Open research questions in Technology Use by Older Adults

What the literature leaves open

• • Information systems help in preventing errors and mistakes associated with medications • Information systems help to avoid duplicate tests and examinations Easiness of access to HIE data Proportion of physicians agreeing with easiness of access to radiology results across organisations has remained high and increased in the public sector. Experiences of easy access to laboratory results was also high from the start, but were reduced in all sectors, most in the private sector by 2017. Experiences of easy access to information on medication prescribed in other organisations has been very poor from the 117 Chapter 4THL – Report 7 | 2019 start (only 5% agreeing), but has grown to 15–26% from 2010 to 2017, with the biggest increase in the private sector (Figure 4.3.2).

  The use and perceived benefits of digital health services among Finnish older adults: Survey study · 2026 · DOI

• Fur- thermore, this study primarily focused on transparency in AI recommendation logic, but future research could explore more complex explainability designs in different contexts. One limitation of the present study is that it did not for- mally model more complex relational mechanisms among social satisfaction, human-AI trust, and digital anxiety beyond the primary between-group comparisons. When AI responses appear opaque, users may remain uncertain about the legitimacy of the recommendation and therefore hesitate to rely on it.

  The role of explainable AI social assistants in digital socialization among older adults in China: impacts on social satisfaction, human–AI trust, and digital anxiety · 2026 · DOI

• Despite encouraging results, several limitations still constrain both the scientific validity and real-world adoption of VR interventions for older adults. A pri- mary concern is the prevalence of small sample sizes, which limits statistical power and reduces generalis- ability [32]. Many studies also evaluate interventions lasting only a few weeks, leaving the durability of the gains uncertain.

  Icarus new rising? A narrative review on virtual reality-based motor interventions in older adults · 2026 · DOI

• Despite encouraging outcomes, current research remains early-stage and methodologically inconsistent. Trials vary widely in design, sample size, duration, and outcomes, limiting the generalisability and comparison. Methodological refinement is needed across four domains: standardised assessment protocols to enable comparability; longitudinal studies to assess sustained effects; contextual analyses, especially in low-resource or rural settings; and systematic monitoring of adverse effects, including cybersickness, fatigue, and emotional strain. The long-term viability of VR depends not only on its clinical effectiveness but also on its scalability across healthcare systems. Future studies should address cost-effectiveness, workforce training, and integration into public health infrastructures, particularly where VR could supplement gaps in conventional care [63, 64]. New advances in motion capture and biometric sensing open the door to even more tailored interventions. These technologies can measure posture, gait variability, movement symmetry, and reaction time in three-dimensional space. Additionally, biometric signals like heart rate, skin conductance, or pupillometry can infer emotional state and cognitive load, allowing real-time adjustments in task complexity [43, 71, 72]. Inclusiveness demands interfaces designed for diverse physical and cognitive capacities. Multimodal systems – voice commands, eye tracking, gesture recognition – must be coupled with adaptive pacing and layered feedback, giving users autonomy over their engagement. Just as crucial is evaluating the subjective user experience, including motivation, enjoyment, frustration, and fatigue, which remains underexplored but essential to long-term success. Integrating behavioural science models, such as the Technology Acceptance Model and the Behaviour Change Support System, can enhance both adoption 11 A. Ramalho, P. Duarte-Mendes, R. Paulo, J. Serrano, J. Petrica, Virtual reality motor interventions in older adultsHUMAN MOVEMENTHuman Movement, Vol. 27, No 1, 2026 and adherence [73–76]. These frameworks emphasise ease of use, perceived value, and intuitive design as key predictors of engagement. Effective strategies should include gradual onboarding with low cognitive load, clear feedback loops and adaptive challenges, and social reinforcement such as peer recognition and cooperative tasks. Together, these elements support sustained participation in VR-based physical and cognitive programs. Combining user-centred design with behavioural modelling and mixedmethods evaluation offers a strong foundation for accessible, engaging, and scalable VR for healthy ageing.

  Icarus new rising? A narrative review on virtual reality-based motor interventions in older adults · 2026 · DOI

• to remind users of marketing recommendations” through simplified operations. attributes and potential risks (Martins et al., 2021). The key to age-friendly algorithms is not to create a Third, decision-support functions should be added, dedicated content pool that is easier for older adults such as auxiliary entries for “check source,” “content to immerse in, but to establish a recommendation verified or not,” and “help me judge,” to help older relationship that balances companionship value, users quickly obtain secondary verification support information quality, and behavioral health. when facing difficulties in judgment. 5.5 Improve collaborative care experience by The core of information discernible design is extending supportive systems not to make decisions for older adults, but to enhance Short video platform addiction among older 145 Journal of Global Humanities and Social Sciences Vol. 7 Iss. 2 2026 adults does not entirely occur within the screen; it is to digital well-being. Especially under the platform also closely related to emotional gaps, insufficient logic centered on retention and conversion, older intergenerational communication, and limited social adults, due to their perceptual and cognitive participation in real life. Therefore, relying solely on characteristics, emotional compensation needs, and interface reminders and usage restrictions is limited media literacy, are more susceptible to insufficient to fundamentally alleviate the immersion immersive interactions, continuous recommendations, dilemma. Age-friendly experience design should also and commercial incentive mechanisms, thus sliding expand from single product design to supportive from “able to use” and “frequent use” to service design, forming a digital usage support “uncontrollable use.” system with more care attributes by connecting From a design science perspective, this paper family, community, and platform resources. summarizes the addiction dilemma of older adults on At the family level, with the consent of older short video platforms into four main manifestations: users, platforms can embed authorized assistance easy access but difficult exit, excessive immersion, functions such as night rest mode settings, abnormal insufficient discernment, and feedback dependence. consumption reminders, and high-risk content It argues that behind these manifestations lie both prompts, based on the principle of “assistance rather individual-level changes in abilities and emotional than monitoring.” At the relational level, platforms needs, as well as platform-level inductive can design more content and task mechanisms mechanisms and biased age-friendly design. Current conducive to intergenerational interaction, such as age-friendly transformations of digital products still co-viewing, co-learning, and co-sharing functions, mainly focus on usability optimization at the access turning isolated immersion into opportunities for real level, with insufficient attention to comprehensibility, communication (Gradiški et al., 2023). Meanwhile, at controllability, discernibility, and exitability during a broader service level, platforms should also link usage, leading “convenience” to become a with community organizations, elderly education prerequisite for addiction in some scenarios. institutions, and grassroots service stations to provide Therefore, age-friendly design of short video older adults with support such as media literacy platforms for older users should further shift from improvement, risk identification education, and “access-friendly” to “moderation-friendly, digital behavior counseling.

  From Digital Inclusion to Behavioral Loss of Control: A Study on Age-Friendly Experience Design for the Dilemma of Short Video Platform Addiction Among Older Adults · 2026 · DOI

• “content accessibility” but also “information mechanisms in health governance. discernibility.” On the one hand, platforms should establish First, content source identification should be more moderate recommendation rules in the elderly strengthened through a clearer, unified, and mode: instead of taking “maximizing viewing understandable identification system. For high-risk duration” as the sole sorting criterion, dimensions information involving health, finance, policies, and such as content diversity, emotional balance, and risk elderly care, official certification, professional sensitivity should be appropriately introduced to qualifications, and platform verification status should restrict the continuous push of highly stimulating, be highlighted in the elderly mode, and their inciting, and consumption-inducing content (Eliseo et authority clearly indicated through concise and al., 2020). On the other hand, the interpretability of intuitive visual methods. Second, risk early warning recommendation logic should be improved, with design in key scenarios should be enhanced, with concise explanations of “why this is recommended to more direct prompts and prominent interface me” added at appropriate locations, and users language used for content such as live-stream allowed to select preference adjustment options such shopping, external link jumps, preferential as “see less of this content,” “reduce shopping live promotions, course payments, and health product streams,” and “lower emotional content recommendations to remind users of marketing recommendations” through simplified operations. attributes and potential risks (Martins et al., 2021). The key to age-friendly algorithms is not to create a Third, decision-support functions should be added, dedicated content pool that is easier for older adults such as auxiliary entries for “check source,” “content to immerse in, but to establish a recommendation verified or not,” and “help me judge,” to help older relationship that balances companionship value, users quickly obtain secondary verification support information quality, and behavioral health. when facing difficulties in judgment. 5.5 Improve collaborative care experience by The core of information discernible design is extending supportive systems not to make decisions for older adults, but to enhance Short video platform addiction among older 145 Journal of Global Humanities and Social Sciences Vol. 7 Iss. 2 2026 adults does not entirely occur within the screen; it is to digital well-being. Especially under the platform also closely related to emotional gaps, insufficient logic centered on retention and conversion, older intergenerational communication, and limited social adults, due to their perceptual and cognitive participation in real life.

  From Digital Inclusion to Behavioral Loss of Control: A Study on Age-Friendly Experience Design for the Dilemma of Short Video Platform Addiction Among Older Adults · 2026 · DOI

• logic, continuous playback, content distribution, trapping users in a cycle of incentive structures, risk prompts, and exit support “more accurate recommendations, more viewing.” (Earnshaw et al., 2017).

  From Digital Inclusion to Behavioral Loss of Control: A Study on Age-Friendly Experience Design for the Dilemma of Short Video Platform Addiction Among Older Adults · 2026 · DOI

• maximizing retention in key links such as increasingly enhance the individual matching of recommendation logic, continuous playback, content distribution, trapping users in a cycle of incentive structures, risk prompts, and exit support “more accurate recommendations, more viewing.” (Earnshaw et al., 2017).

  From Digital Inclusion to Behavioral Loss of Control: A Study on Age-Friendly Experience Design for the Dilemma of Short Video Platform Addiction Among Older Adults · 2026 · DOI

• As the present study analysed respondents recruited through online survey panels (except for Romania), the generalisability of the results is limited to older Internet users. They are like- ly to be in better physical condition and on average more skilled and active Internet users. There were few respondents aged 90 and over. A much longer observation period would be needed to show how respondents belonging to the Technology Spread Generation (the youngest generations) use media when they reach the same age as respondents belonging to the Me- chanical Generation (the oldest generation). Another significant limitation of the study re- lates to its measures. While the time spent on digital media included more variation than, for example, simple measures of use vs. non-use, the total time measure used in the analyses was mainly informed by two time measures: time spent watching TV on a computer and time spent reading online. It also included information on only five different digital media activ- ities, leaving out many others that used by older adults (e.g. social networking sites, listen- ing music). In fact, the narrow scope of the media activities studied may not allow for the detection of all heterogeneity in digital media use or its changes over time. Our results suggest that age differences may in some cases be more related to motivations and reasons for using digital media than to actual use. This calls for more in-depth research in the future. In addition, future studies should consider the ethnic and cultural diversity of the older population. Finally, more attention should be paid to the possibility of discovering increasing similarity (convergence) in older adults’ media use as they age. While striving to better recognise the heterogeneity of older people as media users, it should not be forgotten that they may also start to resemble each other more, especially at a very old age, as their phys- ical and cognitive abilities change.

  Does Heterogeneity in Older Adults’ Digital Media Use Increase as They Age? A Longitudinal Cross-Country Analysis · 2026 · DOI

• However, reviews’ findings were frequently mixed and accompanied with cautions that primary evidence under-reported key elements such as theoretical underpinnings, intervention design process, participant demographics, intervention acceptability and usability, participant retention, adverse events, and long-term outcomes.

  Digital Tools to Support Mental Health in Later Life: Scoping Review of Systematic Reviews · 2026 · DOI

• This paper has reviewed research on wearable technologies for emotion recognition and depression monitoring in older adults. The findings confirm the promising potential of smart wearables to enhance independent mental health care through passive, continuous, and personalised emotion tracking. Such technologies offer significant opportunities for early detection and intervention, which are crucial given the underdiagnosis and underreporting of mental health conditions among older populations. However, the available evidence remains limited, with few studies conducting ecologically valid assessments in real-life contexts or involving participants aged 60 and above. Consequently, the conclusions drawn here represent emerging tendencies rather than generalisable outcomes, and further empirical validation is required before these approaches can inform standard practice. At the same time, significant challenges persist regarding usability, ethical acceptability, data privacy, and technological maturity, all of which become more pronounced in older adults who may experience cognitive, physical, and emotional changes that influence how such technologies are adopted and used. A key implication of this review is the need to integrate age-responsive design principles from the earliest stages of development. Many existing solutions adapt general- purpose wearable systems without sufficient attention to age-related cognitive, physical, or sensory considerations. The preliminary design directions outlined in this paper highlight the importance of comfort, unobtrusiveness, passive interaction, adaptive sensing, transparent data control, and participatory development practices. Taken together, these considerations constitute an emerging set of design directions shaped by the early evidence available in this field. They should be viewed as provisional and subject to refinement as more robust empirical work becomes available. Collectively, they point toward a model of inclusive, unobtrusive, and ethically responsible design that moves beyond one-size-fits-all solutions toward context-aware the dignity, that preferences, and limitations of older adults. Their primary purpose is to guide future interdisciplinary research toward wearable technologies better aligned with the needs and lived experiences of this demographic, supporting the development of scalable and sustainable approaches to mental health monitoring that can enhance independence and quality of life in ageing populations. systems respect Future research should prioritise longitudinal, real-world evaluations involving diverse groups of older adults to ensure ecological validity and capture the variability inherent in ageing populations. There is also a need for unobtrusive and hybrid sensing modalities that reduce user signal quality. Open, burden while maintaining representative datasets involving older adults remain scarce and should be developed to support algorithmic benchmarking and improve classification reliability. Advancing this area of research will require collaboration across engineering, psychology, gerontology, and design to ensure that technological development aligns with clinical 11 EAI Endorsed Transactions on Pervasive Health and Technology | Volume 11 | 2025 | Niki Vogka, Modestos Stavrakis relevance, ethical standards, and user experience. Addressing these areas will contribute to wearable systems better suited to the requirements of ageing societies and strengthen the foundations for autonomous mental health support in older adults. [15] Harte R, Glynn L, Rodríguez-Molinero A, Baker PM, Scharf T, Quinlan LR, et al. A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology. JMIR Hum Factors. 2017 Mar 16;4(1):e8.

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• the is respond to changes in physical and cognitive health. Instead, most wearable solutions employed static detection thresholds or general-purpose emotion classifiers derived from younger, healthier populations. This leads to reduced relevance, poor engagement, and limited impact in older users, whose emotional responses may be more subtle or atypical. Finally, user interface design often remains an afterthought. Many systems feature small screens, nonintuitive feedback mechanisms, or rely on smartphone pairing which may not be accessible or desirable for older individuals with visual, motor, or cognitive impairments. Inclusive design principles, such as voice prompts, tactile feedback, and simplified visuals, are rarely implemented but are essential for meaningful interaction and user satisfaction. In summary, designing ethically sound and technically viable wearable systems for emotion recognition in older adults requires a holistic approach that integrates user empowerment, privacy protection, energy efficiency, and personalization. Without these considerations, even the most advanced sensing technologies may fall short in delivering real-world impact for this vulnerable population. 4.4.

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• that erroneously interprets natural restlessness as anxiety, or that fails to detect genuine depressive signals, may erode user trust or lead to inappropriate interventions. These errors are especially problematic in older adults, whose physiological signals may be influenced by comorbidities, medications, or age-related variability, making emotion in younger classification populations. Therefore, adaptive algorithms that learn personalised baselines and take contextual factors into account are crucial for minimizing misclassification.

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• IEEE 8th International Conference on Serious Games and Applications for Health (SeGAH). 2020. p. 1–8. Kim H, Lee S, Lee S, Hong S, Kang H, Kim N. Depression Prediction by Using Ecological Momentary Assessment, Actiwatch Data, and Machine Learning: Observational Study on Older Adults Living Alone. JMIR Mhealth Uhealth. 2019 Oct 16;7(10):e14149. Choi J, Lee S, Kim S, Kim D, Kim H. Depressed Mood Prediction of Elderly People with a Wearable Band. Sensors (Basel). 2022 May 31;22(11). Mishra R, Park C, York MK, Kunik ME, Wung SF, Naik AD, et al. Decrease in Mobility during the COVID-19 Pandemic and Its Association with Increase in Depression among Older Adults: A Longitudinal Remote Mobility Monitoring Using a Wearable Sensor. Sensors (Basel). 2021 Apr 29;21(9). Chen WL, Chen LB, Chang WJ, Tang JJ. An IoT-based elderly behavioral difference warning system. In: 2018 IEEE International Conference on Applied System Invention (ICASI). 2018. p. 308–9. Gutierrez Maestro E, De Almeida TR, Schaffernicht E, Martinez Mozos Ó. Wearable-Based Intelligent Emotion Monitoring in Older Adults during Daily Life Activities. Applied Sciences. 2023 May 3;13(9):5637. Onim MdSH, Kiselica A, Thapliyal H. Emotion Detection in Older Adults Using Physiological Signals from Wearable Sensors. In 2025. p. 990–5. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0- 105017579226&doi=10.1145%2F3716368.3735280&par tnerID=40&md5=7656a11dc3ccf80dd75d46435458fe98 Jiang Z, Lu L, Huang X, Tan C. Design of wearable home health care system with emotion recognition function. In: 2011 International Conference on Electrical and Control Engineering [Internet]. 2011. p. 2995–8. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0- 80955172038&doi=10.1109%2FICECENG.2011.605783 2&partnerID=40&md5=069927456a44b0cb8520f9eb8b9 ec58e Albites-Sanabria J, Palmerini L, Bandinelli S, Chiari L. Can Motor Outcomes Extracted from Wearables Inform on Non-Motor Clinical Outcomes? The Case of Sensor- Derived Turning Information. In: 2025 IEEE International Conference on Digital Health (ICDH). 2025. p. 175–80. Siddiqui S, Khan AA, Nait-Abdesselam F, Dey I. Anxiety and Depression Management For Elderly Using Internet of Things and Symphonic Melodies. In: ICC 2021 - IEEE International Conference on Communications. 2021. p. 1– 6. Ma Y, Yin K. EMO-Care: Emotional Interaction System Based on Multimodal Fusion and Edge Intelligence for Emotional Care. In: 2024 4th International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI). 2024. p. 32–5. Suzuki K, Iguchi T, Nakagawa Y, Sugaya M. A multimodal interaction robot based on emotion estimation method using physiological signals applied for elderly*. In: 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). 2023. p. 2051–7. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to Meta‐Analysis [Internet]. 1st ed.

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• should systems Support passive operation with minimal user interaction Given that many older users experience reduced dexterity, memory decline, or limited familiarity with digital interfaces, function autonomously, requiring little to no manual input. Passive data collection (e.g., continuous heart rate or skin conductance monitoring) is preferable to methods that require selfreporting or smartphone-based interaction. Automatic syncing, long battery life, and simple charging mechanisms are essential for maintaining usability across a range of physical and cognitive capacities.

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• illness. Subtle form factors, such as wristbands resembling ordinary watches, can help normalise technology and reduce these concerns. In addition, the reviewed literature indicated that user engagement during design and testing phases was minimal. Most systems were developed without substantial input from older users, resulting in features and interfaces poorly suited to their specific needs. This top-down design approach creates a disconnect between engineering intent and practical usability. Participatory design and co-creation, where older adults are involved in iterative feedback cycles, can bridge this gap and lead to more inclusive solutions. In this context, usability extends beyond ergonomics and interface design, encompassing emotional comfort, trust, autonomy, and a sense of empowerment. Older users who feel confused, surveilled, or disregarded by a technology are unlikely to incorporate it into their lives, irrespective of its potential benefits. Subtle, low-effort interactions, also known as micro-interactions, can significantly influence engagement and adherence, as for instance is demonstrated in studies related to smart packaging and medication monitoring systems. Equally important in the design of medical wearable systems is the way these technologies interact with users’ attention and privacy. Devices that require constant monitoring or interrupt users at inappropriate times risk causing frustration, cognitive overload (fatigue), and eventual device abandonment. This issue is especially acute for older adults, for whom usability and acceptance depends on solutions that respect their routines, pace, and cognitive preferences. Research in e-health highlights the necessity of temporal sensitivity in the design of medical wearables which should support rather than disrupt daily life of their users. Researchers emphasise that the adoption of assistive technologies among older populations is closely linked to their perceived usability and the extent to which interaction aligns with users’ needs for privacy, autonomy, and unobtrusive assistance. If these systems are perceived as invasive or too demanding, older users may reject them, regardless of their potential health benefits or general clinical value. Another important design related factor with usability and acceptance is feedback transparency. Older adults often seek reassurance that the device is functioning correctly, without being overwhelmed by excessive data or unclear alerts. Offering layered feedback such as simple confirmation signals (e.g., a gentle vibration or soft LED) to more detailed insights when explicitly requested, can improve the diverse trust and better accommodate cognitive capacities within this group of people. 4.2.

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• "Selection", 1 to 2 in "Comparability", and 2 to 3 in "Outcome" and c) Low quality: 0 to 1 star in "Selection", and 0 stars in "Comparability" or "Outcome" [42]. The quality classification enables a clearer understanding of the reliability of the reviewed data and an estimation of potential bias [43].

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• usability, experience and design implications in elderly populations [38,39]. Identification of new studies via databases and registers (inertial sensors, technologies These studies either involved older adult participants or were explicitly designed for ageing-related use cases, utilised wearable photoplethysmography, electrodermal activity, skin temperature, actigraphy etc.) for emotion or mental health monitoring, and provided sufficient empirical quantitative data (e.g., accuracy rates, correlation coefficients, or statistical associations) suitable for synthesis. Collectively they demonstrated the feasibility of extracting clinically meaningful indicators of depressive symptoms, emotional states, and psychological well-being. A number of studies provided statistically robust associations between wearable-derived metrics and validated mental health scales, such as the correlations reported by [31,36] with CES-D scores. Others focused on machine learning–based emotion or depression classification using physiological signals, as seen in [29,30,33,34], each reporting quantifiable performance metrics such as F1-scores, recall rates, accuracy, or R² values. Additional contributions included early-stage or domain-specific implementations, such as the emotion recognition prototype presented by, the therapeutic IoT-integrated system by, and the robotassisted emotional monitoring framework developed by. Together, these studies form a coherent evidence base illustrating and developmental constraints of current wearable systems for psychological and emotional assessment in ageing populations. technological potential both the Although the number may appear modest when compared with larger reviews, it is consistent with the specialised and interdisciplinary nature of the field, which spans wearable sensing, affective computing, and mental-health monitoring in ageing populations. Few publications meet all these criteria simultaneously, and disciplinary fragmentation - across engineering, psychology, and geriatric medicine - reduces the likelihood of retrieving all relevant studies, even when multiple databases and Heal-Link repositories are used. Within this context, the inclusion of eleven studies - including nine with quantitative data - constitutes an appropriate evidence base for a field still in an early phase of development. The selected studies provided adequate quantitative information on sensor data, user outcomes, or statistical associations to enable quantitative synthesis. Nevertheless, the present quantitative synthesis is framed as exploratory. Its purpose is to identify initial trends and assess the heterogeneous synthesis methodologies, complementing the broader qualitative analysis. The number of eligible studies also highlights the need for more rigorous, large-scale research and greater methodological standardisation in this evolving field. potential across for The overall process of identification, screening, eligibility assessment and inclusion is summarised in the PRISMA 2020 flow diagram (Figure 1).

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• neglect factors crucial to older adults, such as cognitive load, sensory decline, and ease of use [15–17]. wearable emotion recognition technologies for the mental health monitoring of older adults. Some approaches rely on contactless methods, including voice modulation analysis or infrared thermography, to reduce user burden. However, these systems are still in early development. Comprehensive reviews have pointed to the need for integrated systems that prioritise user autonomy, ethical transparency, and adaptability to individual preferences.

  Smart Wearable Technologies for Autonomous Mental Health Monitoring in the Elderly: A Systematic Review and Design Perspectives · 2026 · DOI

• Our search strategy may have missed some HCI papers on older adults’ interactions with connected technologies when the title or abstract does not explicitly mention “IoT” or SPAU, since we required these terms for reproducibility across databases. This re- view also draws on 44 studies published between 2004 and 2024 and excludes non-English publications. Combined with the scarcity of reproducible experiments and detailed accessibility evaluations, limit cross-study comparison and quantitative meta-analysis. To address these gaps, we are collaborating with gerontology and IoT security institutions to conduct empirical studies involving real-world deployments, adversarial testing, and longitudinal mon- itoring, and we will use these to validate and refine the SPAU IoT framework and threat model in operational settings.

  SoK: Reviewing Two Decades of Security, Privacy, Accessibility, and Usability Studies on Internet of Things for Older Adults · 2026 · DOI

• Several limitations should be acknowledged when interpreting the findings. First, the study operationalizes age groups through user-selected age-based flairs. It is important to acknowledge that these labels reflect a voluntary self-categorization within a digital space, rather than objectively verified demographic membership. This choice may also bias the sample toward Reddit users who are both more digitally confident and more comfortable identifying publicly with their age. These individuals likely represent a distinctive subset of older adults. Findings should therefore be understood as characterizing active, self-identifying older Reddit users, who are a distinctive and probably more digitally agentic subset rather than older adults in general. A second and more fundamental limitation is the cross-sectional design, which makes it impossible to disentangle life course effects from cohort effects. The differences observed between the 50s and the 60s and 70s groups could reflect either the distinct life-stage position of each group, the different generational cultures that shaped them, or their interaction. This study treats the two explanatory frameworks as complementary rather than competing but cannot empirically adjudicate their relative contributions. Doing so would require a longitudinal or cohort-sequential design capable of tracking how the same cohort’s expressive patterns shift as it moves through subsequent life stages, and this is a methodologically demanding yet theoretically essential direction for future research.

  Self-Identified Age Cohorts and Personal Experience Sharing in Pseudonymous Online Spaces: Natural Language Processing Analysis of Reddit · 2026 · DOI

• While our analyses used appropriate statistical methods and showed that educational attainment mediated 27.8% of the total effect of digital engagement on depression, several limitations warrant consideration. First, depression was assessed via self-reported frequency of depressive feelings, rather than standardized clinical diagnostic scales, which may affect measurement precision. Second, the cross-sectional nature of the data precludes definitive causal inferences; we can establish associations but not causality. Future longitudinal research is needed to explore these dynamic relationships and strengthen causal interpretations. Third, potentially influential covariates, such as baseline health status, functional limitations, and objective measures of social support, were not included in the models. These factors could significantly confound the observed relationships. Fourth, regarding the mediation model, while we theorize education as an enabling resource (digital engagement → education → depression), we acknowledge that alternative causal orderings (e.g., educa- tion → digital engagement → depression) are plausible given the life- course nature of education. Our cross-sectional design cannot definitively disentangle these pathways. Future longitudinal studies should test com- peting mediation models to establish temporal precedence and strengthen causal inference. Fifth, the measurement of digital engagement was restricted to a binary (yes/no) indicator of any internet use in the past year. This operationalization does not distinguish between different types, fre- quencies, or qualities of online engagement, which may have distinct relationships with mental health. Future studies would benefit from incorporating multidimensional measures of digital behavior to better disentangle these associations. Experimental or quasi-experimental designs (e.g., digital literacy intervention trials) would provide deeper insights into the complex interplay among specific digital engagement patterns, educational attainment, and mental health outcomes.

  Urban–rural disparities in education’s mediating role between digital engagement and depression among Chinese older adults · 2026 · DOI

• The paper does not specify verification protocols for volunteer identity authentication or background screening mechanisms, leaving unclear how the platform ensures trustworthiness of volunteers before they gain access to senior citizens' personal information and home addresses.

  CAREBRIDGE: Senior Citizen Help Platform · 2026 · DOI

• The platform architecture does not address scalability testing with varying numbers of concurrent users; there is no analysis of system performance degradation when handling simultaneous help requests from multiple senior citizens across different geographic regions.

  CAREBRIDGE: Senior Citizen Help Platform · 2026 · DOI

• The user-friendly interface design for elderly users is mentioned but not evaluated against specific usability standards; the paper lacks testing results using standardized geriatric usability assessment tools beyond the SUS scale referenced in citations.

  CAREBRIDGE: Senior Citizen Help Platform · 2026 · DOI

Most-cited papers in Technology Use by Older Adults

• Older adults' use of information and communications technology in everyday life · Ageing and Society · 2003 · 431 citations
• Recovering from the COVID-19 Pandemic: A Focus on Older Adults · Journal of Aging & Social Policy · 2020 · 324 citations
• Active Aging and Public Health: Evidence, Implications, and Opportunities · Annual Review of Public Health · 2021 · 283 citations
• When Going Digital Becomes a Necessity: Ensuring Older Adults’ Needs for Information, Services, and Social Inclusion During COVID-19 · Journal of Aging & Social Policy · 2020 · 283 citations
• Resolving inconsistencies in trends in old-age disability: Report from a technical working group · Demography · 2004 · 259 citations
• Elderly Forgotten? Digital Exclusion in the Information Age and the Rising Grey Digital Divide · INQUIRY The Journal of Health Care Organization Provision and Financing · 2022 · 228 citations
• Computer-Mediated Social Support, Older Adults, and Coping · Journal of Communication · 2000 · 218 citations
• Telehealth Use Among Older Adults During COVID-19: Associations With Sociodemographic and Health Characteristics, Technology Device Ownership, and Technology Learning · Journal of Applied Gerontology · 2021 · 191 citations
• Older People’s Use of Digital Technology During the COVID-19 Pandemic · Bulletin of Science Technology & Society · 2022 · 190 citations
• “These devices have not been made for older people's needs” – Older adults' perceptions of digital technologies in Finland and Ireland · Technology in Society · 2020 · 188 citations

Most recent work

• Digital Exclusion Among Older Adults: A Concept Analysis Based on Scoping Review · Journal of Applied Gerontology · 2026
• Who gains more? subjective socio-economic status in the impact of internet use on older adults’ depression · Current Psychology · 2026
• Family support for digital divide among older people: Contact and proximity · Educational Gerontology · 2026
• From Awareness to Participation: Diffusion of Innovation and Engagement of Older People in Barrier-Free Communities in Zhuhai, China · Journal of Aging & Social Policy · 2026
• Digital Inclusion Among Community Older Adults in Singapore: Measuring Digital Skills and Health Consequences · Journal of Aging and Environment · 2026
• The use and perceived benefits of digital health services among Finnish older adults: Survey study · Health Informatics Journal · 2026
• A digital transformation and consumption patterns of the “New older adults” in China: a systematic review of technological adaptation and learning mechanisms · Frontiers in Public Health · 2026
• CAREBRIDGE: Senior Citizen Help Platform · International Journal of Advanced Research in Science Communication and Technology · 2026
• Urban–rural disparities in education’s mediating role between digital engagement and depression among Chinese older adults · Frontiers in Public Health · 2026
• The Effect of Internet Use on Older Adults’ Executive Function: The Chain Mediation Effect of Social Participation and Loneliness · Healthcare · 2026

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