Gynaecologic cancer refers to the cancer that starts in a woman's reproductive organs, which mainly include cervical, ovarian, uterine/endometrial, vaginal and vulva. It affects women at different age group, and risk increases with age (Harris, 2019). As a unique type of cancer in women, may pose preventable, adverse outcomes, especially on a woman's femininity, fertility and sexual life (Chow et al., 2016). Gynaecologic cancer not only has significant impacts on patients' physical and psychological health, but also affects their

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Background Patients with lung cancer suffer from significant psychological distress. The underlying theoretical model that may explain what predicts or mediates the degree of psychological distress has not been elucidated. Objectives To describe the incidence of psychological distress in patients with lung cancer and to test a predictive theoretical model of psychological distress based on symptom burden, type D personality, social support, and intrusive thoughts. Methods Three hundred eighty-nine patients with stages I to IV lung cancer were recruited. Participants completed a battery of scales, including measures of psychological distress, symptom burden, type D personality, perceived social support, intrusive thoughts, and demographic and clinical characteristics. The predictive theoretical model was tested using structural equation modeling. Results Experiencing clinically significant psychological distress was reported by 63.75% of participants. Consistent with the social cognitive processing model, symptom burden, type D personality, social support, and intrusive thoughts all significantly and directly predicted the level of psychological distress in patients with lung cancer. Moreover, intrusive thoughts mediated the effects of type D personality and symptom burden on psychological distress; social support and symptom burden mediated the effects of type D personality on psychological distress. Conclusions The majority of the participants experienced psychological distress at a clinically significant level. Intrusive thoughts and social support mediated the effects of type D personality and symptom burden on psychological distress. Implications for Practice Patients with type D personality and symptom burden should be identified. Interventions for targeting social support and intrusive thoughts might ultimately reduce their psychological distress.

Purpose This study aimed to develop and test the psychometric properties of a Professional Nursing Support Scale for patients with cancer in mainland China. Methods The study was conducted in two phases from January 2017 to January 2020. Phase I involved item generation and developing a preliminary version of Professional Nursing Support Scale through literature review, qualitative interviews, content validity evaluation and a pilot study. Phase II involved psychometric properties testing of the Professional Nursing Support Scale in 700 patients with cancer recruited from four public hospitals in Anhui Province, China. Results A 49‐item Professional Nursing Support Scale was finally developed. Exploratory factor analysis showed a four‐factor structure of the 49‐item Professional Nursing Support Scale, accounting for 56.95% of variance. Cronbach's α ranged from 0.91 to 0.94 for the four subscales. Confirmatory factor analysis further confirmed the best model fit of four‐factor structure of the Professional Nursing Support Scale. The Professional Nursing Support Scale also showed an acceptable concurrent validity with Supportive Care Needs Scale short form 34 (r = 0.75, p < 0.001) and Psychological Distress Thermometer (r = 0.39, p < 0.001). Conclusions The Professional Nursing Support Scale is a reliable and valid instrument to assess perceived needs of professional nursing support and support acquisition in relation to the care in Chinese patients with cancer.

Objective: The aim of this study was to determine the correlation between sleep disturbance and proinflammatory markers in adult patients with cancer. Methods: A systematic search was conducted in 7 databases from inception to March 1, 2020, for this meta-analysis. Two reviewers independently screened the studies, extracted data, and appraised the quality of the studies. Meta-analyses were conducted using Stata 12.0 software. Results: Sixteen studies were included. Results indicated that sleep disturbance was associated with higher levels of the overall proinflammatory markers and that the effect size was small yet significant. Further subgroup analyses suggested that sleep disturbance was significantly associated with interleukin-6 and C-reactive protein, but not with interleukin-1β or tumor necrosis factor-α. Meta-regression results indicated that only the sample source affected the association between sleep disturbance and proinflammatory markers. Conclusion: There was a positive relationship between sleep disturbance and selected proinflammatory markers in adult patients with cancer.