Department of Neurology, Emory University School of Medicine, Atlanta, GA; Xiangya Hospital, Central South University, Changsha, Hunan, China.
Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA.
Am J Geriatr Psychiatry. 2021 May;29(5):488-498. doi: 10.1016/j.jagp.2020.09.018. Epub 2020 Sep 28.
A wealth of evidence has linked purpose in life (PiL) to better mental and physical health and healthy aging. Here, the authors aimed to determine important correlates of PiL using a machine learning approach.
Participants were recruited from retirement communities by the Rush Memory and Aging Project and assessed for childhood experience, adulthood sociodemographic factors (e.g., education, income, marital status), lifestyle and health behavior (e.g., cognitively stimulating activities, exercise, social activities, social network size), psychological factors (e.g., depression, loneliness, perceived discrimination, perceived social support), personality traits (e.g., PiL, harm avoidance), and medical conditions. Elastic Net was implemented to identify important correlates of PiL.
A total of 1,839 participants were included in our analysis. Among the 23 variables provided to Elastic Net, 10 were identified as important correlates of PiL. In order of decreasing effect size, factors associated with lower PiL were loneliness, harm avoidance, older age, and depressive symptoms, while those associated with greater PiL were perceived social support, more social activities, more years of education, higher income, intact late-life cognitive performance, and more middle-age cognitive activities.
Our findings identify potentially important modifiable factors as targets for intervention strategies to enhance PiL.
大量证据表明人生目标与更好的身心健康和健康衰老有关。在这里，作者旨在使用机器学习方法确定人生目标的重要相关因素。
参与者由拉什记忆与衰老项目从退休社区招募，并评估其童年经历、成年社会人口因素（如教育、收入、婚姻状况）、生活方式和健康行为（如认知刺激活动、锻炼、社交活动、社交网络规模）、心理因素（如抑郁、孤独、感知歧视、感知社会支持）、人格特质（如人生目标、回避伤害）和医疗状况。实施弹性网络以确定人生目标的重要相关因素。
共有 1839 名参与者纳入我们的分析。在提供给弹性网络的 23 个变量中，有 10 个被确定为人生目标的重要相关因素。按效应大小递减的顺序，与较低人生目标相关的因素包括孤独、回避伤害、年龄较大和抑郁症状，而与较高人生目标相关的因素包括感知社会支持、更多的社交活动、更多的受教育年限、更高的收入、晚年认知表现完好以及更多的中年认知活动。
我们的发现确定了潜在的重要可改变因素，这些因素可能成为增强人生目标的干预策略的目标。
