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<p>To date, no study has characterized the heterogeneity of social connectedness among patients undergoing maintenance hemodialysis (MHD). This study used latent profile analysis (LPA) to identify distinct latent profiles of social connectedness in this population and to explore the factors associated with different profiles. This cross-sectional study enrolled 365 patients undergoing MHD at a tertiary hospital in Anhui Province, China, from September 2025 to March 2026. Data were collected using a demographic questionnaire, the Social Connectedness Scale-Revised (SCS-R), the Social Support Rating Scale (SSRS), and the 10-item Connor-Davidson Resilience Scale (CD-RISC-10). Data analysis was performed using SPSS 26.0 and Mplus 8.3. A total of 345 valid questionnaires were collected. The response rate was 94.52% (345/365). We identified three potential profile categories: low social connectedness (<i>n</i> = 110, 31.9%), moderate social connectedness (<i>n</i> = 146, 42.3%), and high social connectedness (<i>n</i> = 89, 25.8%). Multivariate logistic regression analysis identified educational level, employment status, dialysis shift, types of chronic diseases, resilience, and social support as factors significantly associated with these three profiles (<i>P</i> &lt; 0.05). The findings indicate that social connectedness among MHD patients exhibits significant heterogeneity across subgroups and is associated with a variety of factors. Healthcare professionals should identify patients’ social connectedness profiles early and implement targeted interventions to improve their social connectedness.</p>

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Latent profiles of social connectedness and associated factors in maintenance hemodialysis patients

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月24日

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  • Yun Zhang,
  • Zhiyan Sun,
  • Naiyue Ye,
  • Xun Zhou,
  • Menghan Zheng,
  • Peili Xu

摘要

To date, no study has characterized the heterogeneity of social connectedness among patients undergoing maintenance hemodialysis (MHD). This study used latent profile analysis (LPA) to identify distinct latent profiles of social connectedness in this population and to explore the factors associated with different profiles. This cross-sectional study enrolled 365 patients undergoing MHD at a tertiary hospital in Anhui Province, China, from September 2025 to March 2026. Data were collected using a demographic questionnaire, the Social Connectedness Scale-Revised (SCS-R), the Social Support Rating Scale (SSRS), and the 10-item Connor-Davidson Resilience Scale (CD-RISC-10). Data analysis was performed using SPSS 26.0 and Mplus 8.3. A total of 345 valid questionnaires were collected. The response rate was 94.52% (345/365). We identified three potential profile categories: low social connectedness (n = 110, 31.9%), moderate social connectedness (n = 146, 42.3%), and high social connectedness (n = 89, 25.8%). Multivariate logistic regression analysis identified educational level, employment status, dialysis shift, types of chronic diseases, resilience, and social support as factors significantly associated with these three profiles (P < 0.05). The findings indicate that social connectedness among MHD patients exhibits significant heterogeneity across subgroups and is associated with a variety of factors. Healthcare professionals should identify patients’ social connectedness profiles early and implement targeted interventions to improve their social connectedness.