University of Texas Health Science Center at Houston, Texas, USA.
Baylor College of Medicine, Houston, Texas, USA.
Stud Health Technol Inform. 2022 Jun 6;290:819-823. doi: 10.3233/SHTI220193.
Evaluating digital behavior change intervention engagement is complex and requires multidimensional and novel approaches that are emerging. The relationship and interdependence between engagement with the technology and engagement with the psychosocial or behavior change process often presents conceptual and evaluative challenges. Large objective data sets detailing technology use are plentiful but meaningful interpretation can be challenging at granular levels. Affiliation network analysis which describes two-mode network data may provide a novel approach to evaluate engagement of digital behavior change interventions. The purpose of this paper is to use affiliation network analysis as an exploratory method to describe, assess and visualize content-specific patterns underlying psychosocial characteristics related to HPV vaccine safety concerns of parents using the HPVcancerFree intervention. Results indicate that affiliation network analysis shows promise in supplementing existing methods to assess engagement of digital interventions.
评估数字行为改变干预措施的参与度是复杂的，需要多维和新颖的方法，这些方法正在不断涌现。与技术的参与度以及与心理社会或行为改变过程的参与度之间的关系和相互依存关系常常带来概念和评估方面的挑战。详细说明技术使用情况的大量客观数据集很丰富，但在细粒度水平上进行有意义的解释可能具有挑战性。描述双模网络数据的关联网络分析可能为评估数字行为改变干预措施的参与度提供一种新方法。本文的目的是使用关联网络分析作为一种探索性方法，描述、评估和可视化 HPVcancerFree 干预措施中与 HPV 疫苗安全问题相关的父母的心理社会特征背后的特定于内容的模式。结果表明，关联网络分析有望补充现有方法来评估数字干预措施的参与度。
