Basu Sanjay, Simerman Ariela, Hoffman Ari
Department of Medicine, University of California, San Francisco, CA.
Clinical Product Development, Waymark Care, San Francisco, CA.
Mayo Clin Proc Digit Health. 2025 Aug 6;3(3):100256. doi: 10.1016/j.mcpdig.2025.100256. eCollection 2025 Sep.
To systematically examine how digital health startups define and operationalize engagement in the post- coronavirus disease environment (2020-2025).
Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines adapted for web-based literature, we systematically reviewed publicly available information from digital health startups founded or significantly operating between 2020-2025. We extracted engagement definitions from company websites, white papers, blog posts, and press releases. Definitions were coded by type (explicit, implicit, or nondefinition) and dimensional focus (behavioral, cognitive, affective, and social). Inter-rater reliability was assessed using Cohen's κ (κ=0.82). We conducted this systematic review from April 20, 2025, to May 21, 2025.
We analyzed 64 engagement definitions from 30 digital health startups. Only 18.8% (n=12) were explicit definitions with clear measurement criteria, whereas 45.3% (n=29) were implicit definitions and 35.9% (n=23) were nondefinitions that mentioned engagement without defining it. The behavioral dimension dominated (64.1%, n=41), followed by social (28.1%, n=18), cognitive (21.9%, n=14), and affective dimensions (17.2%, n=11). Statistical analysis revealed significant associations between definition type and dimensional focus (<.05). Based on our findings, we developed a taxonomy of engagement definitions and a 5-level engagement definition maturity model.
Digital health startups predominantly use implicit or undefined engagement concepts with a strong behavioral focus. The proposed taxonomy and maturity model provide frameworks for standardizing engagement definitions across the digital health ecosystem, potentially improving measurement consistency, facilitating more meaningful comparisons between solutions, and establishing a baseline for evaluating effectiveness.
系统研究数字健康初创公司如何在新冠疫情后环境（2020 - 2025年）中定义并实施参与度。
遵循适用于基于网络文献的系统评价和Meta分析的首选报告项目指南，我们系统回顾了2020年至2025年期间成立或显著运营的数字健康初创公司的公开可用信息。我们从公司网站、白皮书、博客文章和新闻稿中提取参与度定义。定义按类型（明确、隐含或未定义）和维度重点（行为、认知、情感和社会）进行编码。使用Cohen's κ（κ = 0.82）评估评分者间信度。我们于2025年4月20日至2025年5月21日进行了这项系统评价。
我们分析了30家数字健康初创公司的64个参与度定义。只有18.8%（n = 12）是具有明确测量标准的明确定义，而45.3%（n = 29）是隐含定义，35.9%（n = 23）是未定义，即提及了参与度但未对其进行定义。行为维度占主导（64.1%，n = 41），其次是社会维度（28.1%，n = 18）、认知维度（21.9%，n = 14）和情感维度（17.2%，n = 11）。统计分析显示定义类型与维度重点之间存在显著关联（<.05）。基于我们的研究结果，我们开发了一个参与度定义分类法和一个5级参与度定义成熟度模型。
数字健康初创公司主要使用隐含或未定义的参与度概念，且重点在于行为方面。所提出的分类法和成熟度模型为跨数字健康生态系统规范参与度定义提供了框架，可能会提高测量的一致性，促进不同解决方案之间更有意义的比较，并为评估有效性建立基线。
