A user-centered chatbot to identify and interconnect individual, social and environmental risk factors related to overweight and obesity.

IF 2.5 4区医学 Q2 HEALTH CARE SCIENCES & SERVICES Informatics for Health & Social Care Pub Date : 2022-01-02 Epub Date: 2021-05-25 DOI:10.1080/17538157.2021.1923501

Sabina Asensio-Cuesta, Vicent Blanes-Selva, Alberto Conejero, Manuel Portolés, Miguel García-Gómez

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引用次数: 1

Abstract

The objective of this study was to assess the feasibility of using a user-centered chatbotfor collecting linked data to study overweight and obesity causes ina target population. In total 980 people participated in the feasibility study organized in three studies: (1) within a group of university students (88 participants), (2) in a small town (422 participants), and (3) within a university community (470 participants). We gathered self-reported data through the Wakamola chatbot regarding participants diet, physical activity, social network, living area, obesity-associated diseases, and sociodemographic data. For each study, we calculated the mean Body Mass Index (BMI) and number of people in each BMI level. Also, we defined and calculated scores (1-100 scale) regarding global health, BMI, alimentation, physical activity and social network. Moreover, we graphically represented obesity risk for living areas and the social network with nodes colored by BMI. Students group results: Mean BMI 21.37 (SD 2.57) (normal weight), 8 people underweight, 5 overweight, 0 obesity, global health status 78.21, alimentation 63.64, physical activity 65.08 and social 26.54, 3 areas with mean BMI level of obesity, 17 with overweight level. Small town´s study results: Mean BMI 25.66 (SD 4.29) (overweight), 2 people underweight, 63 overweight, 26 obesity, global health status 69.42, alimentation 64.60, physical activity 60.61 and social 1.14, 1 area with mean BMI in normal weight; University´s study results: Mean BMI 23.63 (SD 3.7) (normal weight), 22 people underweight, 86 overweight, 28 obesity, global health status 81.03, alimentation 81.84, physical activity 70.01 and social 1.47, 3 areas in obesity level, 19 in overweight level. Wakamola is a health care chatbot useful to collect relevant data from populations in the risk of overweight and obesity. Besides, the chatbot provides individual self-assessment of BMI and general status regarding the style of living. Moreover, Wakamola connects users in a social network to help the study of O&O´s causes from an individual, social and socio-economic perspective.

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一个以用户为中心的聊天机器人，用于识别和连接与超重和肥胖相关的个人、社会和环境风险因素。

本研究的目的是评估使用以用户为中心的聊天机器人收集相关数据以研究目标人群中超重和肥胖原因的可行性。共有980人参加了可行性研究，分为三个研究:(1)在一组大学生中(88名参与者)，(2)在一个小镇中(422名参与者)，(3)在一个大学社区中(470名参与者)。我们通过Wakamola聊天机器人收集了参与者关于饮食、身体活动、社交网络、居住区域、肥胖相关疾病和社会人口数据的自我报告数据。对于每项研究，我们计算了平均身体质量指数(BMI)和每个BMI水平的人数。此外，我们定义并计算了全球健康、BMI、营养、身体活动和社交网络的得分(1-100分)。此外，我们用图形表示了生活区域和社会网络的肥胖风险，节点用BMI着色。学生组结果:平均BMI 21.37 (SD 2.57)(体重正常)，体重不足8人，超重5人，肥胖0人，整体健康状况78.21，营养63.64，身体活动65.08，社交26.54，平均BMI水平肥胖3个地区，超重17个地区。小城镇研究结果:平均BMI 25.66 (SD 4.29)(超重)，体重不足2人，超重63人，肥胖26人，全球健康状况69.42，营养64.60，身体活动60.61，社会1.14,1个地区平均BMI体重正常;大学研究结果:平均BMI 23.63 (SD 3.7)(体重正常)，体重不足22人，超重86人，肥胖28人，全球健康状况81.03，营养81.84，体育活动70.01，社会1.47，肥胖3个地区，超重19个地区。Wakamola是一个医疗保健聊天机器人，用于收集超重和肥胖风险人群的相关数据。此外，聊天机器人还提供个人的BMI自我评估和关于生活方式的一般状况。此外，Wakamola将社交网络中的用户联系起来，以帮助从个人，社会和社会经济角度研究O&O的原因。

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来源期刊

Informatics for Health & Social Care 医学-卫生保健

CiteScore

6.10

自引率

4.20%

发文量

审稿时长

>12 weeks

期刊介绍： Informatics for Health & Social Care promotes evidence-based informatics as applied to the domain of health and social care. It showcases informatics research and practice within the many and diverse contexts of care; it takes personal information, both its direct and indirect use, as its central focus. The scope of the Journal is broad, encompassing both the properties of care information and the life-cycle of associated information systems. Consideration of the properties of care information will necessarily include the data itself, its representation, structure, and associated processes, as well as the context of its use, highlighting the related communication, computational, cognitive, social and ethical aspects. Consideration of the life-cycle of care information systems includes full range from requirements, specifications, theoretical models and conceptual design through to sustainable implementations, and the valuation of impacts. Empirical evidence experiences related to implementation are particularly welcome. Informatics in Health & Social Care seeks to consolidate and add to the core knowledge within the disciplines of Health and Social Care Informatics. The Journal therefore welcomes scientific papers, case studies and literature reviews. Examples of novel approaches are particularly welcome. Articles might, for example, show how care data is collected and transformed into useful and usable information, how informatics research is translated into practice, how specific results can be generalised, or perhaps provide case studies that facilitate learning from experience.