Ronteltap Amber, Bukman Andrea J, Nagelhout Gera E, Hermans Roel C J, Hosper Karen, Haveman-Nies Annemien, Lupker Remko, Bolman Catherine A W
Knowledge Centre Healthy and Sustainable Living, University of Applied Sciences Utrecht, P.O. box 12011, 3501 AA, Utrecht, The Netherlands.
IVO Research Institute, The Hague, The Netherlands.
BMC Nutr. 2022 Dec 8;8(1):145. doi: 10.1186/s40795-022-00635-3.
Specific approaches are needed to reach and support people with a lower socioeconomic position (SEP) to achieve healthier eating behaviours. There is a growing body of evidence suggesting that digital health tools exhibit potential to address these needs because of its specific features that enable application of various behaviour change techniques (BCTs). The aim of this scoping review is to identify the BCTs that are used in diet-related digital interventions targeted at people with a low SEP, and which of these BCTs coincide with improved eating behaviour. The systematic search was performed in 3 databases, using terms related to e/m-health, diet quality and socioeconomic position. A total of 17 full text papers were included. The average number of BCTs per intervention was 6.9 (ranged 3-15). BCTs from the cluster 'Goals and planning' were applied most often (25x), followed by the clusters 'Shaping knowledge' (18x) and 'Natural consequences' (18x). Other frequently applied BCT clusters were 'Feedback and monitoring' (15x) and 'Comparison of behaviour' (13x). Whereas some BCTs were frequently applied, such as goal setting, others were rarely used, such as social support. Most studies (n = 13) observed a positive effect of the intervention on eating behaviour (e.g. having breakfast) in the low SEP group, but this was not clearly associated with the number or type of applied BCTs. In conclusion, more intervention studies focused on people with a low SEP are needed to draw firm conclusions as to which BCTs are effective in improving their diet quality. Also, further research should investigate combinations of BCTs, the intervention design and context, and the use of multicomponent approaches. We encourage intervention developers and researchers to describe interventions more thoroughly, following the systematics of a behaviour change taxonomy, and to select BCTs knowingly.
需要采取特定方法来接触并支持社会经济地位较低(SEP)的人群,以促使他们养成更健康的饮食行为。越来越多的证据表明,数字健康工具因其具有能够应用各种行为改变技术(BCTs)的特定功能,因而展现出满足这些需求的潜力。本范围综述的目的是确定针对社会经济地位较低人群的饮食相关数字干预措施中所使用的行为改变技术,以及这些行为改变技术中哪些与改善饮食行为相契合。我们在3个数据库中进行了系统检索,使用了与电子/移动健康、饮食质量和社会经济地位相关的术语。共纳入17篇全文论文。每项干预措施中行为改变技术的平均数量为6.9(范围为3 - 15)。“目标与规划”类别的行为改变技术应用最为频繁(25次),其次是“塑造知识”(18次)和“自然结果”(18次)。其他经常应用的行为改变技术类别包括“反馈与监测”(15次)和“行为比较”(13次)。虽然有些行为改变技术经常被应用,如目标设定,但其他一些则很少被使用,如社会支持。大多数研究(n = 13)观察到干预措施对社会经济地位较低组的饮食行为(如吃早餐)有积极影响,但这与所应用的行为改变技术的数量或类型并无明显关联。总之,需要更多针对社会经济地位较低人群的干预研究,以便就哪些行为改变技术能有效改善他们的饮食质量得出确凿结论。此外,进一步的研究应探讨行为改变技术的组合、干预设计与背景,以及多成分方法的使用。我们鼓励干预措施开发者和研究人员按照行为改变分类法的系统性更全面地描述干预措施,并明智地选择行为改变技术。