Aim This study aimed to investigate the current situation of the spiritual health of maintenance haemodialysis (MHD) patients in China and analyse the influencing factors. Methods A total of 418 patients who underwent maintenance haemodialysis in three grade A tertiary hospitals were selected. The influencing factors were evaluated with demographic questionnaire, the Functional Assessment of Chronic Illness Therapy‐Spiritual Well‐Being (FACIT‐Sp‐12), Family APGAR Index, Herth Hope Index (HHI) and Acceptance of Illness Scale (AIS). Results Spiritual health was positively correlated with the HHI, Family APGAR and AIS scores. Nationality, HHI score, Family APGAR score and AIS score were independent influencing factors of spiritual health. MHD patients had a moderate level of spiritual health. Nationality, hope, family function and acceptance of illness were significant predictors of spiritual health. Patients who have higher hope levels, better family functioning and better illness acceptance may maintain better spiritual health.

Aim and objective:We investigated the correlation between the frailty status of maintenance haemodialysis (MHD) patients and psychosocial factors.Background: Varying degrees of frailty have been reported in MHD patients, which affect their quality of life.Design: We adopted a cross-sectional design in this study. Methods: Clinical data of 187 patients at our centre were collected from December 2017-June 2018 using a cross-sectional survey. Psychosocial factors were measured using the Pittsburgh Sleep Quality Index (PSQI), Hospital Anxiety and Depression Scale, 10-item Connor-Davidson Resilience Scale (CD-RISC), Chronic Disease Self-Efficacy Scales and Perceived Social Support Scale. Frailty status was estimated using the fatigue, resistance, ambulation, illnesses and loss of weight (FRAIL) scale.Spearman's correlation and multiple logistic regression analysis were conducted to identify the risk factors for frailty. This study complied with the STROBE checklist.Results: Of 187 patients, 11 cases (5.9%) of frailty were identified. Patient's age, comorbidities, parathyroid hormone level, sleep quality and depression were positively correlated with frailty (p < .05), while psychological resilience and social support were negatively correlated with frailty (p < .05). Logistic regression analysis revealed four risk factors for frailty among MHD patients, including age (p = .004), comorbidities (p = .023), depression (p = .023) and sleep disorders (p = .029). Conversely, protective factors included high psychological resilience (p = .019) and social support (p = .039). Conclusion:Among MHD patients, the risk factors for frailty included age, comorbidity, depression and sleep disturbance, whereas the protective factors included psychological resilience and social support. Relevance to clinical practice:Frailty is not only common among older patients, but also among people of all age groups suffering from chronic diseases. Therefore, it is important to consider the health status of MHD patients and adopt targeted nursing strategies to alleviate symptoms of frailty and improve physical condition by the following ways: postpone the progress of comorbidities, improve sleep quality, control S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section. P. Exploring psychosocial factors associated with frailty incidence among patients undergoing maintenance hemodialysis.

Purpose We conducted a cross‐sectional investigation of health‐related quality of life (HRQOL) among maintenance haemodialysis (MHD) patients, and determined important predictive factors of HRQOL in these patients. Methods Psychological factors were evaluated with the Hospital Anxiety and Depression Scale (HADS), the Pittsburgh Sleep Quality Index (PSQI) and the General Self‐Efficacy Scale (GSES). HRQOL was evaluated with the EQ‐5D. Laboratory data (albumin, haemoglobin and C‐reactive protein) were collected for medical evaluation. We also collected participants’ demographic data, including gender, age, et al. This study was in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. Results The mean EQ‐5D score was 0.86 ± 0.12, mean HADS‐anxiety score was 5.27 ± 3.41, mean HADS‐depression score was 5.29 ± 3.58, mean PSQI score was 7.00 ± 4.23 and mean GSES score was 6.86 ± 2.03. Participants’ mean haemoglobin was 108.18 ± 16.45 g/L, mean albumin was 41.80 ± 4.61 g/L and mean C‐reactive protein was 8.88 ± 18.50 mg/L. HRQOL was negatively correlated with HADS‐anxiety (r = −0.390, p < 0.001), HADS‐depression (r = −0.385, p < 0.001), PSQI (r = −0.285, p < 0.001) and C‐reactive protein (r = −0.198, p = 0.034). HRQOL was positively correlated with GSES (r = 0.205, p = 0.007). Age (p < 0.001), anxiety (p < 0.001), depression (p = 0.002), and postdialysis unemployment (p < 0.001) were independent risk factors for HRQOL. Conclusion Different health interventions should be implemented to improve patients’ HRQOL. Relevance to clinical practice The results will provide evidence for establishing healthcare interventions to maintain or improve HRQOL among this patient population.