Evaluation of the Feasibility and Acceptability of Perfect Fit, a Virtual Coach-Based mHealth Intervention for Smoking Cessation and Physical Activity in Adults: Mixed Methods Study.

IF 3.9 Q2 HEALTH CARE SCIENCES & SERVICES
JMIR Human Factors Pub Date : 2026-07-14 DOI:10.2196/83456
Milon H M van Vliet, Eline Meijer, Nele Albers, Kristell M Penfornis, Walter Baccinelli, Bouke L Scheltinga, Roxy A van Eersel, Niels H Chavannes, Anke Versluis
{"title":"Evaluation of the Feasibility and Acceptability of Perfect Fit, a Virtual Coach-Based mHealth Intervention for Smoking Cessation and Physical Activity in Adults: Mixed Methods Study.","authors":"Milon H M van Vliet, Eline Meijer, Nele Albers, Kristell M Penfornis, Walter Baccinelli, Bouke L Scheltinga, Roxy A van Eersel, Niels H Chavannes, Anke Versluis","doi":"10.2196/83456","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Mobile health (mHealth) interventions with virtual coaches offer scalable and potentially cost-effective solutions for health behavior change. However, these interventions commonly present challenges, such as limited personalization and insufficient grounding in evidence-based strategies. Perfect Fit (PF; Perfect Fit consortium), a personalized mHealth intervention with a text-based virtual coach, supports adults in quitting smoking and becoming more physically active. By combining innovative techniques, including sensor technology, end user involvement, and evidence-based strategies, PF aims to address common challenges faced by mHealth interventions, including those with virtual coaches.</p><p><strong>Objective: </strong>The study primarily investigated the feasibility and acceptability of PF. The secondary aim was to explore associations between sociodemographic, smoking-, and physical activity-related characteristics and the feasibility and acceptability outcomes. The third aim was to evaluate the feasibility of conducting the research study.</p><p><strong>Methods: </strong>A single-arm, pre-post, mixed methods study was conducted in the Netherlands with 100 adults who smoked. The intervention lasted approximately 16 weeks. Data were collected at baseline, during the intervention, and postintervention (4 months). Quantitative data included usage data and self-report questionnaires on feasibility, acceptability, and baseline characteristics. Qualitative data were gathered through postintervention semistructured interviews. Analyses included descriptive and inferential analyses, as well as the framework approach for the qualitative data.</p><p><strong>Results: </strong>PF usage varied considerably across participants (n=87). The mean satisfaction rating was 2.79 (SD 0.73; scale range 1-4), and perceived usability had a median score of 67.50 (range 12.50-87.50; scoring range 0-100), indicating OK-to-good usability. The mean virtual coach acceptance rating was -0.27 (SD 1.30; scale range -3 to 3; n=77). Higher PF usage was associated with greater satisfaction, usability, and coach acceptance (all P≤.004). Frequent connection issues with the smartwatch were a disruptive factor. Qualitative findings (n=12) provided in-depth insights into PF's feasibility and acceptability, encompassing both positive and negative experiences. For instance, some participants valued the virtual coach for its anonymity, low-threshold access, and the sense of control it offered, while others preferred a human coach for greater accountability. Suggested improvements included more varied content and enhanced adaptability of the coach to users' input and personal situations. Exploratory analyses suggested that high PF users were older than moderate (P=.01) and low PF users (P=.05). Importantly, PF was perceived as similarly feasible and acceptable across socioeconomic groups (P>.05), aligning with one of the project's goals. Finally, research procedures and recruitment strategies proved feasible.</p><p><strong>Conclusions: </strong>PF shows potential as an accessible and inclusive strategy for multiple health behavior changes, contributing to public health. Findings highlight areas for improvement and can guide the future development of virtual coach interventions.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e83456"},"PeriodicalIF":3.9000,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13367948/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Human Factors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/83456","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Mobile health (mHealth) interventions with virtual coaches offer scalable and potentially cost-effective solutions for health behavior change. However, these interventions commonly present challenges, such as limited personalization and insufficient grounding in evidence-based strategies. Perfect Fit (PF; Perfect Fit consortium), a personalized mHealth intervention with a text-based virtual coach, supports adults in quitting smoking and becoming more physically active. By combining innovative techniques, including sensor technology, end user involvement, and evidence-based strategies, PF aims to address common challenges faced by mHealth interventions, including those with virtual coaches.

Objective: The study primarily investigated the feasibility and acceptability of PF. The secondary aim was to explore associations between sociodemographic, smoking-, and physical activity-related characteristics and the feasibility and acceptability outcomes. The third aim was to evaluate the feasibility of conducting the research study.

Methods: A single-arm, pre-post, mixed methods study was conducted in the Netherlands with 100 adults who smoked. The intervention lasted approximately 16 weeks. Data were collected at baseline, during the intervention, and postintervention (4 months). Quantitative data included usage data and self-report questionnaires on feasibility, acceptability, and baseline characteristics. Qualitative data were gathered through postintervention semistructured interviews. Analyses included descriptive and inferential analyses, as well as the framework approach for the qualitative data.

Results: PF usage varied considerably across participants (n=87). The mean satisfaction rating was 2.79 (SD 0.73; scale range 1-4), and perceived usability had a median score of 67.50 (range 12.50-87.50; scoring range 0-100), indicating OK-to-good usability. The mean virtual coach acceptance rating was -0.27 (SD 1.30; scale range -3 to 3; n=77). Higher PF usage was associated with greater satisfaction, usability, and coach acceptance (all P≤.004). Frequent connection issues with the smartwatch were a disruptive factor. Qualitative findings (n=12) provided in-depth insights into PF's feasibility and acceptability, encompassing both positive and negative experiences. For instance, some participants valued the virtual coach for its anonymity, low-threshold access, and the sense of control it offered, while others preferred a human coach for greater accountability. Suggested improvements included more varied content and enhanced adaptability of the coach to users' input and personal situations. Exploratory analyses suggested that high PF users were older than moderate (P=.01) and low PF users (P=.05). Importantly, PF was perceived as similarly feasible and acceptable across socioeconomic groups (P>.05), aligning with one of the project's goals. Finally, research procedures and recruitment strategies proved feasible.

Conclusions: PF shows potential as an accessible and inclusive strategy for multiple health behavior changes, contributing to public health. Findings highlight areas for improvement and can guide the future development of virtual coach interventions.

评估完美契合的可行性和可接受性,一种基于虚拟教练的移动健康干预成人戒烟和体育活动:混合方法研究。
背景:带有虚拟教练的移动健康(mHealth)干预措施为健康行为改变提供了可扩展且具有潜在成本效益的解决方案。然而,这些干预措施通常存在挑战,例如个性化有限,缺乏基于证据的战略基础。Perfect Fit (PF; Perfect Fit consortium)是一种个性化的移动健康干预,有一个基于文本的虚拟教练,帮助成年人戒烟并变得更活跃。通过结合创新技术,包括传感器技术、终端用户参与和基于证据的战略,PF旨在解决移动医疗干预(包括虚拟教练)面临的共同挑战。目的:本研究主要调查了PF的可行性和可接受性,次要目的是探讨社会人口学、吸烟和体育活动相关特征与可行性和可接受性结果之间的关系。第三个目的是评估进行研究的可行性。方法:在荷兰对100名吸烟的成年人进行了单臂、前后、混合方法研究。干预持续了大约16周。在基线、干预期间和干预后(4个月)收集数据。定量数据包括使用数据和关于可行性、可接受性和基线特征的自我报告问卷。通过干预后半结构化访谈收集定性数据。分析包括描述性和推断性分析,以及定性数据的框架方法。结果:参与者之间PF的使用差异很大(n=87)。平均满意度评分为2.79(标准差0.73,量表范围1-4),感知可用性的中位数得分为67.50(范围12.50-87.50,评分范围0-100),表明可用性从ok到良好。虚拟教练接受度平均为-0.27(标准差1.30;量表范围-3 ~ 3;n=77)。更高的PF使用率与更高的满意度、可用性和教练接受度相关(所有P≤0.004)。智能手表的频繁连接问题是一个破坏性因素。定性研究结果(n=12)提供了深入了解PF的可行性和可接受性,包括积极和消极的经验。例如,一些参与者看重虚拟教练的匿名性、低门槛访问以及它提供的控制感,而另一些人则更喜欢人类教练,因为它更负责任。建议的改进包括更多样化的内容和增强教练对用户输入和个人情况的适应性。探索性分析表明,高PF使用者比中等(P= 0.01)和低PF使用者年龄大(P= 0.05)。重要的是,在社会经济群体中,PF被认为是同样可行和可接受的(P < 0.05),与项目的目标之一一致。最后,研究程序和招聘策略被证明是可行的。结论:PF显示出作为多种卫生行为改变的可获取和包容性战略的潜力,有助于公共卫生。研究结果强调了需要改进的领域,并可以指导虚拟教练干预措施的未来发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
JMIR Human Factors
JMIR Human Factors Medicine-Health Informatics
CiteScore
3.40
自引率
3.70%
发文量
123
审稿时长
12 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书