二元体
心理健康
心理学
相似性(几何)
临床心理学
医疗保健
多级模型
相关性(法律)
样品(材料)
发展心理学
精神科
机器学习
法学
化学
经济
人工智能
图像(数学)
经济增长
色谱法
计算机科学
政治学
作者
Christopher S. Lee,Karen S. Lyons
摘要
Abstract Objective To identify distinct patterns of dyadic mental health in a sample of lung cancer dyads over 12 months and associations with other health characteristics and individual, dyadic, and familial predictors. Methods A sample of 113 patient‐care partner dyads living with nonsmall cell lung cancer were examined five times over 12 months. An integrative multilevel and mixture modeling approach was used to generate dyadic mental health summaries and identify common dyadic patterns of mental health over time, respectively. Results Three distinct patterns of dyadic mental health were observed: a congruent pattern (32.7%) characterized by almost identical mental health between members of the dyad, a disparate pattern (29.2%) characterized by better mental health of the patient compared with the care partner, and a parallel pattern (38.1%) characterized by care partner patterns of improvement and greater similarity in mental health over time. Membership of patterns was associated with physical health characteristics of both patient and care partner, levels of patient concealment regarding worries and concerns, and relationship quality reported by the care partner. Patterns did not differ by patient gender, care partner strain, or levels of social support. Conclusions Findings emphasize the importance of examining patterns of dyadic mental health to identify dyads most at risk so we may optimize the health of the dyad in tailored ways.
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