Department of Developmental and Social Psychology, Sapienza, University of Rome, Rome, Italy.
Department of Psychology, University of Notre Dame, South Bend, Indiana, USA.
Ann Behav Med. 2024 Oct 16;58(10):679-691. doi: 10.1093/abm/kaae025.
The study's main aim was to analyze the structure and configuration of distress symptoms and resource factors.
Common methods of assessing distress symptoms in cancer patients (i) do not capture the configuration of individual distress symptoms and (ii) do not take into account resource factors (e.g., social support, coping, caring health professionals). Network analysis focuses on the configuration and relationships among symptoms that can result in tailored interventions for distress. Network analysis was used to derive a symptom-level view of distress and resource factors.
Nine hundred and ninety-two cancer patients (mixed diagnoses) completed an abridged Distress Screening Schedule that included 24 items describing symptoms related to distress (depression, anxiety) and resource factors (social support, coping, caring health professionals).
In network analysis, the centrality strength index (CSI) is the degree to which an item is connected to all other items, thus constituting an important focal point in the network. A depression symptom had the highest CSI value: felt lonely/isolated (CSI = 1.30). In addition, resource factors related to coping efficacy (CSI = 1.20), actively seeking support (CSI = 1.10), perceiving one's doctor as caring (CSI = 1.10), and receiving social support (CSI = 1.10) also all had very high CSI scores.
These results emphasize the integral importance of the social symptoms of loneliness/isolation in distress. Thus, distress symptoms (loneliness) and resource factors (coping efficacy, seeking social support, and perceiving medical professionals as caring) should be integral aspects of distress management and incorporated into assessment tools and interventions to reduce distress.
本研究的主要目的是分析困扰症状和资源因素的结构和配置。
评估癌症患者困扰症状的常用方法（i）无法捕捉个体困扰症状的结构，（ii）不考虑资源因素（例如，社会支持、应对、关怀的医护人员）。网络分析侧重于可以导致针对困扰的定制干预的症状之间的配置和关系。网络分析用于得出困扰和资源因素的症状层面的观点。
992 名（混合诊断）癌症患者完成了一份缩写的困扰筛查表，其中包括 24 个描述与困扰（抑郁、焦虑）和资源因素（社会支持、应对、关怀的医护人员）相关的症状的项目。
在网络分析中，中心性强度指数（CSI）是一个项目与所有其他项目连接的程度，因此构成网络中的一个重要焦点。一个抑郁症状的 CSI 值最高：感到孤独/孤立（CSI = 1.30）。此外，与应对效能相关的资源因素（CSI = 1.20）、积极寻求支持（CSI = 1.10）、感知医生的关怀（CSI = 1.10）和获得社会支持（CSI = 1.10）也都具有非常高的 CSI 分数。
这些结果强调了困扰中社交症状孤独/孤立的整体重要性。因此，困扰症状（孤独）和资源因素（应对效能、寻求社会支持和感知医护人员的关怀）应该是困扰管理的整体方面，并纳入评估工具和干预措施中，以减少困扰。
