To guarantee a systematic and coherent process, this scoping review followed the recommendations of Levac et al [25], which were built on the Arksey and O’Malley [26] framework. The process included the following stages: (1) identifying the research question, (2) identifying relevant studies, (3) selecting studies, (4) charting and collating the data, and (5) summarizing and reporting the results. The findings are reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines [27,28].

The protocol was published [27] and registered under the International Registered Report Identifier (IRRID): PRR1–10.2196/59900 [28] before conducting the full electronic literature search. A search for existing scoping reviews found no studies on the impact of digitalization on physical health, though several focused on its effects on mental health [27]. No changes were made between the published protocol and this scoping review.

We posed the main research question, “How do digital technologies in the workplace affect the physical health of older workers?” Given the wide range of ways in which digital technology can affect an older worker’s physical health (from vision loss to musculoskeletal disorders) and the diversity of workplace digitalization (from working online from home to the use of robotics in a car assembly line), we formulated the following subquestions:

1. What are the most common physical health issues that older workers face as a result of workplace digitalization?

2. Which industries most strongly affect older workers’ physical health as a result of workplace digitalization?

To refine our focus, we applied the population, concepts, and context (PCC) framework [25] (Multimedia Appendix 1 [29,30]). In summary, our review examines studies on older workers aged 50 years and older (Population). Digital technologies (Concept) refer to electronic devices or tools used for data manipulation, storage, and transmission, specifically in work-related activities. The Context focuses on how these technologies impact physical health, excluding nonwork or nondigital applications.

Following the Joanna Briggs Institute Manual for Evidence Synthesis [31] search strategy, we searched for peer-reviewed studies written in English in the following databases: MEDLINE, Cochrane, ProQuest, Web of Science, Scopus, APA PsycInfo, and ERIH PLUS. We used the web-based systematic review platform Covidence (Veritas Health Innovation Ltd) to import the references and remove duplicates. The search terms used are listed in Textbox 1.

A total of 7290 references were imported into Covidence for screening. After removing 461 duplicates, 6638 studies proceeded to title and abstract screening, followed by a full-text review. Through this process, 17 relevant studies addressing the main and secondary research questions were selected [32-48]. Additionally, one more study was added post hoc, as Covidence did not identify it due to the use of “middle-aged” instead of (synonyms for) “older workers” in the title and abstract, despite the sample age range, including individuals aged 35-65 years [9]. Given the lack of a standard definition of “older workers,” we included studies with participants aged 50 years and older, even if younger workers were also part of the sample and analyzed (eg, age group >45 years). Similarly, we included studies across diverse occupational settings, ranging from health care professionals and office workers to farmers and self-employed individuals, as well as studies examining a wide variety of digital technologies. For the purpose of this review, we considered both studies that explicitly examined digital tools (eg, personal computers, smartphones, and specialized apps) and those where technology use was implicit in the work arrangement (eg, telework). This broad approach ensured that potentially relevant evidence was not excluded, though it introduced heterogeneity in populations, contexts, and technologies. A detailed overview of the study characteristics, including design, sample, occupational setting, and type of digital technology examined, is provided in Multimedia Appendix 2 for ease of reference.

All coauthors participated in the selection process, with each study reviewed by at least 2 researchers. Conflicts identified by Covidence regarding study inclusion or exclusion were resolved through discussion or by consulting a third reviewer.

Eligibility was determined based on the PCC framework and additional criteria shown in Textbox 2, while the selection process is synthesized in a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) flowchart. Notably, Covidence allows only one exclusion reason per record during the full-text screening phase. However, many excluded studies met multiple exclusion criteria (eg, lacking both relevant physical health outcomes and age-specific data), which is why only the categories of exclusion—not the number of studies per reason—are reported in the flowchart.

No restrictions were placed on publication year or study location, as the absence of a prior scoping review on this specific topic in a peer-reviewed journal justified including all years, while excluding countries would have required further justification.

From each selected publication in the final Covidence phase, the main outcomes of interest were extracted, including bibliographic information, study designs and aims, population characteristics, the type of digital technology or tools analyzed (concept), the type of physical health addressed (context), and the main findings (Multimedia Appendix 2). These findings were analyzed, evaluated, and discussed following the PRISMA-ScR [49] guidelines.

We assessed study quality using the Mixed Methods Appraisal Tool (MMAT) [50], which evaluates five study design categories: (1) qualitative studies, (2) quantitative randomized controlled trials, (3) quantitative nonrandomized studies, (4) quantitative descriptive studies, and (5) mixed methods studies. The MMAT includes a 2-part checklist: an initial screening with 2 questions to confirm the study’s empirical nature (clarity of research questions and feasibility of addressing them), followed by 5 design-specific criteria guiding the assessment process.

Three reviewers independently appraised each study to minimize bias and ensure reliability. Discrepancies were resolved through discussion. Each study was assessed using 2 initial screening questions (“Yes”=1, “No”=0) and 5 design-specific criteria (“Yes”=1, “No”=0, “Don’t know”=0), evaluating methodology, data collection, relevance of measurements, and coherence between data sources and analysis methods. We subsequently calculated the percentage of “Yes” responses for each study to assess methodological quality, and no studies were excluded based on this assessment. The quality score was calculated by dividing the number of “Yes” responses by the total applicable criteria (2 for screening, 5 for study design) and multiplying by 100. These scores (0%-100%) represent the proportion of MMAT criteria met. We then averaged quality scores across the screening items and each study design category to provide an overview. This quantitative measure contextualizes the reliability and validity of the findings within our review.

All 18 selected studies (Figure 1) stated clear research questions and collected appropriate data to address them (Multimedia Appendix 3). Although not all studies explicitly described their study design, we identified 9 quantitative nonrandomized studies based on the MMAT user guide [50], with an average quality score of 76% (SD 19%) on the MMAT criteria. These included 1 prospective study [32], 3 cohort studies [33-35], 3 cross-sectional studies [9,36,37], 1 quasi-experimental study [38], and 1 retrospective observational study [39]. Furthermore, we identified 4 quantitative descriptive studies (mean score 65%, SD 30%), including 2 prevalence studies [40,41] and 2 survey-based studies [42,43], 2 quantitative randomized controlled trials (mean score 70%, SD 14%) [44,45], 1 qualitative study (mean score 100%) [46], and 2 mixed method studies (mean score 60%, SD 0%) [47,48].

The lower quality of the quantitative descriptive studies was partly due to the lack of reporting on nonresponses in all studies. Similarly, the lower quality of the mixed methods studies stemmed from a lack of integration between qualitative and quantitative findings. For the 2 quantitative randomized controlled trials, the outcome assessors were not blinded, or the blinding process was not clearly reported.

Overall, 4 [9,38,45,46] of the 18 selected studies were published in 2010, and the other 14 studies were published between 2021 and 2024. Around 12 studies used data collected between 2011 and 2023, including 4 studies [34,35,43,47] that explicitly addressed the effect of the COVID-19 pandemic. A total of 6 studies [37,39,41,44-46] did not state the year of data collection.

Regarding the geographic location, 2 studies [42,48] were conducted in Germany, 2 [9,35] in Japan, and 2 [40,47] in Italy, with the latter also analyzing a sample from the Netherlands. The remaining 12 studies were performed in Australia, Canada, China, Denmark, Israel, Latvia, Lebanon, Libya, Norway, Saudi Arabia, the United Kingdom, and the United States. Europe was the most represented region, with 8 studies, followed by 6 in Asia, 2 in North America, 1 in Oceania, and 1 in Africa.

Sample sizes ranged from 91 to 33,087, although 6 studies [36,39,40,43,45,46] did not report participant numbers. Research covered various economic sectors. Around 4 studies [32,36,41,46] focused on health sector–related occupations, including health care workers, home care service workers, radiation technologists, and radiation therapists. Most other studies examined occupations in sectors outside health care—particularly public institutions—or unspecified fields. These included upper-level nonmanual workers (eg, managers and professionals) [35], office, administrative, white collar, and public sector workers [37-40,45], production line employees [38], and computer users [44]. A Lebanese study examined self-employed individuals, freelancers, and temporary workers in any sector [43]. Overall, 1 [9] of 2 studies conducted in Japan focused on employees in electronics-related companies performing generally representative (not industry-specific) jobs, including administration, design, research and development, sales, and manufacturing. In total, 1 study [48] focused on farmers, gardeners, and foresters, while another included a mixed sample of health care and non–health care workers, students, and unemployed individuals [36]. Altogether, 4 studies [33,34,42,47] did not explicitly state respondents’ occupation or economic sector.

Regarding socioeconomic characteristics, age was analyzed differently across studies. A total of 6 studies [33,34,36,37,40,44] presented results for different age categories, while 2 studies [44,45] treated age as a continuous variable, 1 did both [35], and others studied 2 birth cohorts [42]. The remaining 7 studies [32,38,39,43,46-48] did not assess age differences, although they included employed participants aged 50 years and older. Only 3 studies [42,46,47] exclusively analyzed older workers, while all the others included both younger and older workers. Two studies [32,39] did not report gender, and 1 study [9] included both men and women but only analyzed men due to a low female sample size. The rest incorporated both sexes in their analyses. Regarding job position, only 5 studies [35,41,43,46,48] collected such data.

The increasing integration of digital technologies into daily life and work environments has raised the need for researchers to examine their impact on the physical health of older workers. While previous scoping and systematic reviews have predominantly focused on psychosocial outcomes, such as technostress and burnout [27], evidence on physical health consequences has remained fragmented. This scoping review addresses that gap by mapping the physical health impacts of digital technologies among older workers across diverse occupational sectors. Our synthesis shows that digitalization has multifaceted effects on eye health, musculoskeletal health, metabolic and cardiovascular health, and workability, with risks and benefits often varying by age, context, and work design. The integration of digital technologies into the workplace also presents both opportunities and risks. On the one hand, digital tools can automate physically demanding tasks, optimizing work processes and thereby reducing physical strain for older workers [51,52]. However, despite the frequent use of technologies like smartphones, laptops, and tablets, comprehensive studies directly linking digital work environments to physical health outcomes among older workers remain scarce. This highlights critical gaps in the evidence base—including the need for longitudinal designs, sector-specific analyses, and user-centered interventions—that should guide future research. In this way, the review contributes to an expanding body of evidence aiming to ensure that the digital transformation of work supports rather than undermines healthy aging.

This review highlights several key domains in which digital technologies affect physical health outcomes:

Together, these thematic insights suggest that digitalization in later working life is neither uniformly beneficial nor uniformly harmful but rather context-dependent, shaped by technology type, work design, and worker characteristics.

Based on our findings, we emphasize the critical role of employers in mitigating the physical health risks associated with digital work environments. Organizations should proactively implement measures to safeguard the physical well-being of older employees in digitalized work settings. Potential strategies include the following:

Employers who integrate technology with human-centered design principles can create digital workspaces that promote both the health and inclusion of older employees, fostering a sustainable and age-inclusive workforce.

A potential limitation of this scoping review is that, despite an extensive and systematic search across 7 major academic databases, some relevant studies may have been missed. Non-English language publications were excluded due to resource constraints, which may have introduced language bias. Given the rapid pace of digital innovation, newer studies may also have been published after our search was completed. Our analysis reflects only the studies retrieved through our search strategy, with most conducted in Europe and Asia. Therefore, the findings are more applicable to these regions, and future studies from underrepresented parts of the world are needed for a more global understanding. Moreover, cultural and regional workplace differences may influence the applicability of findings. Occupational health frameworks, ergonomic standards, digital literacy, and cultural attitudes toward aging and technology vary across regions, meaning that experiences of digital work in, for example, Norway or Japan may not be directly comparable to contexts with fewer resources or less employer support. These contextual differences highlight the need for future studies to examine workplace cultures and policy environments when assessing the transferability of interventions.

Another limitation concerns the varying definitions of digital technology. Some studies examined explicit tools (eg, personal computers, mobile devices, and specialized apps), while others focused on implicit contexts (eg, telework) where technology use was assumed but not specified. By including both types, the breadth of digitalization in the workplace was captured, but this variability may limit the comparability of findings across studies.

Regarding study design, most intervention-based studies (including 8 of the 9 quantitative nonrandomized, both quantitative randomized controlled trials, and both mixed method studies) were limited in exposure duration, ranging from just 6 weeks to 2.5 years, while the remaining studies were primarily cross-sectional or descriptive.

Our review also highlights broader methodological limitations in the current literature. Many studies rely on cross-sectional designs, restricting the ability to establish causal relationships between technology use and physical health outcomes. A few exceptions point to promising directions; for instance, 1 study [37] used repeated measures and found that both low and high sound levels negatively affected physiological well-being. Such findings suggest that workplace designs addressing sensory environments—for example, providing quiet workspaces for older employees—may represent an important avenue for improving health.

Future studies should therefore emphasize longer-term, longitudinal, and workplace-based intervention designs to better capture the sustained impact of digital technology use on the physical health of older workers.

While our review identifies several ergonomic and digital health programs that may benefit older workers’ physical health [eg, 37,43,44]—demonstrating both the feasibility and potential benefits of workplace-based strategies—the strength of evidence is limited by small samples, heterogeneous designs, and short-term effects. As with all scoping reviews, our goal was to map the existing literature rather than formally evaluate intervention effectiveness. To strengthen our approach, we followed the PRISMA-ScR checklist (Multimedia Appendix 4) and critically appraised all included studies using the MMAT, which allowed us to assess the methodological quality of both quantitative and qualitative evidence and provide a more informed synthesis (Multimedia Appendix 3). Looking ahead, systematic reviews or meta-analyses should apply formal evidence grading frameworks to more rigorously assess the robustness of specific interventions and inform workplace policy.

To the best of our knowledge, this scoping review is the first to provide a comprehensive synthesis of the physical health effects associated with digital technologies in the workplace, offering valuable insights into how digitalization influences the well-being of older workers. The findings highlight a diverse range of physical health implications, spanning eye health, musculoskeletal conditions, metabolic and cardiovascular health, and workplace ergonomics. These results underscore the pressing need for targeted workplace interventions and employer-driven initiatives to ensure a healthier work environment for aging employees.

Although intervention studies remain scarce, existing examples—such as ergonomic learning programs, vision relaxation exercises, and posture improvement interventions—suggest promising avenues. Future research should build on these findings by developing and evaluating evidence-based interventional programs tailored to older workers and diverse workplace contexts, while also conducting longitudinal studies to examine causal relationships between digital technology use and physical health outcomes in greater detail.

Additionally, the design and implementation of digital technologies should adopt an inclusive and adaptive approach, acknowledging age-related changes in sensory, cognitive, and physical functions. Participatory design models—in which older workers actively contribute to the development of digital workplace solutions—will be critical for ensuring usability, acceptance, and sustained engagement.

In conclusion, this review reinforces the necessity of adopting a holistic and integrated approach to safeguarding the physical health of older workers in an increasingly digitalized labor market. By addressing the physical, ergonomic, and psychosocial challenges of modern work environments and leveraging adaptive technologies, it is possible to support healthy aging at work, extend career longevity, and maintain the well-being and productivity of older employees in a sustainable manner.