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Background <p>Digital health technologies are increasingly used to address healthcare challenges among older adults, yet concerns exist about data absenteeism—the underrepresentation of socioeconomically disadvantaged groups. This systematic review examines how data absenteeism affects digital health technology interventions for older adults, focusing on three research questions: (a) participant profiles; (b) implementation characteristics; and (c) metrics for assessing intervention effectiveness.</p> Methods <p>Following PRISMA guidelines, we searched ten databases (MEDLINE, Embase, CINAHL, PsycINFO, SPORTDiscus, WOS, IEEE Xplore, Scopus, PubMed, and ScienceDirect) through September 30, 2022. Eligible studies included peer-reviewed articles in English that evaluated health outcomes of mobile applications, wearables, or exercise games (exergames) interventions. Two independent researchers conducted screening and data extraction, with disputes resolved by a third researcher.</p> Results <p>Of 14,661 identified studies, 58 met inclusion criteria. Key findings revealed: (a) limited reporting of participant demographics, with only 32.8% reporting education levels, 3.4% reporting income, and 17.2% reporting racial composition; (b) predominance of exergames (75.9%) over health apps (10.3%) and wearables (10.3%); (c) concentration of studies in technologically advanced regions, with 70.7% having sample sizes under 50 participants; and (d) diverse outcome measurements including physiological metrics (67.2%), mental and emotional well-being metrics (51.7%), activity-lifestyle metrics (31.0%), and technology acceptability metrics (22.4%).</p> Conclusions <p>This review examines patterns in digital health interventions for older adults, revealing limitations in demographic reporting, geographical concentration of studies, and varied approaches to outcome measurement. Future research should address these findings through: (a) enhanced demographic data collection, with particular attention to socioeconomic factors; (b) increased implementation across diverse geographical and cultural contexts; and (c) integration of physical, mental, and social health measurements. These improvements would support the development of digital health solutions that effectively serve diverse older adult populations.</p>

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Data absenteeism in digital health technology research for older adults: a systematic review

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月6日

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  • Huanyu Bao,
  • Yi Jie Wong,
  • Navrag B. Singh,
  • Sai G. S. Pai,
  • Ben Tan Phat Pham,
  • Yin-Leng Theng,
  • Edmund W. J. Lee

摘要

Background

Digital health technologies are increasingly used to address healthcare challenges among older adults, yet concerns exist about data absenteeism—the underrepresentation of socioeconomically disadvantaged groups. This systematic review examines how data absenteeism affects digital health technology interventions for older adults, focusing on three research questions: (a) participant profiles; (b) implementation characteristics; and (c) metrics for assessing intervention effectiveness.

Methods

Following PRISMA guidelines, we searched ten databases (MEDLINE, Embase, CINAHL, PsycINFO, SPORTDiscus, WOS, IEEE Xplore, Scopus, PubMed, and ScienceDirect) through September 30, 2022. Eligible studies included peer-reviewed articles in English that evaluated health outcomes of mobile applications, wearables, or exercise games (exergames) interventions. Two independent researchers conducted screening and data extraction, with disputes resolved by a third researcher.

Results

Of 14,661 identified studies, 58 met inclusion criteria. Key findings revealed: (a) limited reporting of participant demographics, with only 32.8% reporting education levels, 3.4% reporting income, and 17.2% reporting racial composition; (b) predominance of exergames (75.9%) over health apps (10.3%) and wearables (10.3%); (c) concentration of studies in technologically advanced regions, with 70.7% having sample sizes under 50 participants; and (d) diverse outcome measurements including physiological metrics (67.2%), mental and emotional well-being metrics (51.7%), activity-lifestyle metrics (31.0%), and technology acceptability metrics (22.4%).

Conclusions

This review examines patterns in digital health interventions for older adults, revealing limitations in demographic reporting, geographical concentration of studies, and varied approaches to outcome measurement. Future research should address these findings through: (a) enhanced demographic data collection, with particular attention to socioeconomic factors; (b) increased implementation across diverse geographical and cultural contexts; and (c) integration of physical, mental, and social health measurements. These improvements would support the development of digital health solutions that effectively serve diverse older adult populations.