Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Braunschweig, Germany.
Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover, Germany.
BMC Med Inform Decis Mak. 2021 May 11;21(1):153. doi: 10.1186/s12911-021-01512-y.
Adherence and motivation are key factors for successful treatment of patients with chronic diseases, especially in long-term care processes like rehabilitation. However, only a few patients achieve good treatment adherence. The causes are manifold. Adherence-influencing factors vary depending on indications, therapies, and individuals. Positive and negative effects are rarely confirmed or even contradictory. An ontology seems to be convenient to represent existing knowledge in this domain and to make it available for information retrieval.
First, a manual data extraction of current knowledge in the domain of treatment adherence in rehabilitation was conducted. Data was retrieved from various sources, including basic literature, scientific publications, and health behavior models. Second, all adherence and motivation factors identified were formalized according to the ontology development methodology METHONTOLOGY. This comprises the specification, conceptualization, formalization, and implementation of the ontology "Ontology for factors influencing therapy adherence to rehabilitation" (OnTARi) in Protégé. A taxonomy-oriented evaluation was conducted by two domain experts.
OnTARi includes 281 classes implemented in ontology web language, ten object properties, 22 data properties, 1440 logical axioms, 244 individuals, and 1023 annotations. Six higher-level classes are differentiated: (1) Adherence, (2) AdherenceFactors, (3) AdherenceFactorCategory, (4) Rehabilitation, (5) RehabilitationForm, and (6) RehabilitationType. By means of the class AdherenceFactors 227 adherence factors, thereof 49 hard factors, are represented. Each factor involves a proper description, synonyms, possibly existing acronyms, and a German translation. OnTARi illustrates links between adherence factors through 160 influences-relations. Description logic queries implemented in Protégé allow multiple targeted requests, e.g., for the extraction of adherence factors in a specific rehabilitation area.
With OnTARi, a generic reference model was built to represent potential adherence and motivation factors and their interrelations in rehabilitation of patients with chronic diseases. In terms of information retrieval, this formalization can serve as a basis for implementation and adaptation of conventional rehabilitative measures, taking into account (patient-specific) adherence factors. OnTARi also enables the development of medical assistance systems to increase motivation and adherence in rehabilitation processes.
依从性和动机是慢性疾病患者成功治疗的关键因素,尤其是在康复等长期护理过程中。然而,只有少数患者能够达到良好的治疗依从性。原因有很多。依从性影响因素因适应症、治疗方法和个体而异。积极和消极的影响很少得到证实,甚至相互矛盾。本体似乎是表示该领域现有知识并使其可用于信息检索的便捷方式。
首先,对康复治疗依从性领域的当前知识进行了手动数据提取。数据来自各种来源,包括基础文献、科学出版物和健康行为模型。其次,根据本体开发方法 METHONTOLOGY 对确定的所有依从性和动机因素进行了形式化处理。这包括在 Protégé 中对“影响康复治疗依从性的因素本体”(OnTARi)进行规范、概念化、形式化和实现。两位领域专家进行了面向分类法的评估。
OnTARi 包括 281 个类,以本体网络语言实现,10 个对象属性,22 个数据属性,1440 个逻辑公理,244 个个体和 1023 个注释。区分了六个高级别类别:(1)依从性,(2)依从性因素,(3)依从性因素类别,(4)康复,(5)康复形式,(6)康复类型。通过类 AdherenceFactors 表示 227 个依从性因素,其中 49 个是硬性因素。每个因素都有适当的描述、同义词、可能存在的缩写和德语翻译。OnTARi 通过 160 个影响关系说明了依从性因素之间的联系。Protégé 中实现的描述逻辑查询允许进行多个有针对性的请求,例如,提取特定康复领域的依从性因素。
通过 OnTARi,构建了一个通用参考模型来表示慢性疾病患者康复过程中的潜在依从性和动机因素及其相互关系。在信息检索方面,这种形式化可以作为考虑(患者特定)依从性因素的常规康复措施的实施和调整的基础。OnTARi 还可以为开发医疗辅助系统提供支持,以提高康复过程中的动机和依从性。