Department of Mechanical and Industrial Engineering, College of Engineering, University of Massachusetts Amherst, Amherst, MA, United States of America.
Department of Kinesiology and Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA, United States of America.
PLoS One. 2024 May 24;19(5):e0304214. doi: 10.1371/journal.pone.0304214. eCollection 2024.
Physical inactivity is a growing societal concern with significant impact on public health. Identifying barriers to engaging in physical activity (PA) is a critical step to recognize populations who disproportionately experience these barriers. Understanding barriers to PA holds significant importance within patient-facing healthcare professions like nursing. While determinants of PA have been widely studied, connecting individual and social factors to barriers to PA remains an understudied area among nurses. The objectives of this study are to categorize and model factors related to barriers to PA using the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework. The study population includes nursing students at the study institution (N = 163). Methods include a scoring system to quantify the barriers to PA, and regularized regression models that predict this score. Key findings identify intrinsic motivation, social and emotional support, education, and the use of health technologies for tracking and decision-making purposes as significant predictors. Results can help identify future nursing workforce populations at risk of experiencing barriers to PA. Encouraging the development and employment of health-informatics solutions for monitoring, data sharing, and communication is critical to prevent barriers to PA before they become a powerful hindrance to engaging in PA.
身体活动不足是一个日益严重的社会问题,对公众健康有重大影响。确定参与身体活动(PA)的障碍是认识到不成比例地经历这些障碍的人群的关键步骤。在面向患者的医疗保健专业中,如护理,了解 PA 的障碍具有重要意义。虽然 PA 的决定因素已被广泛研究,但将个人和社会因素与 PA 的障碍联系起来仍然是护士群体中一个研究不足的领域。本研究的目的是使用国家少数民族健康和健康差异研究所(NIMHD)研究框架对与 PA 障碍相关的因素进行分类和建模。研究人群包括研究机构的护理学生(N=163)。方法包括量化 PA 障碍的评分系统和预测该评分的正则化回归模型。主要发现确定内在动机、社会和情感支持、教育以及使用健康技术进行跟踪和决策目的是重要的预测因素。研究结果可以帮助确定未来面临 PA 障碍风险的护理劳动力人群。鼓励开发和使用健康信息学解决方案来进行监测、数据共享和沟通对于在 PA 障碍成为参与 PA 的强大障碍之前预防 PA 障碍至关重要。