Construction and Application of Health Behavior Change Intervention Ontology
Xu Dongdong, Lin Hui, Duan Huilong, Deng Ning*
(The Ministry of Education Key Laboratory of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China)
Abstract：Lifestyle intervention is an essential component of chronic disease management. A new trend in chronic disease management is integrated lifestyle intervention research based on mHealth technology. Faced with the challenge of increasing intervention complexity and comprehensiveness, a standard, detailed and comprehensive framework is desired to deconstruct and analyze complex intervention programs to promote the intervention quality and effectiveness. This study proposed the Health Behavior Change Intervention Ontology (HBCIO). First, content analysis was used to extract and categorize intervention content to obtain a collection of behavior change techniques and their attributes. The ontology was then constructed using a combination of the seven-step method and the OWL language. And an out-of-hospital hypertension management program was described and evaluated as an example. The term collection included 22 behavior change techniques suitable for chronic disease management diet and exercise scenarios based on mobile medical technology and 102 behavior change technique implementation process attributes. The HBCIO ontology has a total of 128 classes, 51 data properties, and 16 object properties. Based on HBCIO, the hypertension intervention program was converted into a combination of intervention units with clear levels and processes, and the evaluation results showed that the program used a total of 14 behavioral change techniques, with a coverage rate of 63.64%. The ontology can be applied to the intervention design, description, analysis, and evaluation of technology-based chronic disease management, and it is helpful to knowledge organization and sharing.
许冬冬, 林惠, 段会龙, 邓宁. 健康行为改变干预本体的构建与应用[J]. 中国生物医学工程学报, 2023, 42(1): 74-81.
Xu Dongdong, Lin Hui, Duan Huilong, Deng Ning. Construction and Application of Health Behavior Change Intervention Ontology. Chinese Journal of Biomedical Engineering, 2023, 42(1): 74-81.
[1] Vos T, Lim SS, Abbafati C, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the global burden of disease study 2019[J/OL]. The Lancet, 2020, 396(10258): 1204-1222. [2] Beaglehole R, Bonita R, Horton R, et al. Priority actions for the non-communicable disease crisis[J/OL]. The Lancet, 2011, 377(9775): 1438-1447. [3] Kearns K, Dee A, Fitzgerald AP, et al. Chronic disease burden associated with overweight and obesity in Ireland: the effects of a small BMI reduction at population level[J/OL]. BMC Public Health, 2014, 14(1): 143. [4] Fiordelli M, Diviani N, Schulz PJ. Mapping mHealth research: a decade of evolution[J/OL]. Journal of Medical Internet Research, 2013, 15(5): e95. [5] Lee JA, Choi M, Lee SA, et al. Effective behavioral intervention strategies using mobile health applications for chronic disease management: a systematic review[J/OL]. BMC Medical Informatics and Decision Making, 2018, 18(1): 12. [6] Webb T, Joseph J, Yardley L, et al. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy[J/OL]. Journal of Medical Internet Research, 2010, 12(1): e1376. [7] Teixeira PJ, Marques MM, Silva MN, et al. A classification of motivation and behavior change techniques used in self-determination theory-based interventions in health contexts[J/OL]. Motivation Science, 2020, 6(4): 438-455. [8] Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions[J/OL]. Health Psychology, 2008, 27(3): 379-387. [9] Connell LE, Carey RN, De Bruin M, et al. Links between behavior change techniques and mechanisms of action: an expert consensus study[J/OL]. Annals of Behavioral Medicine, 2019, 53(8): 708-720. [10] Me W, Ap K, Mw O, et al. Sensing interstitial glucose to nudge active lifestyles (SIGNAL): feasibility of combining novel self-monitoring technologies for persuasive behaviour change[J/OL]. BMJ Open, 2017, 7(10):98282. [11] Howlett N, Jones A, Bain L, et al. How effective is community physical activity promotion in areas of deprivation for inactive adults with cardiovascular disease risk and/or mental health concerns? study protocol for a pragmatic observational evaluation of the “Active Herts” physical activity programme[J/OL]. BMJ Open, 2017, 7(11): e017783. [12] Noy NF, Mcguinness DL. Ontology Development 101: A Guide to Creating Your First Ontology[R]. 2001. [13] 廖莉莉, 沈国华, 黄志球, 等. 本体评估方法研究综述[J]. 计算机应用研究, 2015, 32(3): 647-651. [14] Poveda-Villalón M, Gómez-Pérez A, Suárez-Figueroa MC. OOPS! (ontology pitfall scanner!): an on-line tool for ontology evaluation[J]. International Journal on Semantic Web and Information Systems (IJSWIS), 2014, 10(2): 7-34. [15] Wang Zheyu, An Jiye, Lin Hui, et al. Pathway-driven coordinated telehealth system for management of patients with single or multiple chronic diseases in China: system development and retrospective study[J/OL]. JMIR Medical Informatics, 2021, 9(5): e27228. [16] Wang Zheyu, Li Chengling, Huang Wencai, et al. Effectiveness of a pathway-driven eHealth-based integrated care model (PEICM) for community-based hypertension management in China: study protocol for a randomized controlled trial[J/OL]. Trials, 2021, 22(1): 81. [17] Michie S, West R, Finnerty AN, et al. Representation of behaviour change interventions and their evaluation: development of the upper level of the behavior change intervention ontology[J/OL]. Wellcome Open Research, 2020, 5: 123. [18] Sieverink F, Kelders S, Poel M, et al. Opening the black box of electronic health: collecting, analyzing, and interpreting log data[J/OL]. JMIR Research Protocols, 2017, 6(8): e156. [19] Lorencatto F, West R, Christopherson C, et al. Assessing fidelity of delivery of smoking cessation behavioural support in practice[J/OL]. Implementation Science, 2013, 8(1): 40. [20] Yang CH, Maher JP, Conroy DE. Implementation of behavior change techniques in mobile applications for physical activity[J/OL]. American Journal of Preventive Medicine, 2015, 48(4): 452-455. [21] Direito A, Carraca E, Rawstorn J, et al. mHealth technologies to influence physical activity and sedentary behaviors: behavior change techniques, systematic review and meta-analysis of randomized controlled trials[J/OL]. Annals of Behavioral Medicine, 2017, 51(2): 226-239. [22] Kebede MM, Liedtke TP, Möllers T, et al. Characterizing active ingredients of eHealth interventions targeting persons with poorly controlled type 2 diabetes mellitus using the behavior change techniques taxonomy: scoping review[J/OL]. Journal of Medical Internet Research, 2017, 19(10): e7135. [23] Duff OM, Walsh DM, Furlong BA, et al. Behavior change techniques in physical activity eHealth interventions for people with cardiovascular disease: systematic review[J/OL]. Journal of Medical Internet Research, 2017, 19(8): e281.
