illness-related terms, with words such as cancer, suffering, and death occupying more central positions. Similarly, networks of participants approving euthanasia and PAS were organized around illness and mortality-related terms, whereas disapproving groups showed more diverse and distributed patterns, including positively valenced terms such as appreciation and hope. Although there was moderate-to-high overlap in key terms across groups, each group showed distinct patterns in how these terms were organized.
CONCLUSIONS: Attending to emotionally salient language may provide insights into patients' experiences and could help inform psychosocial support and suicide prevention efforts.