Publications by authors named "Zekun Bian"

Objectives: This study investigated the mediating role of maladaptive cognitive emotion regulation strategies in the relationship between alexithymia and self-perceived aging among older adults.

Methods: We surveyed 478 Chinese community-dwelling older adults from November 2022 to May 2023. The Toronto Alexithymia Scale (TAS-20), Cognitive Emotion Regulation Questionnaire (CERQ), and Brief Aging Perceptions Questionnaire (B-APQ) were used.

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Purpose: Stroke is a major disease endangering the health of Chinese people, and patients need to rely on the care of family members, which brings heavy caregiving burdens and pressures to caregivers and families, thus disrupting the stable family structure. In view of this, this study was to analyse the current status of family resilience among caregivers of stroke patients in Chinese nuclear families, and to explore the correlation and mechanism of action among perceived stress, illness uncertainty and family resilience.

Patients And Methods: This study used a cross-sectional research design.

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Background: In China, about 18.70% of the population aged 60 years and older are at risk of low personal mastery as well as anxiety and depression for a variety of reasons. The purpose of this study was to construct a symptom network model of the relationship between anxiety, depression, and personal mastery in community-dwelling older adults and to identify central and bridge symptoms in this network.

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Objective: In this study, we explore the core and bridge symptoms of demoralization in female cancer patients in China, and provide a basis for precise psychological intervention among female cancer patients.

Methods: This study used a cross-sectional survey. Participants were recruited from three third-class hospitals in Jiangsu Province from June 2022 to June 2023 using the convenience sampling method.

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Background: Colorectal cancer incidence is on the rise, necessitating precise symptom management. However, causal relationships among symptoms have been challenging to establish due to reliance on cross-sectional data. Cross-lagged panel network (CLPN) analysis offers a solution, leveraging longitudinal data for insight.

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