Exploring factors influencing the adoption and use of digital health technology for HIV management among older adults living with HIV: A qualitative study

Abstract

Background

The intersection of aging and HIV presents unique challenges in healthcare, with older adults living with HIV experiencing compounded health issues. Advances in technology, including digital health tools, offer opportunities to improve self-management and care delivery. However, older adults living with HIV face barriers in adopting these digital health tools due to socio-cultural factors and technological challenges.

Objective

This study explores the factors influencing the adoption of digital health technologies for HIV management among older adults, aiming to identify strategies to improve accessibility and effectiveness of these tools.

Methods

A qualitative descriptive study using interviews was conducted within a larger research program on virtual care for socio-culturally diverse older adults. Data were analyzed using the Theoretical Domains Framework (TDF) to identify barriers and facilitators to technology adoption.

Results

Fourteen older adults living with HIV (mean age 58.7, SD 6.5) participated in the study. Key themes included self-management, perceived usefulness, and ease of use, with older adults living with HIV using technology for health tracking and symptom management. Barriers such as affordability, linguistic diversity, and complex user interfaces were identified, along with concerns about privacy and stigma. Facilitators included peer influence, perceived utility of tools, and ease of navigation. Participants emphasized the importance of transparency in consent processes and the need for technology to accommodate cognitive and sensory impairments.

Conclusion

This study highlights the need for tailored digital health interventions that address the unique challenges of older adults living with HIV. Future technologies should prioritize user-friendly interfaces, accessibility, and clear consent processes to enhance adoption and engagement.

Keywords

Aging HIV older adults digital health tools technology adoption self-management

Introduction

The introduction of highly active antiretroviral therapies has significantly prolonged survival for individuals living with HIV, enabling individuals to reach “old age.”¹ Consequently, older adults will acquire HIV infection and the number of long-term HIV/AIDS survivors will grow.¹ The intersection of aging and HIV presents unique challenges for geriatric care, necessitating innovative and culturally sensitive approaches to healthcare delivery. HIV infection is associated with accelerated aging processes, leading to earlier onset of age-related conditions and geriatric syndromes such as frailty and cognitive impairment.² Older adults living with HIV often face compounded health and social issues,^2–4 including cardiovascular disease, diabetes, osteoporosis, and some cancers.^5,6 For example older adults living with HIV are up to five times more likely to experience depression⁷ and twice as likely to develop cognitive decline.⁸ They also report poorer overall health status and higher hospitalization rates than both younger people living with HIV and HIV-negative older adults.^9,10 Despite these growing complexities, older adults living with HIV, particularly those from vulnerable, low-income, and socially marginalized populations, remain understudied in aging and health research.¹¹ This is concerning given that social determinants of health such as poverty, housing insecurity, and systemic discrimination may exacerbate health disparities in this population.^12–15 This dual experience of managing HIV and aging is compounded by socio-cultural factors such as stigma, discrimination, and social isolation, which can significantly impact their health outcomes and quality of life.^3,16 There is a critical gap in evidence related to how aging intersects with HIV within these high-risk groups, limiting the development of inclusive and responsive models of care.¹⁷

Advances in technology, particularly following the COVID-19 pandemic, have significantly transformed the management of chronic health conditions, offering potential benefits in improving access to care, monitoring, and treatment adherence.^18,19 In the United States, about 75% of adults aged 65 and older report using the internet, while roughly 61% own a smartphone, and 44% own a tablet.²⁰ Existing research has focused on adoption and acceptability of digital health interventions for HIV disease management in younger adult populations.²¹ For individuals living with HIV, health technological tools (e.g., virtual care, applications) provide opportunities to enhance self-management, facilitate communication with healthcare providers, and track health outcomes.^21–23 However, older adults living with HIV face unique challenges that may impact their adoption and use of these technologies.^21,23 Both persons living with HIV and healthcare providers feel that that digital health interventions often feel “impersonal” and “lacking in empathy.”²¹ Moreover, the complex health needs of aging with HIV may hinder engagement with digital health tools.²⁴ Additionally, older adults may experience technological barriers such as low digital literacy (e.g., difficulty using digital technologies, platforms, and tools effectively²⁵), accessibility constraints, lack of access to devices, and concerns about privacy and confidentiality.^26,27

Understanding how older adults interact with and adopt health technologies requires a strong theoretical foundation. The Theoretical Domains Framework (TDF)²⁸ and the Senior Technology Acceptance Model (STAM)²⁹ are two widely used frameworks that offer insight into behavior change and technology use in aging populations. The TDF consolidates constructs from across multiple behavior change theories and considers domains such as knowledge, beliefs about capabilities, environmental context, and social influences.²⁸ STAM, by contrast, is tailored to the aging context and extends traditional technology acceptance models to account for factors such as cognitive decline, health status, perceived usefulness, and social support).²⁹ These frameworks are increasingly used to identify barriers and facilitators to health technology adoption among older adults and help inform intervention design.

There is limited research exploring the factors that influence health technology adoption and use among older adults living with HIV. Human–Computer Interaction researchers have shown that older adults often struggle with small text, complex menus, and lack of clear feedback in interfaces, and that they benefit from features like multimodal interaction (e.g., voice plus touch), error-tolerant design, and just-in-time training.^30,31 These insights into usability, accessibility, and user-centered design can inform how we think about barriers and facilitators for health technologies in our population of older adults living with HIV. By building on both HCI best practices and our HIV-specific findings, we can design digital health tools that are both usable and acceptable for this especially vulnerable group. For this study, we define health technology as the use of technologies, including digital tools, devices, and systems, to improve or manage health and healthcare delivery.³² This can encompass a wide range of innovations, from wearable devices (such as accelerometers or glucose monitors) to telehealth platforms, electronic health records, health apps, and artificial intelligence systems.^32,33

Understanding these factors is critical to ensuring that health technologies are inclusive and equitable, meeting the needs of older adults living with HIV. This qualitative study aims to explore the factors influencing the adoption of technology for HIV management among older adults, with the goal of informing the development of strategies to improve the accessibility and effectiveness of these tools. By examining the lived experiences of older adults living with HIV, this study will provide valuable insights into how digital health technologies can be optimized to support HIV management and improve health outcomes in this vulnerable population.

Methods

Study design

We conducted a qualitative descriptive study³⁴ embedded within a larger program of research exploring virtual care for socio-culturally diverse older adults living with HIV.³⁵ A qualitative descriptive study was appropriate for this research as it allows for a detailed exploration of participants’ experiences, capturing their perspectives in a naturalistic manner and providing rich insights into the factors influencing technology adoption and use among older adults living with HIV.³⁴ We have followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) to guide our reporting.³⁶

The study was approved by the Mount Sinai Health Research Ethics Committee (approval MSH REB# 23-0106-E). All participants provided written informed consent to participate in the study, be audio recorded, and have anonymous quotations published. None of the participants were known to the research team prior to the study.

Theoretical framework

This qualitative study is informed by the TDF.²⁸ The TDF is comprised of a cross-disciplinary synthesis of theories from behavioral science and implementation research.²⁸ Specifically, the Framework outlines domains/determinants of behavior at the individual (knowledge, skills, beliefs), social (identity, power, group norms) and environmental (stressors, barriers and facilitators, resources) levels.³⁷ In the context of health research, the TDF has been utilized to uncover barriers and facilitators to engaging with healthcare programing, as well as to contextualize motivations for adopting or adhering to interventions or treatment.³⁷ In this study, we utilize the TDF as a basis to understand and contextualize the behaviors that influence the adoption and use of technology for HIV management among older adults. We utilized this theory inductively, meaning, we used the TDF domains to establish thematic patterns. It should be noted that the TDF was used to contextualize the behavioral determinants that participants convey.³⁷

This study was also informed by the STAM.²⁹ The STAM is an adaptation of the Technology Acceptance Model (TAM), specifically designed to explore how older adults adopt and use technology.²⁹ STAM integrates key factors such as perceived ease of use, perceived usefulness, and social influence, while also considering the unique characteristics of seniors, such as physical and cognitive abilities, technology anxiety, and prior experiences with technology.²⁹ The model suggests that older adults are more likely to adopt technology if they perceive it to be easy to use, beneficial to their lives, and supported by their social networks.²⁹ It also emphasizes the importance of addressing age-related barriers to ensure successful technology adoption among seniors.²⁹ This influenced the interview guide.

Researcher positionality

The research team consists of Canadian experts with diverse backgrounds and expertise in HIV research, equity-informed healthcare, health service research, and implementation science. This interdisciplinary team includes PhD-trained researchers, clinicians specializing in geriatrics, family medicine, and infectious diseases, as well as occupational therapists, social workers, health service administrators, and peer-researchers with lived experience living with HIV.

A community-based advisory team was established prior to protocol development. This advisory team comprised “end users” and interest holders, including administrators from non-profit organizations serving older persons with HIV (such as shelters, community centers, and charities) as well as healthcare providers. Throughout the study, advisory members reviewed and refined the draft semi-structured interview guide, suggesting culturally appropriate wording, adjusting question order, and flagging topics that required additional probing. The team met individually with the principal investigators at three key stages, after the initial guide draft, following pilot interviews, and during preliminary analysis, to ensure that the interview questions remained clear, relevant, and respectful of participants’ lived experiences. Their ongoing feedback directly shaped both the framing of questions and the interpretation of emerging themes.

Recruitment and participants

Our study included older individuals living with HIV who met specific eligibility criteria. Our study included older individuals living with HIV who met specific eligibility criteria. Participants were distinct from our advisory committee. Eligible individuals had to self-identify as HIV-positive, be 50 years of age or older, and reside in Ontario. Individuals were excluded if they did not meet these criteria or had cognitive impairments that hindered informed consent or participation in the study.

We employed purposive sampling to ensure a diverse sample.^38,39 We purposively sought diversity across various dimensions including (a) sex and gender; (b) age; (c) ethnicity and race; (d) socioeconomic status; (e) prior usage of virtual geriatric care (yes or no); (f) geographical location—rural versus urban; (g) duration of time living with HIV; (h) non-English first language; and (i) level of educational attainment. Our advisory team engaged in community outreach at relevant meetings and events to assist with recruitment, leveraging their networks and organizations. We also posted study flyers at community-based organizations, religious institutions, and culturally oriented events. Lastly, our advisory team's websites and social media platforms promoted the study. All participants contacted the research coordinator to learn more about and enroll in the study. Two participants who enrolled dropped out due to scheduling conflicts.

Data collection

Semi-structured interviews explored the factors influencing technology adoption for HIV management among older adults. One area of focus was the challenges participants face when using technology for their HIV care, as these barriers could influence their willingness to engage with digital tools. The interviews also delved into the participants’ comfort levels with using technology to monitor their health, examining the factors that contribute to their comfort or discomfort. A key question explored how healthcare providers could better support older adults in adopting technology for HIV management. Additionally, the interviews sought to understand positive experiences with technology, asking participants to describe any aspects of digital tools that were particularly helpful in managing their care. The role of family members and caregivers in facilitating technology adoption was another topic of interest, with participants sharing their thoughts on how these individuals could assist in their use of health technologies. The interviews also investigated participants’ perceptions of how technology could improve HIV care for older adults and what specific features would make them more likely to adopt such technologies (see Supplemental Material 2). Interviews were conducted by a trained female research assistant (MD student) or a male peer-researcher, supported by the first author, and centered on participants’ experiences of living with HIV, the role of technology in their health management, and their specific needs and concerns regarding digital health tools. No participant was known to the study team before the study. All participants knew of the aims of the study. Demographic information, including age, gender, socioeconomic status, and digital literacy, was collected to inform targeted recruitment and understand the diverse lived experiences of participants. All interviews were audio recorded, transcribed verbatim, and reviewed for accuracy. Anonymized narrative summaries were shared with the research team and advisory board for ongoing feedback. Identifiable information was removed to protect participant confidentiality, and no names were used in the analysis or reporting of results. Data collection occurred from November 2023-April 2024. All participants received a financial honorarium for their time.

Data saturation was achieved during the interview process, with no new themes emerging after 14 interviews. Throughout data collection, the research team conducted ongoing, iterative analysis using a constant comparative approach. After every few interviews, transcripts were reviewed and coded to identify recurring patterns and assess whether new information was still emerging. Once data redundancy was observed, and all major categories were well developed, saturation was considered reached. The advisory committee was engaged throughout the process. They reviewed emerging findings at multiple stages to ensure thematic completeness and confirm that key issues relevant to older adults living with HIV had been captured. This collaborative approach strengthened the validity of the findings and supported the decision that data saturation had been adequately achieved. The sample size of 14 participants was selected to ensure a broad representation of experiences and to confirm the saturation of data, allowing for a comprehensive understanding of the factors influencing technology adoption among older adults living.

Data analysis

The dataset was comprised of audio recordings, transcripts, field notes, meeting notes and reflexive notes. The analysis team, consisting of research team members and selected advisory committee members, conducted thematic content analysis.^40,41 Data analysis occurred concurrently with data collection to determine thematic saturation.⁴² Transcripts were coded using NVivo 14 software by the first and second author with codes generated from the content of the TDF and refined through subsequent data collection and analysis.^28,43,44 Throughout the process, team meetings were held to review and adjust the codebook as new codes emerged and to draft themes. Preliminary findings were shared with peer-researchers and advisory team members one week ahead of the following interview to allow for reflection and feedback, ensuring the inclusion of diverse perspectives in subsequent analysis phases. Themes were developed through triangulation of transcripts, notes, and memos. All members of the research team reviewed and endorsed the final version of the analysis to ensure rigor and accuracy. A lay version of the draft manuscript was also shared with the advisory committee.

Rigor

Rigor and trustworthiness were ensured through several strategies. Firstly, we involved lived and living experiences throughout the research process, which facilitated meaningful end-user engagement and ensured that the perspectives of older adults living with HIV were central to the study's design and outcomes. This approach was consistent with established principles of community-based participatory research.^45,46 This collaborative approach enhanced the reliability and credibility of the findings by ensuring that interpretations were grounded in the data and reflective of diverse perspectives.⁴⁷ Lastly, transparency and reflexivity were maintained throughout the research process. Reflexive notes, memos, and detailed documentation of methodological decisions were kept to provide transparency in data interpretation and analysis. Regular interactions with the advisory team and participants, including sharing preliminary findings and seeking feedback, further strengthened the trustworthiness of the study by ensuring that findings resonated with participant experiences and priorities.⁴⁷ These steps adhered to Tracy's (2010) “big-tent” criteria for excellent qualitative research emphasizing sincerity (through reflexive journaling), credibility (via member-checking of preliminary findings), and transparency (by keeping detailed memos of methodological decisions).⁴⁸

Results

A total of 14 older adults living with HIV (mean 58.7 [SD 6.5] years) participated in this study. Ten interviews were conducted by the trained research assistant (n = 10) and four were conducted by the peer-researcher with lived experience (n = 4).

There were no marked differences in the length, quality, or overall content of the interviews based on the interviewer. Of these 14 participants, the majority were men (n = 10; 71%) and lived in urban settings (n = 9, 64%). Over half of the participants were not born in Canada (n = 8; 57%), and many did not speak English as a first language (n = 6, 43%). The annual household income was most often $0–$29,999 CAD (n = 9; 64%), and a majority of participants lived alone (n = 8, 57%). Almost all participants had access to a computer, a smartphone, and internet (n = 9, 64%); although, 29% of the sample (n = 4) did not respond. Half of the participants noted that they did not need assistance with technology (n = 7; 50%). See Supplemental Table A for further details on participants.

Our findings align with the TDF by highlighting several critical barriers and facilitators to technology adoption among older adults living with HIV²⁸ (Table 1).

Table 1.

Alignment of themes to theoretical domains in technology use for self-management among older adults living with HIV.

Theme	TDF domains	Explanation	Quotes
Self-management	Knowledge, beliefs about capabilities, memory, attention, and decision processes	Participants use technology to self-manage their health and avoid medical visits, indicating knowledge of self-care and belief in their capabilities to manage their condition with technology.	“I just set lots of phone alarms to take my meds and I learned to set many in a day.” (Participant 11, man, 68)
Practical Considerations	Environmental context and resources, social influences	Barriers like affordability, cognitive changes, and linguistic diversity influence participants' ability to use technology. Participants' reliance on existing resources reflects practical constraints.	“I had to stop using that app, it started charging a monthly fee I couldn't afford. I hate when it goes and it’s a trial.” (Participant 1, woman, 57)
Perceived usefulness and ease of use	Knowledge, beliefs about capabilities, optimism, beliefs about consequences	Participants are willing to adopt technology that they perceive as useful, such as medication reminders and symptom trackers. If technology is easy to use, it enhances self-management and confidence.	“If it’s simple and works, I’ll use it. If it’s confusing, forget it.” (Participant 11, man, 68)
Expert culture	Social influences, beliefs about capabilities, emotions	Participants report feeling excluded by an "expert culture," where technology usage is seen as requiring specialized knowledge, leading to hesitance or avoidance. Some also pretend to understand to avoid stigma.	“I just nod like I understand when they tell me about this app or the TikTok or whatever it is they use, but I left out.” (Participant 2, woman, 61)
Consent	Social and environmental context, memory, attention, and decision processes, motivation and intentions	Concerns about privacy and control over personal health data influence willingness to engage with virtual care technologies. Continuous consent and clarity are critical to ensuring trust.	“I don’t like the idea of people online knowing about my HIV.” ( Participant 5, man, 65)
Influence of peers	Social influences, reinforcement	Peers' successful use of technology influences participants' willingness to adopt similar tools, increasing confidence and reducing skepticism about technology.	“When I saw people old like me using it, I figured I could too.” ( Participant 7, man, 66)

Self-management

Participants frequently described using technology to manage their health independently, reflecting TDF domains of Knowledge, Beliefs about Capabilities, and Decision Processes, and aligning with the STAM domain of Perceived Usefulness. Participants shared that they primarily rely on technology for self-management, as they often face difficulties accessing medical treatment. Many expressed a desire for professional care but mentioned challenges in securing appointments, particularly with their trusted family physicians, leaving self-management as their only viable option. Other participants noted a distrust in their providers. Due to these challenges, participants noted using technology—largely the internet, to seek out information. One participant described “Why would I go to the doctor if I know they just judge me. So, when I feel like it, I may just use my app that tracks sugar. Or Google what to eat that isn’t high in sugar” (Participant 1, woman, 57) (TDF: Beliefs about Capabilities; STAM: Perceived Usefulness). This reliance on technology was also seen by some participants as a coping mechanism for those who may not have consistent access to HIV specialists or who face long wait times in the healthcare system. The same participant said, “I guess, for me, technology makes me think I’m a doctor” (Participant 1, woman, 57) (TDF: Decision Processes; STAM: Usefulness).

Participants also noted that they found numerous benefits in searching information or using applications, to help them manage their diet, nutrition and sleep. Digital tools, such as symptom trackers, medication reminders, and nutrition apps, were frequently used to help manage HIV-related complications, such as medication adherence, immune health, and nutritional needs. Participants highlighted how apps empowered them to monitor their own health, reinforcing a sense of control over their condition. One participant said

I am always googling what I should do. Especially in the winter so I don’t get sick because of my immune system. It's how I learned about elderberry. There is also an app I downloaded that tells me little things on staying calm. For stress. (Participant 11, man, 68)

This quote illustrates how digital health tools support self-management and emotional regulation (TDF: Knowledge; Behavioral Regulation; STAM: Usefulness), especially when managing a chronic and episodic condition like HIV.

Participants noted that searching for information online helped them understand their condition better, stay updated on new treatments, and explore holistic approaches to well-being (e.g., immune-boosting supplements like elderberry). Participants noted that the stigmatized nature of HIV lead them to search for information. As one participant shared,

If something comes up, I just look it up. I don’t go to a walk in. I rather see if it's an emergency and unless I’m dying, I don’t want to go see some new doctor and claim it's HIV. There is a stigma. (Participant 15, man, 57)

This comment reflects TDF: Social Influences and Emotion (related to stigma), along with STAM: Subjective Norms and Anxiety, showing how stigma influenced participants’ technology adoption by encouraging private, self-directed alternatives.

Barriers to accessing care and technology

Participants noted numerous practical considerations that influenced their ability or desire to use technology to manage their health. Some participants described affordability constraints, such as not being able to afford different devices or a smartphone, or even always having access to internet at home. One participant said

listen, I cannot afford a new phone. I get hand me downs and that is even when I remember how to charge it. So apps don’t work and sometimes I don’t even have the calling function working if I didn’t pay. I don’t need more confusing information and apps and complexity. I need to pay rent. (Participant 14, woman, 53)

This quote also reflects Beliefs about Consequences, as the participant explicitly prioritizes rent over health technology and views apps as adding unnecessary complexity.

Another significant barrier identified was linguistic diversity. Many participants expressed that they have limited proficiency in English or other dominant languages commonly used in healthcare technology, whereby the options were noted to usually be English, Spanish or French. This language barrier leads to misunderstandings regarding critical health information and instructions, such as medication regimens and appointment schedules. For instance, participants noted that when applications are available only in English, non-native speakers struggle to navigate the information, which ultimately hinders their ability to manage their condition effectively.

Likewise, technological navigation challenges represented another significant barrier. Many participants shared that complex user interfaces, intricate navigation paths, or excessive information presented at once can be overwhelming. For instance, if an app requires numerous steps to schedule a doctor's appointment, it may feel daunting, leading to abandonment of the process altogether. This cognitive load can deter individuals from engaging with technology that could otherwise benefit their health. Features such as step-by-step guided processes, visual icons, and concise instructions were recommended to support navigation and sensory concerns. For instance, a medication management app with straightforward alerts could help users remember their doses without overwhelming them with excessive details.

Perceived usefulness and ease of use

Participants in the study underscored that, for technology to be embraced, it must clearly demonstrate its value in improving their health outcomes. As one participant said,

When I have to choose between medicine or rent or an app- I need to know what is going to help more. If this is just something I don’t even need or someone could look at, I don’t care to be cool. I want it to be helpful. (Participant 14, woman, 53)

This illustrates the Beliefs about Consequences domain, where users weigh the utility and risks of technology against other priorities like cost and privacy. On the other hand, some participants noted that wearable health devices would help them feel supported in monitoring their health. This was especially beneficial for those with mobility challenges or those living in remote areas where access to healthcare services is limited. One participant shared “I am not opposed to even those ‘help I’ve fallen’ things. Something I wear so maybe the police know if I fall on my walk because really all I have to do is put it on. It's easy” (Participant 3, male, 82). This reflects the Environmental Context and Resources domain as well as Reinforcement, in which ease of use and the potential for safety are incentives for adoption.

Moreover, some participants gave examples of applications they used to play games (e.g., for memory) or keep track of their medication adherence. This perception of usefulness encompasses several dimensions, including the technology's ability to facilitate access to medical information, streamline communication with healthcare providers, and support adherence to treatment regimens. For instance, participants described the desire for an application that would allow them to easily schedule appointments. Many participants noted that the pervasive stigma associated with HIV significantly influences the ways individuals approach their self-care routines, with many participants noting to use various forms of technology as measures to keep their diagnosis private. For example, some participants noted that they liked to use applications or phone alarms to offer inconspicuous medication reminders to manage their adherence without drawing attention. One participant said,

I like a lot how I can just set a reminder, and I think apps can do that, to take my medicine but it doesn’t say like “HIV medicine”, it just is an alarm. Sometimes I can pretend it's a call or like ‘oh, I have to leave.’ (Participant 11, man, 68)

This example illustrates the interplay of Beliefs about Consequences, Social/Professional Role and Identity, and Emotion, as technology serves both a practical and a protective function in managing health without disclosing status.

Many participants expressed that technology, particularly wearables and applications, should have intuitive interfaces, clear instructions, and straightforward functionalities to prevent feelings of frustration or overwhelm, in persons living with HIV who may already be frustrated with managing their health conditions. The design of technology tailored for this demographic must consider physical challenges, such as diminished vision or dexterity, ensuring that buttons are adequately sized and text is legible. Participants indicated that when technology is cumbersome or overly complex, it not only hinders usage but can also lead to anxiety about engaging with health management tools, potentially exacerbating feelings of isolation and disengagement from their care. One participant shared, “don’t give me this fancy nonsense. I need it to be useful. I don’t want to be stressed using it. It has to be useful and easy” (Participant 1, woman, 57). Together, these insights underscore that perceived usefulness and simplicity are not just technical requirements but also behavioral drivers shaped by social context, emotional responses, and the broader life circumstances of older adults living with HIV.

“Expert-Culture”

Participants described a prevailing sense that using health technology requires specialized knowledge, aligning with the Skills, Beliefs about Capabilities, and Social/Professional Role and Identity domains of the TDF. Participants felt that using health technology required specialized knowledge and expertise. One participant explained it as,

it's like you have to be an expert, to do it, especially because it is your health. So I can’t just use an app or like I should just know how to use my phone to track sleep, because we have this expert-culture where you just are expected to be an expert. (Participant 3, man, 82)

This comment reflects the Beliefs about Capabilities domain, where the expectation to independently manage health through technology conflicts with a lack of confidence or training. As a result, many of the participants described feeling excluded for not using technology or hesitant to adopt new technological tools, viewing themselves as lacking the necessary skills. One participant described their experience as

I just don’t want to learn. Someone told me to get one of those new watches that count your heartrate. I am old school. Years ago, a cardiologist told me to push my pressure point. I do that. I couldn’t learn an app. (Participant 6, man, 69)

This reflects both Skills and Emotion, as reluctance is tied not only to ability but also to stress or frustration associated with trying to learn.

On the other hand, many participants described pretending to be more proficient than they really were in using technology to manage their health. One participant said

yeah during Covid I had to do this online thing. I had to fill these forms online. I don’t even know if I did them right still. I just pretended I did. Honestly, I should have pretended I lost the email. Sometimes I go to the pharmacy and they ask for my email or number for points and I just make something up. (Participant, 9, man, 53)

This quote reflects how perceived expectations from others and internalized pressure to perform influence behavior even when participants do not feel confident in their abilities.

Consent

Consent for the use of technology in care was identified as an important factor in virtual care for older adults living with HIV. Participants underscored the need for a seamless, transparent, and non-intrusive approach. As one participant explained

I want to know what I’m consenting for. Are they just tracking information to make money off me and HIV? Or do they actually care? What are they tracking? Who is watching? I want to know everything and not read it in size 0 font on a phone screen. (Participant 15,man, 57)

This aligns with the Knowledge, Beliefs about Consequences, and Trust constructs within the TDF, as participants wanted to fully understand what data would be used for and who would access it before giving consent.

Participants noted that health technology must be designed to accommodate the unique needs and preferences of older adults, who may face challenges such as cognitive decline or sensory impairments. For example, participants described that they did not want to be asked to remember if they provided consent. The same participant said, “I can’t even remember things on a good day. If you tell me I agreed to you recording my information on my phone, maybe I did.” (Participant 15, man, 57), highlighting concerns linked to Memory, Attention and Decision Processes. This emphasizes the need for repeated, accessible, and clear consent processes that are not overly reliant on one-time or text-based interactions.

Likewise, they wanted to have many options for providing consent such as verbal and written options. Participants highlighted the necessity for technology to facilitate continuous consent mechanisms, ensuring that users are kept informed about how their data will be used and the implications of their participation in virtual care. This not only fosters trust in the technology but also reassures individuals that they maintain control over their personal information, which is particularly pertinent given the sensitive nature of HIV-related health data.

Influence of peers

Participants noted that their peers (individuals or friends living with HIV) played a significant role in shaping individuals’ willingness to adopt and use technology for managing HIV. Participants noted that when they noticed their peers successfully using a health app, telehealth service, or digital medication reminder, it reduced their skepticism about using technology and increased their confidence in the technology. One participant shared “I am in my 80s so I always thought I wouldn’t want a new phone or even a cell phone. But everyone has one and they [friends] tell me it helps. Now I want one” (Participant 3, man, 82). This reflects the Social Influences domain and suggests that peer modeling can enhance self-efficacy and reduce perceived barriers, aligning with the Beliefs about Capabilities domain.

Conversely, participants described that if their peers expressed distrust in technology or highlight negative experiences, this discouraged others from adopting these tools. In some cases, individuals avoided using technology if they feared judgment from their peer networks or if their community holds beliefs that conflict with the use of digital health tools. For example, concerns around privacy breaches, misinformation, or cultural resistance to technology significantly diminished the willingness to try new digital solutions. The same participant said ‘Like when all those Apple watches came out, a friend told me they track your data and location. So nope- never getting one, even if I could afford it’ (Participant 3, man, 82). This quote further reinforces how Social Influences, Beliefs about Consequences, and Emotion interact to shape technology adoption behaviors. In particular, privacy concerns and stigma related to HIV intersected with technological distrust, amplifying the impact of peer networks in decision-making.

Discussion

There is global interest in how digital health technologies that can help older adults track health, prevent decline, or maintain independence.⁴⁹ Older users often feel overwhelmed or frustrated by complex interfaces.⁴⁹ Concepts like ‘technological dependence’ worry many seniors, who emphasize that health tools should not make them more ‘dependent’ or less independent.⁵⁰ Yet, when adoption is successful, older adults report several positive outcomes, including using digital health technologies to self-monitor and prepare for aging challenges.⁴⁹ This study was conducted to better understand the factors influencing the adoption of digital technology for managing HIV among older adults. Our data analysis, involving the perspectives of 14 older adults living with HIV, revealed that participants relied heavily on technology for self-management due to distrust in healthcare providers and barriers to accessing care. Uptake was facilitated by intuitive interfaces, practical benefits of technology, and the ability to maintain privacy in managing HIV-related health tasks. However, several barriers persisted, including affordability, language challenges, cognitive overload, and concerns about consent and privacy. These findings highlight the need for tailored digital health interventions that consider the specific accessibility, language, cognitive, and privacy needs of older adults with HIV to improve their health management and digital health equity.

Our findings align with existing research on technology adoption among older adults,^51,52 which highlights barriers such as low digital literacy, limited confidence, and concerns about privacy.^25,51,53 Studies have shown that older adults often face difficulties navigating digital health platforms due to inadequate digital skills and confidence, particularly in marginalized populations.⁵⁴ Our study contributes to the literature by highlighting the unique barriers older adults living with HIV face in using digital health tools. These include cognitive challenges, age-related gaps in digital literacy, and heightened privacy concerns stemming from HIV-related stigma. These challenges are often overlooked in existing digital health interventions, despite this group experiencing the dual stigma of aging and HIV status.^55,56 Furthermore, while previous research has noted the importance of access to resources, our study highlights the compounded impact of socioeconomic disparities, revealing how limited access to technology and internet services further marginalizes older adults living with HIV. Participants emphasized the need for technology that is not only user-friendly but also inclusive, accommodating sensory impairments and language barriers prevalent in this group, as many are non-native English speakers. Importantly, participants stressed the need for continuous support, including digital literacy training and real-time technical assistance, to bolster their confidence in using these technologies. Thus, our work not only corroborates existing evidence but also provides deeper insights into the unique challenges faced by this demographic, suggesting the need for tailored interventions that address both technological and socio-cultural barriers.

Our findings align with and extend the STAM by identifying unique factors that influence technology adoption among older adults living with HIV, beyond those captured in traditional models.²⁹ While STAM emphasizes constructs such as perceived usefulness (PU), perceived ease of use (PEOU), self-efficacy, and facilitating conditions as key predictors of technology acceptance among older adults,²⁹ our study reveals additional, condition-specific barriers and facilitators reflective of the critical impact of HIV-related stigma on technology adoption. Participants expressed concerns about privacy, with fears that using health applications could inadvertently disclose their HIV status. This highlights the need for health technology solutions that maintain confidentiality and offer discreet functionalities, an area not fully addressed in existing STAM frameworks. Secondly, while STAM accounts for age-related cognitive and physical limitations, our study introduces the additional layers of language barriers and digital literacy specific to older adults who are also immigrants or non-native speakers. Participants reported challenges navigating health technology due to limited proficiency in English, underscoring the necessity of inclusive design features like multilingual support and simplified interfaces. Furthermore, we expand on the facilitating conditions outlined in STAM by incorporating socio-economic barriers, such as affordability of devices and internet access. Many older adults living with HIV are constrained by low incomes and the high-cost of HIV medications,⁵⁷ struggle to afford the necessary technology or internet connectivity.⁵⁸ This extends the original STAM focus by emphasizing the need for accessible, low-cost technological solutions tailored to socioeconomically disadvantaged older adults. Factors such as finances, which are frequently overlooked or underrepresented in traditional models of technology adoption, are critical in understanding how socio-economic and cultural factors intersect to affect technology uptake. Lastly, our findings highlight the influence of peer networks as a facilitator of technology use, aligning with but expanding on STAM's social influence component. Participants were more likely to adopt technology when they observed peers successfully using digital health tools, suggesting that peer support programs could be instrumental in increasing technology uptake among older adults living with HIV.

Our findings also expand the TDF²⁸ by highlighting novel barriers and facilitators specific to older adults living with HIV and the need for continuous consent mechanisms in digital health. While the TDF addresses domains like knowledge, social influences, and environmental context,²⁸ our study reveals unique condition and contextual-specific challenges (e.g., distrust in healthcare providers and language barriers) that influence technology use, thereby extending the TDF's application to explicitly incorporate socio-economic and cultural factors that are critical for marginalized populations. Additionally, our results emphasize the role of peer influence and practical considerations (e.g., affordability and usability) in technology adoption, extending the TDF's application to include socio-economic and cultural factors critical for marginalized populations. This is particularly relevant for older adults who are more likely to trust and learn from others in their social networks. Moreover, factors such as finances, are often overlooked in traditional models of technology adoption but are critical in understanding how socio-economic and cultural factors intersect to affect technology adoption. By incorporating these insights, we extend the TDF's application to better address the specific needs of marginalized groups, such as older adults living with HIV, and provide a more comprehensive framework for understanding technology acceptance in diverse and underserved populations.

Participants stressed the need for a continuous and transparent consent process. This goes beyond a one-time agreement and becomes an ongoing dialogue where individuals feel comfortable and informed about how their data will be used. The concept of ongoing informed consent is critical in healthcare,^59–61 particularly for individuals living with HIV or other stigmatized health conditions.^62,63 In the context of virtual care, this process is particularly important, as it ensures that patients remain in control of their data and that they understand the implications of participating in digital healthcare services, such as telemedicine or health apps.⁶⁴ Written consent can be provided through digital platforms or paper forms, but verbal consent may be necessary for individuals who have literacy challenges or cognitive difficulties. Furthermore, real-time discussions during consultations or appointments can provide additional opportunities for patients to ask questions and clarify any aspects of the consent process. Additionally, using interactive digital tools to facilitate consent could empower patients to maintain control over their participation.⁶⁵ For instance, consent forms could be integrated into telemedicine platforms in a way that allows individuals to easily adjust their preferences, withdraw consent, or update their information. These tools could include multiple languages, text-to-speech functionality, and other accessibility features to ensure inclusivity. A digital consent process could also provide the option to give consent multiple times as care needs or technologies change, ensuring that patients are consistently updated and reminded about their data usage and rights. This involves not just informing patients about how their data will be used, but also actively engaging them in discussions around how their privacy will be protected, how data will be secured, and what steps will be taken to limit access to their sensitive information. In addition to building trust, a transparent consent process can enhance adherence to care by reassuring patients that they are active participants in their healthcare decisions.⁶⁶ Without this level of engagement, patients may feel disconnected from their care team, which could lead to non-adherence to prescribed treatments or missed appointments.⁶⁷

While participants highlighted important features that could enhance the usability and acceptance of digital health tools for older adults living with HIV, several practical and systemic barriers may limit the implementation of these recommendations. Cost and affordability remain significant challenges, as many suggested adaptations, such as multi-modal consent processes, personalized support, and simplified user interfaces, require ongoing investment in development, maintenance, and user training.^68,69 Additionally, variability in technical infrastructure, including access to reliable internet and compatible devices, may further restrict technology use among socioeconomically marginalized populations.⁷⁰ Sustainability of these features also presents a concern; many digital health innovations rely on short-term funding and pilot projects, with limited capacity to scale or maintain user-centered components over time.⁷¹ Moreover, existing regulatory and commercial frameworks may prioritize data standardization and compliance, potentially conflicting with the need for personalization and user autonomy emphasized by participants. Addressing these barriers will be critical to advancing equitable digital health solutions that are responsive to the needs of older adults living with HIV.

Our study found that older adults may avoid using technology when they fear judgment from their peer networks or when their community holds beliefs that conflict with digital health tools. A key finding in research on technology adoption is that many older adults resist technologies that align with stereotypes of aging or disability.⁷² Our results highlight that concerns over privacy, misinformation, or cultural resistance to technology can diminish willingness to adopt digital solutions. Moreover, the influence of social networks and community beliefs plays a significant role in shaping attitudes toward technology use, as individuals may prioritize maintaining social identity over embracing new tools. This resistance is often tied to a desire to maintain independence and avoid using technologies that track health or support cognitive health, that might emphasize dependency or reinforce stereotypes about aging and declining abilities.⁷² Earlier research posited that that identity-related factors emphasize the importance of designing assistive technologies that allow older adults to retain a sense of control, autonomy, and privacy.⁷² Understanding these dynamics can help in creating more engaging and acceptable technology solutions for older populations.

Limitations

This study has several limitations that should be considered when interpreting the findings. While purposive sampling was used to capture diverse perspectives, the study highlights the experiences of low-income older adults living with HIV in an urban setting with a high cost of living. As such, the results may have limited transferability to broader populations of older adults living with HIV outside of Ontario, particularly those who are not engaged with community networks or using technology to manage their health. Recruitment through community outreach and advisory team networks may have introduced bias by favoring participants who are more comfortable with digital tools or research participation. Additionally, the reliance on self-reported data may have led to social desirability bias,⁷³ with participants potentially providing more positive views on technology adoption. Additionally, a limitation of the study is the use of two different interviewers, which could introduce potential bias in the data due to variations in interview style, interpretation, or interaction with participants. Another limitation is the potential influence of language barriers, as some participants may have faced challenges in expressing themselves fully or accurately, which could have impacted the richness of the data collected. Furthermore, the study's application of the TDF²⁸ was exploratory, limiting the emergence of themes outside its predefined domains, and the framework cannot establish causal relationships.

Conclusion

This study identified themes and theoretical domains provide valuable insights into the barriers and facilitators of technology use for self-management among older adults living with HIV, highlighting areas for targeted interventions and support. Participants valued technologies that provided clear, tangible benefits, such as enabling access to care from home, reducing transportation burdens, and supporting frequent communication with healthcare providers. However, the adoption of digital health tools was not without challenges. Participants identified several barriers that could hinder their ability to fully utilize technology, including complex user interfaces, sensory impairments, cognitive challenges, and language barriers. These factors underscore the importance of designing digital health tools that are intuitive, accessible, and inclusive of the diverse needs of older adults, particularly those with HIV. While digital health tools were appreciated for their convenience, participants emphasized that they should complement, rather than replace, in-person care. This highlights a critical consideration for the future of digital health adoption among older adults: technology should not be viewed as a one-size-fits-all solution, but rather as a flexible tool that can be adapted to meet individual health needs and preferences. In conclusion, for digital health tools to be successfully adopted by older adults living with HIV, they must be perceived as both useful and easy to use, while being adaptable to a diverse range of needs and preferences. Addressing barriers such as technological complexity, accessibility issues, and trust concerns, while ensuring continuous support and engagement, will be crucial for enhancing adoption and ensuring that these tools can improve health outcomes in this population.

Supplemental Material

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Supplemental material, sj-docx-1-dhj-10.1177_20552076251378438 for Exploring factors influencing the adoption and use of digital health technology for HIV management among older adults living with HIV: A qualitative study by Kristina M. Kokorelias, Erica Dove, Dean Valentine, Paige Brown, Stuart McKinlay, Andrew D. Eaton, Esther Su, Christine L. Sheppard, Hardeep Singh, Laura Jamieson, Marina B. Wasilewski, Alice Zhabokritsky, Reham Abdelhalim, Rabea Parpia, Rahel Zewude, Sharon Walmsley and Luxey Sirisegaram in DIGITAL HEALTH

Supplemental Material

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Supplemental material, sj-docx-2-dhj-10.1177_20552076251378438 for Exploring factors influencing the adoption and use of digital health technology for HIV management among older adults living with HIV: A qualitative study by Kristina M. Kokorelias, Erica Dove, Dean Valentine, Paige Brown, Stuart McKinlay, Andrew D. Eaton, Esther Su, Christine L. Sheppard, Hardeep Singh, Laura Jamieson, Marina B. Wasilewski, Alice Zhabokritsky, Reham Abdelhalim, Rabea Parpia, Rahel Zewude, Sharon Walmsley and Luxey Sirisegaram in DIGITAL HEALTH

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Supplemental material, sj-pdf-3-dhj-10.1177_20552076251378438 for Exploring factors influencing the adoption and use of digital health technology for HIV management among older adults living with HIV: A qualitative study by Kristina M. Kokorelias, Erica Dove, Dean Valentine, Paige Brown, Stuart McKinlay, Andrew D. Eaton, Esther Su, Christine L. Sheppard, Hardeep Singh, Laura Jamieson, Marina B. Wasilewski, Alice Zhabokritsky, Reham Abdelhalim, Rabea Parpia, Rahel Zewude, Sharon Walmsley and Luxey Sirisegaram in DIGITAL HEALTH

Footnotes

Acknowledgements

The authors would like to thank the participants for their invaluable insights and contributions to this research. Special thanks to HQ Toronto () for their assistance in organizing the event and supporting the project.

ORCID iDs

Kristina M. Kokorelias

Stuart McKinlay

Esther Su

Contributorship

KMK, ED, AED,CS, HS, MW, SW and LS contributed to the conception and design of the study. KMK ED, VD, PB, SM, ES, conducted the data collection and led the analysis. KMK drafted the manuscript, and all authors contributed to revisions and approved the final version for submission. All authors take responsibility for the accuracy and integrity of the work.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the AGE-WELL Network of Centres of Excellence (NCE) and the Canadian Frailty Network's Catalyst Funding Program in Healthy Aging. AW-CAT-2023-03.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental material

Supplemental material for this article is available online.

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